1
|
Kumar N, Hui SJ, Ali S, Lee R, Jeyachandran P, Tan JH. Vacuum assisted closure and local drug delivery systems in spinal infections: A review of current evidence. N Am Spine Soc J 2023; 16:100266. [PMID: 37727637 PMCID: PMC10505691 DOI: 10.1016/j.xnsj.2023.100266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 08/12/2023] [Accepted: 08/15/2023] [Indexed: 09/21/2023]
Abstract
Background Spinal infections are still showing increased incidence throughout the years as our surgical capabilities increase, coupled with an overall aging population with greater number of chronic comorbidities. The management of spinal infection is of utmost importance, due to high rates of morbidity and mortality, on top of the general difficulty in eradicating spinal infection due to the ease of hematogenous spread in the spine. We aim to summarize the utility of vacuum-assisted closure (VAC) and local drug delivery systems (LDDS) in the management of spinal infections. Methods A narrative review was conducted. All studies that were related to the use of VAC and LDDS in Spinal Infections were included in the study. Results A total of 62 studies were included in this review. We discussed the utility of VAC as a tool for the management of wounds requiring secondary closure, as well as how it is increasingly being used after primary closure as prophylaxis for surgical site infections in high-risk wounds of patients undergoing spinal surgery. The role of LDDS in spinal infections was also discussed, with preliminary studies showing good outcomes when patients were treated with various novel LDDS. Conclusions We have summarized and given our recommendations for the use of VAC and LDDS for spinal infections. A treatment algorithm has also been established, to act as a guide for spine surgeons to follow when tackling various spinal infections in day-to-day clinical practice.
Collapse
Affiliation(s)
- Naresh Kumar
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E, Lower Kent Ridge Road, 119228, Singapore
| | - Si Jian Hui
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E, Lower Kent Ridge Road, 119228, Singapore
| | - Shahid Ali
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E, Lower Kent Ridge Road, 119228, Singapore
| | - Renick Lee
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E, Lower Kent Ridge Road, 119228, Singapore
| | - Praveen Jeyachandran
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E, Lower Kent Ridge Road, 119228, Singapore
| | - Jiong Hao Tan
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E, Lower Kent Ridge Road, 119228, Singapore
| |
Collapse
|
2
|
Tan JYH, Tan JH, Tan SHS, Shen L, Loo LMA, Iau P, Murphy DP, O’Neill GK. Epidemiology and estimated economic impact of musculoskeletal injuries in polytrauma patients in a level one trauma centre in Singapore. Singapore Med J 2023; 64:732-738. [PMID: 35739075 PMCID: PMC10775301 DOI: 10.11622/smedj.2022081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2018] [Accepted: 06/21/2020] [Indexed: 11/18/2022]
Abstract
Introduction Musculoskeletal injuries are the most common reason for surgical intervention in polytrauma patients. Methods This is a retrospective cohort study of 560 polytrauma patients (injury severity score [ISS] >17) who suffered musculoskeletal injuries (ISS >2) from 2011 to 2015 in National University Hospital, Singapore. Results 560 patients (444 [79.3%] male and 116 [20.7%] female) were identified. The mean age was 44 (range 3-90) years, with 45.4% aged 21-40 years. 39.3% of the patients were foreign migrant workers. Motorcyclists were involved in 63% of road traffic accidents. The mean length of hospital stay was 18.8 (range 0-273) days and the mean duration of intensive care unit (ICU) stay was 5.7 (range 0-253) days. Patient mortality rate was 19.8%. A Glasgow Coma Scale (GCS) score <12 and need for blood transfusion were predictive of patient mortality (p < 0.05); lower limb injuries, road traffic accidents, GCS score <8 and need for transfusion were predictive of extended hospital stay (p < 0.05); and reduced GCS score, need for blood transfusion and upper limb musculoskeletal injuries were predictive of extended ICU stay. Inpatient costs were significantly higher for foreign workers and greatly exceeded the minimum insurance coverage currently required. Conclusion Musculoskeletal injuries in polytrauma remain a significant cause of morbidity and mortality, and occur predominantly in economically productive male patients injured in road traffic accidents and falls from height. Increasing insurance coverage for foreign workers in high-risk jobs should be evaluated.
Collapse
Affiliation(s)
- Joel Yong Hao Tan
- Department of Orthopaedic Surgery, University Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Health System, Singapore
| | - Jiong Hao Tan
- Department of Orthopaedic Surgery, University Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Health System, Singapore
| | - Si Heng Sharon Tan
- Department of Orthopaedic Surgery, University Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Health System, Singapore
| | - Liang Shen
- Biostatistics Unit, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Lynette Mee-Ann Loo
- University Surgical Cluster, Division of General Surgery, National University Health System, Singapore
| | - Philip Iau
- University Surgical Cluster, Division of General Surgery, National University Health System, Singapore
| | - Diarmuid Paul Murphy
- Department of Orthopaedic Surgery, University Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Health System, Singapore
| | - Gavin Kane O’Neill
- Department of Orthopaedic Surgery, University Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Health System, Singapore
| |
Collapse
|
3
|
Ong W, Liu RW, Makmur A, Low XZ, Sng WJ, Tan JH, Kumar N, Hallinan JTPD. Artificial Intelligence Applications for Osteoporosis Classification Using Computed Tomography. Bioengineering (Basel) 2023; 10:1364. [PMID: 38135954 PMCID: PMC10741220 DOI: 10.3390/bioengineering10121364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 11/21/2023] [Accepted: 11/23/2023] [Indexed: 12/24/2023] Open
Abstract
Osteoporosis, marked by low bone mineral density (BMD) and a high fracture risk, is a major health issue. Recent progress in medical imaging, especially CT scans, offers new ways of diagnosing and assessing osteoporosis. This review examines the use of AI analysis of CT scans to stratify BMD and diagnose osteoporosis. By summarizing the relevant studies, we aimed to assess the effectiveness, constraints, and potential impact of AI-based osteoporosis classification (severity) via CT. A systematic search of electronic databases (PubMed, MEDLINE, Web of Science, ClinicalTrials.gov) was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 39 articles were retrieved from the databases, and the key findings were compiled and summarized, including the regions analyzed, the type of CT imaging, and their efficacy in predicting BMD compared with conventional DXA studies. Important considerations and limitations are also discussed. The overall reported accuracy, sensitivity, and specificity of AI in classifying osteoporosis using CT images ranged from 61.8% to 99.4%, 41.0% to 100.0%, and 31.0% to 100.0% respectively, with areas under the curve (AUCs) ranging from 0.582 to 0.994. While additional research is necessary to validate the clinical efficacy and reproducibility of these AI tools before incorporating them into routine clinical practice, these studies demonstrate the promising potential of using CT to opportunistically predict and classify osteoporosis without the need for DEXA.
Collapse
Affiliation(s)
- Wilson Ong
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore (A.M.); (X.Z.L.); (W.J.S.); (J.T.P.D.H.)
| | - Ren Wei Liu
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore (A.M.); (X.Z.L.); (W.J.S.); (J.T.P.D.H.)
| | - Andrew Makmur
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore (A.M.); (X.Z.L.); (W.J.S.); (J.T.P.D.H.)
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - Xi Zhen Low
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore (A.M.); (X.Z.L.); (W.J.S.); (J.T.P.D.H.)
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - Weizhong Jonathan Sng
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore (A.M.); (X.Z.L.); (W.J.S.); (J.T.P.D.H.)
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - Jiong Hao Tan
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E Lower Kent Ridge Road, Singapore 119228, Singapore; (J.H.T.); (N.K.)
| | - Naresh Kumar
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E Lower Kent Ridge Road, Singapore 119228, Singapore; (J.H.T.); (N.K.)
| | - James Thomas Patrick Decourcy Hallinan
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore (A.M.); (X.Z.L.); (W.J.S.); (J.T.P.D.H.)
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| |
Collapse
|
4
|
Hallinan JTPD, Zhu L, Tan HWN, Hui SJ, Lim X, Ong BWL, Ong HY, Eide SE, Cheng AJL, Ge S, Kuah T, Lim SWD, Low XZ, Teo EC, Yap QV, Chan YH, Kumar N, Vellayappan BA, Ooi BC, Quek ST, Makmur A, Tan JH. A deep learning-based technique for the diagnosis of epidural spinal cord compression on thoracolumbar CT. Eur Spine J 2023; 32:3815-3824. [PMID: 37093263 DOI: 10.1007/s00586-023-07706-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 03/12/2023] [Accepted: 04/06/2023] [Indexed: 04/25/2023]
Abstract
PURPOSE To develop a deep learning (DL) model for epidural spinal cord compression (ESCC) on CT, which will aid earlier ESCC diagnosis for less experienced clinicians. METHODS We retrospectively collected CT and MRI data from adult patients with suspected ESCC at a tertiary referral institute from 2007 till 2020. A total of 183 patients were used for training/validation of the DL model. A separate test set of 40 patients was used for DL model evaluation and comprised 60 staging CT and matched MRI scans performed with an interval of up to 2 months. DL model performance was compared to eight readers: one musculoskeletal radiologist, two body radiologists, one spine surgeon, and four trainee spine surgeons. Diagnostic performance was evaluated using inter-rater agreement, sensitivity, specificity and AUC. RESULTS Overall, 3115 axial CT slices were assessed. The DL model showed high kappa of 0.872 for normal, low and high-grade ESCC (trichotomous), which was superior compared to a body radiologist (R4, κ = 0.667) and all four trainee spine surgeons (κ range = 0.625-0.838)(all p < 0.001). In addition, for dichotomous normal versus any grade of ESCC detection, the DL model showed high kappa (κ = 0.879), sensitivity (91.82), specificity (92.01) and AUC (0.919), with the latter AUC superior to all readers (AUC range = 0.732-0.859, all p < 0.001). CONCLUSION A deep learning model for the objective assessment of ESCC on CT had comparable or superior performance to radiologists and spine surgeons. Earlier diagnosis of ESCC on CT could reduce treatment delays, which are associated with poor outcomes, increased costs, and reduced survival.
Collapse
Affiliation(s)
- James Thomas Patrick Decourcy Hallinan
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore, 119074, Singapore.
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore, 117597, Singapore.
| | - Lei Zhu
- Department of Computer Science, School of Computing, National University of Singapore, 13 Computing Drive, Singapore, 117417, Singapore
| | - Hui Wen Natalie Tan
- Department of Orthopaedic Surgery, University Spine Centre, National University Health System, 1E, Lower Kent Ridge Road, Singapore, 119228, Singapore
| | - Si Jian Hui
- Department of Orthopaedic Surgery, University Spine Centre, National University Health System, 1E, Lower Kent Ridge Road, Singapore, 119228, Singapore
| | - Xinyi Lim
- Orthopaedic Centre, Alexandra Hospital, 378 Alexandra Road, Singapore, 159964, Singapore
| | - Bryan Wei Loong Ong
- Department of Orthopaedic Surgery, University Spine Centre, National University Health System, 1E, Lower Kent Ridge Road, Singapore, 119228, Singapore
| | - Han Yang Ong
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore, 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore, 117597, Singapore
| | - Sterling Ellis Eide
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore, 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore, 117597, Singapore
| | - Amanda J L Cheng
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore, 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore, 117597, Singapore
| | - Shuliang Ge
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore, 119074, Singapore
| | - Tricia Kuah
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore, 119074, Singapore
| | - Shi Wei Desmond Lim
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore, 119074, Singapore
| | - Xi Zhen Low
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore, 119074, Singapore
| | - Ee Chin Teo
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore, 119074, Singapore
| | - Qai Ven Yap
- Biostatistics Unit, Yong Loo Lin School of Medicine, 10 Medical Drive, Singapore, 117597, Singapore
| | - Yiong Huak Chan
- Biostatistics Unit, Yong Loo Lin School of Medicine, 10 Medical Drive, Singapore, 117597, Singapore
| | - Naresh Kumar
- Department of Orthopaedic Surgery, University Spine Centre, National University Health System, 1E, Lower Kent Ridge Road, Singapore, 119228, Singapore
| | - Balamurugan A Vellayappan
- Department of Radiation Oncology, National University Cancer Institute Singapore, National University Hospital, Singapore, Singapore
| | - Beng Chin Ooi
- Department of Computer Science, School of Computing, National University of Singapore, 13 Computing Drive, Singapore, 117417, Singapore
| | - Swee Tian Quek
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore, 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore, 117597, Singapore
| | - Andrew Makmur
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore, 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore, 117597, Singapore
| | - Jiong Hao Tan
- Department of Orthopaedic Surgery, University Spine Centre, National University Health System, 1E, Lower Kent Ridge Road, Singapore, 119228, Singapore
| |
Collapse
|
5
|
Tan YL, Ong W, Tan JH, Kumar N, Hallinan JTPD. Epithelioid Sarcoma of the Spine: A Review of Literature and Case Report. J Clin Med 2023; 12:5632. [PMID: 37685699 PMCID: PMC10488709 DOI: 10.3390/jcm12175632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 08/24/2023] [Accepted: 08/26/2023] [Indexed: 09/10/2023] Open
Abstract
Epithelioid sarcoma is a rare malignant mesenchymal tumor that represents less than 1% of soft-tissue sarcomas. Despite its slow growth, the overall prognosis is poor with a high rate of local recurrence, lymph-node spread, and hematogenous metastasis. Primary epithelioid sarcoma arising from the spine is extremely rare, with limited data in the literature. We review the existing literature regarding spinal epithelioid sarcoma and report a case of epithelioid sarcoma arising from the spinal cord. A 54 year old male presented with a 1-month history of progressive left upper-limb weakness and numbness. Magnetic resonance imaging (MRI) of the spine showed an enhancing intramedullary mass at the level of T1 also involving the left T1 nerve root. Systemic radiological examination revealed no other lesion at presentation. Surgical excision of the mass was performed, and histology was consistent with epithelioid sarcoma of the spine. Despite adjuvant radiotherapy, there was aggressive local recurrence and development of intracranial metastatic spread. The patient died of the disease within 5 months from presentation. To the best of our knowledge, spinal epithelioid sarcoma arising from the spinal cord has not yet been reported. We review the challenges in diagnosis, surgical treatment, and oncologic outcome of this case.
Collapse
Affiliation(s)
- Yi Liang Tan
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore; (W.O.); (J.T.P.D.H.)
| | - Wilson Ong
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore; (W.O.); (J.T.P.D.H.)
| | - Jiong Hao Tan
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E, Lower Kent Ridge Road, Singapore 119228, Singapore; (J.H.T.); (N.K.)
| | - Naresh Kumar
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E, Lower Kent Ridge Road, Singapore 119228, Singapore; (J.H.T.); (N.K.)
| | - James Thomas Patrick Decourcy Hallinan
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore; (W.O.); (J.T.P.D.H.)
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| |
Collapse
|
6
|
Kumar N, Tan JYH, Chen Z, Ravikumar N, Milavec H, Tan JH. Intraoperative cell-salvaged autologous blood transfusion is safe in metastatic spine tumour surgery: early outcomes of prospective clinical study. Eur Spine J 2023; 32:2493-2502. [PMID: 37191676 DOI: 10.1007/s00586-023-07768-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 03/30/2023] [Indexed: 05/17/2023]
Abstract
PURPOSE Allogeneic blood transfusion (ABT) is current standard of blood replenishment despite known complications. Salvaged blood transfusion (SBT) addresses majority of such complications. Surgeons remain reluctant to employ SBT in metastatic spine tumour surgery (MSTS), despite ample laboratory evidence. This prompted us to conduct a prospective clinical study to ascertain safety of intraoperative cell salvage (IOCS), in MSTS. METHODS Our prospective study included 73 patients who underwent MSTS from 2014 to 2017. Demographics, tumour histology and burden, clinical findings, modified Tokuhashi score, operative and blood transfusion (BT) details were recorded. Patients were divided based on BT type: no blood transfusion (NBT) and SBT/ABT. Primary outcomes assessed were overall survival (OS), and tumour progression was evaluated using RECIST (v1.1) employing follow-up radiological investigations at 6, 12 and 24 months, classifying patients with non-progressive and progressive disease. RESULTS Seventy-three patients [39:34(M/F)] had mean age of 61 years. Overall median follow-up and survival were 26 and 12 months, respectively. All three groups were comparable for demographics and tumour characteristics. Overall median blood loss was 500 mL, and BT was 1000 mL. Twenty-six (35.6%) patients received SBT, 27 (37.0%) ABT and 20 (27.4%) NBT. Females had lower OS and higher risk of tumour progression. SBT had better OS and reduced risk of tumour progression than ABT group. Total blood loss was not associated with tumour progression. Infective complications other than SSI were significantly (p = 0.027) higher in ABT than NBT/SBT groups. CONCLUSIONS Patients of SBT had OS and tumour progression better than ABT/NBT groups. This is the first prospective study to report of SBT in comparison with control groups in MSTS.
Collapse
Affiliation(s)
- Naresh Kumar
- Department of Orthopaedic Surgery, Hand & Reconstructive Microsurgery Cluster, University Orthopaedics, National University Health System (NUHS) - Tower Block, Level 11, 1E Kent Ridge Road, Singapore, 119228, Singapore.
| | - Joel Yong Hao Tan
- Department of Orthopaedic Surgery, Hand & Reconstructive Microsurgery Cluster, University Orthopaedics, National University Health System (NUHS) - Tower Block, Level 11, 1E Kent Ridge Road, Singapore, 119228, Singapore
| | - Zhaojin Chen
- Investigational Medicine Unit, Center for Translational Medicine, 14 Medical Drive, #07-01, Singapore, 117599, Singapore
| | - Nivetha Ravikumar
- Department of Orthopaedic Surgery, Hand & Reconstructive Microsurgery Cluster, University Orthopaedics, National University Health System (NUHS) - Tower Block, Level 11, 1E Kent Ridge Road, Singapore, 119228, Singapore
| | - Helena Milavec
- Department of Orthopaedic Surgery, Hand & Reconstructive Microsurgery Cluster, University Orthopaedics, National University Health System (NUHS) - Tower Block, Level 11, 1E Kent Ridge Road, Singapore, 119228, Singapore
| | - Jiong Hao Tan
- Department of Orthopaedic Surgery, Hand & Reconstructive Microsurgery Cluster, University Orthopaedics, National University Health System (NUHS) - Tower Block, Level 11, 1E Kent Ridge Road, Singapore, 119228, Singapore
| |
Collapse
|
7
|
Ong W, Zhu L, Tan YL, Teo EC, Tan JH, Kumar N, Vellayappan BA, Ooi BC, Quek ST, Makmur A, Hallinan JTPD. Application of Machine Learning for Differentiating Bone Malignancy on Imaging: A Systematic Review. Cancers (Basel) 2023; 15:cancers15061837. [PMID: 36980722 PMCID: PMC10047175 DOI: 10.3390/cancers15061837] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 03/07/2023] [Accepted: 03/16/2023] [Indexed: 03/22/2023] Open
Abstract
An accurate diagnosis of bone tumours on imaging is crucial for appropriate and successful treatment. The advent of Artificial intelligence (AI) and machine learning methods to characterize and assess bone tumours on various imaging modalities may assist in the diagnostic workflow. The purpose of this review article is to summarise the most recent evidence for AI techniques using imaging for differentiating benign from malignant lesions, the characterization of various malignant bone lesions, and their potential clinical application. A systematic search through electronic databases (PubMed, MEDLINE, Web of Science, and clinicaltrials.gov) was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 34 articles were retrieved from the databases and the key findings were compiled and summarised. A total of 34 articles reported the use of AI techniques to distinguish between benign vs. malignant bone lesions, of which 12 (35.3%) focused on radiographs, 12 (35.3%) on MRI, 5 (14.7%) on CT and 5 (14.7%) on PET/CT. The overall reported accuracy, sensitivity, and specificity of AI in distinguishing between benign vs. malignant bone lesions ranges from 0.44–0.99, 0.63–1.00, and 0.73–0.96, respectively, with AUCs of 0.73–0.96. In conclusion, the use of AI to discriminate bone lesions on imaging has achieved a relatively good performance in various imaging modalities, with high sensitivity, specificity, and accuracy for distinguishing between benign vs. malignant lesions in several cohort studies. However, further research is necessary to test the clinical performance of these algorithms before they can be facilitated and integrated into routine clinical practice.
Collapse
Affiliation(s)
- Wilson Ong
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
- Correspondence: ; Tel.: +65-67725207
| | - Lei Zhu
- Department of Computer Science, School of Computing, National University of Singapore, 13 Computing Drive, Singapore 117417, Singapore
| | - Yi Liang Tan
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
| | - Ee Chin Teo
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
| | - Jiong Hao Tan
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E, Lower Kent Ridge Road, Singapore 119228, Singapore
| | - Naresh Kumar
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E, Lower Kent Ridge Road, Singapore 119228, Singapore
| | - Balamurugan A. Vellayappan
- Department of Radiation Oncology, National University Cancer Institute Singapore, National University Hospital, 5 Lower Kent Ridge Road, Singapore 119074, Singapore
| | - Beng Chin Ooi
- Department of Computer Science, School of Computing, National University of Singapore, 13 Computing Drive, Singapore 117417, Singapore
| | - Swee Tian Quek
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - Andrew Makmur
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - James Thomas Patrick Decourcy Hallinan
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| |
Collapse
|
8
|
Tan JH, Cheong FW, Lau YL, Fong MY. Plasmodium knowlesi circumsporozoite protein: genetic characterisation and predicted antigenicity of the central repeat region. Trop Biomed 2023; 40:37-44. [PMID: 37356002 DOI: ttps:/doi.org/10.47665/tb.40.1.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/27/2023]
Abstract
Circumsporozoite protein (CSP) central repeat region is one of the main target regions of the RTS,S/AS01 vaccine for falciparum infection as it consists of immunodominant B cell epitopes. However, there is a lack of study for P. knowlesi CSP central repeat region. This study aims to characterise the CSP repeat motifs of P. knowlesi isolates in Peninsular Malaysia. CSP repeat motifs of 64 P. knowlesi isolates were identified using Rapid Automatic Detection and Alignment of Repeats (RADAR). Antigenicity of the repeat motifs and linear B cell epitopes were predicted using VaxiJen 2.0, BepiPred-2.0 and BCPred, respectively. A total of 35 dominant repeat motifs were identified. The repeat motif "AGQPQAQGDGANAGQPQAQGDGAN" has the highest repeat frequency (n=15) and antigenicity index of 1.7986. All the repeat regions were predicted as B cell epitopes. In silico approaches revealed that all repeat motifs were antigenic and consisted of B cell epitopes which could be designed as knowlesi malaria vaccine.
Collapse
Affiliation(s)
- J H Tan
- Department of Parasitology, Faculty of Medicine, Universiti Malaya, 50603 Kuala Lumpur, Malaysia
| | - F W Cheong
- Department of Parasitology, Faculty of Medicine, Universiti Malaya, 50603 Kuala Lumpur, Malaysia
| | - Y L Lau
- Department of Parasitology, Faculty of Medicine, Universiti Malaya, 50603 Kuala Lumpur, Malaysia
| | - M Y Fong
- Department of Parasitology, Faculty of Medicine, Universiti Malaya, 50603 Kuala Lumpur, Malaysia
| |
Collapse
|
9
|
Hong CC, Chan MC, Wu T, Toh M, Tay YJ, Tan JH. Does concomitant gout in septic arthritis affect surgical outcomes? Injury 2023; 54:409-415. [PMID: 36351859 DOI: 10.1016/j.injury.2022.10.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Revised: 10/22/2022] [Accepted: 10/24/2022] [Indexed: 11/05/2022]
Abstract
BACKGROUND We aim to review and describe the proportion of patients with co-existing gout amongst patients with surgical treated septic arthritis, characterize their clinical presentation, outcomes and complications compared to patients with native joint septic arthritis. METHODS Sixty-one patients with surgically treated primary joint septic arthritis were identified from the period of January 2011 to December 2016. There were 13 (21.3%) patients with co-existing septic arthritis and crystal proven gout. Pertinent details such as demographics, comorbidities, clinical features on presentation, infection markers, number of surgeries, length of stay (LOS) in general and individual LOS in supportive care units, limb amputations, readmissions and mortality were reviewed. Multiple linear and logistic regression models were used to control for confounders during analysis. RESULTS The average age of patients was 60.8 years (range: 23-87 years). The patients with gout are associated with comorbidities such as being hypertensive, hyperlipidemia and renal impaired. They tend to present with ankle joint involvement (46.2% vs 8.3%; p = 0.004) while septic arthritis patients without gout tend to present with knee joint involvement (75% vs 46.2%; p = 0.046). In terms of complications, up to two thirds of them require supportive care in the High Dependency Unit and/or Intensive Care Unit during treatment (61.5% vs 29.2%; p = 0.031) and having gout with septic arthritis independently predicted a significant increase in LOS by an additional 12.6 days on average (95% CI: 2.11 - 23.03; p = 0.019). They are also more likely to end up with limb amputation (23.1% vs 0%; p = 0.008) on univariate analysis. CONCLUSION Gout accompanying septic arthritis in the same joint is potentially associated with major systemic and joint related sequela, complications in terms of prolonged hospital stay, need for complex care and risk for limb amputation. Our findings further indicate the value and need for well-designed prospective controlled cohort studies to explore the relationship between gout and septic arthritis.
Collapse
Affiliation(s)
- Choon Chiet Hong
- Department of Orthopaedic Surgery, National University Hospital, National University Health System, Singapore.
| | - Ming Chun Chan
- Department of Orthopaedic Surgery, National University Hospital, National University Health System, Singapore.
| | - Tianyi Wu
- Department of Orthopaedic Surgery, National University Hospital, National University Health System, Singapore.
| | - Mingzhou Toh
- Department of Orthopaedic Surgery, National University Hospital, National University Health System, Singapore
| | - Yuan Jie Tay
- Department of Orthopaedic Surgery, National University Hospital, National University Health System, Singapore.
| | - Jiong Hao Tan
- Department of Orthopaedic Surgery, National University Hospital, National University Health System, Singapore.
| |
Collapse
|
10
|
Hallinan JTPD, Zhu L, Zhang W, Ge S, Muhamat Nor FE, Ong HY, Eide SE, Cheng AJL, Kuah T, Lim DSW, Low XZ, Yeong KY, AlMuhaish MI, Alsooreti A, Kumarakulasinghe NB, Teo EC, Yap QV, Chan YH, Lin S, Tan JH, Kumar N, Vellayappan BA, Ooi BC, Quek ST, Makmur A. Deep learning assessment compared to radiologist reporting for metastatic spinal cord compression on CT. Front Oncol 2023; 13:1151073. [PMID: 37213273 PMCID: PMC10193838 DOI: 10.3389/fonc.2023.1151073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 03/16/2023] [Indexed: 05/23/2023] Open
Abstract
Introduction Metastatic spinal cord compression (MSCC) is a disastrous complication of advanced malignancy. A deep learning (DL) algorithm for MSCC classification on CT could expedite timely diagnosis. In this study, we externally test a DL algorithm for MSCC classification on CT and compare with radiologist assessment. Methods Retrospective collection of CT and corresponding MRI from patients with suspected MSCC was conducted from September 2007 to September 2020. Exclusion criteria were scans with instrumentation, no intravenous contrast, motion artefacts and non-thoracic coverage. Internal CT dataset split was 84% for training/validation and 16% for testing. An external test set was also utilised. Internal training/validation sets were labelled by radiologists with spine imaging specialization (6 and 11-years post-board certification) and were used to further develop a DL algorithm for MSCC classification. The spine imaging specialist (11-years expertise) labelled the test sets (reference standard). For evaluation of DL algorithm performance, internal and external test data were independently reviewed by four radiologists: two spine specialists (Rad1 and Rad2, 7 and 5-years post-board certification, respectively) and two oncological imaging specialists (Rad3 and Rad4, 3 and 5-years post-board certification, respectively). DL model performance was also compared against the CT report issued by the radiologist in a real clinical setting. Inter-rater agreement (Gwet's kappa) and sensitivity/specificity/AUCs were calculated. Results Overall, 420 CT scans were evaluated (225 patients, mean age=60 ± 11.9[SD]); 354(84%) CTs for training/validation and 66(16%) CTs for internal testing. The DL algorithm showed high inter-rater agreement for three-class MSCC grading with kappas of 0.872 (p<0.001) and 0.844 (p<0.001) on internal and external testing, respectively. On internal testing DL algorithm inter-rater agreement (κ=0.872) was superior to Rad 2 (κ=0.795) and Rad 3 (κ=0.724) (both p<0.001). DL algorithm kappa of 0.844 on external testing was superior to Rad 3 (κ=0.721) (p<0.001). CT report classification of high-grade MSCC disease was poor with only slight inter-rater agreement (κ=0.027) and low sensitivity (44.0), relative to the DL algorithm with almost-perfect inter-rater agreement (κ=0.813) and high sensitivity (94.0) (p<0.001). Conclusion Deep learning algorithm for metastatic spinal cord compression on CT showed superior performance to the CT report issued by experienced radiologists and could aid earlier diagnosis.
Collapse
Affiliation(s)
- James Thomas Patrick Decourcy Hallinan
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- *Correspondence: James Thomas Patrick Decourcy Hallinan,
| | - Lei Zhu
- Department of Computer Science, School of Computing, National University of Singapore, Singapore, Singapore
| | - Wenqiao Zhang
- Department of Computer Science, School of Computing, National University of Singapore, Singapore, Singapore
| | - Shuliang Ge
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore
| | - Faimee Erwan Muhamat Nor
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Han Yang Ong
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Sterling Ellis Eide
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Amanda J. L. Cheng
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Tricia Kuah
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore
| | - Desmond Shi Wei Lim
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore
| | - Xi Zhen Low
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore
| | - Kuan Yuen Yeong
- Department of Radiology, Ng Teng Fong General Hospital, Singapore, Singapore
| | - Mona I. AlMuhaish
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore
- Department of Radiology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Ahmed Mohamed Alsooreti
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore
- Department of Diagnostic Imaging, Salmaniya Medical Complex, Manama, Bahrain
| | | | - Ee Chin Teo
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore
| | - Qai Ven Yap
- Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore, Singapore
| | - Yiong Huak Chan
- Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore, Singapore
| | - Shuxun Lin
- Division of Spine Surgery, Department of Orthopaedic Surgery, Ng Teng Fong General Hospital, Singapore, Singapore
| | - Jiong Hao Tan
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore, Singapore
| | - Naresh Kumar
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore, Singapore
| | - Balamurugan A. Vellayappan
- Department of Radiation Oncology, National University Cancer Institute Singapore, National University Hospital, Singapore, Singapore
| | - Beng Chin Ooi
- Department of Computer Science, School of Computing, National University of Singapore, Singapore, Singapore
| | - Swee Tian Quek
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Andrew Makmur
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| |
Collapse
|
11
|
Liu G, Tan JH, Kong JC, Tan YHJ, Kumar N, Liang S, Shawn SJS, Ting CS, Lim LL, Dennis HHW, Kumar N, Thambiah J, Wong HK. Thoracolumbar Injury Classification and Severity Score Is Predictive of Perioperative Adverse Events in Operatively Treated Thoracic and Lumbar Fractures. Asian Spine J 2022; 16:848-856. [PMID: 36599371 PMCID: PMC9827217 DOI: 10.31616/asj.2021.0231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 01/03/2022] [Indexed: 12/31/2022] Open
Abstract
STUDY DESIGN A retrospective cohort study of patients with surgically treated thoracolumbar fractures. PURPOSE This study aimed to describe the incidence of adverse events (AEs) after surgical stabilization of thoracolumbar spine injuries and to identify predictive factors for the occurrence of AEs. OVERVIEW OF LITERATURE Thoracolumbar spine fractures are frequently present in patients with blunt trauma and are associated with significant morbidity. AEs can occur due to the initial spinal injury or secondary to surgical treatment. There is a lack of emphasis in the literature on the AEs that can occur after operative management of thoracolumbar fractures. METHODS We performed a retrospective review of 199 patients with surgically treated thoracolumbar fractures operated between January 2007 and January 2018. The potential risk factors for the development of AEs as well as the development of common complications were evaluated by univariate analysis, and a multivariate logistic regression analysis was performed to identify independent risk factors predictive of the above. RESULTS The overall rate of AEs was 46.7%; 83 patients (41.7%) had nonsurgical AEs, whereas 24 (12.1%) had surgical adverse events. The most common AEs were urinary tract infections in 43 patients (21.6%), and hospital-acquired pneumonia in 21 patients (10.6%). On multivariate logistic regression, a Thoracolumbar Injury Classification and Severity (TLICS) score of 8-10 (odds ratio [OR], 6.39; 95% confidence interval [CI], 2.33-17.51), the presence of polytrauma (OR, 2.64; 95% CI, 1.17-5.99), and undergoing open surgery (OR, 2.31; 95% CI, 1.09-4.88) were significant risk factors for AEs. The absence of neurological deficit was associated with a lower rate of AEs (OR, 0.47; 95% CI, 0.31-0.70). CONCLUSIONS This study suggests the presence of polytrauma, preoperative American Spinal Injury Association score, and TLICS score are predictive of AEs in patients with surgically treated thoracolumbar fractures. The results might also suggest a role for minimally invasive surgical methods in reducing AEs in these patients.
Collapse
Affiliation(s)
- Gabriel Liu
- University Spine Centre, Department of Orthopaedic Surgery, National University Hospital, Singapore,Corresponding author: Gabriel Liu University Spine Centre, Department of Orthopaedic Surgery, National University Hospital, Singapore Tel: +65-677224330, Fax: +65-67780720, E-mail:
| | - Jiong Hao Tan
- University Spine Centre, Department of Orthopaedic Surgery, National University Hospital, Singapore
| | - Jun Cheong Kong
- University Spine Centre, Department of Orthopaedic Surgery, National University Hospital, Singapore
| | - Yong Hao Joel Tan
- University Spine Centre, Department of Orthopaedic Surgery, National University Hospital, Singapore
| | - Nishant Kumar
- University Spine Centre, Department of Orthopaedic Surgery, National University Hospital, Singapore
| | - Shen Liang
- Biostatistics Unit, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | | | - Chiu Shi Ting
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Lau Leok Lim
- University Spine Centre, Department of Orthopaedic Surgery, National University Hospital, Singapore
| | - Hey Hwee Weng Dennis
- University Spine Centre, Department of Orthopaedic Surgery, National University Hospital, Singapore
| | - Naresh Kumar
- University Spine Centre, Department of Orthopaedic Surgery, National University Hospital, Singapore
| | - Joseph Thambiah
- University Spine Centre, Department of Orthopaedic Surgery, National University Hospital, Singapore
| | - Hee-Kit Wong
- University Spine Centre, Department of Orthopaedic Surgery, National University Hospital, Singapore
| |
Collapse
|
12
|
Hallinan JTPD, Ge S, Zhu L, Zhang W, Lim YT, Thian YL, Jagmohan P, Kuah T, Lim DSW, Low XZ, Teo EC, Barr Kumarakulasinghe N, Yap QV, Chan YH, Tan JH, Kumar N, Vellayappan BA, Ooi BC, Quek ST, Makmur A. Diagnostic Accuracy of CT for Metastatic Epidural Spinal Cord Compression. Cancers (Basel) 2022; 14:cancers14174231. [PMID: 36077767 PMCID: PMC9454807 DOI: 10.3390/cancers14174231] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 08/23/2022] [Accepted: 08/25/2022] [Indexed: 11/16/2022] Open
Abstract
Background: Early diagnosis of metastatic epidural spinal cord compression (MESCC) is vital to expedite therapy and prevent paralysis. Staging CT is performed routinely in cancer patients and presents an opportunity for earlier diagnosis. Methods: This retrospective study included 123 CT scans from 101 patients who underwent spine MRI within 30 days, excluding 549 CT scans from 216 patients due to CT performed post-MRI, non-contrast CT, or a gap greater than 30 days between modalities. Reference standard MESCC gradings on CT were provided in consensus via two spine radiologists (11 and 7 years of experience) analyzing the MRI scans. CT scans were labeled using the original reports and by three radiologists (3, 13, and 14 years of experience) using dedicated CT windowing. Results: For normal/none versus low/high-grade MESCC per CT scan, all radiologists demonstrated almost perfect agreement with kappa values ranging from 0.866 (95% CI 0.787–0.945) to 0.947 (95% CI 0.899–0.995), compared to slight agreement for the reports (kappa = 0.095, 95%CI −0.098–0.287). Radiologists also showed high sensitivities ranging from 91.51 (95% CI 84.49–96.04) to 98.11 (95% CI 93.35–99.77), compared to 44.34 (95% CI 34.69–54.31) for the reports. Conclusion: Dedicated radiologist review for MESCC on CT showed high interobserver agreement and sensitivity compared to the current standard of care.
Collapse
Affiliation(s)
- James Thomas Patrick Decourcy Hallinan
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
- Correspondence:
| | - Shuliang Ge
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - Lei Zhu
- Department of Computer Science, School of Computing, National University of Singapore, 13 Computing Drive, Singapore 117417, Singapore
| | - Wenqiao Zhang
- Department of Computer Science, School of Computing, National University of Singapore, 13 Computing Drive, Singapore 117417, Singapore
| | - Yi Ting Lim
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - Yee Liang Thian
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - Pooja Jagmohan
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - Tricia Kuah
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
| | - Desmond Shi Wei Lim
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
| | - Xi Zhen Low
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
| | - Ee Chin Teo
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
| | - Nesaretnam Barr Kumarakulasinghe
- National University Cancer Institute, NUH Medical Centre (NUHMC), Levels 8–10, 5 Lower Kent Ridge Road, Singapore 119074, Singapore
| | - Qai Ven Yap
- Biostatistics Unit, Yong Loo Lin School of Medicine, 10 Medical Drive, Singapore 117597, Singapore
| | - Yiong Huak Chan
- Biostatistics Unit, Yong Loo Lin School of Medicine, 10 Medical Drive, Singapore 117597, Singapore
| | - Jiong Hao Tan
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E, Lower Kent Ridge Road, Singapore 119228, Singapore
| | - Naresh Kumar
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E, Lower Kent Ridge Road, Singapore 119228, Singapore
| | - Balamurugan A. Vellayappan
- Department of Radiation Oncology, National University Cancer Institute Singapore, National University Hospital, Singapore 119074, Singapore
| | - Beng Chin Ooi
- Department of Computer Science, School of Computing, National University of Singapore, 13 Computing Drive, Singapore 117417, Singapore
| | - Swee Tian Quek
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - Andrew Makmur
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| |
Collapse
|
13
|
Ong W, Zhu L, Zhang W, Kuah T, Lim DSW, Low XZ, Thian YL, Teo EC, Tan JH, Kumar N, Vellayappan BA, Ooi BC, Quek ST, Makmur A, Hallinan JTPD. Application of Artificial Intelligence Methods for Imaging of Spinal Metastasis. Cancers (Basel) 2022; 14:4025. [PMID: 36011018 PMCID: PMC9406500 DOI: 10.3390/cancers14164025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 08/10/2022] [Accepted: 08/15/2022] [Indexed: 11/16/2022] Open
Abstract
Spinal metastasis is the most common malignant disease of the spine. Recently, major advances in machine learning and artificial intelligence technology have led to their increased use in oncological imaging. The purpose of this study is to review and summarise the present evidence for artificial intelligence applications in the detection, classification and management of spinal metastasis, along with their potential integration into clinical practice. A systematic, detailed search of the main electronic medical databases was undertaken in concordance with the PRISMA guidelines. A total of 30 articles were retrieved from the database and reviewed. Key findings of current AI applications were compiled and summarised. The main clinical applications of AI techniques include image processing, diagnosis, decision support, treatment assistance and prognostic outcomes. In the realm of spinal oncology, artificial intelligence technologies have achieved relatively good performance and hold immense potential to aid clinicians, including enhancing work efficiency and reducing adverse events. Further research is required to validate the clinical performance of the AI tools and facilitate their integration into routine clinical practice.
Collapse
Affiliation(s)
- Wilson Ong
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd., Singapore 119074, Singapore
| | - Lei Zhu
- Department of Computer Science, School of Computing, National University of Singapore, 13 Computing Drive, Singapore 117417, Singapore
| | - Wenqiao Zhang
- Department of Computer Science, School of Computing, National University of Singapore, 13 Computing Drive, Singapore 117417, Singapore
| | - Tricia Kuah
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd., Singapore 119074, Singapore
| | - Desmond Shi Wei Lim
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd., Singapore 119074, Singapore
| | - Xi Zhen Low
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd., Singapore 119074, Singapore
| | - Yee Liang Thian
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd., Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - Ee Chin Teo
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd., Singapore 119074, Singapore
| | - Jiong Hao Tan
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E, Lower Kent Ridge Road, Singapore 119228, Singapore
| | - Naresh Kumar
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E, Lower Kent Ridge Road, Singapore 119228, Singapore
| | - Balamurugan A. Vellayappan
- Department of Radiation Oncology, National University Cancer Institute Singapore, National University Hospital, Singapore 119074, Singapore
| | - Beng Chin Ooi
- Department of Computer Science, School of Computing, National University of Singapore, 13 Computing Drive, Singapore 117417, Singapore
| | - Swee Tian Quek
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd., Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - Andrew Makmur
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd., Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - James Thomas Patrick Decourcy Hallinan
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd., Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| |
Collapse
|
14
|
Kuah T, Vellayappan BA, Makmur A, Nair S, Song J, Tan JH, Kumar N, Quek ST, Hallinan JTPD. State-of-the-Art Imaging Techniques in Metastatic Spinal Cord Compression. Cancers (Basel) 2022; 14:cancers14133289. [PMID: 35805059 PMCID: PMC9265325 DOI: 10.3390/cancers14133289] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 06/24/2022] [Accepted: 06/28/2022] [Indexed: 12/23/2022] Open
Abstract
Metastatic Spinal Cord Compression (MSCC) is a debilitating complication in oncology patients. This narrative review discusses the strengths and limitations of various imaging modalities in diagnosing MSCC, the role of imaging in stereotactic body radiotherapy (SBRT) for MSCC treatment, and recent advances in deep learning (DL) tools for MSCC diagnosis. PubMed and Google Scholar databases were searched using targeted keywords. Studies were reviewed in consensus among the co-authors for their suitability before inclusion. MRI is the gold standard of imaging to diagnose MSCC with reported sensitivity and specificity of 93% and 97% respectively. CT Myelogram appears to have comparable sensitivity and specificity to contrast-enhanced MRI. Conventional CT has a lower diagnostic accuracy than MRI in MSCC diagnosis, but is helpful in emergent situations with limited access to MRI. Metal artifact reduction techniques for MRI and CT are continually being researched for patients with spinal implants. Imaging is crucial for SBRT treatment planning and three-dimensional positional verification of the treatment isocentre prior to SBRT delivery. Structural and functional MRI may be helpful in post-treatment surveillance. DL tools may improve detection of vertebral metastasis and reduce time to MSCC diagnosis. This enables earlier institution of definitive therapy for better outcomes.
Collapse
Affiliation(s)
- Tricia Kuah
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore; (A.M.); (S.N.); (J.S.); (S.T.Q.); (J.T.P.D.H.)
- Correspondence: ; Tel.: +65-6779-5555
| | - Balamurugan A. Vellayappan
- Department of Radiation Oncology, National University Cancer Institute Singapore, National University Hospital, Singapore 119074, Singapore;
| | - Andrew Makmur
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore; (A.M.); (S.N.); (J.S.); (S.T.Q.); (J.T.P.D.H.)
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - Shalini Nair
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore; (A.M.); (S.N.); (J.S.); (S.T.Q.); (J.T.P.D.H.)
| | - Junda Song
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore; (A.M.); (S.N.); (J.S.); (S.T.Q.); (J.T.P.D.H.)
| | - Jiong Hao Tan
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E Lower Kent Ridge Road, Singapore 119228, Singapore; (J.H.T.); (N.K.)
| | - Naresh Kumar
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E Lower Kent Ridge Road, Singapore 119228, Singapore; (J.H.T.); (N.K.)
| | - Swee Tian Quek
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore; (A.M.); (S.N.); (J.S.); (S.T.Q.); (J.T.P.D.H.)
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - James Thomas Patrick Decourcy Hallinan
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore; (A.M.); (S.N.); (J.S.); (S.T.Q.); (J.T.P.D.H.)
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| |
Collapse
|
15
|
Lim DSW, Makmur A, Zhu L, Zhang W, Cheng AJL, Sia DSY, Eide SE, Ong HY, Jagmohan P, Tan WC, Khoo VM, Wong YM, Thian YL, Baskar S, Teo EC, Algazwi DAR, Yap QV, Chan YH, Tan JH, Kumar N, Ooi BC, Yoshioka H, Quek ST, Hallinan JTPD. Improved Productivity Using Deep Learning-assisted Reporting for Lumbar Spine MRI. Radiology 2022; 305:160-166. [PMID: 35699577 DOI: 10.1148/radiol.220076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background Lumbar spine MRI studies are widely used for back pain assessment. Interpretation involves grading lumbar spinal stenosis, which is repetitive and time consuming. Deep learning (DL) could provide faster and more consistent interpretation. Purpose To assess the speed and interobserver agreement of radiologists for reporting lumbar spinal stenosis with and without DL assistance. Materials and Methods In this retrospective study, a DL model designed to assist radiologists in the interpretation of spinal canal, lateral recess, and neural foraminal stenoses on lumbar spine MRI scans was used. Randomly selected lumbar spine MRI studies obtained in patients with back pain who were 18 years and older over a 3-year period, from September 2015 to September 2018, were included in an internal test data set. Studies with instrumentation and scoliosis were excluded. Eight radiologists, each with 2-13 years of experience in spine MRI interpretation, reviewed studies with and without DL model assistance with a 1-month washout period. Time to diagnosis (in seconds) and interobserver agreement (using Gwet κ) were assessed for stenosis grading for each radiologist with and without the DL model and compared with test data set labels provided by an external musculoskeletal radiologist (with 32 years of experience) as the reference standard. Results Overall, 444 images in 25 patients (mean age, 51 years ± 20 [SD]; 14 women) were evaluated in a test data set. DL-assisted radiologists had a reduced interpretation time per spine MRI study, from a mean of 124-274 seconds (SD, 25-88 seconds) to 47-71 seconds (SD, 24-29 seconds) (P < .001). DL-assisted radiologists had either superior or equivalent interobserver agreement for all stenosis gradings compared with unassisted radiologists. DL-assisted general and in-training radiologists improved their interobserver agreement for four-class neural foraminal stenosis, with κ values of 0.71 and 0.70 (with DL) versus 0.39 and 0.39 (without DL), respectively (both P < .001). Conclusion Radiologists who were assisted by deep learning for interpretation of lumbar spinal stenosis on MRI scans showed a marked reduction in reporting time and superior or equivalent interobserver agreement for all stenosis gradings compared with radiologists who were unassisted by deep learning. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Hayashi in this issue.
Collapse
Affiliation(s)
- Desmond Shi Wei Lim
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Andrew Makmur
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Lei Zhu
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Wenqiao Zhang
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Amanda J L Cheng
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - David Soon Yiew Sia
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Sterling Ellis Eide
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Han Yang Ong
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Pooja Jagmohan
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Wei Chuan Tan
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Vanessa Meihui Khoo
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Ying Mei Wong
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Yee Liang Thian
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Sangeetha Baskar
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Ee Chin Teo
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Diyaa Abdul Rauf Algazwi
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Qai Ven Yap
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Yiong Huak Chan
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Jiong Hao Tan
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Naresh Kumar
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Beng Chin Ooi
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Hiroshi Yoshioka
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Swee Tian Quek
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - James Thomas Patrick Decourcy Hallinan
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (D.S.W.L., A.M., A.J.L.C., D.S.Y.S., S.E.E., H.Y.O., P.J., W.C.T., V.M.K., Y.M.W., Y.L.T., S.B., E.C.T., S.T.Q., J.T.P.D.H.); Department of Diagnostic Radiology (A.M., S.E.E., P.J., Y.L.T., S.T.Q., J.T.P.D.H.), NUS Graduate School, Integrative Sciences and Engineering Programme (L.Z.), Department of Computer Science, School of Computing (W.Z., B.C.O.), and Biostatistics Unit, Yong Loo Lin School of Medicine (Q.V.Y., Y.H.C.), National University of Singapore, Singapore; Department of Radiology, Qatif Central Hospital, Qatif, Saudi Arabia (D.A.R.A.); Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| |
Collapse
|
16
|
Hallinan JTPD, Zhu L, Zhang W, Lim DSW, Baskar S, Low XZ, Yeong KY, Teo EC, Kumarakulasinghe NB, Yap QV, Chan YH, Lin S, Tan JH, Kumar N, Vellayappan BA, Ooi BC, Quek ST, Makmur A. Deep Learning Model for Classifying Metastatic Epidural Spinal Cord Compression on MRI. Front Oncol 2022; 12:849447. [PMID: 35600347 PMCID: PMC9114468 DOI: 10.3389/fonc.2022.849447] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 03/18/2022] [Indexed: 11/13/2022] Open
Abstract
Background Metastatic epidural spinal cord compression (MESCC) is a devastating complication of advanced cancer. A deep learning (DL) model for automated MESCC classification on MRI could aid earlier diagnosis and referral. Purpose To develop a DL model for automated classification of MESCC on MRI. Materials and Methods Patients with known MESCC diagnosed on MRI between September 2007 and September 2017 were eligible. MRI studies with instrumentation, suboptimal image quality, and non-thoracic regions were excluded. Axial T2-weighted images were utilized. The internal dataset split was 82% and 18% for training/validation and test sets, respectively. External testing was also performed. Internal training/validation data were labeled using the Bilsky MESCC classification by a musculoskeletal radiologist (10-year experience) and a neuroradiologist (5-year experience). These labels were used to train a DL model utilizing a prototypical convolutional neural network. Internal and external test sets were labeled by the musculoskeletal radiologist as the reference standard. For assessment of DL model performance and interobserver variability, test sets were labeled independently by the neuroradiologist (5-year experience), a spine surgeon (5-year experience), and a radiation oncologist (11-year experience). Inter-rater agreement (Gwet’s kappa) and sensitivity/specificity were calculated. Results Overall, 215 MRI spine studies were analyzed [164 patients, mean age = 62 ± 12(SD)] with 177 (82%) for training/validation and 38 (18%) for internal testing. For internal testing, the DL model and specialists all showed almost perfect agreement (kappas = 0.92–0.98, p < 0.001) for dichotomous Bilsky classification (low versus high grade) compared to the reference standard. Similar performance was seen for external testing on a set of 32 MRI spines with the DL model and specialists all showing almost perfect agreement (kappas = 0.94–0.95, p < 0.001) compared to the reference standard. Conclusion A DL model showed comparable agreement to a subspecialist radiologist and clinical specialists for the classification of malignant epidural spinal cord compression and could optimize earlier diagnosis and surgical referral.
Collapse
Affiliation(s)
- James Thomas Patrick Decourcy Hallinan
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore.,Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Lei Zhu
- NUS Graduate School, Integrative Sciences and Engineering Programme, National University of Singapore, Singapore, Singapore
| | - Wenqiao Zhang
- Department of Computer Science, School of Computing, National University of Singapore, Singapore, Singapore
| | - Desmond Shi Wei Lim
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore.,Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Sangeetha Baskar
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore
| | - Xi Zhen Low
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore.,Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Kuan Yuen Yeong
- Department of Radiology, Ng Teng Fong General Hospital, Singapore, Singapore
| | - Ee Chin Teo
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore
| | | | - Qai Ven Yap
- Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore, Singapore
| | - Yiong Huak Chan
- Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore, Singapore
| | - Shuxun Lin
- Division of Spine Surgery, Department of Orthopaedic Surgery, Ng Teng Fong General Hospital, Singapore, Singapore
| | - Jiong Hao Tan
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore, Singapore
| | - Naresh Kumar
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore, Singapore
| | - Balamurugan A Vellayappan
- Department of Radiation Oncology, National University Cancer Institute Singapore, National University Hospital, Singapore, Singapore
| | - Beng Chin Ooi
- Department of Computer Science, School of Computing, National University of Singapore, Singapore, Singapore
| | - Swee Tian Quek
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore.,Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Andrew Makmur
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore.,Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| |
Collapse
|
17
|
Tan JH, Ng S, Foo D. The curious case of missing heartbeats. Med J Malaysia 2022; 77:399-402. [PMID: 35638500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Paroxysmal atrioventricular block (AVB) is a poorly defined and easily missed bradyarrhythmia, which can potentially lead to sudden cardiac death. It is under-recognised due to its abrupt onset and unpredictability. We describe a case that had paroxysmal AVB post-coronary angioplasty and highlight the mechanism as well as the management of this rare condition.
Collapse
Affiliation(s)
- J H Tan
- Tan Tock Seng Hospital, Singapore
| | - S Ng
- Tan Tock Seng Hospital, Singapore
| | - D Foo
- Tan Tock Seng Hospital, Singapore
| |
Collapse
|
18
|
Kamarajah SK, Evans RPT, Nepogodiev D, Hodson J, Bundred JR, Gockel I, Gossage JA, Isik A, Kidane B, Mahendran HA, Negoi I, Okonta KE, Sayyed R, van Hillegersberg R, Vohra RS, Wijnhoven BPL, Singh P, Griffiths EA, Kamarajah SK, Hodson J, Griffiths EA, Alderson D, Bundred J, Evans RPT, Gossage J, Griffiths EA, Jefferies B, Kamarajah SK, McKay S, Mohamed I, Nepogodiev D, Siaw-Acheampong K, Singh P, van Hillegersberg R, Vohra R, Wanigasooriya K, Whitehouse T, Gjata A, Moreno JI, Takeda FR, Kidane B, Guevara Castro R, Harustiak T, Bekele A, Kechagias A, Gockel I, Kennedy A, Da Roit A, Bagajevas A, Azagra JS, Mahendran HA, Mejía-Fernández L, Wijnhoven BPL, El Kafsi J, Sayyed RH, Sousa M M, Sampaio AS, Negoi I, Blanco R, Wallner B, Schneider PM, Hsu PK, Isik A, Gananadha S, Wills V, Devadas M, Duong C, Talbot M, Hii MW, Jacobs R, Andreollo NA, Johnston B, Darling G, Isaza-Restrepo A, Rosero G, Arias-Amézquita F, Raptis D, Gaedcke J, Reim D, Izbicki J, Egberts JH, Dikinis S, Kjaer DW, Larsen MH, Achiam MP, Saarnio J, Theodorou D, Liakakos T, Korkolis DP, Robb WB, Collins C, Murphy T, Reynolds J, Tonini V, Migliore M, Bonavina L, Valmasoni M, Bardini R, Weindelmayer J, Terashima M, White RE, Alghunaim E, Elhadi M, Leon-Takahashi AM, Medina-Franco H, Lau PC, Okonta KE, Heisterkamp J, Rosman C, van Hillegersberg R, Beban G, Babor R, Gordon A, Rossaak JI, Pal KMI, Qureshi AU, Naqi SA, Syed AA, Barbosa J, Vicente CS, Leite J, Freire J, Casaca R, Costa RCT, Scurtu RR, Mogoanta SS, Bolca C, Constantinoiu S, Sekhniaidze D, Bjelović M, So JBY, Gačevski G, Loureiro C, Pera M, Bianchi A, Moreno Gijón M, Martín Fernández J, Trugeda Carrera MS, Vallve-Bernal M, Cítores Pascual MA, Elmahi S, Halldestam I, Hedberg J, Mönig S, Gutknecht S, Tez M, Guner A, Tirnaksiz MB, Colak E, Sevinç B, Hindmarsh A, Khan I, Khoo D, Byrom R, Gokhale J, Wilkerson P, Jain P, Chan D, Robertson K, Iftikhar S, Skipworth R, Forshaw M, Higgs S, Gossage J, Nijjar R, Viswanath YKS, Turner P, Dexter S, Boddy A, Allum WH, Oglesby S, Cheong E, Beardsmore D, Vohra R, Maynard N, Berrisford R, Mercer S, Puig S, Melhado R, Kelty C, Underwood T, Dawas K, Lewis W, Bryce G, Thomas M, Arndt AT, Palazzo F, Meguid RA, Fergusson J, Beenen E, Mosse C, Salim J, Cheah S, Wright T, Cerdeira MP, McQuillan P, Richardson M, Liem H, Spillane J, Yacob M, Albadawi F, Thorpe T, Dingle A, Cabalag C, Loi K, Fisher OM, Ward S, Read M, Johnson M, Bassari R, Bui H, Cecconello I, Sallum RAA, da Rocha JRM, Lopes LR, Tercioti Jr V, Coelho JDS, Ferrer JAP, Buduhan G, Tan L, Srinathan S, Shea P, Yeung J, Allison F, Carroll P, Vargas-Barato F, Gonzalez F, Ortega J, Nino-Torres L, Beltrán-García TC, Castilla L, Pineda M, Bastidas A, Gómez-Mayorga J, Cortés N, Cetares C, Caceres S, Duarte S, Pazdro A, Snajdauf M, Faltova H, Sevcikova M, Mortensen PB, Katballe N, Ingemann T, Morten B, Kruhlikava I, Ainswort AP, Stilling NM, Eckardt J, Holm J, Thorsteinsson M, Siemsen M, Brandt B, Nega B, Teferra E, Tizazu A, Kauppila JH, Koivukangas V, Meriläinen S, Gruetzmann R, Krautz C, Weber G, Golcher H, Emons G, Azizian A, Ebeling M, Niebisch S, Kreuser N, Albanese G, Hesse J, Volovnik L, Boecher U, Reeh M, Triantafyllou S, Schizas D, Michalinos A, Balli E, Mpoura M, Charalabopoulos A, Manatakis DK, Balalis D, Bolger J, Baban C, Mastrosimone A, McAnena O, Quinn A, Ó Súilleabháin CB, Hennessy MM, Ivanovski I, Khizer H, Ravi N, Donlon N, Cervellera M, Vaccari S, Bianchini S, Asti E, Bernardi D, Merigliano S, Provenzano L, Scarpa M, Saadeh L, Salmaso B, De Manzoni G, Giacopuzzi S, La Mendola R, De Pasqual CA, Tsubosa Y, Niihara M, Irino T, Makuuchi R, Ishii K K, Mwachiro M, Fekadu A, Odera A, Mwachiro E, AlShehab D, Ahmed HA, Shebani AO, Elhadi A, Elnagar FA, Elnagar HF, Makkai-Popa ST, Wong LF, Tan YR, Thannimalai S, Ho CA, Pang WS, Tan JH, Basave HNL, Cortés-González R, Lagarde SM, van Lanschot JJB, Cords C, Jansen WA, Martijnse I, Matthijsen R, Bouwense S, Klarenbeek B, Verstegen M, van Workum F, Ruurda JP, van der Sluis PC, de Maat M, Evenett N, Johnston P, Patel R, MacCormick A, Smith B, Ekwunife C, Memon AH, Shaikh K, Wajid A, Khalil N, Haris M, Mirza ZU, Qudus SBA, Sarwar MZ, Shehzadi A, Raza A, Jhanzaib MH, Farmanali J, Zakir Z, Shakeel O, Nasir I, Khattak S, Baig M, Noor MA, Ahmed HH, Naeem A, Pinho AC, da Silva R, Bernardes A, Campos JC, Matos H, Braga T, Monteiro C, Ramos P, Cabral F, Gomes MP, Martins PC, Correia AM, Videira JF, Ciuce C, Drasovean R, Apostu R, Ciuce C, Paitici S, Racu AE, Obleaga CV, Beuran M, Stoica B, Ciubotaru C, Negoita V, Cordos I, Birla RD, Predescu D, Hoara PA, Tomsa R, Shneider V, Agasiev M, Ganjara I, Gunjić D, Veselinović M, Babič T, Chin TS, Shabbir A, Kim G, Crnjac A, Samo H, Díez del Val I, Leturio S, Ramón JM, Dal Cero M, Rifá S, Rico M, Pagan Pomar A, Martinez Corcoles JA, Rodicio Miravalles JL, Pais SA, Turienzo SA, Alvarez LS, Campos PV, Rendo AG, García SS, Santos EPG, Martínez ET, Fernández Díaz MJ, Magadán Álvarez C, Concepción Martín V, Díaz López C, Rosat Rodrigo A, Pérez Sánchez LE, Bailón Cuadrado M, Tinoco Carrasco C, Choolani Bhojwani E, Sánchez DP, Ahmed ME, Dzhendov T, Lindberg F, Rutegård M, Sundbom M, Mickael C, Colucci N, Schnider A, Er S, Kurnaz E, Turkyilmaz S, Turkyilmaz A, Yildirim R, Baki BE, Akkapulu N, Karahan O, Damburaci N, Hardwick R, Safranek P, Sujendran V, Bennett J, Afzal Z, Shrotri M, Chan B, Exarchou K, Gilbert T, Amalesh T, Mukherjee D, Mukherjee S, Wiggins TH, Kennedy R, McCain S, Harris A, Dobson G, Davies N, Wilson I, Mayo D, Bennett D, Young R, Manby P, Blencowe N, Schiller M, Byrne B, Mitton D, Wong V, Elshaer A, Cowen M, Menon V, Tan LC, McLaughlin E, Koshy R, Sharp C, Brewer H, Das N, Cox M, Al Khyatt W, Worku D, Iqbal R, Walls L, McGregor R, Fullarton G, Macdonald A, MacKay C, Craig C, Dwerryhouse S, Hornby S, Jaunoo S, Wadley M, Baker C, Saad M, Kelly M, Davies A, Di Maggio F, McKay S, Mistry P, Singhal R, Tucker O, Kapoulas S, Powell-Brett S, Davis P, Bromley G, Watson L, Verma R, Ward J, Shetty V, Ball C, Pursnani K, Sarela A, Sue Ling H, Mehta S, Hayden J, To N, Palser T, Hunter D, Supramaniam K, Butt Z, Ahmed A, Kumar S, Chaudry A, Moussa O, Kordzadeh A, Lorenzi B, Wilson M, Patil P, Noaman I, Bouras G, Evans R, Singh M, Warrilow H, Ahmad A, Tewari N, Yanni F, Couch J, Theophilidou E, Reilly JJ, Singh P, van Boxel G, Akbari K, Zanotti D, Sanders G, Wheatley T, Ariyarathenam A, Reece-Smith A, Humphreys L, Choh C, Carter N, Knight B, Pucher P, Athanasiou A, Mohamed I, Tan B, Abdulrahman M, Vickers J, Akhtar K, Chaparala R, Brown R, Alasmar MMA, Ackroyd R, Patel K, Tamhankar A, Wyman A, Walker R, Grace B, Abbassi N, Slim N, Ioannidi L, Blackshaw G, Havard T, Escofet X, Powell A, Owera A, Rashid F, Jambulingam P, Padickakudi J, Ben-Younes H, Mccormack K, Makey IA, Karush MK, Seder CW, Liptay MJ, Chmielewski G, Rosato EL, Berger AC, Zheng R, Okolo E, Singh A, Scott CD, Weyant MJ, Mitchell JD. Textbook outcome following oesophagectomy for cancer: international cohort study. Br J Surg 2022. [DOI: https://doi.org/10.1093/bjs/znac016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Abstract
Background
Textbook outcome has been proposed as a tool for the assessment of oncological surgical care. However, an international assessment in patients undergoing oesophagectomy for oesophageal cancer has not been reported. This study aimed to assess textbook outcome in an international setting.
Methods
Patients undergoing curative resection for oesophageal cancer were identified from the international Oesophagogastric Anastomosis Audit (OGAA) from April 2018 to December 2018. Textbook outcome was defined as the percentage of patients who underwent a complete tumour resection with at least 15 lymph nodes in the resected specimen and an uneventful postoperative course, without hospital readmission. A multivariable binary logistic regression model was used to identify factors independently associated with textbook outcome, and results are presented as odds ratio (OR) and 95 per cent confidence intervals (95 per cent c.i.).
Results
Of 2159 patients with oesophageal cancer, 39.7 per cent achieved a textbook outcome. The outcome parameter ‘no major postoperative complication’ had the greatest negative impact on a textbook outcome for patients with oesophageal cancer, compared to other textbook outcome parameters. Multivariable analysis identified male gender and increasing Charlson comorbidity index with a significantly lower likelihood of textbook outcome. Presence of 24-hour on-call rota for oesophageal surgeons (OR 2.05, 95 per cent c.i. 1.30 to 3.22; P = 0.002) and radiology (OR 1.54, 95 per cent c.i. 1.05 to 2.24; P = 0.027), total minimally invasive oesophagectomies (OR 1.63, 95 per cent c.i. 1.27 to 2.08; P < 0.001), and chest anastomosis above azygous (OR 2.17, 95 per cent c.i. 1.58 to 2.98; P < 0.001) were independently associated with a significantly increased likelihood of textbook outcome.
Conclusion
Textbook outcome is achieved in less than 40 per cent of patients having oesophagectomy for cancer. Improvements in centralization, hospital resources, access to minimal access surgery, and adoption of newer techniques for improving lymph node yield could improve textbook outcome.
Collapse
|
19
|
Kamarajah SK, Evans RPT, Nepogodiev D, Hodson J, Bundred JR, Gockel I, Gossage JA, Isik A, Kidane B, Mahendran HA, Negoi I, Okonta KE, Sayyed R, van Hillegersberg R, Vohra RS, Wijnhoven BPL, Singh P, Griffiths EA, Kamarajah SK, Hodson J, Griffiths EA, Alderson D, Bundred J, Evans RPT, Gossage J, Griffiths EA, Jefferies B, Kamarajah SK, McKay S, Mohamed I, Nepogodiev D, Siaw-Acheampong K, Singh P, van Hillegersberg R, Vohra R, Wanigasooriya K, Whitehouse T, Gjata A, Moreno JI, Takeda FR, Kidane B, Guevara Castro R, Harustiak T, Bekele A, Kechagias A, Gockel I, Kennedy A, Da Roit A, Bagajevas A, Azagra JS, Mahendran HA, Mejía-Fernández L, Wijnhoven BPL, El Kafsi J, Sayyed RH, Sousa M M, Sampaio AS, Negoi I, Blanco R, Wallner B, Schneider PM, Hsu PK, Isik A, Gananadha S, Wills V, Devadas M, Duong C, Talbot M, Hii MW, Jacobs R, Andreollo NA, Johnston B, Darling G, Isaza-Restrepo A, Rosero G, Arias-Amézquita F, Raptis D, Gaedcke J, Reim D, Izbicki J, Egberts JH, Dikinis S, Kjaer DW, Larsen MH, Achiam MP, Saarnio J, Theodorou D, Liakakos T, Korkolis DP, Robb WB, Collins C, Murphy T, Reynolds J, Tonini V, Migliore M, Bonavina L, Valmasoni M, Bardini R, Weindelmayer J, Terashima M, White RE, Alghunaim E, Elhadi M, Leon-Takahashi AM, Medina-Franco H, Lau PC, Okonta KE, Heisterkamp J, Rosman C, van Hillegersberg R, Beban G, Babor R, Gordon A, Rossaak JI, Pal KMI, Qureshi AU, Naqi SA, Syed AA, Barbosa J, Vicente CS, Leite J, Freire J, Casaca R, Costa RCT, Scurtu RR, Mogoanta SS, Bolca C, Constantinoiu S, Sekhniaidze D, Bjelović M, So JBY, Gačevski G, Loureiro C, Pera M, Bianchi A, Moreno Gijón M, Martín Fernández J, Trugeda Carrera MS, Vallve-Bernal M, Cítores Pascual MA, Elmahi S, Halldestam I, Hedberg J, Mönig S, Gutknecht S, Tez M, Guner A, Tirnaksiz MB, Colak E, Sevinç B, Hindmarsh A, Khan I, Khoo D, Byrom R, Gokhale J, Wilkerson P, Jain P, Chan D, Robertson K, Iftikhar S, Skipworth R, Forshaw M, Higgs S, Gossage J, Nijjar R, Viswanath YKS, Turner P, Dexter S, Boddy A, Allum WH, Oglesby S, Cheong E, Beardsmore D, Vohra R, Maynard N, Berrisford R, Mercer S, Puig S, Melhado R, Kelty C, Underwood T, Dawas K, Lewis W, Bryce G, Thomas M, Arndt AT, Palazzo F, Meguid RA, Fergusson J, Beenen E, Mosse C, Salim J, Cheah S, Wright T, Cerdeira MP, McQuillan P, Richardson M, Liem H, Spillane J, Yacob M, Albadawi F, Thorpe T, Dingle A, Cabalag C, Loi K, Fisher OM, Ward S, Read M, Johnson M, Bassari R, Bui H, Cecconello I, Sallum RAA, da Rocha JRM, Lopes LR, Tercioti Jr V, Coelho JDS, Ferrer JAP, Buduhan G, Tan L, Srinathan S, Shea P, Yeung J, Allison F, Carroll P, Vargas-Barato F, Gonzalez F, Ortega J, Nino-Torres L, Beltrán-García TC, Castilla L, Pineda M, Bastidas A, Gómez-Mayorga J, Cortés N, Cetares C, Caceres S, Duarte S, Pazdro A, Snajdauf M, Faltova H, Sevcikova M, Mortensen PB, Katballe N, Ingemann T, Morten B, Kruhlikava I, Ainswort AP, Stilling NM, Eckardt J, Holm J, Thorsteinsson M, Siemsen M, Brandt B, Nega B, Teferra E, Tizazu A, Kauppila JH, Koivukangas V, Meriläinen S, Gruetzmann R, Krautz C, Weber G, Golcher H, Emons G, Azizian A, Ebeling M, Niebisch S, Kreuser N, Albanese G, Hesse J, Volovnik L, Boecher U, Reeh M, Triantafyllou S, Schizas D, Michalinos A, Balli E, Mpoura M, Charalabopoulos A, Manatakis DK, Balalis D, Bolger J, Baban C, Mastrosimone A, McAnena O, Quinn A, Ó Súilleabháin CB, Hennessy MM, Ivanovski I, Khizer H, Ravi N, Donlon N, Cervellera M, Vaccari S, Bianchini S, Asti E, Bernardi D, Merigliano S, Provenzano L, Scarpa M, Saadeh L, Salmaso B, De Manzoni G, Giacopuzzi S, La Mendola R, De Pasqual CA, Tsubosa Y, Niihara M, Irino T, Makuuchi R, Ishii K K, Mwachiro M, Fekadu A, Odera A, Mwachiro E, AlShehab D, Ahmed HA, Shebani AO, Elhadi A, Elnagar FA, Elnagar HF, Makkai-Popa ST, Wong LF, Tan YR, Thannimalai S, Ho CA, Pang WS, Tan JH, Basave HNL, Cortés-González R, Lagarde SM, van Lanschot JJB, Cords C, Jansen WA, Martijnse I, Matthijsen R, Bouwense S, Klarenbeek B, Verstegen M, van Workum F, Ruurda JP, van der Sluis PC, de Maat M, Evenett N, Johnston P, Patel R, MacCormick A, Smith B, Ekwunife C, Memon AH, Shaikh K, Wajid A, Khalil N, Haris M, Mirza ZU, Qudus SBA, Sarwar MZ, Shehzadi A, Raza A, Jhanzaib MH, Farmanali J, Zakir Z, Shakeel O, Nasir I, Khattak S, Baig M, Noor MA, Ahmed HH, Naeem A, Pinho AC, da Silva R, Bernardes A, Campos JC, Matos H, Braga T, Monteiro C, Ramos P, Cabral F, Gomes MP, Martins PC, Correia AM, Videira JF, Ciuce C, Drasovean R, Apostu R, Ciuce C, Paitici S, Racu AE, Obleaga CV, Beuran M, Stoica B, Ciubotaru C, Negoita V, Cordos I, Birla RD, Predescu D, Hoara PA, Tomsa R, Shneider V, Agasiev M, Ganjara I, Gunjić D, Veselinović M, Babič T, Chin TS, Shabbir A, Kim G, Crnjac A, Samo H, Díez del Val I, Leturio S, Ramón JM, Dal Cero M, Rifá S, Rico M, Pagan Pomar A, Martinez Corcoles JA, Rodicio Miravalles JL, Pais SA, Turienzo SA, Alvarez LS, Campos PV, Rendo AG, García SS, Santos EPG, Martínez ET, Fernández Díaz MJ, Magadán Álvarez C, Concepción Martín V, Díaz López C, Rosat Rodrigo A, Pérez Sánchez LE, Bailón Cuadrado M, Tinoco Carrasco C, Choolani Bhojwani E, Sánchez DP, Ahmed ME, Dzhendov T, Lindberg F, Rutegård M, Sundbom M, Mickael C, Colucci N, Schnider A, Er S, Kurnaz E, Turkyilmaz S, Turkyilmaz A, Yildirim R, Baki BE, Akkapulu N, Karahan O, Damburaci N, Hardwick R, Safranek P, Sujendran V, Bennett J, Afzal Z, Shrotri M, Chan B, Exarchou K, Gilbert T, Amalesh T, Mukherjee D, Mukherjee S, Wiggins TH, Kennedy R, McCain S, Harris A, Dobson G, Davies N, Wilson I, Mayo D, Bennett D, Young R, Manby P, Blencowe N, Schiller M, Byrne B, Mitton D, Wong V, Elshaer A, Cowen M, Menon V, Tan LC, McLaughlin E, Koshy R, Sharp C, Brewer H, Das N, Cox M, Al Khyatt W, Worku D, Iqbal R, Walls L, McGregor R, Fullarton G, Macdonald A, MacKay C, Craig C, Dwerryhouse S, Hornby S, Jaunoo S, Wadley M, Baker C, Saad M, Kelly M, Davies A, Di Maggio F, McKay S, Mistry P, Singhal R, Tucker O, Kapoulas S, Powell-Brett S, Davis P, Bromley G, Watson L, Verma R, Ward J, Shetty V, Ball C, Pursnani K, Sarela A, Sue Ling H, Mehta S, Hayden J, To N, Palser T, Hunter D, Supramaniam K, Butt Z, Ahmed A, Kumar S, Chaudry A, Moussa O, Kordzadeh A, Lorenzi B, Wilson M, Patil P, Noaman I, Bouras G, Evans R, Singh M, Warrilow H, Ahmad A, Tewari N, Yanni F, Couch J, Theophilidou E, Reilly JJ, Singh P, van Boxel G, Akbari K, Zanotti D, Sanders G, Wheatley T, Ariyarathenam A, Reece-Smith A, Humphreys L, Choh C, Carter N, Knight B, Pucher P, Athanasiou A, Mohamed I, Tan B, Abdulrahman M, Vickers J, Akhtar K, Chaparala R, Brown R, Alasmar MMA, Ackroyd R, Patel K, Tamhankar A, Wyman A, Walker R, Grace B, Abbassi N, Slim N, Ioannidi L, Blackshaw G, Havard T, Escofet X, Powell A, Owera A, Rashid F, Jambulingam P, Padickakudi J, Ben-Younes H, Mccormack K, Makey IA, Karush MK, Seder CW, Liptay MJ, Chmielewski G, Rosato EL, Berger AC, Zheng R, Okolo E, Singh A, Scott CD, Weyant MJ, Mitchell JD. Textbook outcome following oesophagectomy for cancer: international cohort study. Br J Surg 2022; 109:439-449. [PMID: 35194634 DOI: 10.1093/bjs/znac016] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 10/08/2021] [Accepted: 01/04/2022] [Indexed: 11/14/2022]
Abstract
BACKGROUND Textbook outcome has been proposed as a tool for the assessment of oncological surgical care. However, an international assessment in patients undergoing oesophagectomy for oesophageal cancer has not been reported. This study aimed to assess textbook outcome in an international setting. METHODS Patients undergoing curative resection for oesophageal cancer were identified from the international Oesophagogastric Anastomosis Audit (OGAA) from April 2018 to December 2018. Textbook outcome was defined as the percentage of patients who underwent a complete tumour resection with at least 15 lymph nodes in the resected specimen and an uneventful postoperative course, without hospital readmission. A multivariable binary logistic regression model was used to identify factors independently associated with textbook outcome, and results are presented as odds ratio (OR) and 95 per cent confidence intervals (95 per cent c.i.). RESULTS Of 2159 patients with oesophageal cancer, 39.7 per cent achieved a textbook outcome. The outcome parameter 'no major postoperative complication' had the greatest negative impact on a textbook outcome for patients with oesophageal cancer, compared to other textbook outcome parameters. Multivariable analysis identified male gender and increasing Charlson comorbidity index with a significantly lower likelihood of textbook outcome. Presence of 24-hour on-call rota for oesophageal surgeons (OR 2.05, 95 per cent c.i. 1.30 to 3.22; P = 0.002) and radiology (OR 1.54, 95 per cent c.i. 1.05 to 2.24; P = 0.027), total minimally invasive oesophagectomies (OR 1.63, 95 per cent c.i. 1.27 to 2.08; P < 0.001), and chest anastomosis above azygous (OR 2.17, 95 per cent c.i. 1.58 to 2.98; P < 0.001) were independently associated with a significantly increased likelihood of textbook outcome. CONCLUSION Textbook outcome is achieved in less than 40 per cent of patients having oesophagectomy for cancer. Improvements in centralization, hospital resources, access to minimal access surgery, and adoption of newer techniques for improving lymph node yield could improve textbook outcome.
Collapse
|
20
|
Tan JH, Teoh TK, Ivanova J, Jadhav S, Varcoe R, Baig K, Gunarathne A. The impact of the COVID-19 pandemic on transcatheter aortic valve implantation (TAVI) service: a United Kingdom tertiary centre experience. Eur Heart J 2021. [DOI: 10.1093/eurheartj/ehab724.2197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Background/Introduction
Untreated, symptomatic, severe aortic stenosis carries significant mortality and morbidity. Timely intervention is pivotal to ensure patient safety. The COVID-19 pandemic created unprecedented challenges to the UK's National Health Service (NHS), resulting in the deferral of all elective work, including TAVI services from March 2020.
Purpose
To evaluate clinical outcomes and time delays in patients undergoing TAVI during the pandemic period compared to an age and risk factor-matched cohort of patients prior to COVID-19. We hypothesized that there were significant time delays, more emergency procedures and related adverse outcomes in patients who underwent TAVI during the pandemic period.
Methods
We analysed prospectively collected data (patient characteristics, procedural details, complications and in-hospital outcomes) of 210 consecutive patients who underwent TAVI between March 2019 and February 2021 in a tertiary centre in the UK (The centre serves for a population of 2.5 million and provided in-patient treatment for 5590 COVID-positive patients over a 12 month period). We compared time-lags from an initial referral to outpatient review, CT aortograms, valve implantation and 30-day mortality between patients who underwent TAVI between March 2019 and Feburary 2020 (N=134) and those who underwent TAVI between March 2020 and February 2021 (COVID Group=76).
Results
The mean age of the cohort was 81.4±6.6 years and majority were females (51%) and were in moderate risk category (EuroSCORE II=4.55±5.5). Of the total cohort, 4 (5.3%) patients acquired COVID-19 pneumonia during the hospital stay. The age, cardiovascular comorbidities and risk scores were comparable between the control group and the COVID cohort. (Table 1). There were no significant differences in procedural complications in the control group compared to the COVID-19 group (Table 1). The median waiting time from referral to TAVI clinic was significantly shorter in the COVID-19 group (33 (8–66) vs. 51 (17–89) days (P=0.04)) and there was no significant difference in time delays for CT aortogram, MDT or TAVI procedure between the two groups. The median length of stay (2 (2–4) vs 2.5 (2–9) days) and 30 day mortality (1.4% vs 5.3%) was comparable between the two groups (Table 1).
Conclusion
Contrary to our hypothesis, our analysis demonstrated that there were no significant time delays, excess complications or mortality in TAVI procedures during the COVID-19 pandemic period despite the excess burden imposed on our local health services. More importantly, very few TAVI patients acquired COVID-19 infection during in-hospital stay. This is likely due to prompt identification of innovative ways of re-configuring an existing local patient pathway, by the TAVI team, to deliver safe and uninterrupted TAVI services during this unprecedented pandemic setting.
Funding Acknowledgement
Type of funding sources: None. Figure 1. Referral times
Collapse
Affiliation(s)
- J H Tan
- Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
| | - T K Teoh
- Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
| | - J Ivanova
- Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
| | - S Jadhav
- Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
| | - R Varcoe
- Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
| | - K Baig
- Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
| | - A Gunarathne
- Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
| |
Collapse
|
21
|
Tan JH, Teoh TK, Fong J, Amirthalingam A, Baig K. Clinical outcomes up-to 10 years of asymptomatic incidental aortic dissections and large aortic aneurysms detected on computer tomography aortography (CTA) prior to transcatheter aortic valve implantation (TAVI). Eur Heart J 2021. [DOI: 10.1093/eurheartj/ehab724.2196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Background/Introduction
Computer tomography aortography (CTA) is performed routinely to aid planning of transcatheter aortic valve implantation (TAVI). Incidental findings are common, and may influence the decision to proceed with TAVI. The safety and long term outcomes of performing TAVI in patients with previously undiagnosed incidental CT findings of aortic dissections and large aortic aneurysms is currently unknown.
Purpose
To establish the frequency of incidental aortic dissections and large aortic aneurysms prior to TAVI, and subsequent clinical outcomes of patients. We hypothesize that transfemoral access is safe in patients with incidental finding of aortic dissection and large aortic aneurysms.
Methods
This was a retrospective study of 628 sequential TAVI patients in a large, UK tertiary centre between January 2010 and September 2020. Patients were evaluated in 3 groups as per pre-TAVI CTA: incidental aortic dissections, aortic aneurysm >4cm and all others (control group). Endpoints were procedural success, peri-procedural major bleeding and/or vascular complications and/or CVA, length of hospital stay, 30-day and 1-year mortality.
Results
2.9% of patients (n=18) had incidental aortic dissection, of which 66.7% (n=12) were male, with a mean age of 86.7±4.4. 3.8% of patients (n=24) had aortic aneurysms >4 cm. 83.3% (n=20) of them were male and the mean age was 82.8±5.4. Transfemoral approach was favoured in 77.8% of patients in the dissection group and 83.3% of patients in the aneurysm group versus 93.3% in the control group. Procedural characteristics are summarised in Table 1. Vascular access complications, stroke, bleeding and length of hospital stay were comparable between all 3 groups (Table 1). Patients with dissection and large aneurysm had similar success rate of valve implantation compared to the control group (88.9% and 87.5% vs 97.1%, p=0.452). 30-day mortality in the dissection group was higher than the other 2 groups (21.1% vs 0% and 5.6%, p=0.004). Log-rank analysis revealed a higher incidence of MACE in the dissection group over 24 months compared to the other two groups (Figure 1).
Conclusion
A transfemoral approach appears to be a safe choice in patients with incidental findings of aortic dissection or aortic aneurysms >4cm, given no significant difference in terms of valve implant success, vascular injury, major bleeding or unplanned surgical repair. However, patients with stable previous aortic dissections have a significantly higher 30-day mortality and overall lower survival rate over 24 months. This important observation needs to be further investigated in a larger-scale, long-term follow up study, and may in future influence TAVI treatment planning.
Funding Acknowledgement
Type of funding sources: None. Figure 1. Survival curve
Collapse
Affiliation(s)
- J H Tan
- Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
| | - T K Teoh
- Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
| | - J Fong
- Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
| | - A Amirthalingam
- Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
| | - K Baig
- Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
| |
Collapse
|
22
|
Tan JH, Wu TY, Tan JYH, Sharon Tan SH, Hong CC, Shen L, Loo LMA, Iau P, Murphy DP, O'Neill GK. Definitive Surgery Is Safe in Borderline Patients Who Respond to Resuscitation. J Orthop Trauma 2021; 35:e234-e240. [PMID: 33252447 DOI: 10.1097/bot.0000000000001999] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/02/2020] [Indexed: 02/02/2023]
Abstract
OBJECTIVES We hypothesize that in adequately resuscitated borderline polytrauma patients with long bone fractures (femur and tibia) or pelvic fractures, early (within 4 days) definitive stabilization (EDS) can be performed without an increase in postoperative ventilation and postoperative complications. DESIGN Retrospective cohort study. SETTING Level 1 trauma center. PATIENTS In total, 103 patients were included in this study; of whom, 18 (17.5%) were female and 85 (82.5%) were male. These patients were borderline trauma patients who had the following parameters before definitive surgery, normal coagulation profile, lactate of <2.5 mmol/L, pH of ≥7.25, and base excess of ≥5.5. INTERVENTION These patients were treated according to Early Total Care, definitive surgery on day of admission, or Damage Control Orthopaedics principles, temporizing external fixation followed by definitive surgery at a later date. Timing of definitive surgical fixation was recorded as EDS or late definitive surgical fixation (>4 days). MAIN OUTCOME MEASURES Primary outcome measured was the duration of ventilation more than 3 days post definitive surgery and presence of postoperative complications. RESULTS Thirty-five patients (34.0%) received Early Total Care, whereas 68 (66.0%) patients were treated with Damage Control Orthopaedics. In total, 51 (49.5%) of all patients had late definitive surgery, whereas 52 patients (50.5%) had EDS. On logistic regression, the following factors were found to be predictive of higher rates of postoperative ventilation ≥ 3 days, units of blood transfused, and time to definitive surgery > 4 days. Increased age, head abbreviated injury score of 3 or more and time to definitive surgery were found to be associated with an increased risk of postoperative complications. CONCLUSIONS Borderline polytrauma patients with no severe soft tissue injuries, such as chest or head injuries, may be treated with EDS if adequately resuscitated with no increase in need for postoperative ventilation and complications. LEVEL OF EVIDENCE Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.
Collapse
Affiliation(s)
- Jiong Hao Tan
- Department of Orthopaedic Surgery, University Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Health System (NUHS), Singapore
| | - Tian Yi Wu
- Department of Orthopaedic Surgery, University Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Health System (NUHS), Singapore
| | - Joel Yong Hao Tan
- Department of Orthopaedic Surgery, University Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Health System (NUHS), Singapore
| | - Si Heng Sharon Tan
- Department of Orthopaedic Surgery, University Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Health System (NUHS), Singapore
| | - Choon Chiet Hong
- Department of Orthopaedic Surgery, University Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Health System (NUHS), Singapore
| | - Liang Shen
- Biostatistics Unit, Yong Loo Lin School of Medicine, National University of Singapore, Singapore ; and
| | - Lynette Mee-Ann Loo
- Division of General Surgery, University Surgical Cluster, National University Health System (NUHS), Singapore
| | - Philip Iau
- Division of General Surgery, University Surgical Cluster, National University Health System (NUHS), Singapore
| | - Diarmuid P Murphy
- Department of Orthopaedic Surgery, University Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Health System (NUHS), Singapore
| | - Gavin Kane O'Neill
- Department of Orthopaedic Surgery, University Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Health System (NUHS), Singapore
| |
Collapse
|
23
|
Hallinan JTPD, Zhu L, Yang K, Makmur A, Algazwi DAR, Thian YL, Lau S, Choo YS, Eide SE, Yap QV, Chan YH, Tan JH, Kumar N, Ooi BC, Yoshioka H, Quek ST. Deep Learning Model for Automated Detection and Classification of Central Canal, Lateral Recess, and Neural Foraminal Stenosis at Lumbar Spine MRI. Radiology 2021; 300:130-138. [PMID: 33973835 DOI: 10.1148/radiol.2021204289] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background Assessment of lumbar spinal stenosis at MRI is repetitive and time consuming. Deep learning (DL) could improve -productivity and the consistency of reporting. Purpose To develop a DL model for automated detection and classification of lumbar central canal, lateral recess, and neural -foraminal stenosis. Materials and Methods In this retrospective study, lumbar spine MRI scans obtained from September 2015 to September 2018 were included. Studies of patients with spinal instrumentation or studies with suboptimal image quality, as well as postgadolinium studies and studies of patients with scoliosis, were excluded. Axial T2-weighted and sagittal T1-weighted images were used. Studies were split into an internal training set (80%), validation set (9%), and test set (11%). Training data were labeled by four radiologists using predefined gradings (normal, mild, moderate, and severe). A two-component DL model was developed. First, a convolutional neural network (CNN) was trained to detect the region of interest (ROI), with a second CNN for classification. An internal test set was labeled by a musculoskeletal radiologist with 31 years of experience (reference standard) and two subspecialist radiologists (radiologist 1: A.M., 5 years of experience; radiologist 2: J.T.P.D.H., 9 years of experience). DL model performance on an external test set was evaluated. Detection recall (in percentage), interrater agreement (Gwet κ), sensitivity, and specificity were calculated. Results Overall, 446 MRI lumbar spine studies were analyzed (446 patients; mean age ± standard deviation, 52 years ± 19; 240 women), with 396 patients in the training (80%) and validation (9%) sets and 50 (11%) in the internal test set. For internal testing, DL model and radiologist central canal recall were greater than 99%, with reduced neural foramina recall for the DL model (84.5%) and radiologist 1 (83.9%) compared with radiologist 2 (97.1%) (P < .001). For internal testing, dichotomous classification (normal or mild vs moderate or severe) showed almost-perfect agreement for both radiologists and the DL model, with respective κ values of 0.98, 0.98, and 0.96 for the central canal; 0.92, 0.95, and 0.92 for lateral recesses; and 0.94, 0.95, and 0.89 for neural foramina (P < .001). External testing with 100 MRI scans of lumbar spines showed almost perfect agreement for the DL model for dichotomous classification of all ROIs (κ, 0.95-0.96; P < .001). Conclusion A deep learning model showed comparable agreement with subspecialist radiologists for detection and classification of central canal and lateral recess stenosis, with slightly lower agreement for neural foraminal stenosis at lumbar spine MRI. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Hayashi in this issue.
Collapse
Affiliation(s)
- James Thomas Patrick Decourcy Hallinan
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); NUS Graduate School, Integrative Sciences and Engineering Programme, National University of Singapore, Singapore (L.Z.); Department of Computer Science, School of Computing, National University of Singapore, Singapore (K.Y., B.C.O.); Department of Radiology, Dammam Medical Complex, Dammam, Saudi Arabia (D.A.R.A.); Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore (Q.V.Y., Y.H.C.); University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Lei Zhu
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); NUS Graduate School, Integrative Sciences and Engineering Programme, National University of Singapore, Singapore (L.Z.); Department of Computer Science, School of Computing, National University of Singapore, Singapore (K.Y., B.C.O.); Department of Radiology, Dammam Medical Complex, Dammam, Saudi Arabia (D.A.R.A.); Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore (Q.V.Y., Y.H.C.); University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Kaiyuan Yang
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); NUS Graduate School, Integrative Sciences and Engineering Programme, National University of Singapore, Singapore (L.Z.); Department of Computer Science, School of Computing, National University of Singapore, Singapore (K.Y., B.C.O.); Department of Radiology, Dammam Medical Complex, Dammam, Saudi Arabia (D.A.R.A.); Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore (Q.V.Y., Y.H.C.); University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Andrew Makmur
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); NUS Graduate School, Integrative Sciences and Engineering Programme, National University of Singapore, Singapore (L.Z.); Department of Computer Science, School of Computing, National University of Singapore, Singapore (K.Y., B.C.O.); Department of Radiology, Dammam Medical Complex, Dammam, Saudi Arabia (D.A.R.A.); Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore (Q.V.Y., Y.H.C.); University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Diyaa Abdul Rauf Algazwi
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); NUS Graduate School, Integrative Sciences and Engineering Programme, National University of Singapore, Singapore (L.Z.); Department of Computer Science, School of Computing, National University of Singapore, Singapore (K.Y., B.C.O.); Department of Radiology, Dammam Medical Complex, Dammam, Saudi Arabia (D.A.R.A.); Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore (Q.V.Y., Y.H.C.); University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Yee Liang Thian
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); NUS Graduate School, Integrative Sciences and Engineering Programme, National University of Singapore, Singapore (L.Z.); Department of Computer Science, School of Computing, National University of Singapore, Singapore (K.Y., B.C.O.); Department of Radiology, Dammam Medical Complex, Dammam, Saudi Arabia (D.A.R.A.); Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore (Q.V.Y., Y.H.C.); University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Samuel Lau
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); NUS Graduate School, Integrative Sciences and Engineering Programme, National University of Singapore, Singapore (L.Z.); Department of Computer Science, School of Computing, National University of Singapore, Singapore (K.Y., B.C.O.); Department of Radiology, Dammam Medical Complex, Dammam, Saudi Arabia (D.A.R.A.); Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore (Q.V.Y., Y.H.C.); University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Yun Song Choo
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); NUS Graduate School, Integrative Sciences and Engineering Programme, National University of Singapore, Singapore (L.Z.); Department of Computer Science, School of Computing, National University of Singapore, Singapore (K.Y., B.C.O.); Department of Radiology, Dammam Medical Complex, Dammam, Saudi Arabia (D.A.R.A.); Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore (Q.V.Y., Y.H.C.); University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Sterling Ellis Eide
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); NUS Graduate School, Integrative Sciences and Engineering Programme, National University of Singapore, Singapore (L.Z.); Department of Computer Science, School of Computing, National University of Singapore, Singapore (K.Y., B.C.O.); Department of Radiology, Dammam Medical Complex, Dammam, Saudi Arabia (D.A.R.A.); Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore (Q.V.Y., Y.H.C.); University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Qai Ven Yap
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); NUS Graduate School, Integrative Sciences and Engineering Programme, National University of Singapore, Singapore (L.Z.); Department of Computer Science, School of Computing, National University of Singapore, Singapore (K.Y., B.C.O.); Department of Radiology, Dammam Medical Complex, Dammam, Saudi Arabia (D.A.R.A.); Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore (Q.V.Y., Y.H.C.); University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Yiong Huak Chan
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); NUS Graduate School, Integrative Sciences and Engineering Programme, National University of Singapore, Singapore (L.Z.); Department of Computer Science, School of Computing, National University of Singapore, Singapore (K.Y., B.C.O.); Department of Radiology, Dammam Medical Complex, Dammam, Saudi Arabia (D.A.R.A.); Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore (Q.V.Y., Y.H.C.); University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Jiong Hao Tan
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); NUS Graduate School, Integrative Sciences and Engineering Programme, National University of Singapore, Singapore (L.Z.); Department of Computer Science, School of Computing, National University of Singapore, Singapore (K.Y., B.C.O.); Department of Radiology, Dammam Medical Complex, Dammam, Saudi Arabia (D.A.R.A.); Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore (Q.V.Y., Y.H.C.); University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Naresh Kumar
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); NUS Graduate School, Integrative Sciences and Engineering Programme, National University of Singapore, Singapore (L.Z.); Department of Computer Science, School of Computing, National University of Singapore, Singapore (K.Y., B.C.O.); Department of Radiology, Dammam Medical Complex, Dammam, Saudi Arabia (D.A.R.A.); Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore (Q.V.Y., Y.H.C.); University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Beng Chin Ooi
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); NUS Graduate School, Integrative Sciences and Engineering Programme, National University of Singapore, Singapore (L.Z.); Department of Computer Science, School of Computing, National University of Singapore, Singapore (K.Y., B.C.O.); Department of Radiology, Dammam Medical Complex, Dammam, Saudi Arabia (D.A.R.A.); Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore (Q.V.Y., Y.H.C.); University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Hiroshi Yoshioka
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); NUS Graduate School, Integrative Sciences and Engineering Programme, National University of Singapore, Singapore (L.Z.); Department of Computer Science, School of Computing, National University of Singapore, Singapore (K.Y., B.C.O.); Department of Radiology, Dammam Medical Complex, Dammam, Saudi Arabia (D.A.R.A.); Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore (Q.V.Y., Y.H.C.); University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| | - Swee Tian Quek
- From the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (J.T.P.D.H., A.M., Y.L.T., S.L., Y.S.C., S.E.E., S.T.Q.); NUS Graduate School, Integrative Sciences and Engineering Programme, National University of Singapore, Singapore (L.Z.); Department of Computer Science, School of Computing, National University of Singapore, Singapore (K.Y., B.C.O.); Department of Radiology, Dammam Medical Complex, Dammam, Saudi Arabia (D.A.R.A.); Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore (Q.V.Y., Y.H.C.); University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore (J.H.T., N.K.); and Department of Radiological Sciences, University of California, Irvine, Orange, Calif (H.Y.)
| |
Collapse
|
24
|
Mat Salleh NH, Abdul Rahman MF, Samsusah S, De Silva JR, Tan JH, Amir A, Lau YL. Complications of Sub-microscopic Plasmodium vivax Malaria among Orang Asli in Pos Lenjang, Kuala Lipis. Trop Biomed 2021; 38:33-35. [PMID: 33797521 DOI: 10.47665/tb.38.1.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
In recent years, increasing cases of Plasmodium vivax complications had been reported all over the world. This former benign Plasmodium species is now recognized to be one of the human malaria parasites that can produce severe disease. In this article, we report two cases of sub-microscopic P. vivax malaria confirmed by PCR. Both patients were asymptomatic before treatment. They showed unusual presentations few days after initiation of antimalarial treatment. Both patients had subsequently completed antimalarial treatment and recovered completely.
Collapse
Affiliation(s)
- N H Mat Salleh
- Lipis District Health Office, 27200 Kuala Lipis, Pahang, Malaysia
| | - M F Abdul Rahman
- Lipis District Health Office, 27200 Kuala Lipis, Pahang, Malaysia
| | - S Samsusah
- Lipis District Health Office, 27200 Kuala Lipis, Pahang, Malaysia
| | - J R De Silva
- Department of Parasitology, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia
| | - J H Tan
- Department of Parasitology, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia
| | - A Amir
- Department of Parasitology, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia
| | - Y L Lau
- Department of Parasitology, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia
| |
Collapse
|
25
|
Kumar N, Thomas AC, Ramos MRD, Tan JYH, Shen L, Madhu S, Lopez KG, Villanueva A, Tan JH, Vellayappan BA. Readmission-Free Survival Analysis in Metastatic Spine Tumour Surgical Patients: A Novel Concept. Ann Surg Oncol 2021; 28:2474-2482. [PMID: 33393052 DOI: 10.1245/s10434-020-09404-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 11/04/2020] [Indexed: 12/16/2022]
Abstract
BACKGROUND Outcomes commonly used to ascertain success of metastatic spine tumour surgery (MSTS) are 30-day complications/mortality and overall/disease-free survival. We believe a new, effective outcome indicator after MSTS would be the absence of unplanned hospital readmission (UHR) after index discharge. We introduce the concept of readmission-free survival (ReAFS), defined as 'the time duration between hospital discharge after index operation and first UHR or death'. The aim of this study is to identify factors influencing ReAFS in MSTS patients. PATIENTS AND METHODS We retrospectively analysed 266 consecutive patients who underwent MSTS between 2005 and 2016. Demographics, oncological characteristics, procedural, preoperative and postoperative details were collected. ReAFS of patients within 2 years or until death was reviewed. Perioperative factors predictive of reduced ReAFS were evaluated using multivariate regression analysis. RESULTS Of 266 patients, 230 met criteria for analysis. A total of 201 had UHR, whilst 1 in 8 (29/230) had no UHR. Multivariate analysis revealed that haemoglobin ≥ 12 g/dL, ECOG score of ≤ 2, primary prostate, breast and haematological cancers, comorbidities ≤ 3, absence of preoperative radiotherapy and shorter postoperative length of stay significantly prolonged the time to first UHR. CONCLUSIONS Readmission-free survival is a novel concept in MSTS, which relies on patients' general condition, appropriateness of interventional procedures and underlying disease burden. Additionally, it may indicate the successful combination of a multi-disciplinary treatment approach. This information will allow oncologists and surgeons to identify patients who may benefit from increased surveillance following discharge to increase ReAFS. We envisage that ReAFS is a concept that can be extended to other surgical oncological fields.
Collapse
Affiliation(s)
- Naresh Kumar
- Department of Orthopaedic Surgery, National University Health System, Singapore, Singapore.
| | - Andrew Cherian Thomas
- Department of Orthopaedic Surgery, National University Health System, Singapore, Singapore
| | | | - Joel Yong Hao Tan
- Department of Orthopaedic Surgery, National University Health System, Singapore, Singapore
| | - Liang Shen
- Biostatistics Unit, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Sirisha Madhu
- Department of Orthopaedic Surgery, National University Health System, Singapore, Singapore
| | - Keith Gerard Lopez
- Department of Orthopaedic Surgery, National University Health System, Singapore, Singapore
| | - Andre Villanueva
- Department of Orthopaedic Surgery, National University Health System, Singapore, Singapore
| | - Jiong Hao Tan
- Department of Orthopaedic Surgery, National University Health System, Singapore, Singapore
| | | |
Collapse
|
26
|
Kumar N, Patel R, Tan JH, Song J, Pandita N, Hey DHW, Lau LL, Liu G, Thambiah J, Wong HK. Symptomatic Construct Failure after Metastatic Spine Tumor Surgery. Asian Spine J 2020; 15:481-490. [PMID: 33108849 PMCID: PMC8377214 DOI: 10.31616/asj.2020.0166] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Accepted: 07/04/2020] [Indexed: 12/23/2022] Open
Abstract
Study Design Retrospective cohort study. Purpose To evaluate the incidence and presentation of symptomatic failures (SFs) after metastatic spine tumor surgery (MSTS). To identify the associated risk factors. To categorize SFs based on the management in these patients. Overview of Literature Few studies have reported on the incidence (1.9%–16%) and risk factors of SF after MSTS. It is unclear whether all SFs, occurring in MSTS-patients, result in revision surgery. Methods We conducted a retrospective analysis on 288 patients (246 for final analysis) who underwent MSTS between 2005–2015. Data collected were demographics and peri/postoperative clinical and radiological features. Early and late radiological SF were defined as presentation before and after 3 months from index surgery, respectively. Univariate and multivariate models of competing risk regression analysis were designed to determine the risk factors for SF with death as a competing event. Results We observed 14 SFs (5.7%) in 246 patients; 10 (4.1%) underwent revision surgery. Median survival was 13.4 months. The mean age was 58.8 years (range, 21–87 years); 48.4% were women. The median time to failure was 5 months (range, 1–60 months). Patients with SF were categorized into three groups: (1) SF when the primary implant was revised (n=5, 35.7%); (2) peri-construct progression of disease requiring extension (n=5, 35.7%); and (3) SFs that did not warrant revision (n=4, 28.5%). Four patients (28.5%) presented with early failure. SF commonly occurred at the implant-bone interface (9/14) and all patients had a spinal instability neoplastic score (SINS) >7. Thirteen patients (92.8%) who developed failure had fixation spanning junctional regions. Multivariate competing risk regression showed that preoperative Eastern Cooperative Oncology Group score was a significant risk factor for implant failure (adjusted sub-hazard ratio, 7.0; 95% confidence interval, 1.63–30.07; p<0.0009). Conclusions The incidence of SF (5.7%) was low in patients undergoing MSTS although these patients did not undergo spinal fusion. Preoperative ambulators involved a 7 times higher risk of failure than non-ambulators. Preoperative SINS >7 and fixations spanning junctional regions were associated with SF. Majority of construct failures occurred at the implant-bone interface.
Collapse
Affiliation(s)
- Naresh Kumar
- Department of Orthopaedic Surgery, National University Health System, Singapore
| | - Ravish Patel
- Department of Orthopaedic Surgery, National University Health System, Singapore
| | - Jiong Hao Tan
- Department of Orthopaedic Surgery, National University Health System, Singapore
| | - Joshua Song
- Department of Orthopaedic Surgery, National University Health System, Singapore
| | - Naveen Pandita
- Department of Orthopaedic Surgery, National University Health System, Singapore
| | | | - Leok Lim Lau
- Department of Orthopaedic Surgery, National University Health System, Singapore
| | - Gabriel Liu
- Department of Orthopaedic Surgery, National University Health System, Singapore
| | - Joseph Thambiah
- Department of Orthopaedic Surgery, National University Health System, Singapore
| | - Hee-Kit Wong
- Department of Orthopaedic Surgery, National University Health System, Singapore
| |
Collapse
|
27
|
Kumar N, Patel R, Tan BWL, Tan JH, Pandita N, Sonawane D, Lopez KG, Wai KL, Hey HWD, Kumar A, Liu G. Asymptomatic Construct Failure after Metastatic Spine Tumor Surgery: A New Entity or a Continuum with Symptomatic Failure? Asian Spine J 2020; 15:636-649. [PMID: 33108848 PMCID: PMC8561154 DOI: 10.31616/asj.2020.0167] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 06/09/2020] [Indexed: 11/23/2022] Open
Abstract
Study Design Retrospective cohort study. Purpose To study the incidence, onset, underlying mechanism, clinical course, and factors leading to asymptomatic construct failure (AsCF) after metastatic spinal tumor surgery (MSTS). Overview of Literature The reported incidence rates for implant and/or construct failure after MSTS are low (1.9%–16%) and based on clinical presentations and revisions required for symptomatic failures (SFs). AsCF after MSTS has not been reported. Methods We conducted a retrospective analysis of 288 patients (246 for final analysis) who underwent MSTS between 2005–2015. Data collected were demographics and peri/postoperative clinical and radiological features. Early and late radiological AsCF were defined as presentation before and after 3 months, respectively. We analyzed patients with AsCF for risk factors and survival duration by performing competing risk regression analyses where AsCF was the event of interest, with SF and death as competing events. Results We observed AsCF in 41/246 patients (16.7%). The mean time to onset of AsCF after MSTS was 2 months (range, 1–9 months). Median survival of patients with AsCF was 20 and 41 months for early and late failures, respectively. Early AsCF accounted for 80.5% of cases, while late AsCF accounted for 19.5%. The commonest radiologically detectable AsCF mechanism was angular deformity (increase in kyphus) in 29 patients. Increasing age (p<0.02) and primary breast (13/41, 31.7%) (p<0.01) tumors were associated with higher AsCF rates. There was a non-significant trend towards AsCF in patients with a spinal instability neoplastic score ≥7, instrumentation across junctional regions, and construct lengths of 6–9 levels. None of the patients with AsCF underwent revision surgery. Conclusions AsCF after MSTS is a distinct entity. Most patients with early AsCF did not require intervention. Patients who survived and maintained ambulation for longer periods had late failure. Increasing age and tumors with a better prognosis have a higher likelihood of developing AsCF. AsCF is not necessarily an indication for aggressive/urgent intervention.
Collapse
Affiliation(s)
- Naresh Kumar
- Department of Orthopaedic Surgery, National University Health System, Singapore
| | - Ravish Patel
- Department of Orthopaedic Surgery, National University Health System, Singapore
| | - Barry Wei Loong Tan
- Department of Orthopaedic Surgery, National University Health System, Singapore
| | - Jiong Hao Tan
- Department of Orthopaedic Surgery, National University Health System, Singapore
| | - Naveen Pandita
- Department of Orthopaedic Surgery, National University Health System, Singapore
| | - Dhiraj Sonawane
- Department of Orthopaedic Surgery, National University Health System, Singapore
| | - Keith Gerard Lopez
- Department of Orthopaedic Surgery, National University Health System, Singapore
| | - Khin Lay Wai
- Department of Orthopaedic Surgery, National University Health System, Singapore
| | | | - Aravind Kumar
- Department of Orthopaedic Surgery, National University Health System, Singapore
| | - Gabriel Liu
- Department of Orthopaedic Surgery, National University Health System, Singapore
| |
Collapse
|
28
|
Hey HWD, Zhuo WH, Tan YHJ, Tan JH. Accuracy of freehand pedicle screws versus lateral mass screws in the subaxial cervical spine. Spine Deform 2020; 8:1049-1058. [PMID: 32314180 DOI: 10.1007/s43390-020-00119-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Accepted: 04/06/2020] [Indexed: 10/24/2022]
Abstract
STUDY DESIGN Radiographic comparative study with prospectively collected data. OBJECTIVES To assess the accuracy of subaxial cervical pedicle screw (CPS) placement with freehand technique compared to lateral mass screws (LMS). The freehand cervical pedicle screw insertion technique guided by intraoperative lateral C-arm imaging has been shown to be both safe and effective. However, no study has performed a 100% audit of this technique using pre- and postoperative computed tomography (CT) to determine its true accuracy, as well as its reduction capability of CPS and LMS instrumentation. METHODS 36 consecutive patients treated surgically by a single surgeon with the exclusive practice of LMS and subsequently CPS over 2 years were included. CT and EOS slot scanner were performed pre- and post-operatively to determine the extent of pedicle screw breach and to assess sagittal alignment reduction between CPS and LMS groups. Predictors of pedicle screw breaches were also identified using multivariate analysis. RESULTS CPS fixation was more effective in restoring global cervical angle and had superior reduction capability of cervical lordosis at the levels of C3/4 (5.00 ± 3.92, p = 0.008), C4/5 (6.63 ± 5.5, p = 0.010) and C5/6 (7.22 ± 6.19, p = 0.004) compared to LMS fixation. Pedicle screw breaches occurred most commonly at C4 (p = 0.003), and most commonly involved the lateral pedicle wall (p < 0.001). Placement of freehand pedicles screws on the concavity of rotated vertebrae was predictive of pedicle screw breach (OR 2.567, 95% CI 1.058-6.228, p = 0.037). There was no significant difference in the complication rate. CONCLUSIONS Although freehand cervical pedicle screw fixation is technically more demanding, it is generally safe and effective. However, the increased risk of screw breaches in the context of a rotated spine should be taken into consideration. Lateral mass screw fixation is advised if spinal realignment is not necessary.
Collapse
Affiliation(s)
- Hwee Weng Dennis Hey
- Department of Orthopaedic Surgery, National University Health System (NUHS), Singapore, Singapore. .,Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore, Singapore.
| | - Wen-Hai Zhuo
- Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore, Singapore
| | - Yong Hao Joel Tan
- Department of Orthopaedic Surgery, National University Health System (NUHS), Singapore, Singapore
| | - Jiong Hao Tan
- Department of Orthopaedic Surgery, National University Health System (NUHS), Singapore, Singapore
| |
Collapse
|
29
|
Tan HCL, Tan JH, Vellusamy VM, Vasavan Y, Lim CS. Wilms tumour with poor response to pre-operative chemotherapy: A report of 2 cases. Malays J Pathol 2020; 42:267-271. [PMID: 32860380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
INTRODUCTION Majority of Wilms tumour (WT) responds well to pre-operative chemotherapy. In Malaysia, incidence of WT is rare with only two cases reported per one million populations yearly. This case report is to highlight on the awareness of WT in an Asian population and highlight two cases and challenges faced after pre-operative chemotherapy. CASE REPORT In this case series, we report on two cases of WT which had poor response to pre-operative chemotherapy. Both cases underwent surgery after pre-operative chemotherapy and recovery was uneventful during a two-year follow-up. DISCUSSION Both patients had chemotherapy prior planned surgery, but had unfortunate poor tumour response. The tumour progressed in size which required a radical nephrectomy. The histology report for the first case had more than 60% blastemal cells remaining despite giving pre-operative chemotherapy with no focal anaplasia. This showed poor response to chemotherapy evidenced by the high number of blastemal cells. The second case was a stromal type WT which is known for poor response and may lead to enhancement of growth and maturation induced by chemotherapy. These were the possible reason of poor response of WT in these two cases.
Collapse
Affiliation(s)
- H C L Tan
- Universiti Kebangsaan Malaysia Medical Centre, Faculty of Medicine, Department of General Surgery, kuala Lumpur, Malaysia.
| | | | | | | | | |
Collapse
|
30
|
Kumar N, Madhu S, Bohra H, Pandita N, Wang SSY, Lopez KG, Tan JH, Vellayappan BA. Is there an optimal timing between radiotherapy and surgery to reduce wound complications in metastatic spine disease? A systematic review. Eur Spine J 2020; 29:3080-3115. [DOI: 10.1007/s00586-020-06478-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Accepted: 05/25/2020] [Indexed: 12/13/2022]
|
31
|
Liu Y, Ye YL, Lou JL, Yang XF, Baba T, Kimura M, Yang B, Li ZH, Li QT, Xu JY, Ge YC, Hua H, Wang JS, Yang YY, Ma P, Bai Z, Hu Q, Liu W, Ma K, Tao LC, Jiang Y, Hu LY, Zang HL, Feng J, Wu HY, Han JX, Bai SW, Li G, Yu HZ, Huang SW, Chen ZQ, Sun XH, Li JJ, Tan ZW, Gao ZH, Duan FF, Tan JH, Sun SQ, Song YS. Positive-Parity Linear-Chain Molecular Band in ^{16}C. Phys Rev Lett 2020; 124:192501. [PMID: 32469564 DOI: 10.1103/physrevlett.124.192501] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Revised: 03/31/2020] [Accepted: 04/22/2020] [Indexed: 06/11/2023]
Abstract
An inelastic excitation and cluster-decay experiment ^{2}H(^{16}C,^{4}He+^{12}Be or ^{6}He+^{10}Be)^{2}H was carried out to investigate the linear-chain clustering structure in neutron-rich ^{16}C. For the first time, decay paths from the ^{16}C resonances to various states of the final nuclei were determined, thanks to the well-resolved Q-value spectra obtained from the threefold coincident measurement. The close-threshold resonance at 16.5 MeV is assigned as the J^{π}=0^{+} band head of the predicted positive-parity linear-chain molecular band with (3/2_{π}^{-})^{2}(1/2_{σ}^{-})^{2} configuration, according to the associated angular correlation and decay analysis. Other members of this band were found at 17.3, 19.4, and 21.6 MeV based on their selective decay properties, being consistent with the theoretical predictions. Another intriguing high-lying state was observed at 27.2 MeV which decays almost exclusively to ^{6}He+^{10}Be(∼6 MeV) final channel, corresponding well to another predicted linear-chain structure with the pure σ-bond configuration.
Collapse
Affiliation(s)
- Y Liu
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - Y L Ye
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - J L Lou
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - X F Yang
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - T Baba
- Kitami Institute of Technology, 090-8507 Kitami, Japan
| | - M Kimura
- Department of Physics, Hokkaido University, 060-0810 Sapporo, Japan
| | - B Yang
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - Z H Li
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - Q T Li
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - J Y Xu
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - Y C Ge
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - H Hua
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - J S Wang
- School of Science, Huzhou University, Huzhou 313000, China
- Institute of Modern Physics, Chinese Academy of Science, Lanzhou 730000, China
| | - Y Y Yang
- Institute of Modern Physics, Chinese Academy of Science, Lanzhou 730000, China
| | - P Ma
- Institute of Modern Physics, Chinese Academy of Science, Lanzhou 730000, China
| | - Z Bai
- Institute of Modern Physics, Chinese Academy of Science, Lanzhou 730000, China
| | - Q Hu
- Institute of Modern Physics, Chinese Academy of Science, Lanzhou 730000, China
| | - W Liu
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - K Ma
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - L C Tao
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - Y Jiang
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - L Y Hu
- Fundamental Science on Nuclear Safety and Simulation Technology Laboratory, Harbin Engineering University, Harbin 150001, China
| | - H L Zang
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - J Feng
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - H Y Wu
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - J X Han
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - S W Bai
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - G Li
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - H Z Yu
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - S W Huang
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - Z Q Chen
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - X H Sun
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - J J Li
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - Z W Tan
- School of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
| | - Z H Gao
- Institute of Modern Physics, Chinese Academy of Science, Lanzhou 730000, China
| | - F F Duan
- Institute of Modern Physics, Chinese Academy of Science, Lanzhou 730000, China
| | - J H Tan
- Fundamental Science on Nuclear Safety and Simulation Technology Laboratory, Harbin Engineering University, Harbin 150001, China
| | - S Q Sun
- Fundamental Science on Nuclear Safety and Simulation Technology Laboratory, Harbin Engineering University, Harbin 150001, China
| | - Y S Song
- Fundamental Science on Nuclear Safety and Simulation Technology Laboratory, Harbin Engineering University, Harbin 150001, China
| |
Collapse
|
32
|
Kumar N, Tan JH, Ravikumar N, Tan JYH, Milavec H, Agrawal R, Kannan R, Kumar A. Evaluation of the Feasibility of Transfusing Leucocyte Depletion Filter (LDF) Processed Intra-Operative Cell Salvage (IOCS) Blood in Metastatic Spine Tumour Surgery (MSTS): Protocol for a Non Randomised study (Preprint). JMIR Res Protoc 2019. [DOI: 10.2196/16986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
|
33
|
Tan JH, Lip H, Ong W, Omar S. Intrauterine contraceptive device embedded in bladder wall with calculus formation removed successfully with open surgery. Malays Fam Physician 2019; 14:29-31. [PMID: 31827733 PMCID: PMC6818694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
An Intrauterine contraceptive devices (IUCD) is commonly inserted by the primary health care physician. It can migrate into pelvic or abdominal organs. When a pregnancy occurs following an insertion of an IUCD, there should be a high suspicion of uterine perforation or possible migration. A radiograph can be done in the primary health care clinic to search for a missing IUCD. Early referral to the urology service is warranted when a patient presents with recurrent urinary tract infections. Removal of an intravesical IUCD can be managed with cystoscopy, laparoscopy or open surgery. Herein, we report a case of IUCD migration into the bladder. This case will highlight the importance of proper technique, careful insertion and the role of ultrasound.
Collapse
Affiliation(s)
- J H Tan
- (MRCS), Department of General Surgery, Hospital Sultanah Aminah, Jalan Abu Bakar, Masjid Sultan Abu Bakar 80000 Johor Bahru, Johor, Malaysia. E-mail:
| | - Htc Lip
- MD, Department of General Surgery Faculty of Medicine, National University of Malaysia Medical Centre, Kuala Lumpur, Malaysia.
| | - Wlk Ong
- (MRCS), Department of Urology, Hospital Sultanah Aminah, Johor Bahru Malaysia.
| | - S Omar
- (FRCS), Department of General Surgery Hospital Sultanah Aminah, Johor Bahru, Malaysia.
| |
Collapse
|
34
|
Ng ZQ, Tan JH, Tan H. Caecal Volvulus after a dental procedure - not just constipation! Malays Fam Physician 2019; 14:32-35. [PMID: 31827734 PMCID: PMC6818687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Caecal volvulus has been reported to be associated with various abdominal and pelvic pathologies. Its signs and symptoms are usually non-specific and maybe overlooked in favour of benign causes, such as constipation. A high degree of suspicion is required for prompt diagnosis. Herein, we report on an unusual case of caecal volvulus after a dental procedure that was managed initially as constipation.
Collapse
Affiliation(s)
- Z Q Ng
- MBBS Hons, Department of General Surgery St John of God Subiaco Hospital Perth, WA, Australia
| | - J H Tan
- (MRCS), Department of General Surgery Hospital Sultanah Aminah, Jalan Abu Bakar, Masjid Sultan Abu Bake 80000 Johor Bahru, Johor Malaysia.
| | - Hcl Tan
- MD, Department of General Surgery Faculty of Medicine, National University of Malaysia Medical Centre, Kuala Lumpur Malaysia.
| |
Collapse
|
35
|
Chen WS, Tan JH, Mohamad Y, Imran R. External validation of a modified trauma and injury severity score model in major trauma injury. Injury 2019; 50:1118-1124. [PMID: 30591225 DOI: 10.1016/j.injury.2018.12.031] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Revised: 12/08/2018] [Accepted: 12/21/2018] [Indexed: 02/02/2023]
Abstract
BACKGROUND The establishment of an accurate prognostic model in major trauma patients is important mainly because this group of patients will benefit the most. Clinical prediction models must be validated internally and externally on a regular basis to ensure the prediction is accurate and current. This study aims to externally validate two prediction models, the Trauma and Injury Severity Score model developed using the Major Trauma Outcome Study in North America (MTOS-TRISS model), and the NTrD-TRISS model, which is a refined MTOS-TRISS model with coefficients derived from the Malaysian National Trauma Database (NTrD), by regarding mortality as the outcome measurement. METHOD This retrospective study included patients with major trauma injuries reported to a trauma centre of Hospital Sultanah Aminah over a 6-year period from 2011 and 2017. Model validation was examined using the measures of discrimination and calibration. Discrimination was assessed using the area under the receiver operating characteristic curve (AUC) and 95% confidence interval (CI). The Hosmer-Lemeshow (H-L) goodness-of-fit test was used to examine calibration capabilities. The predictive validity of both MTOS-TRISS and NTrD-TRISS models were further evaluated by incorporating parameters such as the New Injury Severity Scale and the Injury Severity Score. RESULTS Total patients of 3788 (3434 blunt and 354 penetrating injuries) with average age of 37 years (standard deviation of 16 years) were included in this study. All MTOS-TRISS and NTrD-TRISS models examined in this study showed adequate discriminative ability with AUCs ranged from 0.86 to 0.89 for patients with blunt trauma mechanism and 0.89 to 0.99 for patients with penetrating trauma mechanism. The H-L goodness-of-fit test indicated the NTrD-TRISS model calibrated as good as the MTOS-TRISS model for patients with blunt trauma mechanism. CONCLUSION For patients with blunt trauma mechanism, both the MTOS-TRISS and NTrD-TRISS models showed good discrimination and calibration performances. Discrimination performance for the NTrD-TRISS model was revealed to be as good as the MTOS-TRISS model specifically for patients with penetrating trauma mechanism. Overall, this validation study has ascertained the discrimination and calibration performances of the NTrD-TRISS model to be as good as the MTOS-TRISS model particularly for patients with blunt trauma mechanism.
Collapse
Affiliation(s)
- W S Chen
- Department of Statistics, Data Science and Epidemiology, Swinburne University of Technology, Melbourne, Australia.
| | - J H Tan
- General Surgery Department, Hospital Sultanah Aminah, Johor Bahru, Malaysia.
| | - Y Mohamad
- General Surgery Department, Hospital Sultanah Aminah, Johor Bahru, Malaysia.
| | - R Imran
- General Surgery Department, Hospital Sultanah Aminah, Johor Bahru, Malaysia.
| |
Collapse
|
36
|
Wang VTJ, Tan JH, Pay LH, Wu T, Shen L, O'Neill GK, Kumar VP. A comparison of Streptococcus agalactiae septic arthritis and non-Streptococcus agalactiae septic arthritis. Singapore Med J 2019; 59:528-533. [PMID: 30386859 DOI: 10.11622/smedj.2018127] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
INTRODUCTION Streptococcus agalactiae (Group B Streptococcus, GBS) is an uncommon cause of septic arthritis in the adult population. In recent years, there has been an increase in the incidence of GBS septic arthritis. This study aims to compare the clinical presentation, investigations, microbiology and outcome of management in patients with GBS and non-GBS septic arthritis. METHODS Retrospective review of hospital surgical records was done to identify all patients treated surgically at our institution from January 2011 to January 2016 for primary septic arthritis. Patients were categorised into two groups: those with culture-proven GBS septic arthritis and those with causative pathogens that were not GBS. Patients who were medically unfit for surgical intervention as well as those who declined interventional procedures were excluded from the study. RESULTS A total of 83 patients were included in the study: 62 (74.7%) had non-GBS septic arthritis and 21 (25.3%) had GBS septic arthritis. Patients with GBS septic arthritis were more likely to have polyarticular involvement (p < 0.001) and involvement of less common sites such as the elbow joint. They were also more likely to have elevated inflammatory markers (C-reactive protein > 150 mg/L; p = 0.017) and positive blood cultures (p = 0.02), and were typically healthy adults with no medical comorbidities (p = 0.012). CONCLUSION Patients with GBS septic arthritis were more likely to present with polyarticular involvement, positive blood cultures and higher levels of C-reactive protein on admission, and tended to be healthier individuals with no medical comorbidities.
Collapse
Affiliation(s)
| | - Jiong Hao Tan
- Department of Orthopaedic Surgery, National University Hospital, Singapore
| | - Leon Han Pay
- Department of Orthopaedic Surgery, National University Hospital, Singapore
| | - Tianyi Wu
- Department of Orthopaedic Surgery, National University Hospital, Singapore
| | - Liang Shen
- Biostatistics Unit, National University of Singapore, Singapore
| | - Gavin Kane O'Neill
- Department of Orthopaedic Surgery, National University Hospital, Singapore
| | | |
Collapse
|
37
|
Ming J, Lei P, Duan JL, Tan JH, Lou HP, Di DY, Wang DY. [National experts consensus on tracheotomy and intubation for burn patients (2018 version)]. Zhonghua Shao Shang Za Zhi 2018; 34:E006. [PMID: 30440148 DOI: 10.3760/cma.j.issn.1009-2587.2018.11.e006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Airway edema, stenosis, obstruction and even asphyxia are easy to occur in patients with extensive burn, deep burn of head, face, and neck area, inhalation injuries, etc., which threaten life. Timely tracheotomy and intubation is an important treatment measure, but lack of knowledge and improper handling in some hospitals resulted in airway obstruction. The technique of percutaneous tracheotomy and intubation provides convenience for emergency treatment of critical burns and mass burn. The Chinese Geriatrics Society organized some experts in China to discuss the indications, timing, methods, extubation, and precautions of tracheotomy and intubation for burn patients. The national experts consensus on tracheotomy and intubation for burn patients (2018 version) was written to provide a reference standard for clinical treatment.
Collapse
Affiliation(s)
| | | | - P Lei
- 030009 Taiyuan, Burn Care Center of Shanxi Province, the Sixth Hospital of Shanxi Medical University
| | | | | | | | | | | |
Collapse
|
38
|
Ming J, Lei P, Duan JL, Tan JH, Lou HP, Di DY, Wang D. [National experts consensus on tracheotomy and intubation for burn patients (2018 version)]. Zhonghua Shao Shang Za Zhi 2018; 34:782-785. [PMID: 30481918 DOI: 10.3760/cma.j.issn.1009-2587.2018.11.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Airway edema, stenosis, obstruction and even asphyxia are easy to occur in patients with extensive burn, deep burn of head, face, and neck area, inhalation injuries, etc., which threaten life. Timely tracheotomy and intubation is an important treatment measure, but lack of knowledge and improper handling in some hospitals resulted in airway obstruction. The technique of percutaneous tracheotomy and intubation provides convenience for emergency treatment of critical burns and mass burn. The Burn and Trauma Branch of Chinese Geriatrics Society organized some experts in China to discuss the indications, timing, methods, extubation, and precautions of tracheotomy and intubation for burn patients. The national experts consensus on tracheotomy and intubation for burn patients (2018 version) was written to provide a reference standard for clinical treatment.
Collapse
|
39
|
Hong CC, Nashi N, Tan JH, Manohara R, Lee WT, Murphy DP. Intraoperative periprosthetic femur fracture during bipolar hemiarthroplasty for displaced femoral neck fractures. Arch Orthop Trauma Surg 2018; 138:1189-1198. [PMID: 29770880 DOI: 10.1007/s00402-018-2952-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2017] [Indexed: 02/09/2023]
Abstract
INTRODUCTION We aim to review the incidence and risk factors for the development of intraoperative periprosthetic femur fractures while performing a bipolar hemiarthroplasty for displaced neck of femur fractures. Our secondary aim is to characterize the types of intraoperative periprosthetic fractures, the steps leading to the fractures, and the salvage treatments instituted. MATERIALS AND METHODS 271 patients treated with bipolar hemiarthroplasty after traumatic displaced femoral neck fractures were retrospectively analyzed. Demographic data, co-morbidities, vitamin D level, consumption of steroids, ASA score, surgical approach, surgeon experience, use of cemented or uncemented implants, proximal femur morphology, and types of anaesthesia were analyzed statistically. RESULTS There were 28 patients (10.3%) with intraoperative periprosthetic femur fractures. We found two significant independent risk factors which were the use of uncemented prosthesis (OR 4.15; 95% CI 1.65-10.46; p = 0.003) and Dorr type C proximal femurs (Dorr A OR 3.6; 95% CI 1.47-8.82; p = 0.005). In addition, patients with Dorr type C proximal femurs who underwent uncemented bipolar hemiarthroplasty were more likely to sustain an intraoperative periprosthetic fracture (14(73.7%) out of 19 patients; p = 0.002). There were no significant differences found in other risk factors. The most common location for these fractures was at the greater trochanter at 11 (39.3%) cases. Majority of them, 15 (53.6%), had intraoperative fractures during trial implant insertion and reduction. CONCLUSION The overall incidence of intraoperative periprosthetic femur fractures during hemiarthroplasty for displaced neck of femur fractures was 10.3%. The incidence was significantly higher for uncemented (14.7%) when compared to cemented prosthesis (5.4%) and the greater trochanter was the commonest area for periprosthetic fractures during trial implant insertion and reduction. Uncemented prosthesis and Dorr type C proximal femurs were two significant independent risk factors contributing to intraoperative periprosthetic fractures. By identifying these risk factors, surgeons can take ample precautions to prevent complications.
Collapse
Affiliation(s)
- Choon Chiet Hong
- c/o Department of Orthopaedic Surgery, University Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Hospital, 1E Kent Ridge Road, Singapore, 119228, Singapore.
| | - Nazrul Nashi
- c/o Department of Orthopaedic Surgery, University Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Hospital, 1E Kent Ridge Road, Singapore, 119228, Singapore
| | - Jiong Hao Tan
- c/o Department of Orthopaedic Surgery, University Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Hospital, 1E Kent Ridge Road, Singapore, 119228, Singapore
| | - Ruben Manohara
- c/o Department of Orthopaedic Surgery, University Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Hospital, 1E Kent Ridge Road, Singapore, 119228, Singapore
| | - Wei Ting Lee
- c/o Department of Orthopaedic Surgery, University Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Hospital, 1E Kent Ridge Road, Singapore, 119228, Singapore
| | - Diarmuid Paul Murphy
- c/o Department of Orthopaedic Surgery, University Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Hospital, 1E Kent Ridge Road, Singapore, 119228, Singapore
| |
Collapse
|
40
|
Jefferis JM, Jones RK, Currie ZI, Tan JH, Salvi SM. Orbital decompression for thyroid eye disease: methods, outcomes, and complications. Eye (Lond) 2017; 32:626-636. [PMID: 29243735 DOI: 10.1038/eye.2017.260] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2017] [Accepted: 10/04/2017] [Indexed: 11/09/2022] Open
Abstract
PurposeTo determine the safety and effectiveness of orbital decompression for thyroid eye disease (TED) in our unit. To put this in the context of previously published literature.Patients and methodsA retrospective case review of all patients undergoing orbital decompression for TED under the care of one orbital surgeon (SMS) between January 2009 and December 2015. A systematic literature review of orbital decompression for TED.ResultsWithin the reviewed period, 93 orbits of 55 patients underwent decompression surgery for TED. There were 61 lateral (single) wall decompressions, 17 medial one-and-a-half wall, 11 two-and-a-half wall, 2 balanced two wall, and 2 orbital fat only decompressions. For the lateral (single) wall decompressions, mean reduction in exophthalmometry (95% confidence interval (CI) was 4.2 mm (3.7-4.8), for the medial one-and-a-half walls it was 2.9 mm (2.1-3.7), and for the two-and-a-half walls it was 7.6 mm (5.8-9.4). The most common complications were temporary postoperative numbness (29% of lateral decompressions, 17% of other bony decompressions, OR 0.50, 95% CI 0.12-2.11) and new postoperative diplopia (9% of lateral decompressions, 39% of other bony decompressions, OR 6.8, 95% CI 1. 5-30.9). Systematic literature searching showed reduction in exophthalmometry for lateral wall surgery of 3.6-4.8 mm, with new diplopia 0-38% and postoperative numbness 12-50%. For other bony decompressions, reduction in exophthalmometry was 2.5-8.0 mm with new diplopia 0-45% and postoperative numbness up to 52%.ConclusionDiffering approaches to orbital decompression exist. If the correct type of surgery is chosen, then safe, adequate surgical outcomes can be achieved.
Collapse
Affiliation(s)
- J M Jefferis
- The Eye Department, Royal Hallamshire Hospital, Sheffield, South Yorkshire, UK
| | - R K Jones
- The Eye Department, Royal Hallamshire Hospital, Sheffield, South Yorkshire, UK
| | - Z I Currie
- The Eye Department, Royal Hallamshire Hospital, Sheffield, South Yorkshire, UK
| | - J H Tan
- The Eye Department, Royal Hallamshire Hospital, Sheffield, South Yorkshire, UK
| | - S M Salvi
- The Eye Department, Royal Hallamshire Hospital, Sheffield, South Yorkshire, UK
| |
Collapse
|
41
|
Tan JH, Yeo JL, Oliver R, Lyons M, Robinson T, Staniforth A, Ahsan A, Walsh J, Jamil-Copley S, Ng Kam Chuen MJ. 122Reducing the burden of unnecessary LINQ implantable loop recorder remote downloads by implementing an in-hospital multidisciplinary strategy to individualise management of patients with high volume downloads. Europace 2017. [DOI: 10.1093/europace/eux283.116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
|
42
|
Cao F, Fang Y, Tan HK, Goh Y, Choy JYH, Koh BTH, Hao Tan J, Bertin N, Ramadass A, Hunter E, Green J, Salter M, Akoulitchev A, Wang W, Chng WJ, Tenen DG, Fullwood MJ. Super-Enhancers and Broad H3K4me3 Domains Form Complex Gene Regulatory Circuits Involving Chromatin Interactions. Sci Rep 2017; 7:2186. [PMID: 28526829 PMCID: PMC5438348 DOI: 10.1038/s41598-017-02257-3] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2016] [Accepted: 04/19/2017] [Indexed: 12/21/2022] Open
Abstract
Stretched histone regions, such as super-enhancers and broad H3K4me3 domains, are associated with maintenance of cell identity and cancer. We connected super-enhancers and broad H3K4me3 domains in the K562 chronic myelogenous leukemia cell line as well as the MCF-7 breast cancer cell line with chromatin interactions. Super-enhancers and broad H3K4me3 domains showed higher association with chromatin interactions than their typical counterparts. Interestingly, we identified a subset of super-enhancers that overlap with broad H3K4me3 domains and show high association with cancer-associated genes including tumor suppressor genes. Besides cell lines, we could observe chromatin interactions by a Chromosome Conformation Capture (3C)-based method, in primary human samples. Several chromatin interactions involving super-enhancers and broad H3K4me3 domains are constitutive and can be found in both cancer and normal samples. Taken together, these results reveal a new layer of complexity in gene regulation by super-enhancers and broad H3K4me3 domains.
Collapse
Affiliation(s)
- Fan Cao
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Yiwen Fang
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Hong Kee Tan
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Yufen Goh
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Jocelyn Yeen Hui Choy
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Bryan Thean Howe Koh
- Department of Orthopedic Surgery, National University Health Systems (NUHS), Singapore, Singapore
| | - Jiong Hao Tan
- Department of Orthopedic Surgery, National University Health Systems (NUHS), Singapore, Singapore
| | - Nicolas Bertin
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore.,Human Longevity Singapore Pte. Ltd., Singapore, Singapore
| | | | | | | | | | | | - Wilson Wang
- Department of Orthopedic Surgery, National University Health Systems (NUHS), Singapore, Singapore
| | - Wee Joo Chng
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore.,National University Cancer Institute, National University Health System, Singapore, Singapore.,Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Daniel G Tenen
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Melissa J Fullwood
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore. .,School of Biological Sciences, Nanyang Technological University, Singapore, Singapore. .,Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore. .,Yale-NUS Liberal Arts College, Singapore, Singapore.
| |
Collapse
|
43
|
Abstract
Distal junctional failure (DJF) with fracture at the last instrumented vertebra is a rare occurrence. In this case report, we present two patients with L5 vertebral fracture post-instrumented fusion of the lumbar spine. The first patient is a 78-year-old female who had multi-level degenerative disc disease, spinal stenosis and degenerative scoliosis involving levels T12 to L5. She underwent instrumented posterolateral fusion (PLF) from T12 to L5, and transforaminal lumbar interbody fusion (TLIF) at L2/3 and L4/5. Six months after her operation, she presented with a fracture of the L5 vertebral body necessitating revision of the L5 pedicle screws, with additional TLIF of L5/S1. The second patient is a 71-year-old female who underwent decompression and TLIF of L3/4 and L4/5 for degenerative spondylolisthesis. Six months after the surgery, she developed a fracture of the L5 vertebral body with loosening of the L5 screws. The patient declined revision surgery despite being symptomatic. DJF remains poorly understood as its rare incidence precludes sufficiently powered studies within a single institution. This report aims to contribute to the currently scarce literature on DJF.
Collapse
Affiliation(s)
- Jiong Hao Tan
- University Orthopaedics, Hand and Reconstructive Microsurgery Cluster (UOHC), National University Health System, Singapore
| | - Kimberly-Anne Tan
- University Orthopaedics, Hand and Reconstructive Microsurgery Cluster (UOHC), National University Health System, Singapore
| | - Hwee Weng Dennis Hey
- University Orthopaedics, Hand and Reconstructive Microsurgery Cluster (UOHC), National University Health System, Singapore
| | - Hee-Kit Wong
- University Orthopaedics, Hand and Reconstructive Microsurgery Cluster (UOHC), National University Health System, Singapore
| |
Collapse
|
44
|
Yang ZQ, Chen H, Tan JH, Xu HL, Jia J, Feng YH. Cloning of three genes involved in the flavonoid metabolic pathway and their expression during insect resistance in Pinus massoniana Lamb. Genet Mol Res 2016; 15:gmr-15-04-gmr.15049332. [PMID: 28081282 DOI: 10.4238/gmr15049332] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Pinus massoniana Lamb. is an important timber and turpentine-producing tree species in China. Dendrolimus punctatus and Dasychira axutha are leaf-eating pests that have harmful effects on P. massoniana production. Few studies have focused on the molecular mechanisms underlying pest resistance in P. massoniana. Based on sequencing analysis of the transcriptomes of insect-resistant P. massoniana, three key genes involved in the flavonoid metabolic pathway were identified in the present study (PmF3H, PmF3'5'H, and PmC4H). Structural domain analysis showed that the PmF3H gene contains typical binding sites for the 2OG-Fe (II) oxygenase superfamily, while PmF3'5'H and PmC4H both contain the cytochrome P450 structural domain, which is specific for P450 enzymes. Phylogenetic analysis showed that each of the three P. massoniana genes, and the homologous genes in gymnosperms, clustered into a group. Expression of these three genes was highest in the stems, and was higher in the insect-resistant P. massoniana varieties than in the controls. The extent of the increased expression in the insect-resistant P. massoniana varieties indicated that these three genes are involved in defense mechanisms against pests in this species. In the insect-resistant varieties, rapid induction of PmF3H increased the levels of PmF3'5'H and PmC4H expression. The enhanced anti-pest capability of the insect-resistant varieties could be related to temperature and humidity. In addition, these results suggest that these three genes maycontribute to the change in flower color during female cone development.
Collapse
Affiliation(s)
| | | | - J H Tan
- Guangxi Forestry Research Institute, Engineering Research Center of Masson Pine of State Forestry Administration, Engineering Research Center of Masson Pine of Guangxi, Nanning, China
| | - H L Xu
- Guangxi Forestry Research Institute, Engineering Research Center of Masson Pine of State Forestry Administration, Engineering Research Center of Masson Pine of Guangxi, Nanning, China
| | - J Jia
- Guangxi Forestry Research Institute, Engineering Research Center of Masson Pine of State Forestry Administration, Engineering Research Center of Masson Pine of Guangxi, Nanning, China
| | - Y H Feng
- Guangxi Forestry Research Institute, Engineering Research Center of Masson Pine of State Forestry Administration, Engineering Research Center of Masson Pine of Guangxi, Nanning, China
| |
Collapse
|
45
|
Cornall AM, Poljak M, Garland SM, Phillips S, Tan JH, Machalek DA, Quinn MA, Tabrizi SN. Anyplex II HPV28 detection and Anyplex II HPV HR detection assays are highly concordant with other commercial assays for detection of high-risk HPV genotypes in women with high grade cervical abnormalities. Eur J Clin Microbiol Infect Dis 2016; 36:545-551. [PMID: 27822653 DOI: 10.1007/s10096-016-2831-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2016] [Accepted: 10/23/2016] [Indexed: 11/25/2022]
Abstract
PURPOSE to evaluate the performance of Anyplex II HPV28 and HPV HR Detection assays against the EuroArray HPV, Cobas 4800 HPV (Cobas), HPV Amplicor (Amp), Linear Array HPV (LA) and Hybrid Capture 2 (HC2) in detection of high-risk HPV (HR-HPV) from liquid-based cervical cytology samples. METHODS cervical specimens from 404 women undergoing management of high-grade cytological abnormality were evaluated by Anyplex II HPV28 and HPV HR Detection assays for detection of HR-HPV genotypes and prediction of histologically-confirmed cervical intraepithelial neoplasia grade 2 or higher (≥CIN2). The results were compared to EuroArray, HC2, Cobas, Amp, and LA. RESULTS specimens were evaluated from 404 women with an average age of 30 years, including 336 with a histological diagnosis of ≥ CIN2 and 68 with ≤ CIN1. Concordance of HR-HPV detection between Anyplex II HPV28 and other genotyping assays was 94.79 % (κ = 0.84; EuroArray) and 97.27 % (κ = 0.91; LA); and between Anyplex II HPV HR and other HR-HPV detection assays was 86.35 % (κ = 0.62; HC2), 96.03 % (κ = 0.87; Cobas) and 96.77 % (κ = 0.89; Amp). Using HR-HPV detection for prediction of ≥ CIN2 by Anyplex II HPV28 and HPV HR, sensitivity (90.18, 95 % CI 86.48-93.14; 90.77, 95 % CI 87.16-93.65) and specificity (both 67.16, 95 % CI 54.60-78.15) were not significantly different to the other HPV assays tested, with one exception. Both Anyplex assays had significantly higher sensitivity than HC2 (p < 0.0001), with a specificity of 96 % (p > 0.05) of HC2 in this high-risk population. CONCLUSIONS both Anyplex II HPV detection assays were concordant with other commercial assays for HR-HPV detection, with comparable sensitivity and specificity for ≥ CIN2 detection.
Collapse
Affiliation(s)
- A M Cornall
- Regional HPV Lab Net Reference Laboratory, Department of Microbiology and Infectious Diseases, The Royal Women's Hospital, Parkville, 3052, Victoria, Australia.
- Murdoch Childrens Research Institute, Parkville, 3052, Victoria, Australia.
- Department of Obstetrics and Gynecology, University of Melbourne, Parkville, 3052, Victoria, Australia.
| | - M Poljak
- Regional HPV Lab Net Reference Laboratory, Department of Microbiology and Infectious Diseases, The Royal Women's Hospital, Parkville, 3052, Victoria, Australia
- Murdoch Childrens Research Institute, Parkville, 3052, Victoria, Australia
| | - S M Garland
- Regional HPV Lab Net Reference Laboratory, Department of Microbiology and Infectious Diseases, The Royal Women's Hospital, Parkville, 3052, Victoria, Australia
- Murdoch Childrens Research Institute, Parkville, 3052, Victoria, Australia
- Department of Obstetrics and Gynecology, University of Melbourne, Parkville, 3052, Victoria, Australia
| | - S Phillips
- Regional HPV Lab Net Reference Laboratory, Department of Microbiology and Infectious Diseases, The Royal Women's Hospital, Parkville, 3052, Victoria, Australia
- Murdoch Childrens Research Institute, Parkville, 3052, Victoria, Australia
| | - J H Tan
- Department of Obstetrics and Gynecology, University of Melbourne, Parkville, 3052, Victoria, Australia
- Oncology and Dysplasia Unit, Royal Women's Hospital, Parkville, 3052, Victoria, Australia
| | - D A Machalek
- Regional HPV Lab Net Reference Laboratory, Department of Microbiology and Infectious Diseases, The Royal Women's Hospital, Parkville, 3052, Victoria, Australia
- Murdoch Childrens Research Institute, Parkville, 3052, Victoria, Australia
| | - M A Quinn
- Department of Obstetrics and Gynecology, University of Melbourne, Parkville, 3052, Victoria, Australia
- Oncology and Dysplasia Unit, Royal Women's Hospital, Parkville, 3052, Victoria, Australia
| | - S N Tabrizi
- Regional HPV Lab Net Reference Laboratory, Department of Microbiology and Infectious Diseases, The Royal Women's Hospital, Parkville, 3052, Victoria, Australia
- Murdoch Childrens Research Institute, Parkville, 3052, Victoria, Australia
- Department of Obstetrics and Gynecology, University of Melbourne, Parkville, 3052, Victoria, Australia
| |
Collapse
|
46
|
Abstract
PURPOSE To assess the compression and flexural strength of bone cement mixed with 0 ml, 1 ml, or 2 ml of blood. METHODS High viscosity polymethyl methacrylate (PMMA) loaded with or without gentamicin was used. Blood was collected from total knee arthroplasty patients. In the same operating room, one pack of cement each was mixed with 0 ml (control), 1 ml, or 2 ml of blood for 1 minute during the dough phase. The dough was extruded into cylindrical and rectangular moulds for 20 minutes of setting, and then cured in phosphate buffered saline at 37±1ºC for 7 days. The samples were visually inspected for fractures and areas of weakness, and then scanned using microcomputed tomography. 48 gentamicin-loaded and 59 non-gentamicin-loaded samples mixed with 0 ml (control), 1 ml, or 2 ml of blood were randomised for flexural and compression strength testing; each group had at least 6 samples. RESULTS In samples loaded with or without gentamicin, the flexural and compressive strength was highest in controls, followed by samples mixed with 1 ml or 2 ml of blood. In samples mixed with 2 ml of blood, the flexural strength fell below the standard of 50 MPa. In samples mixed with 2 ml of blood and all gentamicin-loaded samples, the compressive strength fell below the standard of 70 MPa. Microcomputed tomography revealed areas of voids and pores indicating the presence of laminations and partitions within. CONCLUSION The biomechanical strength of PMMA contaminated with blood may decrease. Precautions such as saline lavage, pack drying the bone, change of gloves, and prompt insertion of the implant should be taken to prevent blood from contaminating bone cement.
Collapse
Affiliation(s)
- J H Tan
- Department of Orthopedic Surgery, National University Health Systems, Singapore
| | - B Th Koh
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - A K Ramruttun
- Department of Orthopedic Surgery, National University Health Systems, Singapore
| | - W Wang
- Department of Orthopedic Surgery, National University Health Systems, Singapore
| |
Collapse
|
47
|
Cornall AM, Poljak M, Garland SM, Phillips S, Machalek DA, Tan JH, Quinn MA, Tabrizi SN. EUROarray human papillomavirus (HPV) assay is highly concordant with other commercial assays for detection of high-risk HPV genotypes in women with high grade cervical abnormalities. Eur J Clin Microbiol Infect Dis 2016; 35:1033-6. [PMID: 27048314 DOI: 10.1007/s10096-016-2634-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2016] [Accepted: 03/21/2016] [Indexed: 10/22/2022]
Abstract
The purpose of this study was to evaluate the performance of the EUROIMMUN EUROArray HPV genotyping assay against the Roche Cobas 4800, Roche HPV Amplicor, Roche Linear Array and Qiagen Hybrid Capture 2 assays in the detection of high-risk HPV (HR-HPV) from liquid based cervical cytology samples collected from women undergoing follow-up for abnormal cervical cytology results. Cervical specimens from 404 women undergoing management of high-grade cytological abnormality were evaluated by EUROarray HPV for detection of HR-HPV genotypes and prediction of histologically-confirmed cervical intraepithelial neoplasia grade 2 or higher (≥CIN2). The results were compared to Hybrid Capture 2, Cobas 4800 HPV, Amplicor and Linear Array HPV. Positivity for 14 HR-HPV types was 80.0 % for EUROarray (95 % CI; 75.7-83.8 %). Agreement (κ, 95 % CI) between the EUROarray and other HPV tests for detection of HR-HPV was good to very good [Hybrid Capture κ = 0.62 (0.54-0.71); Cobas κ = 0.81 (0.74-0.88); Amplicor κ = 0.68 (0.60-0.77); Linear Array κ = 0.77 (0.70-0.85)]. For detection of HR-HPV, agreement with EUROarray was 87.90 % (Hybrid Capture), 93.58 % (Cobas), 92.84 % (Amplicor) and 92.59 % (Linear Array). Detection of HR-HPV was not significantly different between EUROarray and any other test (p < 0.001). EUROarray was concordant with other assays evaluated for detection of high-risk HPV and showed sensitivity and specificity for detection of ≥ CIN2 of 86 % and 71 %, respectively.
Collapse
Affiliation(s)
- A M Cornall
- Regional HPV Lab Net Reference Laboratory, Department of Microbiology and Infectious Diseases, The Royal Women's Hospital, Parkville, 3052, Victoria, Australia. .,Murdoch Childrens Research Institute, Parkville, 3052, Victoria, Australia.
| | - M Poljak
- Regional HPV Lab Net Reference Laboratory, Department of Microbiology and Infectious Diseases, The Royal Women's Hospital, Parkville, 3052, Victoria, Australia.,Murdoch Childrens Research Institute, Parkville, 3052, Victoria, Australia
| | - S M Garland
- Regional HPV Lab Net Reference Laboratory, Department of Microbiology and Infectious Diseases, The Royal Women's Hospital, Parkville, 3052, Victoria, Australia.,Murdoch Childrens Research Institute, Parkville, 3052, Victoria, Australia.,Department of Obstetrics and Gynaecology, University of Melbourne, Parkville, 3052, Victoria, Australia
| | - S Phillips
- Regional HPV Lab Net Reference Laboratory, Department of Microbiology and Infectious Diseases, The Royal Women's Hospital, Parkville, 3052, Victoria, Australia.,Murdoch Childrens Research Institute, Parkville, 3052, Victoria, Australia
| | - D A Machalek
- Regional HPV Lab Net Reference Laboratory, Department of Microbiology and Infectious Diseases, The Royal Women's Hospital, Parkville, 3052, Victoria, Australia.,Murdoch Childrens Research Institute, Parkville, 3052, Victoria, Australia
| | - J H Tan
- Department of Obstetrics and Gynaecology, University of Melbourne, Parkville, 3052, Victoria, Australia.,Oncology and Dysplasia Unit, Royal Women's Hospital, Parkville, 3052, Victoria, Australia
| | - M A Quinn
- Department of Obstetrics and Gynaecology, University of Melbourne, Parkville, 3052, Victoria, Australia.,Oncology and Dysplasia Unit, Royal Women's Hospital, Parkville, 3052, Victoria, Australia
| | - S N Tabrizi
- Regional HPV Lab Net Reference Laboratory, Department of Microbiology and Infectious Diseases, The Royal Women's Hospital, Parkville, 3052, Victoria, Australia.,Murdoch Childrens Research Institute, Parkville, 3052, Victoria, Australia.,Department of Obstetrics and Gynaecology, University of Melbourne, Parkville, 3052, Victoria, Australia
| |
Collapse
|
48
|
Salunke AA, Chen Y, Chen X, Tan JH, Singh G, Tai BC, Khin LW, Puhaindran ME. Does pathological fracture affect the rate of local recurrence in patients with a giant cell tumour of bone?: a meta-analysis. Bone Joint J 2016; 97-B:1566-71. [PMID: 26530662 DOI: 10.1302/0301-620x.97b11.35326] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
We investigated whether the presence of a pathological fracture increased the risk of local recurrence in patients with a giant cell tumour (GCT) of bone. We also assessed if curettage is still an appropriate form of treatment in the presence of a pathological fracture. We conducted a comprehensive review and meta-analysis of papers which reported outcomes in patients with a GCT with and without a pathological fracture at presentation. We computed the odds ratio (OR) of local recurrence in those with and without a pathological fracture. We selected 19 eligible papers for final analysis. This included 3215 patients, of whom 580 (18.0%) had a pathological fracture. The pooled OR for local recurrence between patients with and without a pathological fracture was 1.05 (95% confidence interval (CI) 0.66 to 1.67, p = 0.854). Amongst the subgroup of patients who were treated with curettage, the pooled OR for local recurrence was 1.23 (95% CI 0.75 to 2.01, p = 0.417). A post hoc sample size calculation showed adequate power for both comparisons. There is no difference in local recurrence rates between patients who have a GCT of bone with and without a pathological fracture at the time of presentation. The presence of a pathological fracture should not preclude the decision to perform curettage as carefully selected patients who undergo curettage can have similar outcomes in terms of local recurrence to those without such a fracture.
Collapse
Affiliation(s)
- A A Salunke
- National University Health System Singapore, 1E Kent Ridge Road, NUHS Tower Block, Level 11, Singapore, 119228, Singapore
| | - Y Chen
- National University Health System Singapore, 1E Kent Ridge Road, NUHS Tower Block, Level 11, Singapore, 119228, Singapore
| | - X Chen
- National University Health System Singapore, 1E Kent Ridge Road, NUHS Tower Block, Level 11, Singapore, 119228, Singapore
| | - J H Tan
- National University Health System Singapore, 1E Kent Ridge Road, NUHS Tower Block, Level 11, Singapore, 119228, Singapore
| | - G Singh
- National University Health System Singapore, 1E Kent Ridge Road, NUHS Tower Block, Level 11, Singapore, 119228, Singapore
| | - B C Tai
- National University of Singapore, Tahir Foundation Building, 12 Science Drive 2, #10-01, Singapore 117549, Singapore
| | - L W Khin
- National University of Singapore, 1E Kent Ridge Road, NUHS Tower Block, Level 11, Singapore, 119228, Singapore
| | - M E Puhaindran
- National University Health System Singapore, 1E Kent Ridge Road, NUHS Tower Block, Level 11, Singapore, 119228, Singapore
| |
Collapse
|
49
|
Tan JH, Hong CC, Shen L, Tay EY, Lee JK, Nather A. Costs of Patients Admitted for Diabetic Foot Problems. Ann Acad Med Singap 2015; 44:567-570. [PMID: 27090076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Affiliation(s)
- Jiong Hao Tan
- Department of Orthopaedic Surgery, National University of Singapore and National University Hospital, Singapore
| | | | | | | | | | | |
Collapse
|
50
|
Hong CC, Wang SM, Nather A, Tan JH, Tay SH, Poon KH. Chlorhexidine Anaphylaxis Masquerading as Septic Shock. Int Arch Allergy Immunol 2015; 167:16-20. [PMID: 26111940 DOI: 10.1159/000431358] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2014] [Accepted: 05/13/2015] [Indexed: 11/19/2022] Open
Abstract
Chlorhexidine is a commonly used antiseptic and disinfectant in the health-care setting. Its usage has increased in recent years with intensive campaigns and infection control guidelines to combat hospital-acquired infections. As a result, patients and health-care workers (HCW) are exposed to increasing chlorhexidine usage. In recent years, adverse reactions to chlorhexidine ranging from allergic contact dermatitis, photosensitivity, fixed drug eruptions, urticaria and anaphylactic shock have been reported. Most have been isolated case reports on adverse reactions occurring in healthy individuals or HCW. We report a case of anaphylactic shock caused by applying chlorhexidine cleansing solution and masquerading as septic shock from left-leg necrotising fasciitis.
Collapse
Affiliation(s)
- Choon Chiet Hong
- University Orthopaedics, Hand and Reconstructive Microsurgery Cluster, National University Hospital, Singapore, Singapore
| | | | | | | | | | | |
Collapse
|