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Khadivi G, Akhtari A, Sharifi F, Zargarian N, Esmaeili S, Ahsaie MG, Shahbazi S. Diagnostic accuracy of artificial intelligence models in detecting osteoporosis using dental images: a systematic review and meta-analysis. Osteoporos Int 2024:10.1007/s00198-024-07229-8. [PMID: 39177815 DOI: 10.1007/s00198-024-07229-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 08/10/2024] [Indexed: 08/24/2024]
Abstract
The current study aimed to systematically review the literature on the accuracy of artificial intelligence (AI) models for osteoporosis (OP) diagnosis using dental images. A thorough literature search was executed in October 2022 and updated in November 2023 across multiple databases, including PubMed, Scopus, Web of Science, and Google Scholar. The research targeted studies using AI models for OP diagnosis from dental radiographs. The main outcomes were the sensitivity and specificity of AI models regarding OP diagnosis. The "meta" package from the R Foundation was selected for statistical analysis. A random-effects model, along with 95% confidence intervals, was utilized to estimate pooled values. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool was employed for risk of bias and applicability assessment. Among 640 records, 22 studies were included in the qualitative analysis and 12 in the meta-analysis. The overall sensitivity for AI-assisted OP diagnosis was 0.85 (95% CI, 0.70-0.93), while the pooled specificity equaled 0.95 (95% CI, 0.91-0.97). Conventional algorithms led to a pooled sensitivity of 0.82 (95% CI, 0.57-0.94) and a pooled specificity of 0.96 (95% CI, 0.93-0.97). Deep convolutional neural networks exhibited a pooled sensitivity of 0.87 (95% CI, 0.68-0.95) and a pooled specificity of 0.92 (95% CI, 0.83-0.96). This systematic review corroborates the accuracy of AI in OP diagnosis using dental images. Future research should expand sample sizes in test and training datasets and standardize imaging techniques to establish the reliability of AI-assisted methods in OP diagnosis through dental images.
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Affiliation(s)
- Gita Khadivi
- Department of Oral and Maxillofacial Radiology, School of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Abtin Akhtari
- School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Farshad Sharifi
- Elderly Health Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Nicolette Zargarian
- School of Dentistry, Research Institute for Dental Sciences, Mkhitar Heratsi Yerevan State Medical University, Yerevan, Armenia
| | - Saharnaz Esmaeili
- Dentofacial Deformities Research Center, Research Institute of Dental Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mitra Ghazizadeh Ahsaie
- Department of Oral and Maxillofacial Radiology, School of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Soheil Shahbazi
- Dental Research Center, Research Institute for Dental Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
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Ylade M, Aziz AB, Daag JV, Crisostomo MV, Agrupis KA, Maronilla MA, Sye Lim Hong C, Kim HY, Njau I, Lopez MHJ, Deen J, Kim DR, You YA, Kang SSY, Marks F, Tadesse BT. Using Dried Blood Spots to Quantitatively Detect Anti-SARS-CoV-2 IgG Antibodies by ELISA: A Validation Study. Am J Trop Med Hyg 2024; 111:391-395. [PMID: 38917817 PMCID: PMC11310613 DOI: 10.4269/ajtmh.23-0306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 03/15/2024] [Indexed: 06/27/2024] Open
Abstract
SARS-CoV-2 serological testing is useful to determine seroprevalence, epidemiological trends, and the extent of transmission. The collection and transport of serum samples can be logistically challenging, especially in remote underserved areas. Dried blood spots (DBSs) would allow easier sample collection and logistical handling compared with standard serum collection, particularly for extensive and repeated SARS-CoV-2 serosurveys. We evaluated the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the IgG ELISA (Wantai, Beijing, China) using DBSs against sera for the quantitative detection of SARS-CoV-2 IgG antibody. The IgG ELISA was used to test paired sera and DBSs obtained from individuals with recent virologically confirmed COVID-19 illness and banked paired sera and DBSs collected before the COVID-19 pandemic. We found that 100/100 (100%) seropositive samples were positive using DBSs, and 193/194 (99%) seronegative samples were negative using DBSs. Compared with sera, the DBS method had a 100% sensitivity, 99% specificity, 99% PPV, and 100% NPV. Use of DBSs for SARS-CoV-2 household or population serosurveys may be considered in situations with limitations in sample collection, shipment, and storage.
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Affiliation(s)
- Michelle Ylade
- Institute of Child Health and Human Development, National Institutes of Health, University of the Philippines–Manila, Manila, Philippines
| | | | - Jedas Veronica Daag
- Institute of Child Health and Human Development, National Institutes of Health, University of the Philippines–Manila, Manila, Philippines
| | - Maria Vinna Crisostomo
- Institute of Child Health and Human Development, National Institutes of Health, University of the Philippines–Manila, Manila, Philippines
| | - Kristal-An Agrupis
- Institute of Child Health and Human Development, National Institutes of Health, University of the Philippines–Manila, Manila, Philippines
| | - Maria Angela Maronilla
- Institute of Child Health and Human Development, National Institutes of Health, University of the Philippines–Manila, Manila, Philippines
| | | | | | - Irene Njau
- International Vaccine Institute, Seoul, Korea
| | - March Helena Jane Lopez
- Institute of Child Health and Human Development, National Institutes of Health, University of the Philippines–Manila, Manila, Philippines
| | - Jacqueline Deen
- Institute of Child Health and Human Development, National Institutes of Health, University of the Philippines–Manila, Manila, Philippines
| | | | | | | | - Florian Marks
- International Vaccine Institute, Seoul, Korea
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, United Kingdom
- Heidelberg Institute of Global Health, University of Heidelberg, Heidelberg, Germany
- Madagascar Institute for Vaccine Research, University of Antananarivo, Antananarivo, Madagascar
| | - Birkneh Tilahun Tadesse
- International Vaccine Institute, Seoul, Korea
- Heidelberg Institute of Global Health, University of Heidelberg, Heidelberg, Germany
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
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Hinojosa-Amaya JM, González-Colmenero FD, Alvarez-Villalobos NA, Salcido-Montenegro A, Quintanilla-Sánchez C, Moreno-Peña PJ, Manzanares-Gallegos DM, Gutiérrez-Dávila LF, Castillo-Morales PL, García-Campa M, González-González JG, Varlamov E, Rodriguez-Gutiérrez R, Fleseriu M. The conundrum of differentiating Cushing's syndrome from non-neoplastic hypercortisolism: a systematic review and meta-analysis. Pituitary 2024; 27:345-359. [PMID: 38888685 DOI: 10.1007/s11102-024-01408-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/22/2024] [Indexed: 06/20/2024]
Abstract
CONTEXT Once hypercortisolemia is confirmed, differential diagnosis between Cushing's syndrome (CS) due to neoplastic endogenous hypercortisolism and non-neoplastic hypercortisolism (NNH, pseudo-Cushing's syndrome) is crucial. Due to worldwide corticotropin-releasing hormone (CRH) unavailability, accuracy of alternative tests to dexamethasone (Dex)-CRH, is clearly needed. OBJECTIVE Assess the diagnostic accuracy of Dex-CRH test, desmopressin stimulation test, midnight serum cortisol (MSC), and late-night salivary cortisol (LNSC) levels to distinguish CS from NNH. METHODS Articles through March 2022 were identified from Scopus, Web of Science, MEDLINE, EMBASE, and PubMed. All steps through the systematic review were performed independently and in duplicate and strictly adhered to the updated PRISMA-DTA checklist. DATA SYNTHESIS A total of 24 articles (1900 patients) were included. Dex-CRH had a pooled sensitivity and specificity of 91% (95%CI 87-94%; I2 0%) and 82% (73-88%; I2 50%), desmopressin test 86% (81-90%; I2 28%) and 90% (84-94%; I2 15%), MSC 91% (85-94%; I2 66%) and 81% (70-89%; I2 71%), and LNSC 80% (67-89%; I2 57%) and 90% (84-93%; I2 21%), respectively. Summary receiver operating characteristics areas under the curve were Dex-CRH 0.949, desmopressin test 0.936, MSC 0.942, and LNSC 0.950 without visual or statistical significance. The overall risk of studies bias was moderate. CONCLUSION Dex-CRH, the desmopressin stimulation test, and MSC have similar diagnostic accuracy, with Dex-CRH and MSC having slightly higher sensitivity, and the desmopressin test being more specific. LNSC was the least accurate, probably due to high heterogeneity, intrinsic variability, different assays, and lack of consistent reported cutoffs. When facing this challenging differential diagnosis, the results presented here should increase clinicians' confidence when deciding which test to perform.
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Affiliation(s)
- José Miguel Hinojosa-Amaya
- Pituitary Clinic, Endocrinology Division, Department of Medicine, Hospital Universitario "Dr. José E. González" Universidad Autónoma de Nuevo León, (Gonzalitos) S/N, Mitras Centro, 64460, Monterrey, Mexico
| | - Fernando Díaz González-Colmenero
- Advanced Analysis Center of Scientific Information, Universidad Autónoma de Nuevo León School of Medicine, 64460, Monterrey, Mexico
| | | | - Alejandro Salcido-Montenegro
- Advanced Analysis Center of Scientific Information, Universidad Autónoma de Nuevo León School of Medicine, 64460, Monterrey, Mexico
| | - Carolina Quintanilla-Sánchez
- Advanced Analysis Center of Scientific Information, Universidad Autónoma de Nuevo León School of Medicine, 64460, Monterrey, Mexico
| | - Pablo José Moreno-Peña
- Advanced Analysis Center of Scientific Information, Universidad Autónoma de Nuevo León School of Medicine, 64460, Monterrey, Mexico
| | - Dulce María Manzanares-Gallegos
- Advanced Analysis Center of Scientific Information, Universidad Autónoma de Nuevo León School of Medicine, 64460, Monterrey, Mexico
| | - Luis Fernando Gutiérrez-Dávila
- Advanced Analysis Center of Scientific Information, Universidad Autónoma de Nuevo León School of Medicine, 64460, Monterrey, Mexico
| | - Patricia Lizeth Castillo-Morales
- Advanced Analysis Center of Scientific Information, Universidad Autónoma de Nuevo León School of Medicine, 64460, Monterrey, Mexico
| | - Mariano García-Campa
- Advanced Analysis Center of Scientific Information, Universidad Autónoma de Nuevo León School of Medicine, 64460, Monterrey, Mexico
| | - José Gerardo González-González
- Pituitary Clinic, Endocrinology Division, Department of Medicine, Hospital Universitario "Dr. José E. González" Universidad Autónoma de Nuevo León, (Gonzalitos) S/N, Mitras Centro, 64460, Monterrey, Mexico
| | - Elena Varlamov
- Department of Medicine, Division of Endocrinology, Diabetes and Clinical Nutrition, Oregon Health & Science University, Portland, OR, USA
- Department of Neurological Surgery, Oregon Health & Science University, Portland, OR, USA
- Pituitary Center, Oregon Health & Science University, Portland, OR, USA
| | - René Rodriguez-Gutiérrez
- Pituitary Clinic, Endocrinology Division, Department of Medicine, Hospital Universitario "Dr. José E. González" Universidad Autónoma de Nuevo León, (Gonzalitos) S/N, Mitras Centro, 64460, Monterrey, Mexico.
- Advanced Analysis Center of Scientific Information, Universidad Autónoma de Nuevo León School of Medicine, 64460, Monterrey, Mexico.
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA.
| | - Maria Fleseriu
- Department of Medicine, Division of Endocrinology, Diabetes and Clinical Nutrition, Oregon Health & Science University, Portland, OR, USA.
- Department of Neurological Surgery, Oregon Health & Science University, Portland, OR, USA.
- Pituitary Center, Oregon Health & Science University, Portland, OR, USA.
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Dagher R, Ozkara BB, Karabacak M, Dagher SA, Rumbaut EI, Luna LP, Yedavalli VS, Wintermark M. Artificial intelligence/machine learning for neuroimaging to predict hemorrhagic transformation: Systematic review/meta-analysis. J Neuroimaging 2024. [PMID: 39034604 DOI: 10.1111/jon.13223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2024] [Revised: 06/04/2024] [Accepted: 07/07/2024] [Indexed: 07/23/2024] Open
Abstract
BACKGROUND AND PURPOSE Early and reliable prediction of hemorrhagic transformation (HT) in patients with acute ischemic stroke (AIS) is crucial for treatment decisions and early intervention. The purpose of this study was to conduct a systematic review and meta-analysis on the performance of artificial intelligence (AI) and machine learning (ML) models that utilize neuroimaging to predict HT. METHODS A systematic search of PubMed, EMBASE, and Web of Science was conducted until February 19, 2024. Inclusion criteria were as follows: patients with AIS who received reperfusion therapy; AI/ML algorithm using imaging to predict HT; or presence of sufficient data on the predictive performance. Exclusion criteria were as follows: articles with less than 20 patients; articles lacking algorithms that operate solely on images; or articles not detailing the algorithm used. The quality of eligible studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 and Checklist for Artificial Intelligence in Medical Imaging. Pooled sensitivity, specificity, and diagnostic odds ratio (DOR) were calculated using a random-effects model, and a summary receiver operating characteristic curve was constructed using the Reitsma method. RESULTS We identified six eligible studies, which included 1640 patients. Aside from an unclear risk of bias regarding flow and timing identified in two of the studies, all studies showed low risk of bias and applicability concerns in all categories. Pooled sensitivity, specificity, and DOR were .849, .878, and 45.598, respectively. CONCLUSION AI/ML models can reliably predict the occurrence of HT in AIS patients. More prospective studies are needed for subgroup analyses and higher clinical certainty and usefulness.
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Affiliation(s)
- Richard Dagher
- Department of Neuroradiology, MD Anderson Cancer Center, Houston, Texas, USA
| | - Burak Berksu Ozkara
- Department of Neuroradiology, MD Anderson Cancer Center, Houston, Texas, USA
| | - Mert Karabacak
- Department of Neurosurgery, Mount Sinai Health System, New York, New York, USA
| | - Samir A Dagher
- Department of Neuroradiology, MD Anderson Cancer Center, Houston, Texas, USA
| | | | - Licia P Luna
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, Maryland, USA
| | - Vivek S Yedavalli
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, Maryland, USA
| | - Max Wintermark
- Department of Neuroradiology, MD Anderson Cancer Center, Houston, Texas, USA
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Taha AM, Najah Q, Omar MM, Abouelmagd K, Ali M, Hasan MT, Allam SA, Hamam YA, Arian R, Abd-ElGawad M. Diagnostic and prognostic value of heparin-binding protein in sepsis: A systematic review and meta-analysis. Medicine (Baltimore) 2024; 103:e38525. [PMID: 38905400 PMCID: PMC11191987 DOI: 10.1097/md.0000000000038525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Accepted: 05/17/2024] [Indexed: 06/23/2024] Open
Abstract
BACKGROUND Sepsis remains a leading cause of death worldwide. In this context, heparin-binding protein (HBP) has emerged as a possible biomarker, drawing significant attention for its diagnostic and prognostic usefulness in septic patients. Despite this advancement, the literature yields conflicting results. This study is intended to critically evaluate the diagnostic and prognostic value of HBP in critically ill septic patients. METHODS We searched multiple databases, including PubMed, SCOPUS, Web of Science, and EBSCO, to identify relevant studies on April 27, 2023. We included studies investigating sepsis or its severe outcomes that reported HBP levels and the required data to create 2 × 2 tables. We used R version 4.2.2 and R Studio to analyze the pooled diagnostic accuracy outcomes. The diagmeta package was utilized to calculate the optimum cutoff value. RESULTS In our meta-analysis, we incorporated 28 studies including 5508 patients. The analysis revealed that HBP has a sensitivity of 0.71 (95% CI: 0.60; 0.79) and a specificity of 0.68 (95% CI: 0.51; 0.81) in diagnosing sepsis, respectively. HBP demonstrated moderate prognostic accuracy for mortality at a cutoff value of 161.415 ng/mL, with a sensitivity and specificity of 72%, and for severe sepsis outcomes at a cutoff value of 58.907 ng/mL, with a sensitivity and specificity of 71%. CONCLUSION Our findings indicate a relatively moderate diagnostic and prognostic accuracy of HBP for sepsis. Future studies are required to verify the accuracy of HBP as a biomarker for sepsis.
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Affiliation(s)
| | - Qasi Najah
- Faculty of Medicine, University of EL-Mergib, Al Khums, Libya
| | | | - Khaled Abouelmagd
- Cardiology Department, Faculty of Medicine, Al-Azhar University, Egypt
| | - Mohammed Ali
- Faculty of Medicine, Al-Azhar University, Cairo, Egypt
| | | | | | - Yasser A. Hamam
- Faculty of Medicine, Al-Quds University, Jerusalem, Palestine
| | - Roua Arian
- Faculty of Medicine, University of Aleppo, Aleppo, Syria
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Chen JJ, Lee TH, Lai PC, Chang CH, Wu CH, Huang YT. Prognostic nutritional index as a predictive marker for acute kidney injury in adult critical illness population: a systematic review and diagnostic test accuracy meta-analysis. J Intensive Care 2024; 12:16. [PMID: 38671543 PMCID: PMC11046764 DOI: 10.1186/s40560-024-00729-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2024] [Accepted: 04/06/2024] [Indexed: 04/28/2024] Open
Abstract
BACKGROUND The prognostic nutritional index (PNI), integrating nutrition and inflammation markers, has been increasingly recognized as a prognostic predictor in diverse patient cohorts. Recently, its effectiveness as a predictive marker for acute kidney injury (AKI) in various clinical settings has gained attention. This study aims to assess the predictive accuracy of the PNI for AKI in critically ill populations through systematic review and meta-analysis. METHODS A systematic review was conducted using the databases MEDLINE, EMBASE, PubMed, and China National Knowledge Infrastructure up to August 2023. The included trials reported the PNI assessment in adult population with critical illness and its predictive capacity for AKI. Data on study characteristics, subgroup covariates, and diagnostic performance of PNI, including sensitivity, specificity, and event rates, were extracted. A diagnostic test accuracy meta-analysis was performed. Subgroup analyses and meta-regression were utilized to investigate the sources of heterogeneity. The GRADE framework evaluated the confidence in the meta-analysis's evidence. RESULTS The analysis encompassed 16 studies with 17 separate cohorts, totaling 21,239 patients. The pooled sensitivity and specificity of PNI for AKI prediction were 0.67 (95% CI 0.58-0.74) and 0.74 (95% CI 0.67-0.80), respectively. The pooled positive likelihood ratio was 2.49 (95% CI 1.99-3.11; low certainty), and the negative likelihood ratio was 0.46 (95% CI 0.37-0.56; low certainty). The pooled diagnostic odds ratio was 5.54 (95% CI 3.80-8.07), with an area under curve of summary receiver operating characteristics of 0.76. Subgroup analysis showed that PNI's sensitivity was higher in medical populations than in surgical populations (0.72 vs. 0.55; p < 0.05) and in studies excluding patients with chronic kidney disease (CKD) than in those including them (0.75 vs. 0.56; p < 0.01). Overall, diagnostic performance was superior in the non-chronic kidney disease group. CONCLUSION Our study demonstrated that PNI has practical accuracy for predicting the development of AKI in critically ill populations, with superior diagnostic performance observed in medical and non-CKD populations. However, the diagnostic efficacy of the PNI has significant heterogeneity with different cutoff value, indicating the need for further research.
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Affiliation(s)
- Jia-Jin Chen
- Kidney Research Center, Department of Nephrology, Chang Gung Memorial Hospital, Linkou Branch, Chang Gung university, Taoyuan, 33305, Taiwan
| | - Tao-Han Lee
- Department of Nephrology, Chansn Hospital, Taoyuan City, 33305, Taiwan
| | - Pei-Chun Lai
- Education Center, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Chih-Hsiang Chang
- Kidney Research Center, Department of Nephrology, Chang Gung Memorial Hospital, Linkou Branch, Chang Gung university, Taoyuan, 33305, Taiwan
| | - Che-Hsiung Wu
- Division of Nephrology, Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, New Taipei City, 231, Taiwan.
- School of Medicine, Tzu Chi University, Hualien, 970, Taiwan.
| | - Yen-Ta Huang
- Department of Surgery, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, No. 138, Shengli Road, Tainan, 701, Taiwan.
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Droppelmann G, Rodríguez C, Jorquera C, Feijoo F. Artificial intelligence in diagnosing upper limb musculoskeletal disorders: a systematic review and meta-analysis of diagnostic tests. EFORT Open Rev 2024; 9:241-251. [PMID: 38579757 PMCID: PMC11044087 DOI: 10.1530/eor-23-0174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/07/2024] Open
Abstract
Purpose The integration of artificial intelligence (AI) in radiology has revolutionized diagnostics, optimizing precision and decision-making. Specifically in musculoskeletal imaging, AI tools can improve accuracy for upper extremity pathologies. This study aimed to assess the diagnostic performance of AI models in detecting musculoskeletal pathologies of the upper extremity using different imaging modalities. Methods A meta-analysis was conducted, involving searches on MEDLINE/PubMed, SCOPUS, Cochrane Library, Lilacs, and SciELO. The quality of the studies was assessed using the QUADAS-2 tool. Diagnostic accuracy measures including sensitivity, specificity, diagnostic odds ratio (DOR), positive and negative likelihood ratios (PLR, NLR), area under the curve (AUC), and summary receiver operating characteristic were pooled using a random-effects model. Heterogeneity and subgroup analyses were also included. All statistical analyses and plots were performed using the R software package. Results Thirteen models from ten articles were analyzed. The sensitivity and specificity of the AI models to detect musculoskeletal conditions in the upper extremity were 0.926 (95% CI: 0.900; 0.945) and 0.908 (95% CI: 0.810; 0.958). The PLR, NLR, lnDOR, and the AUC estimates were found to be 19.18 (95% CI: 8.90; 29.34), 0.11 (95% CI: 0.18; 0.46), 4.62 (95% CI: 4.02; 5.22) with a (P < 0.001), and 95%, respectively. Conclusion The AI models exhibited strong univariate and bivariate performance in detecting both positive and negative cases within the analyzed dataset of musculoskeletal pathologies in the upper extremity.
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Affiliation(s)
- Guillermo Droppelmann
- Research Center on Medicine, Exercise, Sport and Health, MEDS Clinic, Santiago, RM, Chile
- Health Sciences PhD Program, Universidad Católica de Murcia UCAM, Murcia, Spain
- Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | | | - Carlos Jorquera
- Facultad de Ciencias, Escuela de Nutrición y Dietética, Universidad Mayor, Santiago, RM, Chile
| | - Felipe Feijoo
- School of Industrial Engineering, Pontificia Universidad Católica de Valparaíso, Valparaíso, Chile
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Kim K, Ha M, Kim SJ. Comparative Study of Different Imaging Modalities for Diagnosis of Bone Metastases of Prostate Cancer: A Bayesian Network Meta-analysis. Clin Nucl Med 2024; 49:312-318. [PMID: 38350066 DOI: 10.1097/rlu.0000000000005078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/15/2024]
Abstract
PURPOSE This study aimed to compare the diagnostic performances of 8 different imaging modalities for preoperative detection of bone metastases in prostate cancer patients by performing a network meta-analysis using direct comparison studies with 2 or more imaging techniques. PATIENTS AND METHODS We searched PubMed, Embase, and Cochrane Library for studies evaluating the performances of 8 different imaging modalities for the preoperative detection of bone metastases in prostate cancer patients. The network meta-analysis was performed in patient-based analysis. The consistency was evaluated by examining the agreement between direct and indirect treatment effects, and the surface under the cumulative ranking curve (SUCRA) values were obtained to calculate the probability of each imaging modality being the most effective diagnostic method. RESULTS A total of 999 patients from 13 direct comparison studies using 8 different imaging modalities for preoperative detection or follow-up of bone metastases in prostate cancer patients were included. For the detection of bone metastases of prostate cancer, 68 Ga-PSMA-11 PET/CT showed the highest SUCRA values of sensitivity, positive predictive value, accuracy, and diagnostic odds ratio. In addition, 18 F-NaF PET/CT and SPECT/CT showed high SUCRA values. CONCLUSIONS 68 Ga-PSMA-11 PET/CT showed the highest SUCRA values. Other imaging modalities showed complementary diagnostic roles for preoperative detection of bone metastases in patients with prostate cancer, except bone scintigraphy and MRI.
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Affiliation(s)
| | - Mihyang Ha
- From the Department of Nuclear Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan
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9
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Amitai Y, Freitas VAR, Golan O, Kessner R, Shalmon T, Neeman R, Mauda-Havakuk M, Mercer D, Sklair-Levy M, Menes TS. The diagnostic performance of ultrafast MRI to differentiate benign from malignant breast lesions: a systematic review and meta-analysis. Eur Radiol 2024:10.1007/s00330-024-10690-y. [PMID: 38512492 DOI: 10.1007/s00330-024-10690-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 02/11/2024] [Accepted: 02/15/2024] [Indexed: 03/23/2024]
Abstract
OBJECTIVES To assess the diagnostic performance of ultrafast magnetic resonance imaging (UF-DCE MRI) in differentiating benign from malignant breast lesions. MATERIALS AND METHODS A comprehensive search was conducted until September 1, 2023, in Medline, Embase, and Cochrane databases. Clinical studies evaluating the diagnostic performance of UF-DCE MRI in breast lesion stratification were screened and included in the meta-analysis. Pooled summary estimates for sensitivity, specificity, diagnostic odds ratio (DOR), and hierarchic summary operating characteristics (SROC) curves were pooled under the random-effects model. Publication bias and heterogeneity between studies were calculated. RESULTS A final set of 16 studies analyzing 2090 lesions met the inclusion criteria and were incorporated into the meta-analysis. Using UF-DCE MRI kinetic parameters, the pooled sensitivity, specificity, DOR, and area under the curve (AUC) for differentiating benign from malignant breast lesions were 83% (95% CI 79-88%), 77% (95% CI 72-83%), 18.9 (95% CI 13.7-26.2), and 0.876 (95% CI 0.83-0.887), respectively. We found no significant difference in diagnostic accuracy between the two main UF-DCE MRI kinetic parameters, maximum slope (MS) and time to enhancement (TTE). DOR and SROC exhibited low heterogeneity across the included studies. No evidence of publication bias was identified (p = 0.585). CONCLUSIONS UF-DCE MRI as a stand-alone technique has high accuracy in discriminating benign from malignant breast lesions. CLINICAL RELEVANCE STATEMENT UF-DCE MRI has the potential to obtain kinetic information and stratify breast lesions accurately while decreasing scan times, which may offer significant benefit to patients. KEY POINTS • Ultrafast breast MRI is a novel technique which captures kinetic information with very high temporal resolution. • The kinetic parameters of ultrafast breast MRI demonstrate a high level of accuracy in distinguishing between benign and malignant breast lesions. • There is no significant difference in accuracy between maximum slope and time to enhancement kinetic parameters.
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Affiliation(s)
- Yoav Amitai
- Department of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel.
| | - Vivianne A R Freitas
- Joint Department of Medical Imaging - University Health Network, Sinai Health System, Women's College Hospital, University of Toronto, 610 University Avenue - M5G 2M9, Toronto, Ontario, Canada
| | - Orit Golan
- Department of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel
| | - Rivka Kessner
- Department of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel
| | - Tamar Shalmon
- Department of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel
| | - Rina Neeman
- Department of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel
| | - Michal Mauda-Havakuk
- Department of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel
| | - Diego Mercer
- Department of Medical Imaging, Tel Aviv University, Sackler School of Medicine, Sourasky Medical Center, Weizmann 6, 6423906, Tel Aviv-Yafo, Israel
| | - Miri Sklair-Levy
- Department of Medical Imaging, Sackler School of Medicine, Chaim Sheba Medical Center, Tel Aviv University, Tel Hashomer, Derech Shiba 2, 52621, Ramat-Gan, Israel
| | - Tehillah S Menes
- Department of Surgery, Sackler School of Medicine, Chaim Sheba Medical Center, Tel Aviv University, Tel Hashomer, Derech Shiba 2, 52621, Ramat-Gan, Israel
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Rachmat A, Kelly GC, Tran LK, Christy N, Supaprom C, Heang V, Dul S, Garcia-Rivera JA, Prom S, Sopheab H, Brooks JS, Sutherland IJ, Corson KS, Letizia AG. Clinical Presentation, Risk Factors, and Comparison of Laboratory Diagnostics for Seasonal Influenza Virus Among Cambodians From 2007 to 2020. Open Forum Infect Dis 2024; 11:ofae062. [PMID: 38524221 PMCID: PMC10960604 DOI: 10.1093/ofid/ofae062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 02/20/2024] [Indexed: 03/26/2024] Open
Abstract
Background Despite its global significance, challenges associated with understanding the epidemiology and accurately detecting, measuring, and characterizing the true burden of seasonal influenza remain in many resource-poor settings. Methods A prospective observational study was conducted in Cambodia at 28 health facilities between 2007 and 2020 utilizing passive surveillance data of patients presenting with acute undifferentiated febrile illness (AUFI) to describe the prevalence of influenza A and B and characterize associated risk factors and symptoms using a questionnaire. A comparison of rapid influenza diagnostic tests (RIDTs) and real-time reverse transcription polymerase chain reaction (rRT-PCR) results was also conducted. Results Of 30 586 total participants, 5634 (18.4%) tested positive for either influenza A or B, with 3557 (11.6%) positive for influenza A and 2288 (7.5%) positive for influenza B during the study. Influenza A and B were strongly associated with the rainy season (odds ratio [OR], 2.30; P < .001) and being from an urban area (OR, 1.45; P < .001). Analysis of individual symptoms identified cough (OR, 2.8; P < .001), chills (OR, 1.4; P < .001), and sore throat (OR, 1.4; P < .001) as having the strongest positive associations with influenza among patients with AUFI. Analysis comparing RIDTs and rRT-PCR calculated the overall sensitivity of rapid tests to be 0.492 (95% CI, 0.479-0.505) and specificity to be 0.993 (95% CI, 0.992-0.994) for both influenza type A and B. Conclusions Findings from this 14-year study include describing the epidemiology of seasonal influenza over a prolonged time period and identifying key risk factors and clinical symptoms associated with infection; we also demonstrate the poor sensitivity of RIDTs in Cambodia.
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Affiliation(s)
- Agus Rachmat
- AC Investment Co, contractor for NAMRU INDO PACIFIC, Phnom Penh, Cambodia
| | | | | | | | - Chonthida Supaprom
- AC Investment Co, contractor for NAMRU INDO PACIFIC, Phnom Penh, Cambodia
| | - Vireak Heang
- AC Investment Co, contractor for NAMRU INDO PACIFIC, Phnom Penh, Cambodia
| | - Sokha Dul
- AC Investment Co, contractor for NAMRU INDO PACIFIC, Phnom Penh, Cambodia
| | | | - Satharath Prom
- Department of Health, Ministry of National Defense, Phnom Penh, Cambodia
| | - Heng Sopheab
- National Institute of Public Health, Ministry of Health, Phnom Penh, Cambodia
| | - John S Brooks
- US Naval Medical Research Unit INDO PACIFIC, Cambodia
| | | | - Karen S Corson
- US Naval Medical Research Unit INDO PACIFIC, Singapore
- US Naval Medical Research Unit INDO PACIFIC, Cambodia
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11
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Chen Z, Zhang J, Cai Y, Zhao H, Wang D, Li C, He Y. Diagnostic performance of angiography-derived fractional flow reserve and CT-derived fractional flow reserve: A systematic review and Bayesian network meta-analysis. J Evid Based Med 2024; 17:119-133. [PMID: 38205918 DOI: 10.1111/jebm.12573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 12/05/2023] [Indexed: 01/12/2024]
Abstract
OBJECTIVE Accumulating evidence has demonstrated that fractional flow reserves (FFRs) derived from invasive coronary angiograms (CA-FFRs) and coronary computed tomography angiography-derived FFRs (CT-FFRs) are promising alternatives to wire-based FFRs. However, it remains unclear which method has better diagnostic performance. This systematic review and meta-analysis aimed to compare the diagnostic performances of the two approaches. METHODS The Cochrane Library, PubMed, Embase, Medline (Ovid), the Chinese China National Knowledge Infrastructure Database (CNKI), VIP, and WanFang Data databases were searched for relevant studies that included comparisons between CA-FFR and CT-FFR, from their respective database inceptions until January 1, 2023. Studies where both noninvasive FFR (including CA-FFR and CT-FFR) and invasive FFR (as a reference standard) were performed for the diagnosis of ischemic coronary artery disease and were designed as prospective, paired diagnostic studies, were pulled. The diagnostic test accuracy method and Bayesian hierarchical summary receiver operating characteristic (ROC) model for network meta-analysis (NMA) of diagnostic tests (HSROC-NMADT) were both used to perform a meta-analysis on the data. RESULTS Twenty-six studies were included in this NMA. The results from both the diagnostic test accuracy and HSROC-NMADT methods revealed that the diagnostic accuracy of CA-FFR was higher than that of CT-FFR, in terms of sensitivity (Se; 0.86 vs. 0.84), specificity (Sp; 0.90 vs. 0.78), positive predictive value (PPV; 0.83 vs. 0.70), and negative predictive value (NPV; 0.91 vs. 0.89) for the detection of myocardial ischemia. A cumulative ranking curve analysis indicated that CA-FFR had a higher diagnostic accuracy than CT-FFR in the context of this study, with a higher area under the ROC curve (AUC; 0.94 vs. 0.87). CONCLUSIONS Although both of these two commonly used virtual FFR methods showed high levels of diagnostic accuracy, we demonstrated that CA-FFR had a better Se, Sp, PPV, NPV, and AUC than CT-FFR. However, this study provided only indirect comparisions; therefore, larger studies are warranted to directly compare the diagnostic performances of these two approaches.
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Affiliation(s)
- Zhongxiu Chen
- Department of Cardiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Junyan Zhang
- Department of Cardiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Yujia Cai
- Chinese Evidence-based Medicine Center and MAGIC-China Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Hongsen Zhao
- Information Center, West China Hospital, Sichuan University, Chengdu, China
| | - Duolao Wang
- Department of Clinical Sciences, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, UK
| | - Chen Li
- Department of Cardiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Yong He
- Department of Cardiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
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12
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Alvi MA, Kwon BK, Hejrati N, Tetreault LA, Evaniew N, Skelly AC, Fehlings MG. Accuracy of Intraoperative Neuromonitoring in the Diagnosis of Intraoperative Neurological Decline in the Setting of Spinal Surgery-A Systematic Review and Meta-Analysis. Global Spine J 2024; 14:105S-149S. [PMID: 38632716 PMCID: PMC10964897 DOI: 10.1177/21925682231196514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/19/2024] Open
Abstract
STUDY DESIGN Systematic review and meta-analysis. OBJECTIVES In an effort to prevent intraoperative neurological injury during spine surgery, the use of intraoperative neurophysiological monitoring (IONM) has increased significantly in recent years. Using IONM, spinal cord function can be evaluated intraoperatively by recording signals from specific nerve roots, motor tracts, and sensory tracts. We performed a systematic review and meta-analysis of diagnostic test accuracy (DTA) studies to evaluate the efficacy of IONM among patients undergoing spine surgery for any indication. METHODS The current systematic review and meta-analysis was performed using the Preferred Reporting Items for a Systematic Review and Meta-analysis statement for Diagnostic Test Accuracy Studies (PRISMA-DTA) and was registered on PROSPERO. A comprehensive search was performed using MEDLINE, EMBASE and SCOPUS for all studies assessing the diagnostic accuracy of neuromonitoring, including somatosensory evoked potential (SSEP), motor evoked potential (MEP) and electromyography (EMG), either on their own or in combination (multimodal). Studies were included if they reported raw numbers for True Positives (TP), False Negatives (FN), False Positives (FP) and True Negative (TN) either in a 2 × 2 contingency table or in text, and if they used postoperative neurologic exam as a reference standard. Pooled sensitivity and specificity were calculated to evaluate the overall efficacy of each modality type using a bivariate model adapted by Reitsma et al, for all spine surgeries and for individual disease groups and regions of spine. The risk of bias (ROB) of included studies was assessed using the quality assessment tool for diagnostic accuracy studies (QUADAS-2). RESULTS A total of 163 studies were included; 52 of these studies with 16,310 patients reported data for SSEP, 68 studies with 71,144 patients reported data for MEP, 16 studies with 7888 patients reported data for EMG and 69 studies with 17,968 patients reported data for multimodal monitoring. The overall sensitivity, specificity, DOR and AUC for SSEP were 71.4% (95% CI 54.8-83.7), 97.1% (95% CI 95.3-98.3), 41.9 (95% CI 24.1-73.1) and .899, respectively; for MEP, these were 90.2% (95% CI 86.2-93.1), 96% (95% CI 94.3-97.2), 103.25 (95% CI 69.98-152.34) and .927; for EMG, these were 48.3% (95% CI 31.4-65.6), 92.9% (95% CI 84.4-96.9), 11.2 (95% CI 4.84-25.97) and .773; for multimodal, these were found to be 83.5% (95% CI 81-85.7), 93.8% (95% CI 90.6-95.9), 60 (95% CI 35.6-101.3) and .895, respectively. Using the QUADAS-2 ROB analysis, of the 52 studies reporting on SSEP, 13 (25%) were high-risk, 10 (19.2%) had some concerns and 29 (55.8%) were low-risk; for MEP, 8 (11.7%) were high-risk, 21 had some concerns and 39 (57.3%) were low-risk; for EMG, 4 (25%) were high-risk, 3 (18.75%) had some concerns and 9 (56.25%) were low-risk; for multimodal, 14 (20.3%) were high-risk, 13 (18.8%) had some concerns and 42 (60.7%) were low-risk. CONCLUSIONS These results indicate that all neuromonitoring modalities have diagnostic utility in successfully detecting impending or incident intraoperative neurologic injuries among patients undergoing spine surgery for any condition, although it is clear that the accuracy of each modality differs.PROSPERO Registration Number: CRD42023384158.
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Affiliation(s)
- Mohammed Ali Alvi
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Brian K Kwon
- International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada
- Department of Orthopaedics, University of British Columbia, Vancouver, BC, Canada
| | - Nader Hejrati
- Division of Neurosurgery, Krembil Neuroscience Centre, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | | | - Nathan Evaniew
- McCaig Institute for Bone and Joint Health, Department of Surgery, Orthopaedic Surgery, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | | | - Michael G Fehlings
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Division of Neurosurgery, Krembil Neuroscience Centre, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
- Division of Neurosurgery and Spine Program, Department of Surgery, University of Toronto, Toronto, ON, Canada
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13
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Miszczyk M, Rajwa P, Yanagisawa T, Nowicka Z, Shim SR, Laukhtina E, Kawada T, von Deimling M, Pradere B, Rivas JG, Gandaglia G, van den Bergh RCN, Goldner G, Supiot S, Zilli T, Trinh QD, Nguyen PL, Briganti A, Ost P, Ploussard G, Shariat SF. The Efficacy and Safety of Metastasis-directed Therapy in Patients with Prostate Cancer: A Systematic Review and Meta-analysis of Prospective Studies. Eur Urol 2024; 85:125-138. [PMID: 37945451 DOI: 10.1016/j.eururo.2023.10.012] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 09/15/2023] [Accepted: 10/16/2023] [Indexed: 11/12/2023]
Abstract
CONTEXT Despite the lack of level 1 evidence, metastasis-directed therapy (MDT) is used widely in the management of metastatic prostate cancer (mPCa) patients. Data are continuously emerging from well-designed prospective studies. OBJECTIVE To summarise and report the evidence on oncological and safety outcomes of MDT in the management of mPCa patients. EVIDENCE ACQUISITION We searched the PubMed, Scopus, and Web of Science databases for prospective studies assessing progression-free survival (PFS), local control (LC), androgen deprivation therapy (ADT)-free survival (ADT-FS), overall survival (OS), and/or adverse events (AEs) in mPCa patients treated with MDT. A meta-analysis was performed for 1- and 2-yr PFS, LC, ADT-FS, OS, and rate of AEs. Meta-regression and sensitivity analysis were performed to account for heterogeneity and identify moderators. EVIDENCE SYNTHESIS We identified 22 prospective studies (n = 1137), including two randomised controlled trials (n = 116). Two studies were excluded from the meta-analysis (n = 120). The estimated 2-yr PFS was 46% (95% confidence interval [CI]: 36-56%) or 42% (95% CI: 33-52%) after excluding studies using biochemical or ADT-related endpoints. The estimated 2-yr LC, ADT-FS, and OS were 97% (95% CI: 94-98%), 55% (95% CI: 44-65%), and 97% (95% CI: 95-98%), respectively. Rates of treatment-related grade 2 and ≥3 AEs were 2.4% (95% CI: 0.2-7%) and 0.3% (95% CI: 0-1%), respectively. CONCLUSIONS MDT is a promising treatment strategy associated with favourable PFS, excellent LC, and a low toxicity profile that allows oligorecurrent hormone-sensitive patients to avoid or defer ADT-related toxicity. Integration of MDT with other therapies offers a promising research direction, in particular, in conjunction with systemic treatments and as a component of definitive care for oligometastatic PCa. However, in the absence of randomised trials, using MDT for treatment intensification remains an experimental approach, and the impact on OS is uncertain. PATIENT SUMMARY Direct treatment of metastases is a promising option for selected prostate cancer patients. It can delay hormone therapy and is being investigated as a way of intensifying treatment at the expense of manageable toxicity.
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Affiliation(s)
- Marcin Miszczyk
- Department of Radiation Oncology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; IIIrd Radiotherapy and Chemotherapy Department, Maria Skłodowska-Curie National Research Institute of Oncology, Gliwice, Poland
| | - Pawel Rajwa
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, Medical University of Silesia, Zabrze, Poland
| | - Takafumi Yanagisawa
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, Dentistry and Pharmaceutical Sciences, Okayama University Graduate School of Medicine, Okayama, Japan
| | - Zuzanna Nowicka
- Department of Biostatistics and Translational Medicine, Medical University of Lodz, Lodz, Poland
| | - Sung Ryul Shim
- Department of Biomedical Informatics, College of Medicine, Konyang University, Daejeon, Republic of Korea
| | - Ekaterina Laukhtina
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Tatsushi Kawada
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
| | - Markus von Deimling
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Benjamin Pradere
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, La Croix Du Sud Hospital, Quint-Fonsegrives, France
| | - Juan Gómez Rivas
- Department of Urology, Hospital Clínico San Carlos, Madrid, Spain
| | - Giorgio Gandaglia
- Unit of Urology/Division of Oncology, IRCCS Ospedale San Raffaele, Milan, Italy
| | | | - Gregor Goldner
- Department of Radiation Oncology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Stephane Supiot
- Department of Radiotherapy, ICO René Gauducheau, Saint-Herblain, France
| | - Thomas Zilli
- Department of Radiation Oncology, Oncological Institute of Southern Switzerland (IOSI-EOC), Bellinzona, Switzerland
| | - Quoc-Dien Trinh
- Division of Urological Surgery and Center for Surgery and Public Health, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Paul L Nguyen
- Department of Radiation Oncology, Brigham and Women's Hospital and Dana Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Alberto Briganti
- Unit of Urology/Division of Oncology, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Piet Ost
- Department of Radiation Oncology, Iridium Network, Wilrijk, Belgium
| | | | - Shahrokh F Shariat
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Karl Landsteiner Institute of Urology and Andrology, Vienna, Austria; Department of Urology, Second Faculty of Medicine, Charles University, Prague, Czech Republic; Division of Urology, Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan; Department of Urology, Weill Cornell Medical College, New York, NY, USA; Department of Urology, University of Texas Southwestern, Dallas, TX, USA.
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Taha AM, Abouelmagd K, Omar MM, Najah Q, Ali M, Hasan MT, Allam SA, Arian R, Rageh OES, Abd-ElGawad M. The diagnostic utility of heparin-binding protein among patients with bacterial infections: a systematic review and meta-analysis. BMC Infect Dis 2024; 24:150. [PMID: 38297213 PMCID: PMC10829335 DOI: 10.1186/s12879-024-09004-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 01/09/2024] [Indexed: 02/02/2024] Open
Abstract
BACKGROUND Bacterial infections are considered a leading cause of hospitalization and death globally. There is still a need for a rapid and feasible biomarker for bacterial infections. Heparin-binding protein (HBP) was shown to be related to bacterial infections. The objective of the study is to investigate the diagnostic accuracy of HBP in bacterial infections. METHODS Articles were screened in PubMed, SCOPUS, Web of Science, and Cochrane to recognize eligible studies. We included studies investigating the diagnostic accuracy of HBP and reported the necessary data to construct 2 × 2 tables. A univariate analysis was conducted to determine the pooled sensitivity and specificity, and a bivariate diagnostic random-effects model was used to calculate the optimal cut-off point. RESULTS The analysis comprised sixteen studies in total. Plasma HBP showed a sensitivity of 0.90 (95% CI: [0.79, 0.96]) and a specificity of 0.87 (95% CI: [0.66, 0.96]) in diagnosing bacterial infections using blood samples. Pooling data from seven studies revealed that HBP in cerebrospinal fluid (CSF) has sensitivity and specificity of 96% (95% CI: [0.85, 0.99]), and 95% (95% CI: [0.89, 0.97]), respectively, for the diagnosis of bacterial meningitis. In urinary tract infections (UTI), urine-HBP was revealed to have a high diagnostic value in discriminating bacterial from non-bacterial UTI infection at a cut-off value of 32.868 ng/ml with sensitivity and specificity of 87%. CONCLUSION HBP has shown a high diagnostic accuracy of bacterial infections, including UTI and meningitis. Further studies are needed to determine its prognostic value and whether it could guide antibiotic therapy.
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Affiliation(s)
- Amira Mohamed Taha
- Faculty of Medicine, Fayoum University, Bank Street, Talat, Fayoum, Egypt.
| | - Khaled Abouelmagd
- Cardiology Department, Faculty of Medicine, Al-Azhar University, Cairo, Egypt
| | | | - Qasi Najah
- Faculty of Medicine, University of EL-Mergib, Al Khums, Libya
| | - Mohammed Ali
- Faculty of Medicine, Al-Azhar University, Cairo, Egypt
| | | | | | - Roua Arian
- Faculty of Medicine, University of Aleppo, Aleppo, Syria
- CME Office, Faculty of Medicine, University of Aleppo, Aleppo, Syria
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Yen TY, Ho CS, Chen YP, Pei YC. Diagnostic Accuracy of Deep Learning for the Prediction of Osteoporosis Using Plain X-rays: A Systematic Review and Meta-Analysis. Diagnostics (Basel) 2024; 14:207. [PMID: 38248083 PMCID: PMC10814351 DOI: 10.3390/diagnostics14020207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 01/04/2024] [Accepted: 01/16/2024] [Indexed: 01/23/2024] Open
Abstract
(1) Background: This meta-analysis assessed the diagnostic accuracy of deep learning model-based osteoporosis prediction using plain X-ray images. (2) Methods: We searched PubMed, Web of Science, SCOPUS, and Google Scholar from no set beginning date to 28 February 2023, for eligible studies that applied deep learning methods for diagnosing osteoporosis using X-ray images. The quality of studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 criteria. The area under the receiver operating characteristic curve (AUROC) was used to quantify the predictive performance. Subgroup, meta-regression, and sensitivity analyses were performed to identify the potential sources of study heterogeneity. (3) Results: Six studies were included; the pooled AUROC, sensitivity, and specificity were 0.88 (95% confidence interval [CI] 0.85-0.91), 0.81 (95% CI 0.78-0.84), and 0.87 (95% CI 0.81-0.92), respectively, indicating good performance. Moderate heterogeneity was observed. Mega-regression and subgroup analyses were not performed due to the limited number of studies included. (4) Conclusion: Deep learning methods effectively extract bone density information from plain radiographs, highlighting their potential for opportunistic screening. Nevertheless, additional prospective multicenter studies involving diverse patient populations are required to confirm the applicability of this novel technique.
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Affiliation(s)
- Tzu-Yun Yen
- Department of Physical Medicine and Rehabilitation, Chang Gung Memorial Hospital, Linkou No. 5, Fuxing Street, Guishan District, Taoyuan City 333, Taiwan; (T.-Y.Y.); (C.-S.H.)
- School of Medicine, Chang Gung University, No. 259, Wenhua 1st Road, Guishan District, Taoyuan City 333, Taiwan
| | - Chan-Shien Ho
- Department of Physical Medicine and Rehabilitation, Chang Gung Memorial Hospital, Linkou No. 5, Fuxing Street, Guishan District, Taoyuan City 333, Taiwan; (T.-Y.Y.); (C.-S.H.)
- School of Medicine, Chang Gung University, No. 259, Wenhua 1st Road, Guishan District, Taoyuan City 333, Taiwan
| | - Yueh-Peng Chen
- Center for Artificial Intelligence in Medicine, Chang Gung Memorial Hospital, Linkou No. 5, Fuxing Street, Guishan District, Taoyuan City 333, Taiwan;
- Master of Science Degree Program in Innovation for Smart Medicine, Chang Gung University, No. 259, Wenhua 1st Road, Guishan District, Taoyuan City 333, Taiwan
| | - Yu-Cheng Pei
- Department of Physical Medicine and Rehabilitation, Chang Gung Memorial Hospital, Linkou No. 5, Fuxing Street, Guishan District, Taoyuan City 333, Taiwan; (T.-Y.Y.); (C.-S.H.)
- School of Medicine, Chang Gung University, No. 259, Wenhua 1st Road, Guishan District, Taoyuan City 333, Taiwan
- Master of Science Degree Program in Innovation for Smart Medicine, Chang Gung University, No. 259, Wenhua 1st Road, Guishan District, Taoyuan City 333, Taiwan
- Center of Vascularized Tissue Allograft, Gung Memorial Hospital, Linkou No. 5, Fuxing Street, Guishan District, Taoyuan City 333, Taiwan
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16
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Chen KC, Kuo SW, Shie RH, Yang HY. Advancing accuracy in breath testing for lung cancer: strategies for improving diagnostic precision in imbalanced data. Respir Res 2024; 25:32. [PMID: 38225616 PMCID: PMC10790556 DOI: 10.1186/s12931-024-02668-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Accepted: 01/02/2024] [Indexed: 01/17/2024] Open
Abstract
BACKGROUND Breath testing using an electronic nose has been recognized as a promising new technique for the early detection of lung cancer. Imbalanced data are commonly observed in electronic nose studies, but methods to address them are rarely reported. OBJECTIVE The objectives of this study were to assess the accuracy of electronic nose screening for lung cancer with imbalanced learning and to select the best mechanical learning algorithm. METHODS We conducted a case‒control study that included patients with lung cancer and healthy controls and analyzed metabolites in exhaled breath using a carbon nanotube sensor array. The study used five machine learning algorithms to build predictive models and a synthetic minority oversampling technique to address imbalanced data. The diagnostic accuracy of lung cancer was assessed using pathology reports as the gold standard. RESULTS We enrolled 190 subjects between 2020 and 2023. A total of 155 subjects were used in the final analysis, which included 111 lung cancer patients and 44 healthy controls. We randomly divided samples into one training set, one internal validation set, and one external validation set. In the external validation set, the summary sensitivity was 0.88 (95% CI 0.84-0.91), the summary specificity was 1.00 (95% CI 0.85-1.00), the AUC was 0.96 (95% CI 0.94-0.98), the pAUC was 0.92 (95% CI 0.89-0.96), and the DOR was 207.62 (95% CI 24.62-924.64). CONCLUSION Electronic nose screening for lung cancer is highly accurate. The support vector machine algorithm is more suitable for analyzing chemical sensor data from electronic noses.
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Affiliation(s)
- Ke-Cheng Chen
- Division of Thoracic Surgery, Department of Surgery, National Taiwan University Hospital, Taipei, Taiwan
- National Taiwan University College of Medicine, Taipei, Taiwan
| | - Shuenn-Wen Kuo
- Division of Thoracic Surgery, Department of Surgery, National Taiwan University Hospital, Taipei, Taiwan
- National Taiwan University College of Medicine, Taipei, Taiwan
| | - Ruei-Hao Shie
- Green Energy and Environmental Research Laboratories, Industrial Technology Research Institute, Hsinchu, Taiwan
| | - Hsiao-Yu Yang
- Institute of Environmental and Occupational Health Sciences, National Taiwan University College of Public Health, No. 17 Xuzhou Road, Taipei, 10055, Taiwan.
- Department of Public Health, National Taiwan University College of Public Health, Taipei, Taiwan.
- Population Health Research Center, National Taiwan University, Taipei, Taiwan.
- Department of Environmental and Occupational Medicine, National Taiwan University Hospital, Taipei, Taiwan.
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Kurniawan SJ, Kaisar MMM, Kristin H, Ali S. Comparable performance of antigen-detecting rapid test by healthcare worker-collected and self-collected swabs for SARS-CoV-2 diagnostic: A systematic review and meta-analysis. Rev Med Virol 2024; 34:e2492. [PMID: 37989714 DOI: 10.1002/rmv.2492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Revised: 09/24/2023] [Accepted: 11/11/2023] [Indexed: 11/23/2023]
Abstract
Usage of self-screening tests has become increasingly relevant in public health perspective for early detection of SARS-CoV-2 infection in the transitioning era of the COVID-19 pandemic into an endemic. This study was designed to compare the diagnostic accuracy of self-conducted and health professional-conducted SARS-CoV-2 rapid antigen tests (Ag-RDTs) and whether the sample was taken from anterior nasal or nasal mid-turbinate. Eligible comparative Ag-RDTs accuracy studies were retrieved from electronic databases systematically, in accordance with PRISMA. Selected studies were assessed for risk of bias using QUADAS-2 and QUADAS-C. In total, we selected five out of 1952 studies retrieved using the keywords. The overall sensitivity for the self-collected nasal swab method and healthcare worker-collected nasopharyngeal swab method was 79% (95% CI 68-87; I2 = 62%) and 83% (95% CI 75-89; I2 = 32%), respectively, which was not statistically different (p = 0.499). Nasal mid-turbinate swabs have a significantly higher sensitivity compared to anterior nasal swabs (p < 0.01). Both sampling methods represent high and comparable specificity values of 98% (95% CI 97-99; I2 = 0%) and 99% (95% CI 98-99; I2 = 0%). Positive predictive value (range 90%-99%) and negative predictive value (range 87%-98%) were equivalent for both methods. Our findings indicated the accuracy of self-collected Ag-RDT on nasal swabs was comparable to those performed by healthcare worker-collected on nasopharyngeal swabs. Self-collected Ag-RDT could be considered as a transmission prevention method in the transition of COVID-19 pandemic.
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Affiliation(s)
- Samuel Johnson Kurniawan
- Undergraduate Program, School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia
| | - Maria Mardalena Martini Kaisar
- Department of Parasitology, School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia
- Master in Biomedicine Study Program, School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia
| | - Helen Kristin
- Department of Parasitology, School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia
| | - Soegianto Ali
- Master in Biomedicine Study Program, School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia
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18
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Gebremeskele BT, Adane G, Adem M, Tajebe F. Diagnostic performance of CL Detect rapid-immunochromatographic test for cutaneous leishmaniasis: a systematic review and meta-analysis. Syst Rev 2023; 12:240. [PMID: 38115138 PMCID: PMC10731771 DOI: 10.1186/s13643-023-02422-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 12/06/2023] [Indexed: 12/21/2023] Open
Abstract
BACKGROUND Sensitive, robust, and fast point-of-care tests are needed for cutaneous leishmaniasis (CL) diagnosis. The recently developed CL Detect rapid test (InBios) for detecting Leishmania peroxidoxin antigen has been evaluated in several studies. However, diagnostic performances were controversial. Therefore, this systematic review and meta-analysis aimed to determine the pooled sensitivity and specificity of CL Detect for CL diagnosis. METHODS PubMed, Scopus, EMBASE, ScienceDirect, and Google Scholar were sources of articles. We included studies reporting the diagnostic accuracy of CL Detect and CL-suspected patients in the English language. The methodological qualities of the included studies were appraised using the quality assessment of diagnostic accuracy studies-2 (QUADAS-2). Meta-analysis was conducted using Stata 14.2 and R software. RESULTS A total of 9 articles were included. The study sample size ranged from 11 to 274. The sensitivities of the individual studies ranged from 23 to 100%, and the specificities ranged from 78 to 100%. Pooled sensitivity and specificity were 68% (95% CI, 41-86%) and 94% (95% CI, 87-97%), respectively. AUC displayed 0.899. Pooled sensitivity was lower (47%, 95% CI, 34-61%) when PCR was used as a reference than microscopy (83%, 95% CI, 39-97%). Pooled sensitivity was lower (48%, 95% CI, 30-67%) for all lesion durations compared to ≤ 4 months (89%, 95% CI, 43-99%). CONCLUSIONS CL Detect has poor sensitivity and does not meet the minimal sensitivity of 95% of target product profiles designed for CL point-of-care tests. Currently, the CL Detect test looks unsuitable for CL diagnosis, despite its high specificity. Findings are limited by the low number of studies available. Further large-scale studies are recommended. SYSTEMATIC REVIEW REGISTRATION PROSPERO CRD42022323497.
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Affiliation(s)
- Behailu Taye Gebremeskele
- Department of Medical Laboratory Science, College of Medicine and Health Science, Dilla University, Dilla, Ethiopia.
- Department of Immunology and Molecular Biology, School of Biomedical and Laboratory Science, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia.
| | - Gashaw Adane
- Department of Immunology and Molecular Biology, School of Biomedical and Laboratory Science, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia
| | - Mohammed Adem
- Department of Immunology and Molecular Biology, School of Biomedical and Laboratory Science, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia
| | - Fitsumbrhan Tajebe
- Department of Immunology and Molecular Biology, School of Biomedical and Laboratory Science, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia
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19
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Maghami M, Sattari SA, Tahmasbi M, Panahi P, Mozafari J, Shirbandi K. Diagnostic test accuracy of machine learning algorithms for the detection intracranial hemorrhage: a systematic review and meta-analysis study. Biomed Eng Online 2023; 22:114. [PMID: 38049809 PMCID: PMC10694901 DOI: 10.1186/s12938-023-01172-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 11/17/2023] [Indexed: 12/06/2023] Open
Abstract
BACKGROUND This systematic review and meta-analysis were conducted to objectively evaluate the evidence of machine learning (ML) in the patient diagnosis of Intracranial Hemorrhage (ICH) on computed tomography (CT) scans. METHODS Until May 2023, systematic searches were conducted in ISI Web of Science, PubMed, Scopus, Cochrane Library, IEEE Xplore Digital Library, CINAHL, Science Direct, PROSPERO, and EMBASE for studies that evaluated the diagnostic precision of ML model-assisted ICH detection. Patients with and without ICH as the target condition who were receiving CT-Scan were eligible for the research, which used ML algorithms based on radiologists' reports as the gold reference standard. For meta-analysis, pooled sensitivities, specificities, and a summary receiver operating characteristics curve (SROC) were used. RESULTS At last, after screening the title, abstract, and full paper, twenty-six retrospective and three prospective, and two retrospective/prospective studies were included. The overall (Diagnostic Test Accuracy) DTA of retrospective studies with a pooled sensitivity was 0.917 (95% CI 0.88-0.943, I2 = 99%). The pooled specificity was 0.945 (95% CI 0.918-0.964, I2 = 100%). The pooled diagnostic odds ratio (DOR) was 219.47 (95% CI 104.78-459.66, I2 = 100%). These results were significant for the specificity of the different network architecture models (p-value = 0.0289). However, the results for sensitivity (p-value = 0.6417) and DOR (p-value = 0.2187) were not significant. The ResNet algorithm has higher pooled specificity than other algorithms with 0.935 (95% CI 0.854-0.973, I2 = 93%). CONCLUSION This meta-analysis on DTA of ML algorithms for detecting ICH by assessing non-contrast CT-Scans shows the ML has an acceptable performance in diagnosing ICH. Using ResNet in ICH detection remains promising prediction was improved via training in an Architecture Learning Network (ALN).
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Affiliation(s)
- Masoud Maghami
- Medical Doctor (MD), School of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Shahab Aldin Sattari
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Marziyeh Tahmasbi
- Department of Medical Imaging and Radiation Sciences, School of Allied Medical Sciences, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Pegah Panahi
- Medical Doctor (MD), School of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Javad Mozafari
- Department of Emergency Medicine, School of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
- Department of Radiology, Resident (MD), EUREGIO-KLINIK Albert-Schweitzer-Straße GmbH, Nordhorn, Germany
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20
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Bhalla D, Jana M, Kandasamy D. Diagnostic accuracy of whole-body magnetic resonance imaging versus positron emission tomography-computed tomography for the staging of pediatric lymphoma: a systematic review and meta-analysis. Pediatr Radiol 2023; 53:2683-2691. [PMID: 37814104 DOI: 10.1007/s00247-023-05775-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 09/07/2023] [Accepted: 09/09/2023] [Indexed: 10/11/2023]
Abstract
BACKGROUND Whole-body magnetic resonance imaging (MRI) has been investigated by multiple authors as a radiation-free alternative to positron emission tomography computed tomography (PET-CT) in children with lymphoma. OBJECTIVE To evaluate the sensitivity, specificity, and diagnostic odds ratio of whole-body MRI compared to PET-CT for the staging of pediatric lymphoma. METHODS The databases PubMed, Embase, and Scopus were searched for studies that reported the accuracy of whole-body MRI compared to PET-CT for lymphoma staging in children. Data was collected from included studies to formulate 2 × 2 contingency tables, including the number of true positive, true negative, false positive, and false negative. The pooled sensitivity, specificity, and diagnostic odds ratio (DOR) were calculated. Summary receiver operating characteristic curves were drawn and the area under the curve (AUC) calculated. In addition, the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS 2) tool was used to assess the risk of bias and applicability concerns. RESULTS A total of seven studies were included in the final analysis. Of these, six studies used unenhanced whole-body MRI. The pooled sensitivity of whole-body MRI-based staging was 95.8%, while the pooled specificity was 21.8%. The DOR for whole-body MRI was 1.19. For extranodal staging, the pooled sensitivity was 88.9%, specificity was 97.4%, and DOR was 25.29. The partial AUC for overall staging was 0.63, whereas that for extranodal staging stood at 0.88. Based on the QUADAS 2 tool, all seven studies were at risk of bias (six at high risk, one at unclear risk). CONCLUSION Whole-body MRI has high sensitivity for staging of pediatric lymphoma and may be a useful alternative to PET-CT.
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Affiliation(s)
- Deeksha Bhalla
- Department of Radiodiagnosis and Interventional Radiology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India
| | - Manisha Jana
- Department of Radiodiagnosis and Interventional Radiology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India.
| | - Devasenathipathy Kandasamy
- Department of Radiodiagnosis and Interventional Radiology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India
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21
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Lin Q, Zhang C, Weng H, Lin Y, Lin Y, Ruan Z. The utility of long non-coding RNAs in chronic obstructive pulmonary disease: a comprehensive analysis. BMC Pulm Med 2023; 23:340. [PMID: 37697291 PMCID: PMC10496340 DOI: 10.1186/s12890-023-02635-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 09/05/2023] [Indexed: 09/13/2023] Open
Abstract
OBJECTIVES Chronic obstructive pulmonary disease (COPD) is one of the main causes of morbidity and mortality in the world. However, there are some patients who are not diagnosed early and correctly through routine methods because of inconspicuous or serious symptoms. This study aims to assess the diagnostic role of long non-coding RNA (lncRNA) in COPD. METHODS We searched literature from electronic databases, after excluding non-COPD literature, the bibliometric analysis was performed, and VOSviewer software was used to represent the data analyzed. Literature evaluating the diagnostic test accuracy of lncRNA for COPD was eligible, and the QUADAS-2 checklist was used to evaluate the quality. The pooled sensitivity (SEN), specificity (SPE), diagnostic odds ratio (DOR), and summary receiver operating characteristic curve (sROC) were used to analyze the overall diagnostic performance. Subgroup and meta-regression analyses were performed to explore the heterogeneity, and a funnel plot was assessed for publication bias. Also, lncRNAs related to COPD were identified and explored for their potential biological function. RESULTS An increased annual growth rate of literature on this subject from 2016 focused on COPD, humans, RNA, and lncRNA. The meta-analysis enrolled 17 literature indicated that the SEN, SPE, and DOR differentiating COPD patients from normal controls (NCs) were 0.86 (95% CI [0.80, 0.90]), 0.78 (95% CI [0.67, 0.86]), and 21.59 (95% CI [11.39, 40.91]), respectively. Meanwhile, lncRNAs had the ability to distinguish acute exacerbations of COPD (AECOPD) patients from COPD; the SEN, SPE, and DOR were 0.75 (95% CI [0.62, 0.85]), 0.81 (95% CI [0.71, 0.89]), and 13.02 (95% CI [7.76, 21.85]), respectively. The area under the sROC were calculated to be greater than 0.8 at least. Subgroup and meta-regression analysis showed that the types of specimens and dysregulated lncRNAs might affect the diagnostic accuracy. The funnel plot showed there was a certain publication bias. 41 lncRNAs related to COPD were identified and mainly located in the nucleus and cytoplasm, associated with proliferation, invasion, and prognosis. These lncRNA-binding proteins were involved in the spliceosome, Rap1 signaling pathway, MAPK signaling pathway, and so on. CONCLUSION LncRNA suggests potential diagnostic biomarkers and therapeutic targets for COPD patients.
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Affiliation(s)
- Qi Lin
- Department of Pharmacy, The Affiliated Hospital of Putian University, Putian, Fujian Province, China.
- Pharmaceutical and Medical Technology College, Putian University, Putian, Fujian Province, China.
| | - Chaofeng Zhang
- Department of Hematology and Rheumatology, The Affiliated Hospital of Putian University, Putian, Fujian Province, China
- Key Laboratory of Translational Tumor Medicine in Fujian Province, Putian University, Putian, Fujian Province, China
| | - Huixin Weng
- Pharmaceutical and Medical Technology College, Putian University, Putian, Fujian Province, China
| | - Yating Lin
- Pharmaceutical and Medical Technology College, Putian University, Putian, Fujian Province, China
| | - Yucang Lin
- Department of Information, The Affiliated Hospital of Putian University, Putian, Fujian Province, China
| | - Zhipeng Ruan
- Pharmaceutical and Medical Technology College, Putian University, Putian, Fujian Province, China.
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22
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Reintam Blaser A, Starkopf J, Björck M, Forbes A, Kase K, Kiisk E, Laisaar KT, Mihnovits V, Murruste M, Mändul M, Voomets AL, Tamme K. Diagnostic accuracy of biomarkers to detect acute mesenteric ischaemia in adult patients: a systematic review and meta-analysis. World J Emerg Surg 2023; 18:44. [PMID: 37658356 PMCID: PMC10474684 DOI: 10.1186/s13017-023-00512-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Accepted: 08/20/2023] [Indexed: 09/03/2023] Open
Abstract
BACKGROUND Acute mesenteric ischaemia (AMI) is a disease with different pathophysiological mechanisms, leading to a life-threatening condition that is difficult to diagnose based solely on clinical signs. Despite widely acknowledged need for biomarkers in diagnosis of AMI, a broad systematic review on all studied biomarkers in different types of AMI is currently lacking. The aim of this study was to estimate the diagnostic accuracy of all potential biomarkers of AMI studied in humans. METHODS A systematic literature search in PubMed, The Cochrane Library, Web of Science and Scopus was conducted in December 2022. Studies assessing potential biomarkers of AMI in (at least 10) adult patients and reporting their diagnostic accuracy were included. Meta-analyses of biomarkers' sensitivity, specificity, and positive and negative likelihood ratios were conducted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed, and the study quality was assessed with the QUADAS-2 tool. RESULTS Seventy-five studies including a total of 9914 patients assessed 18 different biomarkers in serum/plasma and one in urine (each reported in at least two studies), which were included in meta-analyses. None of the biomarkers reached a conclusive level for accurate prediction. The best predictive value overall (all studies with any type and stage of AMI pooled) was observed for Ischaemia-modified albumin (2 studies, sensitivity 94.7 and specificity 90.5), interleukin-6 (n = 4, 96.3 and 82.6), procalcitonin (n = 6, 80.1 and 86.7), and intestinal fatty acid-binding protein (I-FABP) measured in serum (n = 16, 73.9 and 90.5) or in urine (n = 4, 87.9 and 78.9). In assessment of transmural mesenteric ischaemia, urinary I-FABP (n = 2, 92.3 and 85.2) and D-dimer (n = 3, 87.6 and 83.6) showed moderate predictive value. Overall risk of bias was high, mainly because of selected study populations and unclear timings of the biomarker measurements after onset of symptoms. Combinations of biomarkers were rarely studied, not allowing meta-analyses. CONCLUSIONS None of the studied biomarkers had sufficient sensitivity and specificity to diagnose AMI, although some biomarkers showed moderate predictive accuracy. Future studies should focus on timing of measurements of biomarkers, distinguishing between early stage and transmural necrosis, and between different types of AMI. Additionally, studies on combinations of biomarkers are warranted. PROSPERO registration: CRD42022379341.
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Affiliation(s)
- Annika Reintam Blaser
- Institute of Clinical Medicine, University of Tartu, Puusepa 8, 50406, Tartu, Estonia.
- Department of Intensive Care Medicine, Lucerne Cantonal Hospital, Lucerne, Switzerland.
| | - Joel Starkopf
- Institute of Clinical Medicine, University of Tartu, Puusepa 8, 50406, Tartu, Estonia
- Department of Anaesthesiology and Intensive Care, Tartu University Hospital, Tartu, Estonia
| | - Martin Björck
- Institute of Clinical Medicine, University of Tartu, Puusepa 8, 50406, Tartu, Estonia
- Department of Surgical Sciences, Section of Vascular Surgery, Uppsala University, Uppsala, Sweden
| | - Alastair Forbes
- Institute of Clinical Medicine, University of Tartu, Puusepa 8, 50406, Tartu, Estonia
| | - Karri Kase
- Institute of Clinical Medicine, University of Tartu, Puusepa 8, 50406, Tartu, Estonia
- Department of Surgery, Tartu University Hospital, Tartu, Estonia
| | - Ele Kiisk
- Institute of Family Medicine and Public Health, University of Tartu, Tartu, Estonia
| | - Kaja-Triin Laisaar
- Institute of Family Medicine and Public Health, University of Tartu, Tartu, Estonia
| | - Vladislav Mihnovits
- Department of Anaesthesiology and Intensive Care, Tartu University Hospital, Tartu, Estonia
| | - Marko Murruste
- Department of Surgery, Tartu University Hospital, Tartu, Estonia
| | - Merli Mändul
- Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Anna-Liisa Voomets
- Department of Anaesthesiology and Intensive Care, Tartu University Hospital, Tartu, Estonia
| | - Kadri Tamme
- Institute of Clinical Medicine, University of Tartu, Puusepa 8, 50406, Tartu, Estonia
- Department of Anaesthesiology and Intensive Care, Tartu University Hospital, Tartu, Estonia
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23
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Rahim F, Zaki Zadeh A, Javanmardi P, Emmanuel Komolafe T, Khalafi M, Arjomandi A, Ghofrani HA, Shirbandi K. Machine learning algorithms for diagnosis of hip bone osteoporosis: a systematic review and meta-analysis study. Biomed Eng Online 2023; 22:68. [PMID: 37430259 DOI: 10.1186/s12938-023-01132-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Accepted: 06/26/2023] [Indexed: 07/12/2023] Open
Abstract
BACKGROUND Osteoporosis is a significant health problem in the skeletal system, associated with bone tissue changes and its strength. Machine Learning (ML), on the other hand, has been accompanied by improvements in recent years and has been in the spotlight. This study is designed to investigate the Diagnostic Test Accuracy (DTA) of ML to detect osteoporosis through the hip dual-energy X-ray absorptiometry (DXA) images. METHODS The ISI Web of Science, PubMed, Scopus, Cochrane Library, IEEE Xplore Digital Library, CINAHL, Science Direct, PROSPERO, and EMBASE were systematically searched until June 2023 for studies that tested the diagnostic precision of ML model-assisted for predicting an osteoporosis diagnosis. RESULTS The pooled sensitivity of univariate analysis of seven studies was 0.844 (95% CI 0.791 to 0.885, I2 = 94% for 7 studies). The pooled specificity of univariate analysis was 0.781 (95% CI 0.732 to 0.824, I2 = 98% for 7 studies). The pooled diagnostic odds ratio (DOR) was 18.91 (95% CI 14.22 to 25.14, I2 = 93% for 7 studies). The pooled mean positive likelihood ratio (LR+) and the negative likelihood ratio (LR-) were 3.7 and 0.22, respectively. Also, the summary receiver operating characteristics (sROC) of the bivariate model has an AUC of 0.878. CONCLUSION Osteoporosis can be diagnosed by ML with acceptable accuracy, and hip fracture prediction was improved via training in an Architecture Learning Network (ALN).
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Affiliation(s)
- Fakher Rahim
- Department of Anesthesia, Cihan University - Sulaimaniya, Sulaymaniyah, Kurdistan Region, Iraq
| | - Amin Zaki Zadeh
- Medical Doctor (MD), School of Medicine, Ahvaz Jondishapour University of Medical Sciences, Ahvaz, Iran
| | - Pouya Javanmardi
- Department of Radiologic Technology, Faculty of Paramedicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | | | - Mohammad Khalafi
- School of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran.
| | - Ali Arjomandi
- Department of Radiologic Technology, Faculty of Paramedicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Haniye Alsadat Ghofrani
- Department of Radiologic Technology, Faculty of Paramedicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Kiarash Shirbandi
- Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran.
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Rescinito R, Ratti M, Payedimarri AB, Panella M. Prediction Models for Intrauterine Growth Restriction Using Artificial Intelligence and Machine Learning: A Systematic Review and Meta-Analysis. Healthcare (Basel) 2023; 11:healthcare11111617. [PMID: 37297757 DOI: 10.3390/healthcare11111617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 05/29/2023] [Accepted: 05/30/2023] [Indexed: 06/12/2023] Open
Abstract
BACKGROUND IntraUterine Growth Restriction (IUGR) is a global public health concern and has major implications for neonatal health. The early diagnosis of this condition is crucial for obtaining positive outcomes for the newborn. In recent years Artificial intelligence (AI) and machine learning (ML) techniques are being used to identify risk factors and provide early prediction of IUGR. We performed a systematic review (SR) and meta-analysis (MA) aimed to evaluate the use and performance of AI/ML models in detecting fetuses at risk of IUGR. METHODS We conducted a systematic review according to the PRISMA checklist. We searched for studies in all the principal medical databases (MEDLINE, EMBASE, CINAHL, Scopus, Web of Science, and Cochrane). To assess the quality of the studies we used the JBI and CASP tools. We performed a meta-analysis of the diagnostic test accuracy, along with the calculation of the pooled principal measures. RESULTS We included 20 studies reporting the use of AI/ML models for the prediction of IUGR. Out of these, 10 studies were used for the quantitative meta-analysis. The most common input variable to predict IUGR was the fetal heart rate variability (n = 8, 40%), followed by the biochemical or biological markers (n = 5, 25%), DNA profiling data (n = 2, 10%), Doppler indices (n = 3, 15%), MRI data (n = 1, 5%), and physiological, clinical, or socioeconomic data (n = 1, 5%). Overall, we found that AI/ML techniques could be effective in predicting and identifying fetuses at risk for IUGR during pregnancy with the following pooled overall diagnostic performance: sensitivity = 0.84 (95% CI 0.80-0.88), specificity = 0.87 (95% CI 0.83-0.90), positive predictive value = 0.78 (95% CI 0.68-0.86), negative predictive value = 0.91 (95% CI 0.86-0.94) and diagnostic odds ratio = 30.97 (95% CI 19.34-49.59). In detail, the RF-SVM (Random Forest-Support Vector Machine) model (with 97% accuracy) showed the best results in predicting IUGR from FHR parameters derived from CTG. CONCLUSIONS our findings showed that AI/ML could be part of a more accurate and cost-effective screening method for IUGR and be of help in optimizing pregnancy outcomes. However, before the introduction into clinical daily practice, an appropriate algorithmic improvement and refinement is needed, and the importance of quality assessment and uniform diagnostic criteria should be further emphasized.
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Affiliation(s)
- Riccardo Rescinito
- Department of Translational Medicine (DiMeT), University of Eastern Piedmont/Piemonte Orientale (UPO), 28100 Novara, Italy
| | - Matteo Ratti
- Department of Translational Medicine (DiMeT), University of Eastern Piedmont/Piemonte Orientale (UPO), 28100 Novara, Italy
| | - Anil Babu Payedimarri
- Department of Translational Medicine (DiMeT), University of Eastern Piedmont/Piemonte Orientale (UPO), 28100 Novara, Italy
| | - Massimiliano Panella
- Department of Translational Medicine (DiMeT), University of Eastern Piedmont/Piemonte Orientale (UPO), 28100 Novara, Italy
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Vilca-Alosilla JJ, Candia-Puma MA, Coronel-Monje K, Goyzueta-Mamani LD, Galdino AS, Machado-de-Ávila RA, Giunchetti RC, Ferraz Coelho EA, Chávez-Fumagalli MA. A Systematic Review and Meta-Analysis Comparing the Diagnostic Accuracy Tests of COVID-19. Diagnostics (Basel) 2023; 13:diagnostics13091549. [PMID: 37174941 PMCID: PMC10177430 DOI: 10.3390/diagnostics13091549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 04/06/2023] [Accepted: 04/11/2023] [Indexed: 05/15/2023] Open
Abstract
In this paper, we present a systematic review and meta-analysis that aims to evaluate the reliability of coronavirus disease diagnostic tests in 2019 (COVID-19). This article seeks to describe the scientific discoveries made because of diagnostic tests conducted in recent years during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Between 2020 and 2021, searches for published papers on the COVID-19 diagnostic were made in the PubMed database. Ninety-nine scientific articles that satisfied the requirements were analyzed and included in the meta-analysis, and the specificity and sensitivity of the diagnostic accuracy were assessed. When compared to serological tests such as the enzyme-linked immunosorbent assay (ELISA), chemiluminescence immunoassay (CLIA), lateral flow immunoassay (LFIA), and chemiluminescent microparticle immunoassay (CMIA), molecular tests such as reverse transcription polymerase chain reaction (RT-PCR), reverse transcription loop-mediated isothermal amplification (RT-LAMP), and clustered regularly interspaced short palindromic repeats (CRISPR) performed better in terms of sensitivity and specificity. Additionally, the area under the curve restricted to the false-positive rates (AUCFPR) of 0.984 obtained by the antiviral neutralization bioassay (ANB) diagnostic test revealed significant potential for the identification of COVID-19. It has been established that the various diagnostic tests have been effectively adapted for the detection of SARS-CoV-2; nevertheless, their performance still must be enhanced to contain potential COVID-19 outbreaks, which will also help contain potential infectious agent outbreaks in the future.
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Affiliation(s)
- Juan Jeferson Vilca-Alosilla
- Computational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Católica de Santa María, Arequipa 04000, Peru
- Facultad de Ciencias Farmacéuticas, Bioquímicas y Biotecnológicas, Universidad Católica de Santa María, Arequipa 04000, Peru
| | - Mayron Antonio Candia-Puma
- Computational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Católica de Santa María, Arequipa 04000, Peru
- Facultad de Ciencias Farmacéuticas, Bioquímicas y Biotecnológicas, Universidad Católica de Santa María, Arequipa 04000, Peru
| | - Katiusca Coronel-Monje
- Computational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Católica de Santa María, Arequipa 04000, Peru
- Facultad de Ciencias Farmacéuticas, Bioquímicas y Biotecnológicas, Universidad Católica de Santa María, Arequipa 04000, Peru
| | - Luis Daniel Goyzueta-Mamani
- Computational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Católica de Santa María, Arequipa 04000, Peru
- Sustainable Innovative Biomaterials Department, Le Qara Research Center, Arequipa 04000, Peru
| | - Alexsandro Sobreira Galdino
- Laboratório de Biotecnologia de Microrganismos, Universidade Federal São João Del-Rei, Divinópolis 35501-296, MG, Brazil
| | | | - Rodolfo Cordeiro Giunchetti
- Laboratório de Biologia das Interações Celulares, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, MG, Brazil
- Instituto Nacional de Ciência e Tecnologia em Doenças Tropicais, INCT-DT, Salvador 40015-970, BA, Brazil
| | - Eduardo Antonio Ferraz Coelho
- Programa de Pós-Graduação em Ciências da Saúde: Infectologia e Medicina Tropical, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, MG, Brazil
- Departamento de Patologia Clínica, COLTEC, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, MG, Brazil
| | - Miguel Angel Chávez-Fumagalli
- Computational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Católica de Santa María, Arequipa 04000, Peru
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Matthies A, Trauer M, Chopra K, Jarman RD. Diagnostic accuracy of point-of-care lung ultrasound for COVID-19: a systematic review and meta-analysis. Emerg Med J 2023; 40:407-417. [PMID: 36868811 DOI: 10.1136/emermed-2021-212092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 01/31/2023] [Indexed: 03/05/2023]
Abstract
BACKGROUND Point-of-care (POC) lung ultrasound (LUS) is widely used in the emergency setting and there is an established evidence base across a range of respiratory diseases, including previous viral epidemics. The necessity for rapid testing combined with the limitations of other diagnostic tests has led to the proposal of various potential roles for LUS during the COVID-19 pandemic. This systematic review and meta-analysis focused specifically on the diagnostic accuracy of LUS in adult patients presenting with suspected COVID-19 infection. METHODS Traditional and grey-literature searches were performed on 1 June 2021. Two authors independently carried out the searches, selected studies and completed the Quality Assessment Tool for Diagnostic Test Accuracy Studies (QUADAS-2). Meta-analysis was carried out using established open-source packages in R. We report overall sensitivity, specificity, positive and negative predictive values, and the hierarchical summary receiver operating characteristic curve for LUS. Heterogeneity was determined using the I2 statistic. RESULTS Twenty studies were included, published between October 2020 and April 2021, providing data from a total of 4314 patients. The prevalence and admission rates were generally high across all studies. Overall, LUS was found to be 87.2% sensitive (95% CI 83.6 to 90.2) and 69.5% specific (95% CI 62.2 to 72.5) and demonstrated overall positive and negative likelihood ratios of 3.0 (95% CI 2.3 to 4.1) and 0.16 (95% CI 0.12 to 0.22), respectively. Separate analyses for each reference standard revealed similar sensitivities and specificities for LUS. Heterogeneity was found to be high across the studies. Overall, the quality of studies was low with a high risk of selection bias due to convenience sampling. There were also applicability concerns because all studies were undertaken during a period of high prevalence. CONCLUSION During a period of high prevalence, LUS had a sensitivity of 87% for the diagnosis of COVID-19 infection. However, more research is required to confirm these results in more generalisable populations, including those less likely to be admitted to hospital. PROSPERO REGISTRATION NUMBER CRD42021250464.
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Affiliation(s)
- Ashley Matthies
- Emergency Department, Homerton University Hospital NHS Foundation Trust, London, UK .,School of Health and Life Sciences, Teesside University, Middlesbrough, UK
| | - Michael Trauer
- School of Health and Life Sciences, Teesside University, Middlesbrough, UK.,Emergency Department, Guy's and Saint Thomas' NHS Foundation Trust, London, UK
| | - Karl Chopra
- Emergency Department, Homerton University Hospital NHS Foundation Trust, London, UK.,School of Health and Life Sciences, Teesside University, Middlesbrough, UK
| | - Robert David Jarman
- Accident and Emergency Department, Royal Victoria Infirmary, Newcastle upon Tyne, UK
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Krishnamoorthy A, Chandrapalan S, JalayeriNia G, Hussain Y, Bannaga A, Lei II, Arasaradnam R. Influence of seasonal and operator variations on diagnostic accuracy of lateral flow devices during the COVID-19 pandemic: a systematic review and meta-analysis. Clin Med (Lond) 2023; 23:144-150. [PMID: 36921988 PMCID: PMC11046551 DOI: 10.7861/clinmed.2022-0319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2023]
Abstract
BACKGROUND Lateral flow tests (LFT) are point-of-care rapid antigen tests that allow isolation and control of disease outbreaks through convenient, practical testing. However, studies have shown significant variation in their diagnostic accuracy. We conducted a systematic review of the diagnostic accuracy of LFTs for the detection of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) to identify potential factors affecting their performance. METHODS A systematic search of online databases was carried out to identify studies assessing the sensitivity and specificity of LFTs compared with polymerase chain reaction (PCR) tests. Data were extracted and used to calculate pooled sensitivity and specificity. Meta-regression analysis was conducted to identify covariates influencing diagnostic accuracy. RESULTS In total, 76 articles with 108,820 test results were identified for analysis. Pooled sensitivity and specificity were 72% (95% confidence interval (CI): 0.68-0.76) and 100% (95% CI: 0.99-1.00), respectively. Staff operation of the LFT showed a statistically significant increase in sensitivity (p=0.04) and specificity (p=0.001) compared with self-operation by the test subjects. The use of LFTs in symptomatic patient subgroups also resulted in higher test sensitivity. CONCLUSION LFTs display good sensitivity and extremely good specificity for SARS-CoV-2 antigen detection; they become more sensitive in patients with symptoms and when performed by trained professionals.
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Affiliation(s)
| | | | - Gohar JalayeriNia
- University Hospital of Coventry & Warwickshire NHS Trust, Coventry, UK
| | - Yaqza Hussain
- University Hospital of Coventry & Warwickshire NHS Trust, Coventry, UK
| | - Ayman Bannaga
- University Hospital of Coventry & Warwickshire NHS Trust, Coventry, UK
| | - Ian Io Lei
- University Hospital of Coventry & Warwickshire NHS Trust, Coventry, UK
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Lin HJ, Hu RM, Chen HC, Lin CC, Lee CY, Chou CY. CA125 for the Diagnosis of Advanced Urothelial Carcinoma of the Bladder: A Systematic Review and Meta-Analysis. Cancers (Basel) 2023; 15:cancers15030813. [PMID: 36765770 PMCID: PMC9913454 DOI: 10.3390/cancers15030813] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 01/23/2023] [Accepted: 01/26/2023] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Urothelial carcinoma of the bladder (UCB) is the second most common genitourinary cancer. This study aims to assess the diagnostic accuracy of CA125 in advanced UCB. METHODS We searched prevalent studies in PubMed, the Cochrane Library, Scopus, Embase, the Web of Science China National Knowledge Infrastructure database, and Wanfang data before October 2022. Pooled sensitivity, specificity, and summary receiver operating characteristics were used to assess the diagnostic value of CA125. RESULTS One thousand six hundred forty-one patients from 14 studies were analyzed. UCB stage T3-4N1 was defined as advanced UCB in ten studies; T2-4 was used in three studies; and N1M1 in one study. Patients' age was between 21 to 92, and 21% to 48.6% of patients were female. The pooled sensitivity was 0.695 (95% confidence interval (CI): 0.426-0.875). The pooled specificity was 0.846 (95% CI: 0.713-0.924). The diagnostic odds ratio was 8.138 (95% CI: 4.559-14.526). The AUC was 0.797. CONCLUSION CA125 may provide significant diagnostic accuracy in identifying muscle-invasive, lymph node-involved, and distant metastatic tumors in patients with urothelial carcinoma of the bladder. Limited studies have been conducted on the prognostic role of CA125. More studies are needed for a meta-analysis on the prognostic role of CA125 in UCB.
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Affiliation(s)
- Hsuan-Jen Lin
- Division of Nephrology, Asia University Hospital, Taichung 41354, Taiwan
- Department of Bioinformatics and Medical Engineering, Asia University, Taichung 41354, Taiwan
| | - Rouh-Mei Hu
- Department of Bioinformatics and Medical Engineering, Asia University, Taichung 41354, Taiwan
| | - Hung-Chih Chen
- Division of Nephrology, Asia University Hospital, Taichung 41354, Taiwan
| | - Chung-Chih Lin
- Division of Nephrology, Asia University Hospital, Taichung 41354, Taiwan
| | - Chi-Yu Lee
- Division of Nephrology, Asia University Hospital, Taichung 41354, Taiwan
| | - Che-Yi Chou
- Division of Nephrology, Asia University Hospital, Taichung 41354, Taiwan
- College of Medicine, China Medical University, Taichung 404332, Taiwan
- Division of Nephrology and Kidney Institute, China Medical University Hospital, Taichung 404332, Taiwan
- Department of Post-baccalaureate Veterinary Medicine, Asia University, Taichung 41354, Taiwan
- Correspondence: ; Tel.: +886-4-3706-1668-1878; Fax: +886-4-3706-1668-1338
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29
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Frazzoni L, Laterza L, La Marca M, Zagari RM, Radaelli F, Hassan C, Repici A, Facciorusso A, Gkolfakis P, Spada C, Triantafyllou K, Bazzoli F, Dinis-Ribeiro M, Fuccio L. Clinical value of alarm features for colorectal cancer: a meta-analysis. Endoscopy 2023; 55:458-468. [PMID: 36241197 DOI: 10.1055/a-1961-4266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
BACKGROUND Colorectal cancer (CRC) is a common neoplasm in Western countries. Prioritizing access to colonoscopy appears of critical relevance. Alarm features are considered to increase the likelihood of CRC. Our aim was to assess the diagnostic performance of alarm features for CRC diagnosis. METHODS We performed a systematic review and meta-analysis of studies reporting the diagnostic accuracy of alarm features (rectal bleeding, anemia, change in bowel habit, and weight loss) for CRC, published up to September 2021. Colonoscopy was required as the reference diagnostic test. Diagnostic accuracy measures were pooled by a bivariate mixed-effects regression model. The number needed to scope (NNS; i. e. the number of patients who need to undergo colonoscopy to diagnose one CRC) according to each alarm feature was calculated. RESULTS 31 studies with 45 100 patients (mean age 31-88 years; men 36 %-63 %) were included. The prevalence of CRC ranged from 0.2 % to 22 %. Sensitivity was suboptimal, ranging from 12.4 % for weight loss to 49 % for rectal bleeding, whereas specificity ranged from 69.8 % for rectal bleeding to 91.9 % for weight loss. Taken individually, rectal bleeding and anemia would be the only practical alarm features mandating colonoscopy (NNS 5.3 and 6.7, respectively). CONCLUSIONS When considered independently, alarm features have variable accuracy for CRC, given the high heterogeneity of study populations reflected by wide variability in CRC prevalence. Rectal bleeding and anemia are the most practical to select patients for colonoscopy. Integration of alarm features in a comprehensive evaluation of patients should be considered.
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Affiliation(s)
- Leonardo Frazzoni
- Department of Digestive Diseases, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Liboria Laterza
- Department of Digestive Diseases, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Marina La Marca
- Department of Medical and Surgical Sciences - DIMEC, University of Bologna, Bologna, Italy
| | - Rocco Maurizio Zagari
- Department of Digestive Diseases, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.,Department of Medical and Surgical Sciences - DIMEC, University of Bologna, Bologna, Italy
| | | | - Cesare Hassan
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy.,Endoscopy Unit, IRCCS Humanitas Clinical and Research Center, Rozzano, Milan, Italy
| | - Alessandro Repici
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy.,Endoscopy Unit, IRCCS Humanitas Clinical and Research Center, Rozzano, Milan, Italy
| | - Antonio Facciorusso
- Department of Medical and Surgical Sciences, Section of Gastroenterology, University of Foggia, Foggia, Italy
| | - Paraskevas Gkolfakis
- Department of Gastroenterology, Hepatopancreatology, and Digestive Oncology, CUB Erasme Hospital, Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Cristiano Spada
- Digestive Endoscopy Unit and Gastroenterology, Fondazione Poliambulanza, Brescia, Italy
| | - Konstantinos Triantafyllou
- Hepatogastroenterology Unit, 2nd Department of Propaedeutic Internal Medicine, Medical School, National and Kapodistrian University of Athens, Attikon University General Hospital, Athens, Greece
| | - Franco Bazzoli
- Department of Medical and Surgical Sciences - DIMEC, University of Bologna, Bologna, Italy
| | - Mario Dinis-Ribeiro
- Porto Comprehensive Cancer Center (Porto.CCC), Porto, Portugal.,RISE@CI-IPOP (Health Research Network), Porto, Portugal
| | - Lorenzo Fuccio
- Department of Digestive Diseases, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.,Department of Medical and Surgical Sciences - DIMEC, University of Bologna, Bologna, Italy
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30
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Zhou P, Wu Y, Wang M, Zhao Y, Yu Y, Waresi M, Li H, Jin B, Luo X, Li J. Identifying the culprit artery via 12-lead electrocardiogram in inferior wall ST-segment elevation myocardial infarction: A meta-analysis. Ann Noninvasive Electrocardiol 2023; 28:e13016. [PMID: 36317727 PMCID: PMC9833364 DOI: 10.1111/anec.13016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Revised: 10/09/2022] [Accepted: 10/12/2022] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Inferior wall ST-segment elevation myocardial infarction (STEMI) is mostly caused by acute occlusion of right coronary artery (RCA) and left circumflex artery (LCX). Several methods and algorithms using 12-lead ECG were developed to localize the lesion in inferior wall STEMI. However, the diagnostic properties of these methods remain under-recognized. AIMS The aim of this meta-analysis is to compare the diagnostic properties among the methods of identifying culprit artery in inferior wall STEMI using 12-lead ECG. METHODS We performed a meta-analysis to calculate the pooled sensitive, specificity, area under the curve (AUC) and diagnostic odds ratio (DOR) of each method. RESULTS Thirty-three studies with 4414 participants were included in the analysis. Methods using double leads had better diagnostic properties, especially ST-segment elevation (STE) in III > II [with pooled sensitivity 0.89 (0.84-0.93), specificity 0.68 (0.57-0.79), DOR 17 (9-32), AUC 0.88 (0.85-0.91)], ST-segment depression (STD) in aVL > I [with pooled sensitivity 0.82 (0.72-0.90), specificity 0.69 (0.48-0.86), DOR 11 (4-29), AUC 0.85 (0.81-0.88)], and STD V3/STE III ≤1.2 [with pooled sensitivity 0.88 (0.78-0.95), specificity 0.59 (0.42-0.75), DOR 12 (5-27), AUC 0.82 (0.78-0.85)]. Diagnostic algorithms, including Jim score[pooled sensitivity 0.70 (0.55-0.85), specificity 0.88 (0.75-0.96)], Fiol's algorithm [pooled sensitivity 0.54 (0.44-0.62), specificity 0.92 (0.88-0.96)] and Tierala's algorithm [pooled sensitivity 0.60 (0.49-0.71), specificity 0.91 (0.86-0.96)], were not superior to these simple methods. CONCLUSIONS Our meta-analysis indicated that diagnostic methods using double leads had better properties. STE in III > II together with STD in aVL > I may be the most ideal method, for its accuracy and convenience.
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Affiliation(s)
- Peng Zhou
- Department of CardiologyHuashan Hospital, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Yingying Wu
- Department of CardiologyHuashan Hospital, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Meng Wang
- Department of Endocrinology and MetabolismHuashan Hospital, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Yikai Zhao
- Department of CardiologyHuashan Hospital, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Yangjie Yu
- Department of CardiologyHuashan Hospital, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Maieryemu Waresi
- Department of CardiologyHuashan Hospital, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Huiyang Li
- Department of CardiologyHuashan Hospital, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Bo Jin
- Department of CardiologyHuashan Hospital, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Xinping Luo
- Department of CardiologyHuashan Hospital, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Jian Li
- Department of CardiologyHuashan Hospital, Shanghai Medical College, Fudan UniversityShanghaiChina
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Smith SK, Nwosu O, Edwards A, Zerihun M, Chung MH, Suvada K, Ali MK. Performance of screening tools for cervical neoplasia among women in low- and middle-income countries: A systematic review and meta-analysis. PLOS GLOBAL PUBLIC HEALTH 2023; 3:e0001598. [PMID: 36963095 PMCID: PMC10021669 DOI: 10.1371/journal.pgph.0001598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 01/24/2023] [Indexed: 02/25/2023]
Abstract
OBJECTIVE To evaluate the performance of visual inspection with acetic acid (VIA) testing, visual inspection with Lugol's iodine (VILI), primary HPV testing, and conventional Pap smear in detecting CIN2+ among non-pregnant women aged 30-65 in LMICs between 1990 and 2020. DESIGN Systematic review and meta-analysis. SETTING AND PARTICIPANTS Low- and middle-income countries, non-pregnant women aged 30-65. METHODS CENTRAL (Cochrane Library), CINAHL, Embase, Global Health, PubMed, and Web of Science databases were systematically searched to identify studies evaluating the performance of cervical cancer screening methods in LMICs. A diagnostic test accuracy meta-analysis was conducted to evaluate the performance of 4 screening methods in detecting CIN2+ relative to biopsy or cytology reference standards. Pooled statistics for sensitivity, specificity, diagnostic odds ratios, and summary receiver operating characteristic curves were determined for each method. Subgroup analyses were performed to examine whether there was variation in performance based on different reference standards for defining CIN2+, specifically: colposcopy-directed biopsy, biopsy alone, colposcopy alone, or liquid-based cytology. RESULTS Eighteen studies were identified through systematic review. Twelve studies were included in meta-analysis; 11 were cross-sectional and 1 was a randomized controlled clinical trial. The remaining six of the eighteen studies were inclided in a narrative syntehsis. Pooled estimates for sensitivity for VIA, VILI, primary HPV testing, and conventional Pap smear were 72.3%, 64.5%, 79.5%, and 60.2%, respectively; pooled estimates for specificity were 74.5%, 68.5%, 72.6%, and 97.4%, respectively; the diagnostic odds ratios were 7.31, 3.73, 10.42, 69.48, respectively; and the area under the summary receiver operating characteristic curves were 0.766, 0.647, 0.959, and 0.818, respectively. Performance of the screening method varied based on the reference standard used; pooled estimates using either colposcopy-directed biopsy or biopsy alone as the reference standard generally reported lower estimates; pooled estimates using either colposcopy alone or liquid-based cytology as references reported higher estimates. CONCLUSIONS AND IMPLICATIONS This meta-analysis found primary HPV testing to be the highest performing cervical cancer screening method in accurately identifying or excluding CIN2+. Further evaluation of performance at different CIN thresholds is warranted.
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Affiliation(s)
- Sabrina K Smith
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
| | - Oguchi Nwosu
- Department of Family and Preventive Medicine, School of Medicine, Emory University, Atlanta, Georgia, United States of America
| | - Alex Edwards
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
| | - Meseret Zerihun
- Department of Family Medicine, Addis Abba University, Addis Abba, Ethiopia
| | - Michael H Chung
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
- Division of Infectious Diseases, Department of Medicine, Emory University, Atlanta, Georgia, United States of America
| | - Kara Suvada
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
| | - Mohammed K Ali
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
- Department of Family and Preventive Medicine, School of Medicine, Emory University, Atlanta, Georgia, United States of America
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Huynh KQ, Le AT, Phan TT, Ho TT, Pho SP, Nguyen HT, Le BT, Nguyen TT, Nguyen ST. The Diagnostic Power of Circulating miR-1246 in Screening Cancer: An Updated Meta-analysis. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2023; 2023:8379231. [PMID: 37122536 PMCID: PMC10139802 DOI: 10.1155/2023/8379231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 03/28/2023] [Accepted: 04/11/2023] [Indexed: 05/02/2023]
Abstract
Background MicroRNA-1246 (miR-1246), an oncomiR that regulates the expression of multiple cancer-related genes, has been attracted and studied as a promising indicator of various tumors. However, diverse conclusions on diagnostic accuracy have been shown due to the small sample size and limited studies included. This meta-analysis is aimed at systematically assessing the performance of extracellular circulating miR-1246 in screening common cancers. Methods We searched the PubMed/MEDLINE, Web of Science, Cochrane Library, and Google Scholar databases for relevant studies until November 28, 2022. Then, the summary receiver operating characteristic (SROC) curves were drawn and calculated area under the curve (AUC), diagnostic odds ratio (DOR), sensitivity, and specificity values of circulating miR-1246 in the cancer surveillance. Results After selection and quality assessment, 29 eligible studies with 5914 samples (3232 cases and 2682 controls) enrolled in the final analysis. The pooled AUC, DOR, sensitivity, and specificity of circulating miR-1246 in screening cancers were 0.885 (95% confidence interval (CI): 0.827-0.892), 27.7 (95% CI: 17.1-45.0), 84.2% (95% CI: 79.4-88.1), and 85.3% (95% CI: 80.5-89.2), respectively. Among cancer types, superior performance was noted for breast cancer (AUC = 0.950, DOR = 98.5) compared to colorectal cancer (AUC = 0.905, DOR = 47.6), esophageal squamous cell carcinoma (AUC = 0.757, DOR = 8.0), hepatocellular carcinoma (AUC = 0.872, DOR = 18.6), pancreatic cancer (AUC = 0.767, DOR = 12.3), and others (AUC = 0.887, DOR = 27.5, P = 0.007). No significant publication bias in DOR was observed in the meta-analysis (funnel plot asymmetry test with P = 0.652; skewness value = 0.672, P = 0.071). Conclusion Extracellular circulating miR-1246 may serve as a reliable biomarker with good sensitivity and specificity in screening cancers, especially breast cancer.
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Affiliation(s)
- Khanh Quang Huynh
- The Breast Unit, Cancer Center, Cho Ray Hospital, HCMC 700000, Vietnam
| | - Anh Tuan Le
- Department of Chemo-Radiotherapy, Cancer Center, Cho Ray Hospital, HCMC 700000, Vietnam
| | - Thang Thanh Phan
- The Laboratory D Unit, Cancer Center, Cho Ray Hospital, HCMC 700000, Vietnam
| | - Toan Trong Ho
- The Laboratory D Unit, Cancer Center, Cho Ray Hospital, HCMC 700000, Vietnam
| | - Suong Phuoc Pho
- The Laboratory D Unit, Cancer Center, Cho Ray Hospital, HCMC 700000, Vietnam
| | - Hang Thuy Nguyen
- Department of Clinical Pathology, Cho Ray Hospital, HCMC 700000, Vietnam
| | - Binh Thanh Le
- Department of General Director, Cho Ray Hospital, HCMC 700000, Vietnam
| | - Thuc Tri Nguyen
- Department of General Director, Cho Ray Hospital, HCMC 700000, Vietnam
| | - Son Truong Nguyen
- Department of General Director, Cho Ray Hospital, HCMC 700000, Vietnam
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Vereecke N, Van Hoorde S, Sperling D, Theuns S, Devriendt B, Cox E. Virotyping and genetic antimicrobial susceptibility testing of porcine ETEC/STEC strains and associated plasmid types. Front Microbiol 2023; 14:1139312. [PMID: 37143544 PMCID: PMC10151945 DOI: 10.3389/fmicb.2023.1139312] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 03/13/2023] [Indexed: 05/06/2023] Open
Abstract
Introduction Enterotoxigenic Escherichia coli (ETEC) infections are the most common cause of secretory diarrhea in suckling and post-weaning piglets. For the latter, Shiga toxin-producing Escherichia coli (STEC) also cause edema disease. This pathogen leads to significant economic losses. ETEC/STEC strains can be distinguished from general E. coli by the presence of different host colonization factors (e.g., F4 and F18 fimbriae) and various toxins (e.g., LT, Stx2e, STa, STb, EAST-1). Increased resistance against a wide variety of antimicrobial drugs, such as paromomycin, trimethoprim, and tetracyclines, has been observed. Nowadays, diagnosing an ETEC/STEC infection requires culture-dependent antimicrobial susceptibility testing (AST) and multiplex PCRs, which are costly and time-consuming. Methods Here, nanopore sequencing was used on 94 field isolates to assess the predictive power, using the meta R package to determine sensitivity and specificity and associated credibility intervals of genotypes associated with virulence and AMR. Results Genetic markers associated with resistance for amoxicillin (plasmid-encoded TEM genes), cephalosporins (ampC promoter mutations), colistin (mcr genes), aminoglycosides (aac(3) and aph(3) genes), florfenicol (floR), tetracyclines (tet genes), and trimethoprim-sulfa (dfrA genes) could explain most acquired resistance phenotypes. Most of the genes were plasmid-encoded, of which some collocated on a multi-resistance plasmid (12 genes against 4 antimicrobial classes). For fluoroquinolones, AMR was addressed by point mutations within the ParC and GyrA proteins and the qnrS1 gene. In addition, long-read data allowed to study the genetic landscape of virulence- and AMR-carrying plasmids, highlighting a complex interplay of multi-replicon plasmids with varying host ranges. Conclusion Our results showed promising sensitivity and specificity for the detection of all common virulence factors and most resistance genotypes. The use of the identified genetic hallmarks will contribute to the simultaneous identification, pathotyping, and genetic AST within a single diagnostic test. This will revolutionize future quicker and more cost-efficient (meta)genomics-driven diagnostics in veterinary medicine and contribute to epidemiological studies, monitoring, tailored vaccination, and management.
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Affiliation(s)
- Nick Vereecke
- Laboratory of Virology, Department of Translational Physiology, Infectiology and Public Health, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
- PathoSense BV, Lier, Belgium
- *Correspondence: Nick Vereecke,
| | - Sander Van Hoorde
- Laboratory of Immunology, Department of Translational Physiology, Infectiology and Public Health, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | | | - Sebastiaan Theuns
- Laboratory of Virology, Department of Translational Physiology, Infectiology and Public Health, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Bert Devriendt
- Laboratory of Immunology, Department of Translational Physiology, Infectiology and Public Health, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Eric Cox
- Laboratory of Immunology, Department of Translational Physiology, Infectiology and Public Health, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
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Mesquita SG, Caldeira RL, Favre TC, Massara CL, Beck LCNH, Simões TC, de Carvalho GBF, dos Santos Neves FG, de Oliveira G, de Souza Barbosa Lacerda L, de Almeida MA, dos Santos Carvalho O, Moraes Mourão M, Oliveira E, Silva-Pereira RA, Fonseca CT. Assessment of the accuracy of 11 different diagnostic tests for the detection of Schistosomiasis mansoni in individuals from a Brazilian area of low endemicity using latent class analysis. Front Microbiol 2022; 13:1048457. [PMID: 36590409 PMCID: PMC9797737 DOI: 10.3389/fmicb.2022.1048457] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 11/04/2022] [Indexed: 12/16/2022] Open
Abstract
Background Schistosomiasis is a parasitic disease associated with poverty. It is estimated that 7.1 million people are infected with Schistosoma mansoni in Latin America, with 95% of them living in Brazil. Accurate diagnosis and timely treatment are important measures to control and eliminate schistosomiasis, but diagnostic improvements are needed to detect infections, especially in areas of low endemicity. Methodology This research aimed to evaluate the performance of 11 diagnostic tests using latent class analysis (LCA). A cross-sectional survey was undertaken in a low endemicity area of the municipality of Malacacheta, Minas Gerais, Brazil. Feces, urine, and blood samples were collected from 400 residents older than 6 years of age, who had not been treated with praziquantel in the 12 months previous to the collection of their samples. The collected samples were examined using parasitological (Helm Test® kit Kato-Katz), nucleic acid amplification tests -NAATs (PCR, qPCR and LAMP on urine; PCR-ELISA, qPCR and LAMP on stool), and immunological (POC-CCA, the commercial anti-Schistosoma mansoni IgG ELISA kit from Euroimmun, and two in-house ELISA assays using either the recombinant antigen PPE or the synthetic peptide Smp150390.1) tests. Results The positivity rate of the 11 tests evaluated ranged from 5% (qPCR on urine) to 40.8% (commercial ELISA kit). The estimated prevalence of schistosomiasis was 12% (95% CI: 9-15%) according to the LCA. Among all tests assessed, the commercial ELISA kit had the highest estimated sensitivity (100%), while the Kato-Katz had the highest estimated specificity (99%). Based on the accuracy measures observed, we proposed three 2-step diagnostic approaches for the active search of infected people in endemic settings. The approaches proposed consist of combinations of commercial ELISA kit and NAATs tests performed on stool. All the approaches had higher sensitivity and specificity than the mean values observed for the 11 tests (70.4 and 89.5%, respectively). Conclusion We showed that it is possible to achieve high specificity and sensitivity rates with lower costs by combining serological and NAATs tests, which would assist in the decision-making process for appropriate allocation of public funding aiming to achieve the WHO target of eliminating schistosomiasis as a public health problem by 2030.
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Affiliation(s)
- Silvia Gonçalves Mesquita
- Grupo de Pesquisa em Helmintologia e Malacologia Médica, Instituto René Rachou, Fundação Oswaldo Cruz, Belo Horizonte, Minas Gerais, Brazil
| | - Roberta Lima Caldeira
- Grupo de Pesquisa em Helmintologia e Malacologia Médica, Instituto René Rachou, Fundação Oswaldo Cruz, Belo Horizonte, Minas Gerais, Brazil
| | - Tereza Cristina Favre
- Laboratório de Educação em Ambiente e Saúde, Instituto Oswaldo Cruz, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil
| | - Cristiano Lara Massara
- Grupo de Pesquisa em Helmintologia e Malacologia Médica, Instituto René Rachou, Fundação Oswaldo Cruz, Belo Horizonte, Minas Gerais, Brazil
| | | | - Taynãna César Simões
- Núcleo de Estudos em Saúde Pública e Envelhecimento, Instituto René Rachou, Fundação Oswaldo Cruz, Belo Horizonte, Minas Gerais, Brazil
| | - Gardênia Braz Figueiredo de Carvalho
- Grupo de Pesquisa em Biologia e Imunologia de Doenças Infecciosas e Parasitárias, Instituto René Rachou, Fundação Oswaldo Cruz, Belo Horizonte, Minas Gerais, Brazil
| | - Flória Gabriela dos Santos Neves
- Grupo de Pesquisa em Helmintologia e Malacologia Médica, Instituto René Rachou, Fundação Oswaldo Cruz, Belo Horizonte, Minas Gerais, Brazil
| | - Gabriela de Oliveira
- Grupo de Pesquisa em Biologia e Imunologia de Doenças Infecciosas e Parasitárias, Instituto René Rachou, Fundação Oswaldo Cruz, Belo Horizonte, Minas Gerais, Brazil
| | - Larisse de Souza Barbosa Lacerda
- Grupo de Pesquisa em Biologia e Imunologia de Doenças Infecciosas e Parasitárias, Instituto René Rachou, Fundação Oswaldo Cruz, Belo Horizonte, Minas Gerais, Brazil
| | - Matheus Alves de Almeida
- Grupo de Pesquisa em Genômica Funcional de Parasitos, Instituto René Rachou, Fundação Oswaldo Cruz, Belo Horizonte, Minas Gerais, Brazil
| | - Omar dos Santos Carvalho
- Grupo de Pesquisa em Helmintologia e Malacologia Médica, Instituto René Rachou, Fundação Oswaldo Cruz, Belo Horizonte, Minas Gerais, Brazil
| | - Marina Moraes Mourão
- Grupo de Pesquisa em Helmintologia e Malacologia Médica, Instituto René Rachou, Fundação Oswaldo Cruz, Belo Horizonte, Minas Gerais, Brazil
| | - Edward Oliveira
- Grupo de Pesquisa em Genômica Funcional de Parasitos, Instituto René Rachou, Fundação Oswaldo Cruz, Belo Horizonte, Minas Gerais, Brazil
| | - Rosiane A. Silva-Pereira
- Grupo de Pesquisa em Biologia e Imunologia de Doenças Infecciosas e Parasitárias, Instituto René Rachou, Fundação Oswaldo Cruz, Belo Horizonte, Minas Gerais, Brazil
| | - Cristina Toscano Fonseca
- Grupo de Pesquisa em Biologia e Imunologia de Doenças Infecciosas e Parasitárias, Instituto René Rachou, Fundação Oswaldo Cruz, Belo Horizonte, Minas Gerais, Brazil
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Teunissen WHT, Govaerts CW, Kramer MCA, Labrecque JA, Smits M, Dirven L, van der Hoorn A. Diagnostic accuracy of MRI techniques for treatment response evaluation in patients with brain metastasis: A systematic review and meta-analysis. Radiother Oncol 2022; 177:121-133. [PMID: 36377093 DOI: 10.1016/j.radonc.2022.10.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 10/11/2022] [Accepted: 10/21/2022] [Indexed: 11/12/2022]
Abstract
BACKGROUND Treatment response assessment in patients with brain metastasis uses contrast enhanced T1-weighted MRI. Advanced MRI techniques have been studied, but the diagnostic accuracy is not well known. Therefore, we performed a metaanalysis to assess the diagnostic accuracy of the currently available MRI techniques for treatment response. METHODS A systematic literature search was done. Study selection and data extraction were done by two authors independently. Meta-analysis was performed using a bivariate random effects model. An independent cohort was used for DSC perfusion external validation of diagnostic accuracy. RESULTS Anatomical MRI (16 studies, 726 lesions) showed a pooled sensitivity of 79% and a specificity of 76%. DCE perfusion (4 studies, 114 lesions) showed a pooled sensitivity of 74% and a specificity of 92%. DSC perfusion (12 studies, 418 lesions) showed a pooled sensitivity was 83% with a specificity of 78%. Diffusion weighted imaging (7 studies, 288 lesions) showed a pooled sensitivity of 67% and a specificity of 79%. MRS (4 studies, 54 lesions) showed a pooled sensitivity of 80% and a specificity of 78%. Combined techniques (6 studies, 375 lesions) showed a pooled sensitivity of 84% and a specificity of 88%. External validation of DSC showed a lower sensitivity and a higher specificity for the reported cut-off values included in this metaanalysis. CONCLUSION A combination of techniques shows the highest diagnostic accuracy differentiating tumor progression from treatment induced abnormalities. External validation of imaging results is important to better define the reliability of imaging results with the different techniques.
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Affiliation(s)
- Wouter H T Teunissen
- Erasmus MC, department of Radiology and Nuclear Medicine, Rotterdam, the Netherlands; Brain Tumor Centre, Erasmus MC Cancer Institute, Rotterdam, the Netherlands; Medical Delta, Delft, The Netherlands
| | - Chris W Govaerts
- University Medical Center Groningen, Medical imaging center, department of Radiology, Groningen, the Netherlands
| | - Miranda C A Kramer
- University Medical Center Groningen, department of Radiotherapy, Groningen, the Netherlands
| | - Jeremy A Labrecque
- Erasmus MC, Netherlands Institute for Health Science (NIHES), Rotterdam, the Netherlands
| | - Marion Smits
- Erasmus MC, department of Radiology and Nuclear Medicine, Rotterdam, the Netherlands; Brain Tumor Centre, Erasmus MC Cancer Institute, Rotterdam, the Netherlands; Medical Delta, Delft, The Netherlands
| | - Linda Dirven
- Leiden University Medical Center, department of Neurology, Leiden, the Netherlands; Haaglanden Medical Center, department of Neurology, The Hague, the Netherlands
| | - Anouk van der Hoorn
- University Medical Center Groningen, Medical imaging center, department of Radiology, Groningen, the Netherlands.
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Candia-Puma MA, Machaca-Luque LY, Roque-Pumahuanca BM, Galdino AS, Giunchetti RC, Coelho EAF, Chávez-Fumagalli MA. Accuracy of Diagnostic Tests for the Detection of Chagas Disease: A Systematic Review and Meta-Analysis. Diagnostics (Basel) 2022; 12:2752. [PMID: 36359595 PMCID: PMC9689806 DOI: 10.3390/diagnostics12112752] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 11/03/2022] [Accepted: 11/04/2022] [Indexed: 11/02/2023] Open
Abstract
The present systematic review and meta-analysis about the accuracy of diagnostic tests aim to describe the findings of literature over the last thirty years for the diagnosis of Chagas disease (CD). This work aimed to determine the accuracy of diagnostic techniques for CD in the disease's acute and chronic phases. The PubMed database was searched for studies published between 1990 and 2021 on CD diagnostics. Fifty-six published studies that met the criteria were analyzed and included in the meta-analysis, evaluating diagnostic accuracy through sensitivity and specificity. For Enzyme-Linked Immunosorbent Assay (ELISA), Fluorescent Antibody Technique (IFAT), Hemagglutination Test (HmT), Polymerase Chain Reaction (PCR), and Real-Time Polymerase Chain Reaction (qPCR) diagnosis methods, the sensitivity had a median of 99.0%, 78.0%, 75.0%, 76.0%, and 94.0%, respectively; while specificity presented a median of 99.0%, 99.0%, 99.0%, 98.0%, and 98.0%, respectively. This meta-analysis showed that ELISA and qPCR techniques had a higher performance compared to other methods of diagnosing CD in the chronic and acute phases, respectively. It was concluded utilizing the Area Under the Curve restricted to the false positive rates (AUCFPR), that the ELISA diagnostic test presents the highest performance in diagnosing acute and chronic CD, compared to serological and molecular tests. Future studies focusing on new CD diagnostics approaches should be targeted.
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Affiliation(s)
- Mayron Antonio Candia-Puma
- Computational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Católica de Santa María, Arequipa 04000, Peru
- Facultad de Ciencias Farmacéuticas, Bioquímicas y Biotecnológicas, Universidad Católica de Santa María, Arequipa 04000, Peru
| | - Laura Yesenia Machaca-Luque
- Computational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Católica de Santa María, Arequipa 04000, Peru
- Facultad de Ciencias Farmacéuticas, Bioquímicas y Biotecnológicas, Universidad Católica de Santa María, Arequipa 04000, Peru
| | - Brychs Milagros Roque-Pumahuanca
- Computational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Católica de Santa María, Arequipa 04000, Peru
- Facultad de Ciencias Farmacéuticas, Bioquímicas y Biotecnológicas, Universidad Católica de Santa María, Arequipa 04000, Peru
| | - Alexsandro Sobreira Galdino
- Laboratório de Biotecnologia de Microrganismos, Universidade Federal São João Del-Rei, Divinópolis 35501-296, MG, Brazil
| | - Rodolfo Cordeiro Giunchetti
- Laboratório de Biologia das Interações Celulares, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, MG, Brazil
- Instituto Nacional de Ciência e Tecnologia em Doenças Tropicais, INCT-DT, Salvador 40015-970, BA, Brazil
| | - Eduardo Antonio Ferraz Coelho
- Programa de Pós-Graduação em Ciências da Saúde, Infectologia e Medicina Tropical, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, MG, Brazil
- Departamento de Patologia Clínica, COLTEC, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, MG, Brazil
| | - Miguel Angel Chávez-Fumagalli
- Computational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Católica de Santa María, Arequipa 04000, Peru
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Afonso HA, Farraia MV, Vieira MA, Cavaleiro Rufo J. Diagnosis of pathological conditions through electronic nose analysis of urine samples: a systematic review and meta-analysis. Porto Biomed J 2022; 7:e188. [PMID: 37152083 PMCID: PMC10158878 DOI: 10.1097/j.pbj.0000000000000188] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 04/19/2022] [Accepted: 04/28/2022] [Indexed: 12/23/2022] Open
Abstract
Currently available urinalysis methods are often applied for screening and monitoring of several pathologies. However, traditionally analyzed biomarkers in urinalysis still lack sensitivity and specificity to accurately diagnose some diseases. Several studies have proposed the use of electronic noses (eNoses) for the analysis of volatile organic compounds in urine samples that may, directly or indirectly, correlate with certain pathologies. Hence, the aim of this study was to perform a systematic review and meta-analysis of studies concerning the use of portable electronic noses for diagnosis or monitoring of pathologies through analysis of urine samples. A systematic review of the literature was held according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Twenty-four articles met the inclusion criteria and were included in the analysis. The results of the revised studies showed that there are various volatile organic compound profiles, identified through eNose analysis, that may be applied for diagnosis or monitoring of several diseases, such as diabetes, urinary tract infection, inflammatory bowel disease, and kidney disease. A meta-analysis was conducted taking into consideration the data of 10 of the initial 24 articles. The pooled sensitivity, specificity, and diagnostic odds ratio were 84% (95% CI, 0.72-0.92), 85% (95% CI, 0.75-0.91), and 24.17 (95% CI: 7.85-74.41), respectively. The area under the receiver operating characteristic curve was 0.897. These results suggest that eNose technology has adequate diagnostic accuracy for several pathologies and could be a promising screening tool for clinical settings. However, more studies are needed to reduce heterogeneity between results.
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Roy D, Modi A, Purohit P, Khokhar M, Goyal M, Sharma S, Setia P, Facciorusso A, Sharma P. Growth Differentiation Factor-15 as a candidate biomarker in gynecologic malignancies: A meta-analysis. Cancer Invest 2022; 40:901-910. [PMID: 36200606 DOI: 10.1080/07357907.2022.2133138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Growth Differentiation Factor-15 (GDF-15), though emerged as a novel marker in gynecological cancers, is yet to be recognized in clinical diagnostics. Eligible studies were sorted from multiple online databases, namely PubMed, Cochrane, ClinicalTrials.gov, Google Scholar, Web of Science, Embase, Scopus, LILACS, Opengrey. From six studies, histopathologically diagnosed cases without prior treatment, and with diagnostic accuracy data for GDF-15 in gynecological cancers, were included. Our meta-analysis shows that GDF-15 has pooled diagnostic odds ratio of 12.74 at 80.5% sensitivity and 74.1% specificity, and an AUC of 0.84. Hence, GDF-15 is a potential marker to differentiate gynecological malignancy from non-malignant tumors.
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Affiliation(s)
- Dipayan Roy
- Department of Biochemistry, AIIMS Jodhpur, India
| | - Anupama Modi
- Department of Biochemistry, AIIMS Jodhpur, India
| | | | | | - Manu Goyal
- Department of Obstetrics & Gynaecology, AIIMS Jodhpur, India
| | | | - Puneet Setia
- Department of Forensic Medicine & Toxicology, AIIMS Jodhpur, India
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Shim SR. Meta-analysis of diagnostic test accuracy studies with multiple thresholds for data integration. Epidemiol Health 2022; 44:e2022083. [PMID: 36228672 PMCID: PMC10106543 DOI: 10.4178/epih.e2022083] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 09/28/2022] [Indexed: 01/12/2023] Open
Abstract
OBJECTIVES The objective of this study is to introduce methods to use all of the information without omission when individual studies provide multiple effect sizes according to multiple cut-off values (thresholds) during diagnostic test accuracy (DTA) for data integration. For diagnostic test meta-analysis, a general performance method for synthesizing data according to one cut value in one study and a performance method for synthesizing data according to two or more cut values in one study were compared and analyzed. METHODS As sample data for meta-analysis of DTA studies, 13 DTA studies on prostate cancer (34 effect sizes including total cut-offs) were collected. The summary statistics were calculated and the summary line was analyzed using the "meta", "mada", and "diagmeta" packagesof the R software. RESULTS The summary statistics of the random effect model univariate analysis of the "meta" package with a single cut-off corresponding to the highest Youden index in a single study and those of the bivariate analysis of the "mada" package were highly similar. However, in the bivariate analysis of the "diagmeta" package including all cut-off values, the sensitivity decreased and the specificity increased as the amount of data increased. CONCLUSIONS Considering the heterogeneity of the summary receiver op erating characteristic curve and the use of all given cut-offs, the use of the bivariate analysis model of the "diagmeta" package is recommended. This study focused on practical methods of DTA rather than theoretical concepts for use by researchers whose fields of study are non-statistics related. By performing this study, we hope that many researchers will use R software to determine the DTA more easily, and that there will be greater interest in related research.
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Affiliation(s)
- Sung Ryul Shim
- Department of Health and Medical Informatics, Kyungnam University College of Health Sciences, Changwon, Korea
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Hopkins D, Rickwood DJ, Hallford DJ, Watsford C. Structured data vs. unstructured data in machine learning prediction models for suicidal behaviors: A systematic review and meta-analysis. Front Digit Health 2022; 4:945006. [PMID: 35983407 PMCID: PMC9378826 DOI: 10.3389/fdgth.2022.945006] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 06/29/2022] [Indexed: 11/23/2022] Open
Abstract
Suicide remains a leading cause of preventable death worldwide, despite advances in research and decreases in mental health stigma through government health campaigns. Machine learning (ML), a type of artificial intelligence (AI), is the use of algorithms to simulate and imitate human cognition. Given the lack of improvement in clinician-based suicide prediction over time, advancements in technology have allowed for novel approaches to predicting suicide risk. This systematic review and meta-analysis aimed to synthesize current research regarding data sources in ML prediction of suicide risk, incorporating and comparing outcomes between structured data (human interpretable such as psychometric instruments) and unstructured data (only machine interpretable such as electronic health records). Online databases and gray literature were searched for studies relating to ML and suicide risk prediction. There were 31 eligible studies. The outcome for all studies combined was AUC = 0.860, structured data showed AUC = 0.873, and unstructured data was calculated at AUC = 0.866. There was substantial heterogeneity between the studies, the sources of which were unable to be defined. The studies showed good accuracy levels in the prediction of suicide risk behavior overall. Structured data and unstructured data also showed similar outcome accuracy according to meta-analysis, despite different volumes and types of input data.
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Affiliation(s)
- Danielle Hopkins
- Faculty of Health, University of Canberra, Canberra, ACT, Australia
- *Correspondence: Danielle Hopkins
| | | | | | - Clare Watsford
- Faculty of Health, University of Canberra, Canberra, ACT, Australia
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Gutiérrez-Tobal GC, Álvarez D, Kheirandish-Gozal L, Del Campo F, Gozal D, Hornero R. Reliability of machine learning to diagnose pediatric obstructive sleep apnea: Systematic review and meta-analysis. Pediatr Pulmonol 2022; 57:1931-1943. [PMID: 33856128 DOI: 10.1002/ppul.25423] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 04/07/2021] [Accepted: 04/10/2021] [Indexed: 12/27/2022]
Abstract
BACKGROUND Machine-learning approaches have enabled promising results in efforts to simplify the diagnosis of pediatric obstructive sleep apnea (OSA). A comprehensive review and analysis of such studies increase the confidence level of practitioners and healthcare providers in the implementation of these methodologies in clinical practice. OBJECTIVE To assess the reliability of machine-learning-based methods to detect pediatric OSA. DATA SOURCES Two researchers conducted an electronic search on the Web of Science and Scopus using term, and studies were reviewed along with their bibliographic references. ELIGIBILITY CRITERIA Articles or reviews (Year 2000 onwards) that applied machine learning to detect pediatric OSA; reported data included information enabling derivation of true positive, false negative, true negative, and false positive cases; polysomnography served as diagnostic standard. APPRAISAL AND SYNTHESIS METHODS Pooled sensitivities and specificities were computed for three apnea-hypopnea index (AHI) thresholds: 1 event/hour (e/h), 5 e/h, and 10 e/h. Random-effect models were assumed. Summary receiver-operating characteristics (SROC) analyses were also conducted. Heterogeneity (I 2 ) was evaluated, and publication bias was corrected (trim and fill). RESULTS Nineteen studies were finally retained, involving 4767 different pediatric sleep studies. Machine learning improved diagnostic performance as OSA severity criteria increased reaching optimal values for AHI = 10 e/h (0.652 sensitivity; 0.931 specificity; and 0.940 area under the SROC curve). Publication bias correction had minor effect on summary statistics, but high heterogeneity was observed among the studies.
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Affiliation(s)
- Gonzalo C Gutiérrez-Tobal
- Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Zaragoza, Spain
| | - Daniel Álvarez
- Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Zaragoza, Spain.,Department of Pneumology, Río Hortega University Hospital, Valladolid, Spain
| | - Leila Kheirandish-Gozal
- Department of Child Health, Child Health Research Institute, The University of Missouri School of Medicine, Columbia, Missouri, USA
| | - Félix Del Campo
- Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Zaragoza, Spain.,Department of Pneumology, Río Hortega University Hospital, Valladolid, Spain
| | - David Gozal
- Department of Child Health, Child Health Research Institute, The University of Missouri School of Medicine, Columbia, Missouri, USA
| | - Roberto Hornero
- Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Zaragoza, Spain.,Department of Pneumology, Río Hortega University Hospital, Valladolid, Spain
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Usmani S, Ahmed N, Gnanasegaran G, Al Kandari F, Marafi F, Bani-Mustafa A, Musbah A, Jassem Almashmoum M, Van den Wyngaert T. Prospective study of Na[ 18F]F PET/CT for cancer staging in morbidly obese patients compared with [ 99mTc]Tc-MDP whole-body planar, SPECT and SPECT/CT. Acta Oncol 2022; 61:1230-1239. [PMID: 35862646 DOI: 10.1080/0284186x.2022.2101899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Abstract
PURPOSE This prospective study aims to assess the diagnostic test characteristics of Na[18F]F PET/CT for the skeletal staging of cancer in morbidly obese patients compared with 99mTc-methylene diphosphonate (MDP), whole-body planar (WBS), SPECT, and SPECT/CT acquisitions. MATERIAL AND METHODS One hundred seventeen obese patients (BMI 46.5 ± 6.1 kg/m2 and mean age, 59.0 years; range 32-89 years) with BMI > 40 kg/m2 were prospectively enrolled and underwent [99mTc]Tc-MDP WBS, SPECT, SPECT/CT, and Na[18F]F PET/CT within two weeks for the osseous staging of a malignancy. Images were assessed qualitatively using a 3-point scale. Patient and lesion-based diagnostic test characteristics were estimated using an optimistic and pessimistic dichotomization method. RESULTS Bone metastases were confirmed in 44 patients. Patient-based optimistic diagnostic test characteristics were (sensitivity, specificity, overall accuracy): Na[18F]F PET/CT (95.5%, 95.9%, 95.7%), [99mTc]Tc-MDP WBS (52.3%, 71.2%, 64.1%), SPECT (61.4%, 80.8%, 73.5%) and SPECT/CT (65.9%, 91.8%, 82.1%). Lesion-based optimistic diagnostic test characteristics were: Na[18F]F PET/CT (97.7%, 97.9%, 97.7%), [99mTc]Tc-MDP WBS (39%, 67%, 48.9%), SPECT (52.9%, 93.6%, 67.3%) and SPECT/CT (65.9%, 91.8%, 82.1%). There was no significant difference in the specificity of Na[18F]F and SPECT/CT. All other pairwise comparisons were significant (p<.001). ROC curve analysis showed a high overall accuracy of Na[18F]F with significantly higher AUCs for Na[18F]F PET/CT compared to [99mTc]Tc-MDP WBS, SPECT, and SPECT/CT on both patient and lesion-based analysis (p<.001). Moreover, Na[18F]F PET/CT changed patient management in 38% of patients. CONCLUSIONS Na[18F]F PET/CT may be the preferred imaging modality for skeletal staging in morbidly obese patients. The technique provides excellent diagnostic test characteristics superior to [99mTc]Tc-MDP bone scan (including SPECT/CT), impacts patient management, has an acceptable radiation exposure profile, and is well-tolerated. Further cost-effectiveness evaluations are warranted.
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Affiliation(s)
- Sharjeel Usmani
- Department of Nuclear Medicine, Kuwait Cancer Control Centre, Shuwaikh, Kuwait.,Jaber Al-Ahmad Molecular Imaging Center, Kuwait, Kuwait.,Faculty of Medicine and Health Sciences, University of Antwerp, Wilrijk, Belgium
| | - Najeeb Ahmed
- Jack Brignall PET/CT Centre, Castle Hill Hosptial, Cottingham, UK
| | | | - Fareeda Al Kandari
- Department of Nuclear Medicine, Kuwait Cancer Control Centre, Shuwaikh, Kuwait
| | - Fahad Marafi
- Jaber Al-Ahmad Molecular Imaging Center, Kuwait, Kuwait
| | - Ahmed Bani-Mustafa
- Department of Mathematics and Physics, Australian University of Kuwait, Kuwait
| | - Ahmed Musbah
- Department of Nuclear Medicine, Kuwait Cancer Control Centre, Shuwaikh, Kuwait
| | | | - Tim Van den Wyngaert
- Antwerp University Hospital, Edegem, Belgium.,Faculty of Medicine and Health Sciences, University of Antwerp, Wilrijk, Belgium
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Rotstein D, Solomon JM, Sormani MP, Montalban X, Ye XY, Dababneh D, Muccilli A, Shah P. Association of No Evidence of Disease Activity With No Long-term Disability Progression in Multiple Sclerosis: A Systematic Review and Meta-analysis. Neurology 2022; 99:e209-e220. [PMID: 35473761 DOI: 10.1212/wnl.0000000000200549] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 03/02/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES We conducted a systematic review and meta-analysis to evaluate the relationship between no evidence of disease activity (NEDA) and no long-term disability progression on low- and high-efficacy therapy in relapsing-remitting multiple sclerosis (RRMS). METHODS MEDLINE, Embase, and the Cochrane Database were searched from January 1, 2006, to January 26, 2021. We selected studies that evaluated NEDA-3 (no relapse, new MRI lesion, or confirmed disability progression) at 1 or 2 years and had a minimum of 4 years of follow-up for determination of disability progression. Data were extracted by 2 independent reviewers and were meta-analyzed with a random-effects model. Primary outcome of no disability progression was defined as no confirmed progression on the Expanded Disability Status Scale during follow-up. We assessed the odds ratio (OR) for no disability progression with NEDA vs evidence of disease activity (EDA). Positive predictive value (PPV) of NEDA for no disability progression was summarized for studies with prevalence of no progression >80% vs ≤80% separately. RESULTS We included 29 studies in our qualitative synthesis, of which 27 (16 low efficacy, 11 high efficacy) were included in the meta-analysis (N = 10,935 participants). Median follow-up was 5.6 years (interquartile range 4.3-8.0 years). The pooled ORs for no progression with NEDA-3 vs EDA were 2.32 (95% CI 1.58-3.42; I 2 = 73%) for low-efficacy therapy and 3.19 (95% CI 1.86-5.47; I 2 = 86%) for high-efficacy therapy. Among studies with prevalence of no progression at follow-up >80%, the pooled PPV for low efficacy therapy was 91% (95% CI 89%-93%) and for high-efficacy therapy was 92% (95% CI 88%-94%). Among studies with prevalence of no progression ≤80%, the pooled PPV for low-efficacy therapy was 81% (95% CI 75%-86%) and for high-efficacy therapy was 86% (95% CI 80%-90%). DISCUSSION NEDA-3 is associated with no long-term disability progression in RRMS on both low- and high-efficacy therapies. Further studies of early composite outcome measures incorporating easily measurable biomarkers and longer follow-up may help to improve the prognostic value of NEDA-3 in RRMS. TRIAL REGISTRATION INFORMATION International Prospective Register of Systematic Reviews Identifier: CRD42020189316.
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Affiliation(s)
- Dalia Rotstein
- From the Department of Medicine (D.R., A.M.), University of Toronto; St. Michael's Hospital (D.R., A.M.), Toronto; Department of Medicine (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Section of Biostatistics (M.P.S.), Department of Health Sciences, University of Genova; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology (X.M.), Cemcat, Hospital Universitari Vall d-Hebron, Universitat Autonoma de Barcelona, Spain; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Ontario, Canada; Department of Neurology (D.D.), Columbia University Irving Medical Center; New York Presbyterian Hospital (D.D.), New York City; and Institute of Health, Policy, Management and Evaluation (P.S.), University of Toronto, Ontario, Canada.
| | - Jacqueline Madeleine Solomon
- From the Department of Medicine (D.R., A.M.), University of Toronto; St. Michael's Hospital (D.R., A.M.), Toronto; Department of Medicine (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Section of Biostatistics (M.P.S.), Department of Health Sciences, University of Genova; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology (X.M.), Cemcat, Hospital Universitari Vall d-Hebron, Universitat Autonoma de Barcelona, Spain; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Ontario, Canada; Department of Neurology (D.D.), Columbia University Irving Medical Center; New York Presbyterian Hospital (D.D.), New York City; and Institute of Health, Policy, Management and Evaluation (P.S.), University of Toronto, Ontario, Canada
| | - Maria Pia Sormani
- From the Department of Medicine (D.R., A.M.), University of Toronto; St. Michael's Hospital (D.R., A.M.), Toronto; Department of Medicine (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Section of Biostatistics (M.P.S.), Department of Health Sciences, University of Genova; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology (X.M.), Cemcat, Hospital Universitari Vall d-Hebron, Universitat Autonoma de Barcelona, Spain; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Ontario, Canada; Department of Neurology (D.D.), Columbia University Irving Medical Center; New York Presbyterian Hospital (D.D.), New York City; and Institute of Health, Policy, Management and Evaluation (P.S.), University of Toronto, Ontario, Canada
| | - Xavier Montalban
- From the Department of Medicine (D.R., A.M.), University of Toronto; St. Michael's Hospital (D.R., A.M.), Toronto; Department of Medicine (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Section of Biostatistics (M.P.S.), Department of Health Sciences, University of Genova; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology (X.M.), Cemcat, Hospital Universitari Vall d-Hebron, Universitat Autonoma de Barcelona, Spain; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Ontario, Canada; Department of Neurology (D.D.), Columbia University Irving Medical Center; New York Presbyterian Hospital (D.D.), New York City; and Institute of Health, Policy, Management and Evaluation (P.S.), University of Toronto, Ontario, Canada
| | - Xiang Y Ye
- From the Department of Medicine (D.R., A.M.), University of Toronto; St. Michael's Hospital (D.R., A.M.), Toronto; Department of Medicine (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Section of Biostatistics (M.P.S.), Department of Health Sciences, University of Genova; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology (X.M.), Cemcat, Hospital Universitari Vall d-Hebron, Universitat Autonoma de Barcelona, Spain; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Ontario, Canada; Department of Neurology (D.D.), Columbia University Irving Medical Center; New York Presbyterian Hospital (D.D.), New York City; and Institute of Health, Policy, Management and Evaluation (P.S.), University of Toronto, Ontario, Canada
| | - Dina Dababneh
- From the Department of Medicine (D.R., A.M.), University of Toronto; St. Michael's Hospital (D.R., A.M.), Toronto; Department of Medicine (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Section of Biostatistics (M.P.S.), Department of Health Sciences, University of Genova; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology (X.M.), Cemcat, Hospital Universitari Vall d-Hebron, Universitat Autonoma de Barcelona, Spain; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Ontario, Canada; Department of Neurology (D.D.), Columbia University Irving Medical Center; New York Presbyterian Hospital (D.D.), New York City; and Institute of Health, Policy, Management and Evaluation (P.S.), University of Toronto, Ontario, Canada
| | - Alexandra Muccilli
- From the Department of Medicine (D.R., A.M.), University of Toronto; St. Michael's Hospital (D.R., A.M.), Toronto; Department of Medicine (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Section of Biostatistics (M.P.S.), Department of Health Sciences, University of Genova; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology (X.M.), Cemcat, Hospital Universitari Vall d-Hebron, Universitat Autonoma de Barcelona, Spain; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Ontario, Canada; Department of Neurology (D.D.), Columbia University Irving Medical Center; New York Presbyterian Hospital (D.D.), New York City; and Institute of Health, Policy, Management and Evaluation (P.S.), University of Toronto, Ontario, Canada
| | - Prakesh Shah
- From the Department of Medicine (D.R., A.M.), University of Toronto; St. Michael's Hospital (D.R., A.M.), Toronto; Department of Medicine (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Section of Biostatistics (M.P.S.), Department of Health Sciences, University of Genova; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology (X.M.), Cemcat, Hospital Universitari Vall d-Hebron, Universitat Autonoma de Barcelona, Spain; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Ontario, Canada; Department of Neurology (D.D.), Columbia University Irving Medical Center; New York Presbyterian Hospital (D.D.), New York City; and Institute of Health, Policy, Management and Evaluation (P.S.), University of Toronto, Ontario, Canada
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Diagnostic Accuracy of Machine Learning Models on Mammography in Breast Cancer Classification: A Meta-Analysis. Diagnostics (Basel) 2022; 12:diagnostics12071643. [PMID: 35885548 PMCID: PMC9320089 DOI: 10.3390/diagnostics12071643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 06/29/2022] [Accepted: 06/29/2022] [Indexed: 11/16/2022] Open
Abstract
In this meta-analysis, we aimed to estimate the diagnostic accuracy of machine learning models on digital mammograms and tomosynthesis in breast cancer classification and to assess the factors affecting its diagnostic accuracy. We searched for related studies in Web of Science, Scopus, PubMed, Google Scholar and Embase. The studies were screened in two stages to exclude the unrelated studies and duplicates. Finally, 36 studies containing 68 machine learning models were included in this meta-analysis. The area under the curve (AUC), hierarchical summary receiver operating characteristics (HSROC) curve, pooled sensitivity and pooled specificity were estimated using a bivariate Reitsma model. Overall AUC, pooled sensitivity and pooled specificity were 0.90 (95% CI: 0.85–0.90), 0.83 (95% CI: 0.78–0.87) and 0.84 (95% CI: 0.81–0.87), respectively. Additionally, the three significant covariates identified in this study were country (p = 0.003), source (p = 0.002) and classifier (p = 0.016). The type of data covariate was not statistically significant (p = 0.121). Additionally, Deeks’ linear regression test indicated that there exists a publication bias in the included studies (p = 0.002). Thus, the results should be interpreted with caution.
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Shim SR, Kim SJ, Hong M, Lee J, Kang MG, Han HW. Diagnostic Performance of Antigen Rapid Diagnostic Tests, Chest Computed Tomography, and Lung Point-of-Care-Ultrasonography for SARS-CoV-2 Compared with RT-PCR Testing: A Systematic Review and Network Meta-Analysis. Diagnostics (Basel) 2022; 12:1302. [PMID: 35741112 PMCID: PMC9222155 DOI: 10.3390/diagnostics12061302] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 05/04/2022] [Accepted: 05/20/2022] [Indexed: 12/10/2022] Open
Abstract
(1) Background: The comparative performance of various diagnostic methods for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection remains unclear. This study aimed to investigate the comparison of the 3 index test performances of rapid antigen diagnostic tests (RDTs), chest computed tomography (CT), and lung point-of-care-ultrasonography (US) with reverse transcription-polymerase chain reaction (RT-PCR), the reference standard, to provide more evidence-based data on the appropriate use of these index tests. (2) Methods: We retrieved data from electronic literature searches of PubMed, Cochrane Library, and EMBASE from 1 January 2020, to 1 April 2021. Diagnostic performance was examined using bivariate random-effects diagnostic test accuracy (DTA) and Bayesian network meta-analysis (NMA) models. (3) Results: Of the 3992 studies identified in our search, 118 including 69,445 participants met our selection criteria. Among these, 69 RDT, 38 CT, and 15 US studies in the pairwise meta-analysis were included for DTA with NMA. CT and US had high sensitivity of 0.852 (95% credible interval (CrI), 0.791-0.914) and 0.879 (95% CrI, 0.784-0.973), respectively. RDT had high specificity, 0.978 (95% CrI, 0.960-0.996). In accuracy assessment, RDT and CT had a relatively higher than US. However, there was no significant difference in accuracy between the 3 index tests. (4) Conclusions: This meta-analysis suggests that, compared with the reference standard RT-PCR, the 3 index tests (RDTs, chest CT, and lung US) had similar and complementary performances for diagnosis of SARS-CoV-2 infection. To manage and control COVID-19 effectively, future large-scale prospective studies could be used to obtain an optimal timely diagnostic process that identifies the condition of the patient accurately.
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Affiliation(s)
- Sung Ryul Shim
- Department of Health and Medical Informatics, Kyungnam University College of Health Sciences, Changwon 51767, Korea;
| | - Seong-Jang Kim
- Department of Nuclear Medicine, Pusan National University Yangsan Hospital, Yangsan 50615, Korea;
- Department of Nuclear Medicine, College of Medicine, Pusan National University, Yangsan 50615, Korea
- BioMedical Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan 50615, Korea
| | - Myunghee Hong
- Department of Biomedical Informatics, CHA University School of Medicine, CHA University, Seongnam 13488, Korea;
- Institute for Biomedical Informatics, School of Medicine, CHA University, Seongnam 13488, Korea
| | - Jonghoo Lee
- Department of Internal Medicine, Jeju National University Hospital, Jeju National University School of Medicine, Jeju 63241, Korea;
| | - Min-Gyu Kang
- Department of Internal Medicine, Chungbuk National University College of Medicine, Chungbuk National University Hospital, Cheongju 28644, Korea;
| | - Hyun Wook Han
- Department of Biomedical Informatics, CHA University School of Medicine, CHA University, Seongnam 13488, Korea;
- Institute for Biomedical Informatics, School of Medicine, CHA University, Seongnam 13488, Korea
- Institute of Basic Medical Sciences, School of Medicine, CHA University, Seongnam 13488, Korea
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van Geel JJL, Boers J, Elias SG, Glaudemans AWJM, de Vries EFJ, Hospers GAP, van Kruchten M, Kuip EJM, Jager A, Menke-van der Houven van Oordt WC, van der Vegt B, de Vries EGE, Schröder CP. Clinical Validity of 16α-[ 18F]Fluoro-17β-Estradiol Positron Emission Tomography/Computed Tomography to Assess Estrogen Receptor Status in Newly Diagnosed Metastatic Breast Cancer. J Clin Oncol 2022; 40:3642-3652. [PMID: 35584346 DOI: 10.1200/jco.22.00400] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
PURPOSE Determining the estrogen receptor (ER) status is essential in metastatic breast cancer (MBC) management. Whole-body ER imaging with 16α-[18F]fluoro-17β-estradiol positron emission tomography ([18F]FES-PET) is increasingly used for this purpose. To establish the clinical validity of the [18F]FES-PET, we studied the diagnostic accuracy of qualitative and quantitative [18F]FES-PET assessment to predict ER expression by immunohistochemistry in a metastasis. METHODS In a prospective multicenter trial, 200 patients with newly diagnosed MBC underwent extensive workup including molecular imaging. For this subanalysis, ER expression in the biopsied metastasis was related to qualitative whole-body [18F]FES-PET evaluation and quantitative [18F]FES uptake in the corresponding metastasis. A review and meta-analysis regarding [18F]FES-PET diagnostic performance were performed. RESULTS Whole-body [18F]FES-PET assessment predicted ER expression in the biopsied metastasis with good accuracy: a sensitivity of 95% (95% CI, 89 to 97), a specificity of 80% (66 to 89), a positive predictive value (PPV) of 93% (87 to 96), and a negative predictive value (NPV) of 85% (72 to 92) in 181 of 200 evaluable patients. Quantitative [18F]FES uptake predicted ER immunohistochemistry in the corresponding metastasis with a sensitivity/specificity of 91%/69% and a PPV/NPV of 90%/71% in 156 of 200 evaluable patients. For bone metastases, PPV/NPV was 92%/81%. Meta-analysis with addition of our data has increased diagnostic performance and narrowed the 95% CIs compared with previous studies with a sensitivity/specificity of both 86% (81 to 90 and 73 to 93, respectively). CONCLUSION In this largest prospective series so far, we established the clinical validity of [18F]FES-PET to determine tumor ER status in MBC. In view of the high diagnostic accuracy of qualitatively assessed whole-body [18F]FES-PET, this noninvasive imaging modality can be considered a valid alternative to a biopsy of a metastasis to determine ER status in newly MBC (ClinicalTrials.gov identifier: NCT01957332).
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Affiliation(s)
- Jasper J L van Geel
- Department of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Jorianne Boers
- Department of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Sjoerd G Elias
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Andor W J M Glaudemans
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Erik F J de Vries
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Geke A P Hospers
- Department of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Michel van Kruchten
- Department of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Evelien J M Kuip
- Department of Medical Oncology, Radboud Medical Center, Nijmegen, the Netherlands
| | - Agnes Jager
- Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
| | | | - Bert van der Vegt
- Department of Pathology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Elisabeth G E de Vries
- Department of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Carolina P Schröder
- Department of Medical Oncology, Dutch Cancer Institute, Amsterdam and University Medical Center Groningen, Groningen, the Netherlands
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Comparison of Diagnostic Test Accuracy of Cone-Beam Breast Computed Tomography and Digital Breast Tomosynthesis for Breast Cancer: A Systematic Review and Meta-Analysis Approach. SENSORS 2022; 22:s22093594. [PMID: 35591290 PMCID: PMC9101306 DOI: 10.3390/s22093594] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 04/24/2022] [Accepted: 05/05/2022] [Indexed: 01/27/2023]
Abstract
BACKGROUND Cone-beam breast computed tomography (CBBCT) and digital breast tomosynthesis (DBT) remain the main 3D modalities for X-ray breast imaging. This study aimed to systematically evaluate and meta-analyze the comparison of diagnostic accuracy of CBBCT and DBT to characterize breast cancers. METHODS Two independent reviewers identified screening on diagnostic studies from 1 January 2015 to 30 December 2021, with at least reported sensitivity and specificity for both CBBCT and DBT. A univariate pooled meta-analysis was performed using the random-effects model to estimate the sensitivity and specificity while other diagnostic parameters like the area under the ROC curve (AUC), positive likelihood ratio (LR+), and negative likelihood ratio (LR-) were estimated using the bivariate model. RESULTS The pooled sensitivity specificity, LR+ and LR- and AUC at 95% confidence interval are 86.7% (80.3-91.2), 87.0% (79.9-91.8), 6.28 (4.40-8.96), 0.17 (0.12-0.25) and 0.925 for the 17 included studies in DBT arm, respectively, while, 83.7% (54.6-95.7), 71.3% (47.5-87.2), 2.71 (1.39-5.29), 0.20 (0.04-1.05), and 0.831 are the pooled sensitivity specificity, LR+ and LR- and AUC for the five studies in the CBBCT arm, respectively. CONCLUSIONS Our study demonstrates that DBT shows improved diagnostic performance over CBBCT regarding all estimated diagnostic parameters; with the statistical improvement in the AUC of DBT over CBBCT. The CBBCT might be a useful modality for breast cancer detection, thus we recommend more prospective studies on CBBCT application.
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Demandt JPA, Zelis JM, Koks A, Smits GHJM, van der Harst P, Tonino PAL, Dekker LRC, van Het Veer M, Vlaar PJ. Prehospital risk assessment in patients suspected of non-ST-segment elevation acute coronary syndrome: a systematic review and meta-analysis. BMJ Open 2022; 12:e057305. [PMID: 35383078 PMCID: PMC8984055 DOI: 10.1136/bmjopen-2021-057305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Accepted: 03/15/2022] [Indexed: 11/29/2022] Open
Abstract
OBJECTIVE To review, inventory and compare available diagnostic tools and investigate which tool has the best performance for prehospital risk assessment in patients suspected of non-ST-segment elevation acute coronary syndrome (NSTE-ACS). METHODS Systematic review and meta-analysis. Medline and Embase were searched up till 1 April 2021. Prospective studies with patients, suspected of NSTE-ACS, presenting in the primary care setting or by emergency medical services (EMS) were included. The most important exclusion criteria were studies including only patients with ST-elevation myocardial infarction and studies before 1995, the pretroponin era. The primary end point was the final hospital discharge diagnosis of NSTE-ACS or major adverse cardiac events (MACE) within 6 weeks. Risk of bias was evaluated by the Quality Assessment of Diagnostic Accuracy Studies Criteria. MAIN OUTCOME AND MEASURES Sensitivity, specificity and likelihood ratio of findings for risk stratification in patients suspected of NSTE-ACS. RESULTS In total, 15 prospective studies were included; these studies reflected in total 26 083 patients. No specific variables related to symptoms, physical examination or risk factors were useful in risk stratification for NSTE-ACS diagnosis. The most useful electrocardiographic finding was ST-segment depression (LR+3.85 (95% CI 2.58 to 5.76)). Point-of-care troponin was found to be a strong predictor for NSTE-ACS in primary care (LR+14.16 (95% CI 4.28 to 46.90) and EMS setting (LR+6.16 (95% CI 5.02 to 7.57)). Combined risk scores were the best for risk assessment in an NSTE-ACS. From the combined risk scores that can be used immediately in a prehospital setting, the PreHEART score, a validated combined risk score for prehospital use, derived from the HEART score (History, ECG, Age, Risk factors, Troponin), was most useful for risk stratification in patients with NSTE-ACS (LR+8.19 (95% CI 5.47 to 12.26)) and for identifying patients without ACS (LR-0.05 (95% CI 0.02 to 0.15)). DISCUSSION Important study limitations were verification bias and heterogeneity between studies. In the prehospital setting, several diagnostic tools have been reported which could improve risk stratification, triage and early treatment in patients suspected for NSTE-ACS. On-site assessment of troponin and combined risk scores derived from the HEART score are strong predictors. These results support further studies to investigate the impact of these new tools on logistics and clinical outcome. FUNDING This study is funded by ZonMw, the Dutch Organisation for Health Research and Development. TRIAL REGISTRATION NUMBER This meta-analysis was published for registration in PROSPERO prior to starting (CRD York, CRD42021254122).
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Affiliation(s)
- Jesse P A Demandt
- Department of Cardiology, Catharina Hospital, Eindhoven, Noord-Brabant, The Netherlands
| | - Jo M Zelis
- Department of Cardiology, Catharina Hospital, Eindhoven, Noord-Brabant, The Netherlands
| | - Arjan Koks
- EMS, GGD Brabant-Zuidoost, Eindhoven, Noord-Brabant, The Netherlands
| | | | | | - Pim A L Tonino
- Department of Cardiology, Catharina Hospital, Eindhoven, Noord-Brabant, The Netherlands
| | - Lukas R C Dekker
- Department of Cardiology, Catharina Hospital, Eindhoven, Noord-Brabant, The Netherlands
| | - Marcel van Het Veer
- Department of Cardiology, Catharina Hospital, Eindhoven, Noord-Brabant, The Netherlands
| | - Pieter-Jan Vlaar
- Department of Cardiology, Catharina Hospital, Eindhoven, Noord-Brabant, The Netherlands
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Chin J, Kleyn L, Dube E, Terrell M, Lomiguen CM, Volokitin M. Assessing the Knowledge of the Osteopathic Profession in New York City’s Eastern European Communities. Cureus 2022; 14:e21664. [PMID: 35233332 PMCID: PMC8881986 DOI: 10.7759/cureus.21664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2021] [Accepted: 01/27/2022] [Indexed: 11/17/2022] Open
Abstract
Background According to the decennial Osteopathic Survey of Healthcare in America, the osteopathic profession has been steadily gaining recognition in the United States, particularly among the White/Caucasian demographic. This, however, does not take into account immigrant European communities that, while racially classified as White/Caucasian, may be unexposed to osteopathic physicians (DOs) in their home country and may be reticent to osteopathic manipulative medicine. Data on non-English-speaking communities are limited and can mask the need for further outreach. This study aimed to identify literature in osteopathic outreach to minority communities and assess osteopathic awareness in New York City’s Eastern European communities. Secondary objectives include characterization of potential barriers in hindering access to osteopathic medicine, and, by extension, other minority groups. Methodology An anonymous survey prepared in Russian and English was used to gather demographics, education level, healthcare habits, and knowledge of the osteopathic profession. To provide a clinical scenario, a health habit question regarding low back pain (LBP) was provided to participants. Participants over the age of 18 were randomly selected from high density Eastern European areas at two separate time points. Statistical analysis was performed using R to evaluate independence between questions using chi-square tests. Results A total of 150 surveys met the inclusion criteria, with 71 males and 79 females, an age range of 18-92, and a median age of 62. On comparing demographics, education level, and healthcare habits, only English proficiency showed statistical significance (p = 0.039) in determining recognition of the osteopathic profession. Overall, 60% (n = 94) stated that they have heard of osteopathic medicine and knew what a DO physician does. However, only 35% (n = 53) would see a DO for LBP, with 50% (n = 77) seeing a physical therapist. Conclusions Compared to research examining osteopathic awareness in ethnic minority communities, the Russian community in New York appears to have greater recognition of the osteopathic profession. This, however, does not translate into a clinical scenario as more participants were more likely to see a physical therapist. While this difference can be attributed to numerous factors, it stands without doubt that greater osteopathic outreach and data collection needs to be performed in minority communities.
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Li W, Takahashi T, Rios SA, Latib A, Lee JM, Fearon WF, Kobayashi Y. Diagnostic performance and prognostic impact of coronary angiography-based Index of Microcirculatory Resistance assessment: A systematic review and meta-analysis. Catheter Cardiovasc Interv 2022; 99:286-292. [PMID: 35019220 DOI: 10.1002/ccd.30076] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 12/26/2021] [Indexed: 12/29/2022]
Abstract
BACKGROUND The Index of Microcirculatory Resistance (IMR), measured with a pressure-thermistor tipped coronary guidewire has been established as a gold standard for coronary microvascular assessment. Angiography-based IMR (angio-IMR) is a novel method to derive IMR without intracoronary instrumentation or the need for adenosine. METHODS PubMed and Embase databases were systemically searched in November 2021 for studies that measured angio-IMR. The primary outcomes were pooled sensitivity and specificity as well as the area under the curve (AUC) of the summary receiver operating characteristic curve using IMR as a reference standard. RESULTS A total of 129 records were initially identified and 8 studies were included in the final analysis. Overall, 1653 lesions were included in this study, of which 733 were in patients presenting with ST-segment elevation myocardial infarction. Angio-IMR yielded high diagnostic performance predicting wire-based IMR with pooled sensitivity = 0.81 (95% confidence interval: 0.76, 0.85), specificity = 0.80 (0.72, 0.86), and AUC = 0.86 (0.82, 0.88), which was similar irrespective of patient presentation. When the clinical outcome was compared between high versus low angio-IMR in patients presenting with myocardial infarction, high angio-IMR predicted an increased risk of major adverse cardiac events (MACE). CONCLUSION Our study found that coronary angio-IMR has relatively high diagnostic performance as well as prognostic values predicting MACE, supporting its use in clinical practice.
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Affiliation(s)
- Weijia Li
- Department of Medicine, Jacobi Medical Center, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Tatsunori Takahashi
- Department of Medicine, Jacobi Medical Center, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Saul A Rios
- Division of Cardiology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Azeem Latib
- Division of Cardiology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Joo Myung Lee
- Division of Cardiology, Department of Internal Medicine, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - William F Fearon
- Division of Cardiovascular Medicine, Stanford University Medical Center and Stanford Cardiovascular Institute, Stanford, California, USA
| | - Yuhei Kobayashi
- Division of Cardiology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York, USA
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