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Read GJM, McLean S, Thompson J, Stanton NA, Baber C, Carden T, Salmon PM. Managing the risks associated with technological disruption in the road transport system: a control structure modelling approach. Ergonomics 2024; 67:498-514. [PMID: 37381733 DOI: 10.1080/00140139.2023.2226850] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 06/11/2023] [Indexed: 06/30/2023]
Abstract
Road transport is experiencing disruptive change from new first-of-a-kind technologies. While such technologies offer safety and operational benefits, they also pose new risks. It is critical to proactively identify risks during the design, development and testing of new technologies. The Systems Theoretic Accident Model and Processes (STAMP) method analyses the dynamic structure in place to manage safety risks. This study applied STAMP to develop a control structure model for emerging technologies in the Australian road transport system and identified control gaps. The control structure shows the actors responsible for managing risks associated with first-of-a-kind technologies and the existing control and feedback mechanisms. Gaps identified related to controls (e.g. legislation) and feedback mechanisms (e.g. monitoring for behavioural adaptation). The study provides an example of how STAMP can be used to identify control structure gaps requiring attention to support the safe introduction of new technologies.
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Affiliation(s)
- G J M Read
- Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Maroochydore, Australia
- School of Health, University of the Sunshine Coast, Maroochydore, Australia
| | - S McLean
- Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Maroochydore, Australia
| | - J Thompson
- Transport, Health and Urban Design Research Hub, University of Melbourne, Melbourne, Australia
- University Department of Rural Health, School of Medicine, University of Melbourne, Melbourne, Australia
| | - N A Stanton
- Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Maroochydore, Australia
- Transportation Research Group, University of Southampton, Southampton, UK
| | - C Baber
- School of Computer Science, University of Birmingham, Birmingham, UK
| | - T Carden
- Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Maroochydore, Australia
| | - P M Salmon
- Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Maroochydore, Australia
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Vincent F, Thompson J, Gray L, Bradberry S, Sandilands E, Thanacoody R, Tuthill D. Medication errors involving intravenous paracetamol in children: experience from enquiries to the National Poisons Information Service. Arch Dis Child 2024:archdischild-2023-326460. [PMID: 38233098 DOI: 10.1136/archdischild-2023-326460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 12/30/2023] [Indexed: 01/19/2024]
Abstract
INTRODUCTION Children are at higher risk of medication errors due to the complexity of drug prescribing and administration in this patient group. Intravenous (IV) paracetamol overdose differs from overdose by ingestion as there is no enteral absorptive buffering. We provide the first national UK data focusing on paediatric IV paracetamol poisoning. METHODS All telephone enquiries to the National Poisons Information Service between 2008 and 2021 regarding children less than 18 years old in the UK concerning IV paracetamol overdose were extracted from the UK Poisons Information Database (UKPID). Data were analysed using descriptive statistics. RESULTS Enquiries were made concerning 266 children, mostly involving children under the age of 1 year (n=145; 54.5%). Acute and staggered overdoses were the most frequent types of exposure. Common error themes included 10-fold overdose in 45 cases (16.9%) and inadvertent concomitant oral and IV dosing in 64 cases (24.1%). A high proportion of cases were asymptomatic (87.1%), with many calls regarding overdoses below the treatable dose of 60 mg/kg (41.4%). Treatment with the antidote acetylcysteine was advised in 113 cases (42.5%). CONCLUSIONS Inadvertent IV paracetamol overdose appears to occur more frequently in young children. A significant proportion were calculation errors which were often 10-fold errors. While these errors have the potential for causing serious harm, thankfully most cases were asymptomatic. Errors with IV paracetamol might be reduced by electronic prescribing support systems, better communication regarding administration and consideration of whether other routes are more appropriate.
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Affiliation(s)
| | | | | | | | | | | | - David Tuthill
- Paediatrics, Children's Hospital for Wales, Cardiff, UK
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Ochuba A, Murdock CJ, Xu AL, Snow M, Schmerler J, Leland CR, McDaniel C, Thompson J, Aiyer AA. Open Reduction Internal Fixation vs Primary Arthrodesis for Lisfranc Fracture-Dislocations: A Cost Analysis. Foot Ankle Orthop 2024; 9:24730114231224727. [PMID: 38298264 PMCID: PMC10829492 DOI: 10.1177/24730114231224727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2024] Open
Abstract
Background Lisfranc fracture-dislocation is an uncommon but serious injury that currently lacks universal consensus on optimal operative treatment. Two common fixation methods are open reduction and internal fixation (ORIF) and primary arthrodesis (PA). The objective of this study is to analyze the cost difference between ORIF and PA of Lisfranc injuries, along with the contribution of medical services to overall costs. Methods This was a retrospective cost analysis of the MarketScan database from 2010 to 2020. MarketScan is an insurance and commercial claims database that integrates deidentified patient information. It captures person-specific clinical utilization, expenditures, and enrollment across inpatient and outpatient services. Patients undergoing primary ORIF (CPT code 28615) vs PA (28730 and 28740) for Lisfranc fracture-dislocation were identified. The primary independent variable was ORIF vs PA of Lisfranc injury. Total costs due to operative management was the primary objective. The utilization of and costs contributed by medical services was a secondary outcome. Results From 2010 to 2020, a total of 7268 patients underwent operative management of Lisfranc injuries, with 5689 (78.3%) ORIF and 1579 (21.7%) PA. PA was independently associated with increased net and total payment and coinsurance, clinic visits, and imaging, and patients attended significantly more PT sessions. Conclusion Using this large database that does not characterize severity or extent of injury, we found that treatment of Lisfranc fracture-dislocation with ORIF was associated with substantially lower initial episode of treatment costs compared with PA. Specific excessive cost drivers for PA were clinic visits, PT sessions, and imaging. Level of Evidence Level III, retrospective cohort study.
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Affiliation(s)
- Arinze Ochuba
- Orthopaedic Surgery, The Johns Hopkins Hospital, Baltimore, MD, USA
| | | | - Amy L. Xu
- Orthopaedic Surgery, The Johns Hopkins Hospital, Baltimore, MD, USA
| | - Morgan Snow
- Orthopaedic Surgery, The Johns Hopkins Hospital, Baltimore, MD, USA
| | | | - Christopher R. Leland
- Massachusetts General Hospital/Brigham and Women’s Hospital/Harvard Medical School, Boston, MA, USA
| | - Claire McDaniel
- Orthopaedic Surgery, The Johns Hopkins Hospital, Baltimore, MD, USA
| | - John Thompson
- Orthopaedic Surgery, The Johns Hopkins Hospital, Baltimore, MD, USA
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England A, Thompson J, Dorey S, Al Islam S, Long M, Maiorino C, McEntee MF. Corrigendum to "A comparison of perceived image quality between computer display monitors and augmented reality smart glasses" [Radiography 29 (3) (May 2023) 641-646]. Radiography (Lond) 2024; 30:1. [PMID: 37586969 DOI: 10.1016/j.radi.2023.08.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/18/2023]
Affiliation(s)
- A England
- Discipline of Medical Imaging & Radiation Therapy, University College Cork, Cork, Ireland.
| | - J Thompson
- University Hospitals of Morecambe Bay NHS Foundation Trust, Barrow-in-Furness, UK
| | - S Dorey
- Tameside and Glossop Integrated Care NHS Foundation Trust, Tameside, UK
| | - S Al Islam
- East Lancashire Hospitals NHS Trust, Blackburn, UK
| | - M Long
- Discipline of Medical Imaging & Radiation Therapy, University College Cork, Cork, Ireland
| | - C Maiorino
- Discipline of Medical Imaging & Radiation Therapy, University College Cork, Cork, Ireland
| | - M F McEntee
- Discipline of Medical Imaging & Radiation Therapy, University College Cork, Cork, Ireland
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Wang C, Thompson J, Lee B. Data Formulator: AI-Powered Concept-Driven Visualization Authoring. IEEE Trans Vis Comput Graph 2024; 30:1128-1138. [PMID: 37871079 DOI: 10.1109/tvcg.2023.3326585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
With most modern visualization tools, authors need to transform their data into tidy formats to create visualizations they want. Because this requires experience with programming or separate data processing tools, data transformation remains a barrier in visualization authoring. To address this challenge, we present a new visualization paradigm, concept binding, that separates high-level visualization intents and low-level data transformation steps, leveraging an AI agent. We realize this paradigm in Data Formulator, an interactive visualization authoring tool. With Data Formulator, authors first define data concepts they plan to visualize using natural languages or examples, and then bind them to visual channels. Data Formulator then dispatches its AI-agent to automatically transform the input data to surface these concepts and generate desired visualizations. When presenting the results (transformed table and output visualizations) from the AI agent, Data Formulator provides feedback to help authors inspect and understand them. A user study with 10 participants shows that participants could learn and use Data Formulator to create visualizations that involve challenging data transformations, and presents interesting future research directions.
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McLean S, King BJ, Thompson J, Carden T, Stanton NA, Baber C, Read GJM, Salmon PM. Forecasting emergent risks in advanced AI systems: an analysis of a future road transport management system. Ergonomics 2023; 66:1750-1767. [PMID: 38009364 DOI: 10.1080/00140139.2023.2286907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 11/19/2023] [Indexed: 11/28/2023]
Abstract
Artificial Intelligence (AI) is being increasingly implemented within road transport systems worldwide. Next generation of AI, Artificial General Intelligence (AGI) is imminent, and is anticipated to be more powerful than current AI. AGI systems will have a broad range of abilities and be able to perform multiple cognitive tasks akin to humans that will likely produce many expected benefits, but also potential risks. This study applied the EAST Broken Links approach to forecast the functioning of an AGI system tasked with managing a road transport system and identify potential risks. In total, 363 risks were identified that could have adverse impacts on the stated goals of safety, efficiency, environmental sustainability, and economic performance of the road system. Further, risks beyond the stated goals were identified; removal from human control, mismanaging public relations, and self-preservation. A diverse set of systemic controls will be required when designing, implementing, and operating future advanced technologies.Practitioner summary: This study demonstrated the utility of HFE methods for formally considering risks associated with the design, implementation, and operation of future technologies. This study has implications for AGI research, design, and development to ensure safe and ethical AGI implementation.
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Affiliation(s)
- S McLean
- Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Sippy Downs, Australia
| | - B J King
- Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Sippy Downs, Australia
| | - J Thompson
- Transport, Health and Urban Design (THUD) Research Lab, Melbourne School of Design, The University of Melbourne, Melbourne, Australia
| | - T Carden
- Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Sippy Downs, Australia
| | - N A Stanton
- Transportation Research Group, University of Southampton, Southampton, UK
| | - C Baber
- School of Computer Science, University of Birmingham, Birmingham, UK
| | - G J M Read
- Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Sippy Downs, Australia
- School of Health, University of the Sunshine Coast, Sippy Downs, Australia
| | - P M Salmon
- Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Sippy Downs, Australia
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Clark AR, Fontinha H, Thompson J, Couper S, Jani D, Mirjalili A, Bennet L, Stone P. Maternal Cardiovascular Responses to Position Change in Pregnancy. Biology (Basel) 2023; 12:1268. [PMID: 37759669 PMCID: PMC10525953 DOI: 10.3390/biology12091268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 08/07/2023] [Accepted: 09/19/2023] [Indexed: 09/29/2023]
Abstract
The maternal cardiovascular-circulatory system undergoes profound changes almost from the conception of a pregnancy until the postpartum period to support the maternal adaptions required for pregnancy and lactation. Maintenance of cardiovascular homeostasis requires changes in the cardiovascular autonomic responses. Here, we present a longitudinal study of the maternal cardiovascular autonomic responses to pregnancy and maternal position. Over a normal gestation, in the left lateral position there are significant changes in both time and frequency domain parameters reflecting heart rate variability. We show that cardiovascular autonomic responses to physiological stressors (standing and supine positions in late pregnancy) became significantly different with advancing gestation. In the third trimester, 60% of the subjects had an unstable heart rate response on standing, and these subjects had a significantly reduced sample entropy evident in their heart rate variability data. By 6 weeks, postpartum function returned to near the non-pregnant state, but there were consistent differences in high-frequency power when compared to nulligravid cases. Finally, we review complementary evidence, in particular from magnetic resonance imaging, that provides insights into the maternal and fetal impacts of positioning in pregnancy. This demonstrates a clear relationship between supine position and maternal hemodynamic parameters, which relates to compression of the inferior vena cava (p = 0.05). Together, these studies demonstrate new understanding of the physiology of physiological stressors related to position.
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Affiliation(s)
- Alys R. Clark
- Auckland Bioengineering Institute, University of Auckland, Auckland 1010, New Zealand
| | - Hanna Fontinha
- Department of Obstetrics and Gynaecology, Faculty of Medical and Health Sciences, University of Auckland, Auckland 1023, New Zealand
| | - John Thompson
- Department of Obstetrics and Gynaecology, Faculty of Medical and Health Sciences, University of Auckland, Auckland 1023, New Zealand
| | - Sophie Couper
- Department of Obstetrics and Gynaecology, Faculty of Medical and Health Sciences, University of Auckland, Auckland 1023, New Zealand
| | - Devanshi Jani
- Department of Obstetrics and Gynaecology, Faculty of Medical and Health Sciences, University of Auckland, Auckland 1023, New Zealand
| | - Ali Mirjalili
- Department of Anatomy and Medical Imaging, Faculty of Medical and Health Sciences, University of Auckland, Auckland 1023, New Zealand
| | - Laura Bennet
- Department of Physiology, Faculty of Medical and Health Sciences, University of Auckland, Auckland 1023, New Zealand
| | - Peter Stone
- Department of Obstetrics and Gynaecology, Faculty of Medical and Health Sciences, University of Auckland, Auckland 1023, New Zealand
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Lim N, Leventhal TM, Thomson MJ, Hassan M, Thompson J, Adams A, Chinnakotla S, Humphreville V, Kandaswamy R, Kirchner V, Pruett TL, Schuller L, McCarty M, Lake J. Protocolized screening and detection of occult alcohol use before and after liver transplant: Lessons learned from a quality improvement initiative. Clin Transplant 2023; 37:e15036. [PMID: 37218656 DOI: 10.1111/ctr.15036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 05/09/2023] [Accepted: 05/13/2023] [Indexed: 05/24/2023]
Abstract
INTRODUCTION Detection of alcohol (ETOH) use with biomarkers provides an opportunity to intervene and treat patients with alcohol use disorder before and after liver transplant (LT). We describe our center's experience using urine ethyl glucuronide (EtG) and serum phosphatidylethanol (PEth) in alcohol screening protocols. METHODS Single-center, retrospective review of patients presenting for LT evaluation, patients waitlisted for LT for alcohol-associated liver disease (ALD), and patients who received a LT for ALD over a 12-month period, from October 1, 2019 through September 30, 2020. Patients were followed from waitlisting to LT, or for up to 12 months post-LT. We monitored protocol adherence to screening for ETOH use- defined as completion of all possible tests over the follow-up period- at the initial LT visit, while on the LT waitlist and after LT. RESULTS During the study period, 227 patients were evaluated for LT (median age 57 years, 58% male, 78% white, 54.2% ALD). Thirty-one patients with ALD were placed on the waitlist, and 38 patients underwent LT for ALD during this time period. Protocolized adherence to screening for alcohol use was higher for PEth for all LT evaluation patients (191 [84.1%] vs. 146 [67%] eligible patients, p < .001), in patients with ALD waitlisted for LT (22 [71%] vs. 14 (48%] eligible patients, p = .04) and after LT for ALD, 20 (33 [86.8%] vs. 20 [52.6%] eligible patients, p < .01). Few patients with a positive test in any group completed chemical dependency treatment. CONCLUSIONS When screening for ETOH use in pre- and post-LT patients, protocol adherence is higher using PEth compared to EtG. While protocolized biomarker screening can detect recurrent ETOH use in this population, engagement of patients into chemical dependency treatment remains challenging.
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Affiliation(s)
- N Lim
- Division of Gastroenterology, Hepatology and Nutrition, University of Minnesota, Minneapolis, Minnesota, USA
| | - T M Leventhal
- Division of Gastroenterology, Hepatology and Nutrition, University of Minnesota, Minneapolis, Minnesota, USA
| | - M J Thomson
- Division of Gastroenterology, Hepatology and Nutrition, University of Minnesota, Minneapolis, Minnesota, USA
| | - M Hassan
- Division of Gastroenterology, Hepatology and Nutrition, University of Minnesota, Minneapolis, Minnesota, USA
| | - J Thompson
- Division of Gastroenterology, Hepatology and Nutrition, University of Minnesota, Minneapolis, Minnesota, USA
| | - A Adams
- Division of Transplant Surgery, University of Minnesota, Minneapolis, Minnesota, USA
| | - S Chinnakotla
- Division of Transplant Surgery, University of Minnesota, Minneapolis, Minnesota, USA
| | - V Humphreville
- Division of Transplant Surgery, University of Minnesota, Minneapolis, Minnesota, USA
| | - R Kandaswamy
- Division of Transplant Surgery, University of Minnesota, Minneapolis, Minnesota, USA
| | - V Kirchner
- Division of Abdominal Transplantation, Stanford University, Palo Alto, California, USA
| | - T L Pruett
- Division of Transplant Surgery, University of Minnesota, Minneapolis, Minnesota, USA
| | - L Schuller
- University of Minnesota Physicians, Minneapolis, Minnesota, USA
| | - M McCarty
- Complex Care Analytics, Fairview Health Services, Minneapolis, Minnesota, USA
| | - J Lake
- Division of Gastroenterology, Hepatology and Nutrition, University of Minnesota, Minneapolis, Minnesota, USA
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Alvarado Sandino CO, Barnes AP, Sepúlveda I, Garratt MPD, Thompson J, Escobar-Tello MP. Examining factors for the adoption of silvopastoral agroforestry in the Colombian Amazon. Sci Rep 2023; 13:12252. [PMID: 37507434 PMCID: PMC10382530 DOI: 10.1038/s41598-023-39038-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 07/19/2023] [Indexed: 07/30/2023] Open
Abstract
Current land use systems in the Amazon largely consist of extensive conventional productivist livestock operations that drive deforestation. Silvopastoral systems (SPS) support a transition to low carbon production if they intensify in sympathy with the needs of biophysical and socio-economic contexts. SPS have been promoted for decades as an alternative livestock production system but widespread uptake has yet to be seen. We provide a schema of associating factors for adoption of SPS based on past literature in tropical agriculture and apply this to a bespoke survey of 172 farms in the Caquetá region of the Colombian Amazon. We find a number of factors which do not apply to this region and argue for a context specific approach. The impact of managing increased market access and opportunities for SPS producers are crucial to avoiding additional deforestation. Further understanding of the underlying antecedents of common factors, such as perceptions of silvopastoral systems, would reduce the risk of perverse policy outcomes.
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Affiliation(s)
- C O Alvarado Sandino
- Rural Economy, Environment and Society, SRUC, The Kings Buildings, West Mains Road, Edinburgh, UK
- Faculty of Geosciences, University of Edinburgh, West Mains Road, Edinburgh, UK
| | - A P Barnes
- Rural Economy, Environment and Society, SRUC, The Kings Buildings, West Mains Road, Edinburgh, UK.
| | - I Sepúlveda
- Rural Economy, Environment and Society, SRUC, The Kings Buildings, West Mains Road, Edinburgh, UK
| | - M P D Garratt
- Sustainable Land Management, School of Agriculture, Policy and Development, University of Reading, Reading, UK
| | - J Thompson
- UK Centre for Ecology and Hydrology, Bush Estate, Penicuik, UK
| | - M P Escobar-Tello
- Bristol Veterinary School, University of Bristol, Langford House, Bristol, UK
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Cao W, Li L, Mathur P, Thompson J, Milks MW. A mobile health application for patients eligible for statin therapy: app development and qualitative feedback on design and usability. BMC Med Inform Decis Mak 2023; 23:128. [PMID: 37468892 PMCID: PMC10357764 DOI: 10.1186/s12911-023-02221-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 06/28/2023] [Indexed: 07/21/2023] Open
Abstract
BACKGROUND Cardiovascular disease is the leading cause of death in the United States (US). Despite the well-recognized efficacy of statins, statin discontinuation rates remain high. Statin intolerance is a major cause of statin discontinuation. To accurately diagnose statin intolerance, healthcare professionals must distinguish between statin-associated and non-statin-associated muscle symptoms, because many muscle symptoms can be unrelated to statin therapy. Patients' feedback on muscle-related symptoms would help providers make decisions about statin treatment. Given the potential benefits and feasibility of existing apps for cardiovascular disease (CVD) management and the unmet need for an app specifically addressing statin intolerance management, the objectives of the study were 1) to describe the developmental process of a novel app designed for patients who are eligible for statin therapy to lower the risk of CVD; 2) to explore healthcare providers' feedback of the app; and 3) to explore patients' app usage experience. METHODS The app was developed by an interdisciplinary team. Healthcare provider participants and patient participants were recruited in the study. Providers were interviewed to provide their feedback about the app based on screenshots of the app. Patients were interviewed after a 30 days of app usage. RESULTS The basic features of the app included symptom logging, vitals tracking, patient education, and push notifications. Overall, both parties provided positive feedback about the app. Areas to be improved mentioned by both parties included: the pain question asked in symptom tracking and the patient education section. Both parties agreed that it was essential to add the trend report of the logged symptoms. CONCLUSIONS The results indicated that providers were willing to use patient-reported data for disease management and perceived that the app had the potential to facilitate doctor-patient communication. Results also indicated that user engagement is the key to the success of app efficacy. To promote app engagement, app features should be tailored to individual patient's needs and goals. In the future, after it is upgraded, we plan to test the app usability and feasibility among a more diverse sample.
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Affiliation(s)
- Weidan Cao
- Department of Biomedical Informatics, The Ohio State University, Columbus, OH, 43210, USA.
| | - Lang Li
- Department of Biomedical Informatics, The Ohio State University, Columbus, OH, 43210, USA
| | - Puneet Mathur
- Department of Research Information Technology, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - John Thompson
- Department of Research Information Technology, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - M Wesley Milks
- Division of Cardiovascular Medicine, The Ohio State University College of Medicine, Columbus, OH, USA
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Davies RL, Thompson J, McGuire R, Smith JE, Webster S, Woolley T. Haemostatic resuscitation in practice: a descriptive analysis of blood products administered during Operation HERRICK, Afghanistan. BMJ Mil Health 2023:e002408. [PMID: 37400127 DOI: 10.1136/military-2023-002408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Accepted: 06/10/2023] [Indexed: 07/05/2023]
Abstract
INTRODUCTION Life-threatening haemorrhage is the leading cause of potentially survivable injury in battlefield casualties. During Operation HERRICK (Afghanistan), mortality rates improved year on year due to a number of advances in trauma care, including haemostatic resuscitation. Blood transfusion practice has not previously been reported in detail during this period. METHODS A retrospective analysis of blood transfusion at the UK role 3 medical treatment facility (MTF) at Camp Bastion between March 2006 and September 2014 was performed. Data were extracted from two sources: the UK Joint Theatre Trauma Registry (JTTR) and the newly established Deployed Blood Transfusion Database (DBTD). RESULTS 3840 casualties were transfused 72 138 units of blood and blood products. 2709 adult casualties (71%) were fully linked with JTTR data and were transfused a total of 59 842 units. Casualties received between 1 unit and 264 units of blood product with a median of 13 units per patient. Casualties wounded by explosion required almost twice the volume of blood product transfusion as those wounded by small arms fire or in a motor vehicle collision (18 units, 9 units, and 10 units, respectively). More than half of blood products were transfused within the first 2 hours following arrival at the MTF. There was a trend towards balanced resuscitation with more equal ratios of blood and blood products being used over time. CONCLUSION This study has defined the epidemiology of blood transfusion practice during Operation HERRICK. The DBTD is the largest combined trauma database of its kind. It will ensure that lessons learnt during this period are defined and not forgotten; it should also allow further research questions to be answered in this important area of resuscitation practice.
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Affiliation(s)
- Rhys L Davies
- Anaesthetic Department, University Hospital Southampton NHS Foundation Trust, Southampton, UK
- Academic Department of Military Anaesthesia and Critical Care, Royal Centre for Defence Medicine, Birmingham, UK
| | - J Thompson
- Academic Department of Military Anaesthesia and Critical Care, Royal Centre for Defence Medicine, Birmingham, UK
| | | | - J E Smith
- Academic Department of Military Emergency Medicine, Royal Centre for Defence Medicine, Birmingham, UK
- Emergency Department, University Hospitals Plymouth NHS Trust, Plymouth, UK
| | - S Webster
- Academic Department of Military Emergency Medicine, Royal Centre for Defence Medicine, Birmingham, UK
| | - T Woolley
- Academic Department of Military Anaesthesia and Critical Care, Royal Centre for Defence Medicine, Birmingham, UK
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Thompson J, Bujalka H, McKeever S, Lipscomb A, Moore S, Hill N, Kinney S, Cham KM, Martin J, Bowers P, Gerdtz M. Educational strategies in the health professions to mitigate cognitive and implicit bias impact on decision making: a scoping review. BMC Med Educ 2023; 23:455. [PMID: 37340395 DOI: 10.1186/s12909-023-04371-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Accepted: 05/17/2023] [Indexed: 06/22/2023]
Abstract
BACKGROUND Cognitive and implicit biases negatively impact clinicians' decision-making capacity and can have devastating consequences for safe, effective, and equitable healthcare provision. Internationally, health care clinicians play a critical role in identifying and overcoming these biases. To be workforce ready, it is important that educators proactively prepare all pre-registration healthcare students for real world practice. However, it is unknown how and to what extent health professional educators incorporate bias training into curricula. To address this gap, this scoping review aims to explore what approaches to teaching cognitive and implicit bias, for entry to practice students, have been studied, and what are the evidence gaps that remain. METHODS This scoping review was guided by the Joanna Briggs Institute (JBI) methodology. Databases were searched in May 2022 and included CINAHL, Cochrane, JBI, Medline, ERIC, Embase, and PsycINFO. The Population, Concept and Context framework was used to guide keyword and index terms used for search criteria and data extraction by two independent reviewers. Quantitative and qualitative studies published in English exploring pedagogical approaches and/or educational techniques, strategies, teaching tools to reduce the influence of bias in health clinicians' decision making were sought to be included in this review. Results are presented numerically and thematically in a table accompanied by a narrative summary. RESULTS Of the 732 articles identified, 13 met the aim of this study. Most publications originated from the United States (n=9). Educational practice in medicine accounted for most studies (n=8), followed by nursing and midwifery (n=2). A guiding philosophy or conceptual framework for content development was not indicated in most papers. Educational content was mainly provided via face-to-face (lecture/tutorial) delivery (n=10). Reflection was the most common strategy used for assessment of learning (n=6). Cognitive biases were mainly taught in a single session (n=5); implicit biases were taught via a mix of single (n=4) and multiple sessions (n=4). CONCLUSIONS A range of pedagogical strategies were employed; most commonly, these were face-to-face, class-based activities such as lectures and tutorials. Assessments of student learning were primarily based on tests and personal reflection. There was limited use of real-world settings to educate students about or build skills in biases and their mitigation. There may be a valuable opportunity in exploring approaches to building these skills in the real-world settings that will be the workplaces of our future healthcare workers.
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Affiliation(s)
- John Thompson
- Department of Nursing, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Level 6, Alan Gilbert Building, 161 Barry Street, Victoria, 3010, Australia.
| | - Helena Bujalka
- Department of Nursing, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Level 6, Alan Gilbert Building, 161 Barry Street, Victoria, 3010, Australia
| | - Stephen McKeever
- Department of Nursing, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Level 6, Alan Gilbert Building, 161 Barry Street, Victoria, 3010, Australia
- Royal Children's Hospital, Parkville, Australia
| | - Adrienne Lipscomb
- Department of Nursing, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Level 6, Alan Gilbert Building, 161 Barry Street, Victoria, 3010, Australia
| | - Sonya Moore
- Department of Physiotherapy, Melbourne School of Health Sciences, University of Melbourne, Melbourne, Australia
| | - Nicole Hill
- Department of Social Work, Melbourne School of Health Sciences, University of Melbourne, Melbourne, Australia
| | - Sharon Kinney
- Department of Nursing, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Level 6, Alan Gilbert Building, 161 Barry Street, Victoria, 3010, Australia
- Royal Children's Hospital, Parkville, Australia
| | - Kwang Meng Cham
- Department of Optometry and Vision Sciences, Melbourne School of Health Sciences, University of Melbourne, Melbourne, Australia
| | - Joanne Martin
- Department of Nursing, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Level 6, Alan Gilbert Building, 161 Barry Street, Victoria, 3010, Australia
| | - Patrick Bowers
- Department of Audiology and Speech Pathology, School of Health Sciences, University of Melbourne, Melbourne, Australia
| | - Marie Gerdtz
- Department of Nursing, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Level 6, Alan Gilbert Building, 161 Barry Street, Victoria, 3010, Australia
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England A, Thompson J, Dorey S, Al-Islam S, Long M, Maiorino C, McEntee MF. A comparison of perceived image quality between computer display monitors and augmented reality smart glasses. Radiography (Lond) 2023; 29:641-646. [PMID: 37130492 DOI: 10.1016/j.radi.2023.04.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 03/28/2023] [Accepted: 04/14/2023] [Indexed: 05/04/2023]
Abstract
INTRODUCTION Augmented-reality (AR) smart glasses provide an alternative to standard computer display monitors (CDM). AR smart glasses may provide an opportunity to improve visualisation during fluoroscopy and interventional radiology (IR) procedures when there can be difficulty in viewing intra-procedural images on a CDM. The aim of this study was to evaluate radiographer perception of image quality (IQ) when comparing CDM and AR smart glasses. METHODS 38 radiographers attending an international congress evaluated ten fluoroscopic-guided surgery and IR images on both a CDM (1920 × 1200 pixels) and a set of Epson Moverio BT-40 AR smart glasses (1920 × 1080 pixels). Participants provided oral responses to pre-defined IQ questions generated by study researchers. Summative IQ scores for each participant/image were compared between CDM and AR smart glasses. RESULTS Of the 38 participants, the mean age was 39 ± 1 years. 23 (60.5%) participants required corrective glasses. In terms of generalisability, participants were from 12 different countries, the majority (n = 9, 23.7%) from the United Kingdom. For eight out of ten images, the AR smart glasses demonstrated a statistically significant increase in perceived IQ (median [IQR] 2.0 [-1.0 to 7.0] points) when compared to the CDM. CONCLUSION AR smart glasses appear to show improvements in perceived IQ when compared to a CDM. AR smart glasses could provide an option for improving the experiences of radiographers involved in image-guided procedures and should be subject to further clinical evaluations. IMPLICATIONS FOR PRACTICE Opportunities exist to improve perceived IQ for radiographers when reviewing fluoroscopy and IR images. AR smart glasses should be further evaluated as a potential opportunity to improve practice when visual attention is split between positioning equipment and image review.
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Affiliation(s)
- A England
- Discipline of Medical Imaging & Radiation Therapy, University College Cork, Cork, Ireland.
| | - J Thompson
- University Hospitals of Morecambe Bay NHS Foundation Trust, Barrow-in-Furness, UK
| | - S Dorey
- Tameside and Glossop Integrated Care NHS Foundation Trust, Tameside, UK
| | - S Al-Islam
- East Lancashire Hospitals NHS Trust, Blackburn, UK
| | - M Long
- Discipline of Medical Imaging & Radiation Therapy, University College Cork, Cork, Ireland
| | - C Maiorino
- Discipline of Medical Imaging & Radiation Therapy, University College Cork, Cork, Ireland
| | - M F McEntee
- Discipline of Medical Imaging & Radiation Therapy, University College Cork, Cork, Ireland
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Abdelsalam A, Corsaletti G, Haniff R, Sheinberg DL, Ramsay I, Ehiemua U, Starke RM, Thompson J. 305 Enhancing Endothelialization of Flow Diverting Stents: An In Vitro Study. Neurosurgery 2023. [DOI: 10.1227/neu.0000000000002375_305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023] Open
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Richards T, Miles LF, Clevenger B, Keegan A, Abeysiri S, Rao Baikady R, Besser MW, Browne JP, Klein AA, Macdougall IC, Murphy GJ, Anker SD, Dahly D, Besser M, Browne J, Clevenger B, Kegan A, Klein A, Miles L, MacDougall I, Baikady RR, Dahly D, Bradbury A, Richards T, Burley T, Van Loen S, Anker S, Klein A, MacDougall I, Murphy G, Besser M, Unsworth I, Clayton T, Collier T, Potter K, Abeysiri S, Evans R, Knight R, Swinson R, Van Dyck L, Keidan J, Williamson L, Crook A, Pepper J, Dobson J, Newsome S, Godec T, Dodd M, Richards T, Van Dyck L, Evans R, Abeysiri S, Clevenger B, Butcher A, Swinson R, Collier T, Potter K, Anker S, Kelly J, Morris S, Browne J, Keidan J, Grocott M, Chau M, Knight R, Collier T, Baikady RR, Black E, Lawrence H, Kouthra M, Horner K, Jhanji S, Todman E, Keon‐Cohen Z, Rooms M, Tomlinson J, Bailes I, Walker S, Pirie K, Gerstman M, Kasivisvanathan R, Uren S, Magee D, Eeles A, Anker R, McCanny J, O'Mahony M, Reynolds T, Batley S, Hegarty A, Trundle S, Mazzola F, Tatham K, Balint A, Morrison B, Evans M, Pang CL, Smith L, Wilson C, Sjorin V, Khatri P, Wilson M, Parkinson D, Crosbie J, Dawas K, Smyth D, Bercades G, Ryu J, Reyes A, Martir G, Gallego L, Macklin A, Rocha M, Tam DK, Brealey DD, Dhesi J, Morrison C, Hardwick J, Partridge J, Braude P, Rogerson A, Jahangir N, Thomson C, Biswell L, Cross J, Pritchard F, Mohammed A, Wallace D, Galat MG, Okello J, Symes R, Leon J, Gibbs C, Sanghera S, Dennis A, Kibutu F, Fofie J, Bird S, Alli A, Jackson Y, Albuheissi S, Brain C, Shiridzinomwa C, Ralph C, Wroath B, Hammonds F, Adams B, Faulds J, Staddon S, Hughes T, Saha S, Finney C, Harris C, Mellis C, Johnson L, Riozzi P, Yarnold A, Buchanan F, Hopkins P, Greig L, Noble H, Edwards M, Grocott M, Plumb J, Harvie D, Dushianthan A, Wakatsuki M, Leggett S, Salmon K, Bolger C, Burnish R, Otto J, Rayat G, Golder K, Bartlett P, Bali S, Seaward L, Wadams B, Tyrell B, Collins H, Tantony N, Geale R, Wilson A, Ball D, Lindsey I, Barker D, Thyseen M, Chiam P, Hannaway C, Colling K, Messer C, Verma N, Nasseri M, Poonawala G, Sellars A, Mainali P, Hammond T, Hughes A, O'Hara D, McNeela F, Shillito L, Kotze A, Moriarty C, Wilson J, Davies S, Yates D, Carter J, Redman J, Ma S, Howard K, Redfearn H, Wilcock D, Lowe J, Alexander T, Jose J, Hornzee G, Akbar F, Rey S, Patel A, Coulson S, Saini R, Santipillai J, McCretton T, McCanny J, Chima K, Collins K, Pathmanathan B, Chattersingh A, McLeavy L, Al‐Saadi Z, Patel M, Skampardoni S, Chinnadurai R, Thomas V, Keen A, Pagett K, Keatley C, Howard J, Greenhalgh M, Jenkins S, Gidda R, Watts A, Breaton C, Parker J, Mallett S, James S, Penny L, Chan K, Reeves T, Catterall M, Williams S, Birch J, Hammerton K, Williamson N, Thomas A, Evans M, Mercer L, Horsfield G, Hughes C, Cupitt J, Stoddard E, McNamara H, Birt C, Hardy A, Dennis R, Butcher D, O'Sullivan S, Pope A, Elhanash S, Preston S, Officer H, Stoker A, Moss S, Walker A, Gipson A, Melville J, Bradley‐Potts J, McCormac R, Benson V, Melia K, Fielding J, Guest W, Ford S, Murdoch H, Beames S, Townshend P, Collins K, Glass J, Cartwright B, Altemimi B, Berresford L, Jones C, Kelliher L, de Silva S, Blightman K, Pendry K, Pinto L, Allard S, Taylor L, Chishti A, Scott J, O'Hare D, Lewis M, Hussain Z, Hallett K, Dermody S, Corbett C, Morby L, Hough M, Williams S, Williams P, Horton S, Ashcroft P, Homer A, Lang A, Dawson H, Harrison E, Thompson J, Hariharan V, Goss V, Ravi R, Butt G, Vertue M, Acheson A, Ng O, Bush D, Dickson E, Ward A, Morris S, Taylor A, Casey R, Wilson L, Vimalachandran D, Faulkner M, Jeffrey H, Gabrielle C, Martin S, Bracewell A, Ritzema J, Sproates D, Alexander‐Sefre F, Kubitzek C, Humphreys S, Curtis J, Oats P, Swann S, Holden A, Adam C, Flintoff L, Paoloni C, Bobruk K. The association between iron deficiency and outcomes: a secondary analysis of the intravenous iron therapy to treat iron deficiency anaemia in patients undergoing major abdominal surgery (PREVENTT) trial. Anaesthesia 2023; 78:320-329. [PMID: 36477695 PMCID: PMC10107684 DOI: 10.1111/anae.15926] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/10/2022] [Indexed: 12/13/2022]
Abstract
In the intravenous iron therapy to treat iron deficiency anaemia in patients undergoing major abdominal surgery (PREVENTT) trial, the use of intravenous iron did not reduce the need for blood transfusion or reduce patient complications or length of hospital stay. As part of the trial protocol, serum was collected at randomisation and on the day of surgery. These samples were analysed in a central laboratory for markers of iron deficiency. We performed a secondary analysis to explore the potential interactions between pre-operative markers of iron deficiency and intervention status on the trial outcome measures. Absolute iron deficiency was defined as ferritin <30 μg.l-1 ; functional iron deficiency as ferritin 30-100 μg.l-1 or transferrin saturation < 20%; and the remainder as non-iron deficient. Interactions were estimated using generalised linear models that included different subgroup indicators of baseline iron status. Co-primary endpoints were blood transfusion or death and number of blood transfusions, from randomisation to 30 days postoperatively. Secondary endpoints included peri-operative change in haemoglobin, postoperative complications and length of hospital stay. Most patients had iron deficiency (369/452 [82%]) at randomisation; one-third had absolute iron deficiency (144/452 [32%]) and half had functional iron deficiency (225/452 [50%]). The change in pre-operative haemoglobin with intravenous iron compared with placebo was greatest in patients with absolute iron deficiency, mean difference 8.9 g.l-1 , 95%CI 5.3-12.5; moderate in functional iron deficiency, mean difference 2.8 g.l-1 , 95%CI -0.1 to 5.7; and with little change seen in those patients who were non-iron deficient. Subgroup analyses did not suggest that intravenous iron compared with placebo reduced the likelihood of death or blood transfusion at 30 days differentially across subgroups according to baseline ferritin (p = 0.33 for interaction), transferrin saturation (p = 0.13) or in combination (p = 0.45), or for the number of blood transfusions (p = 0.06, 0.29, and 0.39, respectively). There was no beneficial effect of the use of intravenous iron compared with placebo, regardless of the metrics to diagnose iron deficiency, on postoperative complications or length of hospital stay.
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Affiliation(s)
- T Richards
- Division of Surgery, University of Western Australia, Perkins South Building, Fiona Stanley Hospital, Murdoch, Perth, WA, Australia.,Institute of Clinical Trials and Methodology and Division of Surgery, University College London, UK
| | - L F Miles
- Department of Critical Care, Melbourne Medical School, The University of Melbourne, VIC, Australia.,Department of Anaesthesia, Austin Health, Melbourne, VIC, Australia
| | - B Clevenger
- Department of Anaesthesia, Royal National Orthopaedic Hospital, Stanmore, UK
| | - A Keegan
- Department of Haematology, PathWest Laboratory Medicine, King Edward Memorial Hospital, Subiaco, WA, Australia
| | - S Abeysiri
- Division of Surgery, University of Western Australia, Perkins South Building, Fiona Stanley Hospital, Murdoch, Perth, WA, Australia
| | - R Rao Baikady
- Department of Anaesthesia, The Royal Marsden NHS Foundation Trust, London, UK
| | - M W Besser
- Department of Haematology, Addenbrooke's Hospital, Cambridge, UK
| | - J P Browne
- School of Public Health, University College Cork, Ireland
| | - A A Klein
- Department of Anaesthesia and Intensive Care, Royal Papworth Hospital, Cambridge, UK
| | - I C Macdougall
- Department of Renal Medicine, King's College Hospital, London, UK
| | - G J Murphy
- Department of Cardiovascular Sciences, University of Leicester, UK
| | - S D Anker
- Department of Cardiology, Berlin Institute of Health Centre for Regenerative Therapies; German Centre for Cardiovascular Research partner site Berlin; Charité Universitätsmedizin Berlin, Germany
| | - D Dahly
- School of Public Health, University College Cork, Ireland.,Health Research Board Clinical Research Facility, University College Cork, Ireland
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Casciato DJ, Stone R, Thompson J, Venero M, Chiu M, Blum J, Barron I, Hyer C. Radiodensity Analysis of Lateral Column Superconstruct Fixation Sites in Midfoot Charcot Neuroarthropathy. J Foot Ankle Surg 2023; 62:377-381. [PMID: 36335049 DOI: 10.1053/j.jfas.2022.09.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 09/26/2022] [Accepted: 09/28/2022] [Indexed: 12/14/2022]
Abstract
Lateral column deterioration and subsequent loss of function poses a challenge for limb preservation in patients with Charcot neuroarthropathy (CN). Application of "superconstructs" provides stability and clinical improvement to an often-ulcerated lateral foot. This study examines radiodensity in Hounsfield units (HU) to compare bone quality of lateral column fixation targets using computed tomography (CT) scans between patients with and without midfoot CN. A retrospective chart review identified control (nondiabetic, non-CN; n = 29) and midfoot CN (n = 21) groups. Patient demographics and medical history were collected. Two reviewers measured the mean HU of circular regions of interest centered on the fourth and fifth metatarsal heads as well as the anterior, middle, and posterior thirds of the calcaneus. Radiodensity was compared between groups, among calcaneal locations, Eichenholtz stages and Brodsky types. A p value ≤.05 was considered statistically significant. Age and body mass index were not significantly different between groups. The CN group exhibited greater HU than the control group at the metatarsal head and calcaneus (p < .001). The anterior calcaneus exhibited greater HU than the posterior calcaneus in the CN group (p = .02). The difference in HU was not statistically significant between Stages 0-1 and Stages 2-3 or midfoot Brodsky Types. Indirect bone density analysis revealed an increased density in CN compared to control patients with no significant difference between midfoot CN stages or types. The anterior calcaneus was the densest rearfoot bone among the CN patients, a result that may have implications in surgical fixation.
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Affiliation(s)
| | - Ryan Stone
- Resident Physician, OhioHealth Grant Medical Center, Columbus, OH
| | - John Thompson
- Fellow, Orthopedic Foot and Ankle Center, Worthington, OH
| | - Marissa Venero
- Resident Physician, Orlando VA Medical Center, Orlando, FL
| | - Michael Chiu
- Resident Physician, Orlando VA Medical Center, Orlando, FL
| | | | - Ian Barron
- Teaching Faculty, OhioHealth Grant Medical Center, Columbus, OH
| | - Christopher Hyer
- Fellowship Co-Director, Orthopedic Foot and Ankle Center, Worthington, OH
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Guerisoli MM, Fergnani DM, Fracassi NG, Thompson J, Pereira JA. Activity patterns of the marsh deer: Effects of proxies of human movement, cattle presence, and moon phases on its behavior. J Zool (1987) 2023. [DOI: 10.1111/jzo.13053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/20/2023]
Affiliation(s)
- M. M. Guerisoli
- División Mastozoología, Museo Argentino de Ciencias Naturales "Bernardino Rivadavia" (MACN‐CONICET) Buenos Aires Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) Buenos Aires Argentina
| | - D. M. Fergnani
- División Mastozoología, Museo Argentino de Ciencias Naturales "Bernardino Rivadavia" (MACN‐CONICET) Buenos Aires Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) Buenos Aires Argentina
| | - N. G. Fracassi
- Instituto Nacional de Tecnología Agropecuaria (INTA) Paraná de las Palmas and Canal Laurentino Comas (2804) Buenos Aires Argentina
| | - J. Thompson
- Guyra Paraguay, Asunción, Paraguay Instituto Saite, Consejo Nacional de Ciencia y Tecnología (CONACYT) Asunción Paraguay
| | - J. A. Pereira
- División Mastozoología, Museo Argentino de Ciencias Naturales "Bernardino Rivadavia" (MACN‐CONICET) Buenos Aires Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) Buenos Aires Argentina
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Pati S, Baid U, Edwards B, Sheller M, Wang SH, Reina GA, Foley P, Gruzdev A, Karkada D, Davatzikos C, Sako C, Ghodasara S, Bilello M, Mohan S, Vollmuth P, Brugnara G, Preetha CJ, Sahm F, Maier-Hein K, Zenk M, Bendszus M, Wick W, Calabrese E, Rudie J, Villanueva-Meyer J, Cha S, Ingalhalikar M, Jadhav M, Pandey U, Saini J, Garrett J, Larson M, Jeraj R, Currie S, Frood R, Fatania K, Huang RY, Chang K, Balaña C, Capellades J, Puig J, Trenkler J, Pichler J, Necker G, Haunschmidt A, Meckel S, Shukla G, Liem S, Alexander GS, Lombardo J, Palmer JD, Flanders AE, Dicker AP, Sair HI, Jones CK, Venkataraman A, Jiang M, So TY, Chen C, Heng PA, Dou Q, Kozubek M, Lux F, Michálek J, Matula P, Keřkovský M, Kopřivová T, Dostál M, Vybíhal V, Vogelbaum MA, Mitchell JR, Farinhas J, Maldjian JA, Yogananda CGB, Pinho MC, Reddy D, Holcomb J, Wagner BC, Ellingson BM, Cloughesy TF, Raymond C, Oughourlian T, Hagiwara A, Wang C, To MS, Bhardwaj S, Chong C, Agzarian M, Falcão AX, Martins SB, Teixeira BCA, Sprenger F, Menotti D, Lucio DR, LaMontagne P, Marcus D, Wiestler B, Kofler F, Ezhov I, Metz M, Jain R, Lee M, Lui YW, McKinley R, Slotboom J, Radojewski P, Meier R, Wiest R, Murcia D, Fu E, Haas R, Thompson J, Ormond DR, Badve C, Sloan AE, Vadmal V, Waite K, Colen RR, Pei L, Ak M, Srinivasan A, Bapuraj JR, Rao A, Wang N, Yoshiaki O, Moritani T, Turk S, Lee J, Prabhudesai S, Morón F, Mandel J, Kamnitsas K, Glocker B, Dixon LVM, Williams M, Zampakis P, Panagiotopoulos V, Tsiganos P, Alexiou S, Haliassos I, Zacharaki EI, Moustakas K, Kalogeropoulou C, Kardamakis DM, Choi YS, Lee SK, Chang JH, Ahn SS, Luo B, Poisson L, Wen N, Tiwari P, Verma R, Bareja R, Yadav I, Chen J, Kumar N, Smits M, van der Voort SR, Alafandi A, Incekara F, Wijnenga MMJ, Kapsas G, Gahrmann R, Schouten JW, Dubbink HJ, Vincent AJPE, van den Bent MJ, French PJ, Klein S, Yuan Y, Sharma S, Tseng TC, Adabi S, Niclou SP, Keunen O, Hau AC, Vallières M, Fortin D, Lepage M, Landman B, Ramadass K, Xu K, Chotai S, Chambless LB, Mistry A, Thompson RC, Gusev Y, Bhuvaneshwar K, Sayah A, Bencheqroun C, Belouali A, Madhavan S, Booth TC, Chelliah A, Modat M, Shuaib H, Dragos C, Abayazeed A, Kolodziej K, Hill M, Abbassy A, Gamal S, Mekhaimar M, Qayati M, Reyes M, Park JE, Yun J, Kim HS, Mahajan A, Muzi M, Benson S, Beets-Tan RGH, Teuwen J, Herrera-Trujillo A, Trujillo M, Escobar W, Abello A, Bernal J, Gómez J, Choi J, Baek S, Kim Y, Ismael H, Allen B, Buatti JM, Kotrotsou A, Li H, Weiss T, Weller M, Bink A, Pouymayou B, Shaykh HF, Saltz J, Prasanna P, Shrestha S, Mani KM, Payne D, Kurc T, Pelaez E, Franco-Maldonado H, Loayza F, Quevedo S, Guevara P, Torche E, Mendoza C, Vera F, Ríos E, López E, Velastin SA, Ogbole G, Soneye M, Oyekunle D, Odafe-Oyibotha O, Osobu B, Shu'aibu M, Dorcas A, Dako F, Simpson AL, Hamghalam M, Peoples JJ, Hu R, Tran A, Cutler D, Moraes FY, Boss MA, Gimpel J, Veettil DK, Schmidt K, Bialecki B, Marella S, Price C, Cimino L, Apgar C, Shah P, Menze B, Barnholtz-Sloan JS, Martin J, Bakas S. Author Correction: Federated learning enables big data for rare cancer boundary detection. Nat Commun 2023; 14:436. [PMID: 36702828 PMCID: PMC9879935 DOI: 10.1038/s41467-023-36188-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Affiliation(s)
- Sarthak Pati
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
| | - Ujjwal Baid
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | | | | | | | | | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Chiharu Sako
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Satyam Ghodasara
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michel Bilello
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Suyash Mohan
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Philipp Vollmuth
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Gianluca Brugnara
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | | | - Felix Sahm
- Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neuropathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Klaus Maier-Hein
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
- Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Maximilian Zenk
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Wolfgang Wick
- Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ), Heidelberg, Germany
- Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany
| | - Evan Calabrese
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Jeffrey Rudie
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Javier Villanueva-Meyer
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Soonmee Cha
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Madhura Ingalhalikar
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Manali Jadhav
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Umang Pandey
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Jitender Saini
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - John Garrett
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Matthew Larson
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Robert Jeraj
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Stuart Currie
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Russell Frood
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Kavi Fatania
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Raymond Y Huang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ken Chang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | | | | | - Josep Puig
- Department of Radiology (IDI), Girona Biomedical Research Institute (IdIBGi), Josep Trueta University Hospital, Girona, Spain
| | - Johannes Trenkler
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Josef Pichler
- Department of Neurooncology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Georg Necker
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Andreas Haunschmidt
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Stephan Meckel
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
- Institute of Diagnostic and Interventional Neuroradiology, RKH Klinikum Ludwigsburg, Ludwigsburg, Germany
| | - Gaurav Shukla
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiation Oncology, Christiana Care Health System, Philadelphia, PA, USA
| | - Spencer Liem
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Gregory S Alexander
- Department of Radiation Oncology, University of Maryland, Baltimore, MD, USA
| | - Joseph Lombardo
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Joshua D Palmer
- Department of Radiation Oncology, The James Cancer Hospital and Solove Research Institute, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Adam E Flanders
- Department of Radiology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Adam P Dicker
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Haris I Sair
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Craig K Jones
- The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Archana Venkataraman
- Department of Electrical and Computer Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Meirui Jiang
- The Chinese University of Hong Kong, Hong Kong, China
| | - Tiffany Y So
- The Chinese University of Hong Kong, Hong Kong, China
| | - Cheng Chen
- The Chinese University of Hong Kong, Hong Kong, China
| | | | - Qi Dou
- The Chinese University of Hong Kong, Hong Kong, China
| | - Michal Kozubek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Filip Lux
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Jan Michálek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Petr Matula
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Miloš Keřkovský
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
| | - Tereza Kopřivová
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
| | - Marek Dostál
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
- Department of Biophysics, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Václav Vybíhal
- Department of Neurosurgery, Faculty of Medicine, Masaryk University, Brno, and University Hospital and Czech Republic, Brno, Czech Republic
| | - Michael A Vogelbaum
- Department of Neuro Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - J Ross Mitchell
- University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Joaquim Farinhas
- Department of Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | | | | | - Marco C Pinho
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Divya Reddy
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - James Holcomb
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | | | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- UCLA Neuro-Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CaA, USA
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CaA, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Talia Oughourlian
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Akifumi Hagiwara
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Chencai Wang
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Minh-Son To
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
- Division of Surgery and Perioperative Medicine, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Sargam Bhardwaj
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
| | - Chee Chong
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Marc Agzarian
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | | | | | - Bernardo C A Teixeira
- Instituto de Neurologia de Curitiba, Curitiba, Paraná, Brazil
- Department of Radiology, Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Flávia Sprenger
- Department of Radiology, Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - David Menotti
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Diego R Lucio
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Pamela LaMontagne
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Daniel Marcus
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Benedikt Wiestler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
| | - Florian Kofler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
- Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany
| | - Ivan Ezhov
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
- Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany
| | - Marie Metz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Rajan Jain
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
- Department of Neurosurgery, NYU Grossman School of Medicine, New York, NY, USA
| | - Matthew Lee
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Yvonne W Lui
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Richard McKinley
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Johannes Slotboom
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Piotr Radojewski
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Raphael Meier
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Derrick Murcia
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Eric Fu
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Rourke Haas
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - John Thompson
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - David Ryan Ormond
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Chaitra Badve
- Department of Radiology, University Hospitals Cleveland, Cleveland, OH, USA
| | - Andrew E Sloan
- Department of Neurological Surgery, University Hospitals-Seidman Cancer Center, Cleveland, OH, USA
- Case Comprehensive Cancer Center, Cleveland, OH, USA
- Department of Neurosurgery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Vachan Vadmal
- Department of Neurosurgery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Kristin Waite
- National Cancer Institute, National Institute of Health, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
| | - Rivka R Colen
- Department of Radiology, Neuroradiology Division, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Linmin Pei
- University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Murat Ak
- Department of Radiology, Neuroradiology Division, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ashok Srinivasan
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - J Rajiv Bapuraj
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Arvind Rao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas Wang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Ota Yoshiaki
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Toshio Moritani
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Sevcan Turk
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Joonsang Lee
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Snehal Prabhudesai
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Fanny Morón
- Department of Radiology, Baylor College of Medicine, Houston, TX, USA
| | - Jacob Mandel
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | - Konstantinos Kamnitsas
- Department of Computing, Imperial College London, London, UK
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Ben Glocker
- Department of Computing, Imperial College London, London, UK
| | - Luke V M Dixon
- Department of Radiology, Imperial College NHS Healthcare Trust, London, UK
| | - Matthew Williams
- Computational Oncology Group, Institute for Global Health Innovation, Imperial College London, London, UK
| | - Peter Zampakis
- Department of NeuroRadiology, University of Patras, Patras, Greece
| | | | - Panagiotis Tsiganos
- Clinical Radiology Laboratory, Department of Medicine, University of Patras, Patras, Greece
| | - Sotiris Alexiou
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
| | - Ilias Haliassos
- Department of Neuro-Oncology, University of Patras, Patras, Greece
| | - Evangelia I Zacharaki
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
| | | | | | | | | | | | | | - Sung Soo Ahn
- Yonsei University College of Medicine, Seoul, Korea
| | - Bing Luo
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
| | - Laila Poisson
- Public Health Sciences, Henry Ford Health System, Detroit, MI, USA
| | - Ning Wen
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
- SJTU-Ruijin-UIH Institute for Medical Imaging Technology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China
| | | | - Ruchika Verma
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
- Case Western Reserve University, Cleveland, OH, USA
| | - Rohan Bareja
- Case Western Reserve University, Cleveland, OH, USA
| | - Ipsa Yadav
- Case Western Reserve University, Cleveland, OH, USA
| | | | - Neeraj Kumar
- University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Sebastian R van der Voort
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Ahmed Alafandi
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Fatih Incekara
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Maarten M J Wijnenga
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Georgios Kapsas
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Renske Gahrmann
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Joost W Schouten
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Hendrikus J Dubbink
- Department of Pathology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Arnaud J P E Vincent
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Martin J van den Bent
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Pim J French
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Stefan Klein
- Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Yading Yuan
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sonam Sharma
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tzu-Chi Tseng
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Saba Adabi
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Simone P Niclou
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Olivier Keunen
- Translation Radiomics, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Ann-Christin Hau
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
- Luxembourg Center of Neuropathology, Laboratoire National De Santé, Luxembourg, Luxembourg
| | - Martin Vallières
- Department of Computer Science, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - David Fortin
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Division of Neurosurgery and Neuro-Oncology, Faculty of Medicine and Health Science, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Martin Lepage
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Department of Nuclear Medicine and Radiobiology, Sherbrooke Molecular Imaging Centre, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Bennett Landman
- Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Karthik Ramadass
- Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Kaiwen Xu
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Silky Chotai
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lola B Chambless
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Akshitkumar Mistry
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Reid C Thompson
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yuriy Gusev
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Krithika Bhuvaneshwar
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Anousheh Sayah
- Division of Neuroradiology & Neurointerventional Radiology, Department of Radiology, MedStar Georgetown University Hospital, Washington, DC, USA
| | - Camelia Bencheqroun
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Anas Belouali
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Subha Madhavan
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Thomas C Booth
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
- Department of Neuroradiology, Ruskin Wing, King's College Hospital NHS Foundation Trust, London, UK
| | - Alysha Chelliah
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Marc Modat
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Haris Shuaib
- Stoke Mandeville Hospital, Mandeville Road, Aylesbury, UK
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
| | - Carmen Dragos
- Stoke Mandeville Hospital, Mandeville Road, Aylesbury, UK
| | | | | | | | | | - Shady Gamal
- University of Cairo School of Medicine, Giza, Egypt
| | | | | | | | - Ji Eun Park
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Jihye Yun
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Ho Sung Kim
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Abhishek Mahajan
- The Clatterbridge Cancer Centre NHS Foundation Trust Pembroke Place, Liverpool, UK
| | - Mark Muzi
- Department of Radiology, University of Washington, Seattle, WA, USA
| | - Sean Benson
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Regina G H Beets-Tan
- Department of Radiology, Netherlands Cancer Institute, Amsterdam, Netherlands
- GROW School of Oncology and Developmental Biology, Maastricht, Netherlands
| | - Jonas Teuwen
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | | | | | - William Escobar
- Clínica Imbanaco Grupo Quirón Salud, Cali, Colombia
- Universidad del Valle, Cali, Colombia
| | | | - Jose Bernal
- Universidad del Valle, Cali, Colombia
- The University of Edinburgh, Edinburgh, UK
| | | | - Joseph Choi
- Department of Industrial and Systems Engineering, University of Iowa, Iowa, USA
| | - Stephen Baek
- Department of Industrial and Systems Engineering, Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Yusung Kim
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Heba Ismael
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Bryan Allen
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - John M Buatti
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | | | - Hongwei Li
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Tobias Weiss
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Michael Weller
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Andrea Bink
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Bertrand Pouymayou
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | | | - Joel Saltz
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Prateek Prasanna
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Sampurna Shrestha
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Kartik M Mani
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
- Department of Radiation Oncology, Stony Brook University, Stony Brook, NY, USA
| | - David Payne
- Department of Radiology, Stony Brook University, Stony Brook, NY, USA
| | - Tahsin Kurc
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
- Scientific Data Group, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Enrique Pelaez
- Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
| | | | - Francis Loayza
- Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
| | | | | | | | | | - Franco Vera
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Elvis Ríos
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Eduardo López
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Sergio A Velastin
- School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK
| | - Godwin Ogbole
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Mayowa Soneye
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Dotun Oyekunle
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | | | - Babatunde Osobu
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Mustapha Shu'aibu
- Department of Radiology, Muhammad Abdullahi Wase Teaching Hospital, Kano, Nigeria
| | - Adeleye Dorcas
- Department of Radiology, Obafemi Awolowo University Ile-Ife, Ile-Ife, Osun, Nigeria
| | - Farouk Dako
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Global Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Amber L Simpson
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Mohammad Hamghalam
- School of Computing, Queen's University, Kingston, ON, Canada
- Department of Electrical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
| | - Jacob J Peoples
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Ricky Hu
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Anh Tran
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Danielle Cutler
- The Faculty of Arts & Sciences, Queen's University, Kingston, ON, Canada
| | - Fabio Y Moraes
- Department of Oncology, Queen's University, Kingston, ON, Canada
| | - Michael A Boss
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - James Gimpel
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Deepak Kattil Veettil
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Kendall Schmidt
- Data Science Institute, American College of Radiology, Reston, VA, USA
| | - Brian Bialecki
- Data Science Institute, American College of Radiology, Reston, VA, USA
| | - Sailaja Marella
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Cynthia Price
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Lisa Cimino
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Charles Apgar
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | | | - Bjoern Menze
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Jill S Barnholtz-Sloan
- National Cancer Institute, National Institute of Health, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
- Center for Biomedical Informatics and Information Technology, National Cancer Institute (NCI), National Institute of Health, Bethesda, MD, USA
| | | | - Spyridon Bakas
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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19
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Casciato DJ, Chandra A, Nguyen K, Starcher N, Thompson J, Mendicino RW, Taylor BC. Correlation of Lisfranc Injuries With Regional Bone Density. J Foot Ankle Surg 2022; 62:173-177. [PMID: 35918263 DOI: 10.1053/j.jfas.2022.06.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 06/09/2022] [Accepted: 06/22/2022] [Indexed: 02/03/2023]
Abstract
Lisfranc injuries present a challenge due to their ubiquity though frequent missed diagnoses. A paucity of data exists associating the contribution of bone density to injury type. This investigation compares the regional bone density between Lisfranc injury types using computed-tomography (CT)-derived Hounsfield units. A retrospective chart review identified patients with gross ligamentous and avulsion-type Lisfranc injuries determined by CT examination of the second metatarsal base and medial cuneiform. Regional bone density was assessed by averaging the Hounsfield units of the first metatarsal base, navicular, cuboid, calcaneus, and talus between 2 reviewers. Density was compared between injury type, isolated concomitant forefoot, and mid/hindfoot fractures. One hundred thirty-four patients were separated into avulsion (n = 85) and ligamentous (n = 49) groups. No statistically significant difference in patient body mass index, age, smoking status, or Quenu and Kuss injury pattern was observed between groups. The regional bone density of the cuboid (p = .03) and talus (p = .04) was greater in the ligamentous group. Lower extremity concomitant mid/hindfoot fracture patients exhibited greater regional bone density in the ligamentous group in all assessed bones (p ≤ .04) except the calcaneus. Ligamentous injuries of the Lisfranc complex are associated with increased regional bone density among patients sustaining concomitant mid/hindfoot fractures. This study expands the utility of regional bone density analysis in foot and ankle trauma.
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Affiliation(s)
| | - Amar Chandra
- Resident Physician, OhioHealth Grant Medical Center, Columbus, OH
| | - Kevin Nguyen
- Resident Physician, OhioHealth Grant Medical Center, Columbus, OH
| | - Nathaniel Starcher
- Student, Ohio University Heritage College of Osteopathic Medicine, Dublin, OH
| | - John Thompson
- Fellow, Orthopedic Foot and Ankle Center, Worthington, OH
| | | | - Benjamin C Taylor
- Fellowship Director, Orthopaedic Trauma and Reconstructive Surgery, Department of Orthopedic Surgery, Grant Medical Center, Columbus, OH
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20
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Pessin M, Campos-Chillon F, Hanna J, Thompson J. 50 Effects of lipoic acid, L-carnitine, and vitamin C on oocyte maturation and cryopreservation of. Reprod Fertil Dev 2022. [DOI: 10.1071/rdv35n2ab50] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2022] Open
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21
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Thompson J, Hanna J, Pessin M, Campos-Chillon F. 217 Effects of mature - recombinant GDF9 and BMP15 on. Reprod Fertil Dev 2022. [DOI: 10.1071/rdv35n2ab217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
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22
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Pati S, Baid U, Edwards B, Sheller M, Wang SH, Reina GA, Foley P, Gruzdev A, Karkada D, Davatzikos C, Sako C, Ghodasara S, Bilello M, Mohan S, Vollmuth P, Brugnara G, Preetha CJ, Sahm F, Maier-Hein K, Zenk M, Bendszus M, Wick W, Calabrese E, Rudie J, Villanueva-Meyer J, Cha S, Ingalhalikar M, Jadhav M, Pandey U, Saini J, Garrett J, Larson M, Jeraj R, Currie S, Frood R, Fatania K, Huang RY, Chang K, Balaña C, Capellades J, Puig J, Trenkler J, Pichler J, Necker G, Haunschmidt A, Meckel S, Shukla G, Liem S, Alexander GS, Lombardo J, Palmer JD, Flanders AE, Dicker AP, Sair HI, Jones CK, Venkataraman A, Jiang M, So TY, Chen C, Heng PA, Dou Q, Kozubek M, Lux F, Michálek J, Matula P, Keřkovský M, Kopřivová T, Dostál M, Vybíhal V, Vogelbaum MA, Mitchell JR, Farinhas J, Maldjian JA, Yogananda CGB, Pinho MC, Reddy D, Holcomb J, Wagner BC, Ellingson BM, Cloughesy TF, Raymond C, Oughourlian T, Hagiwara A, Wang C, To MS, Bhardwaj S, Chong C, Agzarian M, Falcão AX, Martins SB, Teixeira BCA, Sprenger F, Menotti D, Lucio DR, LaMontagne P, Marcus D, Wiestler B, Kofler F, Ezhov I, Metz M, Jain R, Lee M, Lui YW, McKinley R, Slotboom J, Radojewski P, Meier R, Wiest R, Murcia D, Fu E, Haas R, Thompson J, Ormond DR, Badve C, Sloan AE, Vadmal V, Waite K, Colen RR, Pei L, Ak M, Srinivasan A, Bapuraj JR, Rao A, Wang N, Yoshiaki O, Moritani T, Turk S, Lee J, Prabhudesai S, Morón F, Mandel J, Kamnitsas K, Glocker B, Dixon LVM, Williams M, Zampakis P, Panagiotopoulos V, Tsiganos P, Alexiou S, Haliassos I, Zacharaki EI, Moustakas K, Kalogeropoulou C, Kardamakis DM, Choi YS, Lee SK, Chang JH, Ahn SS, Luo B, Poisson L, Wen N, Tiwari P, Verma R, Bareja R, Yadav I, Chen J, Kumar N, Smits M, van der Voort SR, Alafandi A, Incekara F, Wijnenga MMJ, Kapsas G, Gahrmann R, Schouten JW, Dubbink HJ, Vincent AJPE, van den Bent MJ, French PJ, Klein S, Yuan Y, Sharma S, Tseng TC, Adabi S, Niclou SP, Keunen O, Hau AC, Vallières M, Fortin D, Lepage M, Landman B, Ramadass K, Xu K, Chotai S, Chambless LB, Mistry A, Thompson RC, Gusev Y, Bhuvaneshwar K, Sayah A, Bencheqroun C, Belouali A, Madhavan S, Booth TC, Chelliah A, Modat M, Shuaib H, Dragos C, Abayazeed A, Kolodziej K, Hill M, Abbassy A, Gamal S, Mekhaimar M, Qayati M, Reyes M, Park JE, Yun J, Kim HS, Mahajan A, Muzi M, Benson S, Beets-Tan RGH, Teuwen J, Herrera-Trujillo A, Trujillo M, Escobar W, Abello A, Bernal J, Gómez J, Choi J, Baek S, Kim Y, Ismael H, Allen B, Buatti JM, Kotrotsou A, Li H, Weiss T, Weller M, Bink A, Pouymayou B, Shaykh HF, Saltz J, Prasanna P, Shrestha S, Mani KM, Payne D, Kurc T, Pelaez E, Franco-Maldonado H, Loayza F, Quevedo S, Guevara P, Torche E, Mendoza C, Vera F, Ríos E, López E, Velastin SA, Ogbole G, Soneye M, Oyekunle D, Odafe-Oyibotha O, Osobu B, Shu'aibu M, Dorcas A, Dako F, Simpson AL, Hamghalam M, Peoples JJ, Hu R, Tran A, Cutler D, Moraes FY, Boss MA, Gimpel J, Veettil DK, Schmidt K, Bialecki B, Marella S, Price C, Cimino L, Apgar C, Shah P, Menze B, Barnholtz-Sloan JS, Martin J, Bakas S. Federated learning enables big data for rare cancer boundary detection. Nat Commun 2022; 13:7346. [PMID: 36470898 PMCID: PMC9722782 DOI: 10.1038/s41467-022-33407-5] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 09/16/2022] [Indexed: 12/12/2022] Open
Abstract
Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.
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Affiliation(s)
- Sarthak Pati
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
| | - Ujjwal Baid
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | | | | | | | | | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Chiharu Sako
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Satyam Ghodasara
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michel Bilello
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Suyash Mohan
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Philipp Vollmuth
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Gianluca Brugnara
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | | | - Felix Sahm
- Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neuropathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Klaus Maier-Hein
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
- Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Maximilian Zenk
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Wolfgang Wick
- Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ), Heidelberg, Germany
- Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany
| | - Evan Calabrese
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Jeffrey Rudie
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Javier Villanueva-Meyer
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Soonmee Cha
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Madhura Ingalhalikar
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Manali Jadhav
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Umang Pandey
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Jitender Saini
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - John Garrett
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Matthew Larson
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Robert Jeraj
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Stuart Currie
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Russell Frood
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Kavi Fatania
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Raymond Y Huang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ken Chang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | | | | | - Josep Puig
- Department of Radiology (IDI), Girona Biomedical Research Institute (IdIBGi), Josep Trueta University Hospital, Girona, Spain
| | - Johannes Trenkler
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Josef Pichler
- Department of Neurooncology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Georg Necker
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Andreas Haunschmidt
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Stephan Meckel
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
- Institute of Diagnostic and Interventional Neuroradiology, RKH Klinikum Ludwigsburg, Ludwigsburg, Germany
| | - Gaurav Shukla
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiation Oncology, Christiana Care Health System, Philadelphia, PA, USA
| | - Spencer Liem
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Gregory S Alexander
- Department of Radiation Oncology, University of Maryland, Baltimore, MD, USA
| | - Joseph Lombardo
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Joshua D Palmer
- Department of Radiation Oncology, The James Cancer Hospital and Solove Research Institute, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Adam E Flanders
- Department of Radiology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Adam P Dicker
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Haris I Sair
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Craig K Jones
- The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Archana Venkataraman
- Department of Electrical and Computer Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Meirui Jiang
- The Chinese University of Hong Kong, Hong Kong, China
| | - Tiffany Y So
- The Chinese University of Hong Kong, Hong Kong, China
| | - Cheng Chen
- The Chinese University of Hong Kong, Hong Kong, China
| | | | - Qi Dou
- The Chinese University of Hong Kong, Hong Kong, China
| | - Michal Kozubek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Filip Lux
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Jan Michálek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Petr Matula
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Miloš Keřkovský
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
| | - Tereza Kopřivová
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
| | - Marek Dostál
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
- Department of Biophysics, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Václav Vybíhal
- Department of Neurosurgery, Faculty of Medicine, Masaryk University, Brno, and University Hospital and Czech Republic, Brno, Czech Republic
| | - Michael A Vogelbaum
- Department of Neuro Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - J Ross Mitchell
- University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Joaquim Farinhas
- Department of Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | | | | | - Marco C Pinho
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Divya Reddy
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - James Holcomb
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | | | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- UCLA Neuro-Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CaA, USA
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CaA, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Talia Oughourlian
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Akifumi Hagiwara
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Chencai Wang
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Minh-Son To
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
- Division of Surgery and Perioperative Medicine, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Sargam Bhardwaj
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
| | - Chee Chong
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Marc Agzarian
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | | | | | - Bernardo C A Teixeira
- Instituto de Neurologia de Curitiba, Curitiba, Paraná, Brazil
- Department of Radiology, Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Flávia Sprenger
- Department of Radiology, Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - David Menotti
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Diego R Lucio
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Pamela LaMontagne
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Daniel Marcus
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Benedikt Wiestler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
| | - Florian Kofler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
- Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany
| | - Ivan Ezhov
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
- Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany
| | - Marie Metz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Rajan Jain
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
- Department of Neurosurgery, NYU Grossman School of Medicine, New York, NY, USA
| | - Matthew Lee
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Yvonne W Lui
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Richard McKinley
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Johannes Slotboom
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Piotr Radojewski
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Raphael Meier
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Derrick Murcia
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Eric Fu
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Rourke Haas
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - John Thompson
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - David Ryan Ormond
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Chaitra Badve
- Department of Radiology, University Hospitals Cleveland, Cleveland, OH, USA
| | - Andrew E Sloan
- Department of Neurological Surgery, University Hospitals-Seidman Cancer Center, Cleveland, OH, USA
- Case Comprehensive Cancer Center, Cleveland, OH, USA
- Department of Neurosurgery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Vachan Vadmal
- Department of Neurosurgery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Kristin Waite
- National Cancer Institute, National Institute of Health, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
| | - Rivka R Colen
- Department of Radiology, Neuroradiology Division, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Linmin Pei
- University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Murat Ak
- Department of Radiology, Neuroradiology Division, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ashok Srinivasan
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - J Rajiv Bapuraj
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Arvind Rao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas Wang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Ota Yoshiaki
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Toshio Moritani
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Sevcan Turk
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Joonsang Lee
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Snehal Prabhudesai
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Fanny Morón
- Department of Radiology, Baylor College of Medicine, Houston, TX, USA
| | - Jacob Mandel
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | - Konstantinos Kamnitsas
- Department of Computing, Imperial College London, London, UK
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Ben Glocker
- Department of Computing, Imperial College London, London, UK
| | - Luke V M Dixon
- Department of Radiology, Imperial College NHS Healthcare Trust, London, UK
| | - Matthew Williams
- Computational Oncology Group, Institute for Global Health Innovation, Imperial College London, London, UK
| | - Peter Zampakis
- Department of NeuroRadiology, University of Patras, Patras, Greece
| | | | - Panagiotis Tsiganos
- Clinical Radiology Laboratory, Department of Medicine, University of Patras, Patras, Greece
| | - Sotiris Alexiou
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
| | - Ilias Haliassos
- Department of Neuro-Oncology, University of Patras, Patras, Greece
| | - Evangelia I Zacharaki
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
| | | | | | | | | | | | | | - Sung Soo Ahn
- Yonsei University College of Medicine, Seoul, Korea
| | - Bing Luo
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
| | - Laila Poisson
- Public Health Sciences, Henry Ford Health System, Detroit, MI, USA
| | - Ning Wen
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
- SJTU-Ruijin-UIH Institute for Medical Imaging Technology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China
| | | | - Ruchika Verma
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
- Case Western Reserve University, Cleveland, OH, USA
| | - Rohan Bareja
- Case Western Reserve University, Cleveland, OH, USA
| | - Ipsa Yadav
- Case Western Reserve University, Cleveland, OH, USA
| | | | - Neeraj Kumar
- University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Sebastian R van der Voort
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Ahmed Alafandi
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Fatih Incekara
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Maarten M J Wijnenga
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Georgios Kapsas
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Renske Gahrmann
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Joost W Schouten
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Hendrikus J Dubbink
- Department of Pathology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Arnaud J P E Vincent
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Martin J van den Bent
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Pim J French
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Stefan Klein
- Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Yading Yuan
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sonam Sharma
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tzu-Chi Tseng
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Saba Adabi
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Simone P Niclou
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Olivier Keunen
- Translation Radiomics, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Ann-Christin Hau
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
- Luxembourg Center of Neuropathology, Laboratoire National De Santé, Luxembourg, Luxembourg
| | - Martin Vallières
- Department of Computer Science, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - David Fortin
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Division of Neurosurgery and Neuro-Oncology, Faculty of Medicine and Health Science, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Martin Lepage
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Department of Nuclear Medicine and Radiobiology, Sherbrooke Molecular Imaging Centre, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Bennett Landman
- Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Karthik Ramadass
- Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Kaiwen Xu
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Silky Chotai
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lola B Chambless
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Akshitkumar Mistry
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Reid C Thompson
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yuriy Gusev
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Krithika Bhuvaneshwar
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Anousheh Sayah
- Division of Neuroradiology & Neurointerventional Radiology, Department of Radiology, MedStar Georgetown University Hospital, Washington, DC, USA
| | - Camelia Bencheqroun
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Anas Belouali
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Subha Madhavan
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Thomas C Booth
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
- Department of Neuroradiology, Ruskin Wing, King's College Hospital NHS Foundation Trust, London, UK
| | - Alysha Chelliah
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Marc Modat
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Haris Shuaib
- Stoke Mandeville Hospital, Mandeville Road, Aylesbury, UK
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
| | - Carmen Dragos
- Stoke Mandeville Hospital, Mandeville Road, Aylesbury, UK
| | | | | | | | | | - Shady Gamal
- University of Cairo School of Medicine, Giza, Egypt
| | | | | | | | - Ji Eun Park
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Jihye Yun
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Ho Sung Kim
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Abhishek Mahajan
- The Clatterbridge Cancer Centre NHS Foundation Trust Pembroke Place, Liverpool, UK
| | - Mark Muzi
- Department of Radiology, University of Washington, Seattle, WA, USA
| | - Sean Benson
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Regina G H Beets-Tan
- Department of Radiology, Netherlands Cancer Institute, Amsterdam, Netherlands
- GROW School of Oncology and Developmental Biology, Maastricht, Netherlands
| | - Jonas Teuwen
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | | | | | - William Escobar
- Clínica Imbanaco Grupo Quirón Salud, Cali, Colombia
- Universidad del Valle, Cali, Colombia
| | | | - Jose Bernal
- Universidad del Valle, Cali, Colombia
- The University of Edinburgh, Edinburgh, UK
| | | | - Joseph Choi
- Department of Industrial and Systems Engineering, University of Iowa, Iowa, USA
| | - Stephen Baek
- Department of Industrial and Systems Engineering, Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Yusung Kim
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Heba Ismael
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Bryan Allen
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - John M Buatti
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | | | - Hongwei Li
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Tobias Weiss
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Michael Weller
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Andrea Bink
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Bertrand Pouymayou
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | | | - Joel Saltz
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Prateek Prasanna
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Sampurna Shrestha
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Kartik M Mani
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
- Department of Radiation Oncology, Stony Brook University, Stony Brook, NY, USA
| | - David Payne
- Department of Radiology, Stony Brook University, Stony Brook, NY, USA
| | - Tahsin Kurc
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
- Scientific Data Group, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Enrique Pelaez
- Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
| | | | - Francis Loayza
- Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
| | | | | | | | | | - Franco Vera
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Elvis Ríos
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Eduardo López
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Sergio A Velastin
- School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK
| | - Godwin Ogbole
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Mayowa Soneye
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Dotun Oyekunle
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | | | - Babatunde Osobu
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Mustapha Shu'aibu
- Department of Radiology, Muhammad Abdullahi Wase Teaching Hospital, Kano, Nigeria
| | - Adeleye Dorcas
- Department of Radiology, Obafemi Awolowo University Ile-Ife, Ile-Ife, Osun, Nigeria
| | - Farouk Dako
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Global Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Amber L Simpson
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Mohammad Hamghalam
- School of Computing, Queen's University, Kingston, ON, Canada
- Department of Electrical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
| | - Jacob J Peoples
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Ricky Hu
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Anh Tran
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Danielle Cutler
- The Faculty of Arts & Sciences, Queen's University, Kingston, ON, Canada
| | - Fabio Y Moraes
- Department of Oncology, Queen's University, Kingston, ON, Canada
| | - Michael A Boss
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - James Gimpel
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Deepak Kattil Veettil
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Kendall Schmidt
- Data Science Institute, American College of Radiology, Reston, VA, USA
| | - Brian Bialecki
- Data Science Institute, American College of Radiology, Reston, VA, USA
| | - Sailaja Marella
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Cynthia Price
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Lisa Cimino
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Charles Apgar
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | | | - Bjoern Menze
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Jill S Barnholtz-Sloan
- National Cancer Institute, National Institute of Health, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
- Center for Biomedical Informatics and Information Technology, National Cancer Institute (NCI), National Institute of Health, Bethesda, MD, USA
| | | | - Spyridon Bakas
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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Hanna J, Thompson J, Pessin M, Jeffs E, Campos-Chillon F. 221 Supplementation of bovine oocyte maturation media with umbilical cord-derived exosomes. Reprod Fertil Dev 2022. [DOI: 10.1071/rdv35n2ab221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/09/2022] Open
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24
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Casciato DJ, Thompson J, Rushing CJ, McKenna B, Hyer C. Consumer Interest in Total Ankle Replacements Over the Last 10 Years: A Google Trends™ Analysis From 2009 to 2019. J Foot Ankle Surg 2022; 62:492-497. [PMID: 36564307 DOI: 10.1053/j.jfas.2022.11.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2019] [Revised: 05/11/2021] [Accepted: 11/19/2022] [Indexed: 11/27/2022]
Abstract
With an aging population, the incidence of osteoarthritis (OA) continues to grow. After exhausting conservative therapy for many forms of OA, patients regularly opt for surgical intervention in the form of total joint replacement surgery. One form, total ankle replacement, has continued to gain favorability in the medical community. Improved implant design and surgical technique have enabled success rates of total ankle replacements to approach those of the hip and knee. As a new and improving therapy to address end-stage ankle OA, knowledge of patient-interest has yet to be determined. We used search inquiry data for the keywords "ankle arthritis" "ankle replacement" and "ankle fusion" available from Google Trends™ to identify trends in patient and geographic interest from 2009 to 2019. Search inquiries significantly increased for all keywords over time (p < .001). Trend analysis over this 10-year period revealed a strong correlation for ankle arthritis (0.88) and ankle replacement (0.76). Moreover, the correlation between "ankle arthritis" and "ankle replacement" was strong (0.83) during this period. The geographic distribution of these search terms showed the greatest increase in interest for the keywords "ankle arthritis" "ankle replacement" and "ankle fusion" in Arizona, New York, and Virginia respectively. Results of this study illustrate a similar increasing patient interest in ankle arthritis and ankle replacements. This data can be used effectively identify, educate, and treat populations interested in ankle replacements. To the best of our knowledge, this is the first study to utilize Google Trends™ to analyze patient interest in foot and ankle surgery.
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Affiliation(s)
| | - John Thompson
- Resident, OhioHealth Grant Medical Center, Columbus, OH
| | | | - Bryon McKenna
- Fellow, Orthopedic Foot and Ankle Center, Worthington, OH
| | - Christopher Hyer
- Fellowship Co-Director, Orthopedic Foot and Ankle Center, Worthington, OH
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Joe R, Matsumura Y, Siddiqui A, Foulks J, Beg M, Thompson J, Yamamoto N, Spira A, Sarantopoulos J, Melear J, Lou Y, Lebedinsky C, Li J, Watanabe A, Warner S. The AXL inhibitor, TP-0903, reverses EMT and shows activity in non-small cell lung cancer preclinical models. Eur J Cancer 2022. [DOI: 10.1016/s0959-8049(22)00954-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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26
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Rej A, Avery A, Aziz I, Black CJ, Bowyer RK, Buckle RL, Seamark L, Shaw CC, Thompson J, Trott N, Williams M, Sanders DS. Diet and irritable bowel syndrome: an update from a UK consensus meeting. BMC Med 2022; 20:287. [PMID: 36096789 PMCID: PMC9469508 DOI: 10.1186/s12916-022-02496-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 07/25/2022] [Indexed: 11/17/2022] Open
Abstract
There has been a renewed interest in the role of dietary therapies to manage irritable bowel syndrome (IBS), with diet high on the agenda for patients. Currently, interest has focussed on the use of traditional dietary advice (TDA), a gluten-free diet (GFD) and the low FODMAP diet (LFD). A consensus meeting was held to assess the role of these dietary therapies in IBS, in Sheffield, United Kingdom.Evidence for TDA is from case control studies and clinical experience. Randomised controlled trials (RCT) have demonstrated the benefit of soluble fibre in IBS. No studies have assessed TDA in comparison to a habitual or sham diet. There have been a number of RCTs demonstrating the efficacy of a GFD at short-term follow-up, with a lack of long-term outcomes. Whilst gluten may lead to symptom generation in IBS, other components of wheat may also play an important role, with recent interest in the role of fructans, wheat germ agglutinins, as well as alpha amylase trypsin inhibitors. There is good evidence for the use of a LFD at short-term follow-up, with emerging evidence demonstrating its efficacy at long-term follow-up. There is overlap between the LFD and GFD with IBS patients self-initiating gluten or wheat reduction as part of their LFD. Currently, there is a lack of evidence to suggest superiority of one diet over another, although TDA is more acceptable to patients.In view of this evidence, our consensus group recommends that dietary therapies for IBS should be offered by dietitians who first assess dietary triggers and then tailor the intervention according to patient choice. Given the lack of dietetic services, novel approaches such as employing group clinics and online webinars may maximise capacity and accessibility for patients. Further research is also required to assess the comparative efficacy of dietary therapies to other management strategies available to manage IBS.
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Affiliation(s)
- A Rej
- Academic Unit of Gastroenterology, Royal Hallamshire Hospital, Sheffield Teaching Hospital NHS Foundation Trust, Sheffield, UK.
| | - A Avery
- Division of Nutritional Sciences, School of Biosciences, University of Nottingham, Nottingham, UK
| | - I Aziz
- Academic Unit of Gastroenterology, Royal Hallamshire Hospital, Sheffield Teaching Hospital NHS Foundation Trust, Sheffield, UK
| | - C J Black
- Leeds Gastroenterology Institute, St James's University Hospital, Leeds, UK; Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK
| | - R K Bowyer
- Department of Nutrition and Dietetics, Royal United Hospitals NHS Foundation Trust, Bath, UK
| | - R L Buckle
- Academic Unit of Gastroenterology, Royal Hallamshire Hospital, Sheffield Teaching Hospital NHS Foundation Trust, Sheffield, UK
| | - L Seamark
- Specialist Gastroenterology Community Dietetic Service, Somerset Partnership NHS Foundation Trust, Bridgwater, UK
| | - C C Shaw
- Academic Unit of Gastroenterology, Royal Hallamshire Hospital, Sheffield Teaching Hospital NHS Foundation Trust, Sheffield, UK
| | - J Thompson
- Information Manager/Specialist Gastroenterology Dietitian, Guts UK Charity, 3 St Andrews Place, London, NW1 4LB, UK
| | - N Trott
- Academic Unit of Gastroenterology, Royal Hallamshire Hospital, Sheffield Teaching Hospital NHS Foundation Trust, Sheffield, UK
| | - M Williams
- Specialist Gastroenterology Community Dietetic Service, Somerset Partnership NHS Foundation Trust, Bridgwater, UK
| | - D S Sanders
- Academic Unit of Gastroenterology, Royal Hallamshire Hospital, Sheffield Teaching Hospital NHS Foundation Trust, Sheffield, UK
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Casciato DJ, Stone R, Thompson J, Venero M, Chiu M, Blum J, Barron I, Hyer C. Radiodensity Analysis of Medial Column Superconstruct Fixation Sites in Midfoot Charcot Neuroarthropathy. J Foot Ankle Surg 2022; 61:1076-1080. [PMID: 35181205 DOI: 10.1053/j.jfas.2022.01.023] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Revised: 07/06/2021] [Accepted: 01/11/2022] [Indexed: 02/03/2023]
Abstract
Charcot neuroarthropathy (CN) is a highly destructive, pathologic process with devastating consequences to foot structure and viability. The use of intramedullary fixation "superconstructs" allows for "re-bar" support of compromised bone and allows for some dynamic fixation. This study examines radiodensity in Hounsfield units (HU) to compare bone quality of medial column fixation targets using computed tomography scans between patients with and without midfoot CN. A retrospective chart review identified control (nondiabetic, non-CN; n = 29) and midfoot CN (n = 21) groups. Patient demographics and medical history were collected. Two reviewers measured the mean HU of a circular region of interest centered on the first metatarsal head and the anterior, middle, and posterior thirds of the talar body. Radiodensity was compared between groups, and among talar locations, Eichenholtz stages and Brodsky types, with statistical significance set at p ≤ .05. Age and body mass index were not significantly different between groups. The CN group maintained greater mean HU than the control group at the metatarsal head (p < .001), and talar body locations (p < .019). The difference in mean HU of these bones was not statistically significant between Stages 0 to 1 and Stages 2 to 3 or Brodsky Types 1 and 2. Mean HU differences among talus positions were not statistically significant. Indirect bone density analysis using HU showed an increased density in CN patients with no significant difference among talar body locations or midfoot Charcot stages and types. These results may assist in optimizing fixation length. Future studies may examine these densities in ankle CN.
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Affiliation(s)
| | - Ryan Stone
- Resident Physician, OhioHealth Grant Medical Center, Columbus, OH
| | - John Thompson
- Resident Physician, OhioHealth Grant Medical Center, Columbus, OH
| | - Marissa Venero
- Resident Physician, Orlando VA Medical Center, Orlando, FL
| | - Michael Chiu
- Resident Physician, Orlando VA Medical Center, Orlando, FL
| | - Jonathan Blum
- Site Director, University of Central Florida College of Medicine, Orlando, FL
| | - Ian Barron
- Teaching Faculty, OhioHealth Grant Medical Center, Columbus, OH
| | - Christopher Hyer
- Fellowship Co-Director, Orthopedic Foot and Ankle Center, Worthington, OH
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Lim E, Reeves J, Gandhi S, Spigel D, Arrowsmith E, George D, Karlix J, Pouliot G, Hattersley M, Gangl E, James G, Thompson J, Russell D, Patel B, Kumar R, Falchook G. 1396P Phase II study of AZD4635 in combination with durvalumab or oleclumab in patients (pts) with metastatic castrate-resistant prostate cancer (mCRPC). Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.07.1882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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29
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Zhang T, Duong P, Dayuha R, Collins CJ, Beckman E, Thies J, Chang I, Lam C, Sun A, Scott AI, Thompson J, Singh A, Khaledi H, Gelb MH, Hahn SH. A rapid and non-invasive proteomic analysis using DBS and buccal swab for multiplexed second-tier screening of Pompe disease and Mucopolysaccharidosis type I. Mol Genet Metab 2022; 136:296-305. [PMID: 35787971 PMCID: PMC10387444 DOI: 10.1016/j.ymgme.2022.06.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 06/21/2022] [Accepted: 06/23/2022] [Indexed: 11/19/2022]
Abstract
PURPOSE Current newborn screening programs for Pompe disease (PD) and mucopolysaccharidosis type I (MPS I) suffer from a high false positive rate and long turnaround time for clinical follow up. This study aimed to develop a novel proteomics-based assay for rapid and accurate second-tier screening of PD and MPS I. A fast turnaround assay would enable the identification of severe cases who need immediate clinical follow up and treatment. METHODS We developed an immunocapture coupled with mass spectrometry-based proteomics (Immuno-SRM) assay to quantify GAA and IDUA proteins in dried blood spots (DBS) and buccal swabs. Sensitivity, linearity, reproducibility, and protein concentration range in healthy control samples were determined. Clinical performance was evaluated in known PD and MPS I patients as well as pseudodeficiency and carrier cases. RESULTS Using three 3.2 mm punches (~13.1 μL of blood) of DBS, the assay showed reproducible and sensitive quantification of GAA and IDUA. Both proteins can also be quantified in buccal swabs with high reproducibility and sensitivity. Infantile onset Pompe disease (IOPD) and severe MPS I cases are readily identifiable due to the absence of GAA and IDUA, respectively. In addition, late onset Pompe disease (LOPD) and attenuated MPS I patients showed much reduced levels of the target protein. By contrast, pseudodeficiency and carrier cases exhibited significant higher target protein levels compared to true patients. CONCLUSION Direct quantification of endogenous GAA and IDUA peptides in DBS by Immuno-SRM can be used for second-tier screening to rapidly identify severe PD and MPS I patients with a turnaround time of <1 week. Such patients could benefit from immediate clinical follow up and possibly earlier treatment.
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Affiliation(s)
- Tong Zhang
- Seattle Children's Research Institute, Seattle, WA, United States of America
| | - Phi Duong
- Seattle Children's Research Institute, Seattle, WA, United States of America
| | - Remwilyn Dayuha
- Seattle Children's Research Institute, Seattle, WA, United States of America
| | | | - Erika Beckman
- Division of Genetic Medicine, Seattle Children's Hospital, Seattle, WA, United States of America
| | - Jenny Thies
- Division of Genetic Medicine, Seattle Children's Hospital, Seattle, WA, United States of America
| | - Irene Chang
- Biochemical Genetics Clinic, Seattle Children's Hospital, Seattle, WA, United States of America; Department of Pediatrics, Division of Genetic Medicine, University of Washington School of Medicine, Seattle, WA, United States of America
| | - Christina Lam
- Biochemical Genetics Clinic, Seattle Children's Hospital, Seattle, WA, United States of America; Department of Pediatrics, Division of Genetic Medicine, University of Washington School of Medicine, Seattle, WA, United States of America
| | - Angela Sun
- Biochemical Genetics Clinic, Seattle Children's Hospital, Seattle, WA, United States of America; Department of Pediatrics, Division of Genetic Medicine, University of Washington School of Medicine, Seattle, WA, United States of America
| | - Anna I Scott
- Department of Laboratory, Seattle Children's Hospital, Seattle, WA, United States of America
| | - John Thompson
- WA State Department of Health, Seattle, WA, United States of America
| | - Aranjeet Singh
- WA State Department of Health, Seattle, WA, United States of America
| | - Hamid Khaledi
- Department of Chemistry, University of Washington, Seattle, WA, United States of America
| | - Michael H Gelb
- Department of Chemistry, University of Washington, Seattle, WA, United States of America
| | - Si Houn Hahn
- Seattle Children's Research Institute, Seattle, WA, United States of America; Biochemical Genetics Clinic, Seattle Children's Hospital, Seattle, WA, United States of America; Department of Pediatrics, Division of Genetic Medicine, University of Washington School of Medicine, Seattle, WA, United States of America.
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Ipe TS, Ugwumba B, Spencer HJ, Le T, Ridenour T, Armitage J, Ryan S, Pearson S, Kothari A, Patil N, Dare R, Crescencio JCR, Venkata A, Laudadio J, Mohammad K, Jamal N, Thompson J, McNew H, Gibbs M, Hennigan S, Kellar S, Reitzel K, Walser BE, Novak A, Quinn B. Treatment of COVID-19 Patients with Two Units of Convalescent Plasma in a Resource-Constrained State. Lab Med 2022; 53:623-628. [PMID: 35771890 PMCID: PMC9278218 DOI: 10.1093/labmed/lmac055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
IMPORTANCE Many therapies are used to treat COVID-19, the disease caused by the virus SARS-CoV-2, including convalescent plasma. The clinical utility of using 2 units of convalescent plasma for COVID-19 hospitalized patients is not fully understood. OBJECTIVE Many therapies are used to treat COVID-19, the disease caused by the virus SARS-CoV-2, including convalescent plasma. The clinical utility of using 2 units of convalescent plasma for COVID-19 hospitalized patients is not fully understood. Our study aims to determine the safety and efficacy of treating hospitalized COVID-19 patients with 2 units of COVID-19 convalescent plasma (CCP). METHOD This was a retrospective study of Arkansas patients treated with CCP using the (US) Food and Drug Administration (FDA) emergency Investigational New Drug (eIND) mechanism from April 9, 2020, through August 9, 2020. It was a multicenter, statewide study in a low-resource setting, which are areas that lack funding for health care cost coverage on various levels including individual, family, or social. Adult patients (n = 165, volunteer sample) in Arkansas who were hospitalized with severe or life-threatening acute COVID-19 disease as defined by the FDA criteria were transfused with 2 units of CCP (250 mL/unit) using the FDA eIND mechanism. The primary outcome was 7- and 30-day mortality after the second unit of CCP. RESULTS Unadjusted mortality was 12.1% at 7 days and 23.0% at 30 days. The unadjusted mortality was reduced to 7.7% if the first CCP unit was transfused on the date of diagnosis, 8.7% if transfused within 3 days of diagnosis, and 32.0% if transfused at or after 4 or more days of diagnosis. The risk of death was higher in patients that received low, negative, or missing titer CCP units in comparison to those that received higher titer units. CONCLUSION The provision of 2 units of CCP was associated with a reduction in mortality in patients treated with high titer units within 3 days of COVID-19 diagnosis. Given the results, CCP is a viable, low-cost therapy in resource-constrained states and countries.
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Affiliation(s)
- Tina S Ipe
- To whom correspondence should be addressed.
| | - Blessing Ugwumba
- Department of Pathology and Laboratory Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Horace J Spencer
- Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Tuan Le
- Oklahoma/Texas/and Arkansas Blood Institute, Oklahoma City, OK, USA
| | - Terry Ridenour
- Oklahoma/Texas/and Arkansas Blood Institute, Oklahoma City, OK, USA
| | - John Armitage
- Oklahoma/Texas/and Arkansas Blood Institute, Oklahoma City, OK, USA
| | | | | | - Atul Kothari
- Arkansas Department of Health, Little Rock, AR, USA
| | - Naveen Patil
- Arkansas Department of Health, Little Rock, AR, USA
| | - Ryan Dare
- Department of Internal Medicine, Division of Infectious Diseases, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Juan C R Crescencio
- Department of Internal Medicine, Division of Infectious Diseases, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Anand Venkata
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Jennifer Laudadio
- Department of Pathology and Laboratory Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Khalid Mohammad
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Jefferson Regional Medical Center, Pine Bluff, AR, USA
| | - Naznin Jamal
- Department of Internal Medicine, Jefferson Regional Medical Center, Pine Bluff, AR, USA
| | - John Thompson
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, St Bernards Healthcare, Jonesboro, AR, USA
| | - Hailey McNew
- Research Center, St Bernards Healthcare, Jonesboro, AR, USA
| | - McKenzie Gibbs
- Department of Laboratory Medicine, Northwest Medical Center, Springdale, AR, USA
| | - Steve Hennigan
- Department of Internal Medicine, Washington Regional Medical Center, Fayetteville, AR, USA
| | - Stan Kellar
- Department of Pulmonary Medicine, Baptist Health, Little Rock, AR, USA
| | | | - Brandon E Walser
- Department of Infectious Diseases, Baptist Health, Little Rock, AR, USA
| | - Amanda Novak
- Department of Infectious Diseases, Baptist Health, North Little Rock, AR, USA
| | - Brian Quinn
- Department of Pathology, Baptist Health, Little Rock, AR, USA
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Casciato DJ, Thompson J, Hyer CF. Post-Fellowship Foot and Ankle Surgeon Research Productivity: A Systematic Review. J Foot Ankle Surg 2022; 61:896-899. [PMID: 35153140 DOI: 10.1053/j.jfas.2021.12.028] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 12/29/2021] [Accepted: 12/31/2021] [Indexed: 02/03/2023]
Abstract
Though foot and ankle surgery fellowships have been around for decades, contributing factors for long-term research productivity remain unreported. Along with enhancing surgical training, the American College of Foot and Ankle Surgeons (ACFAS) tasked programs with fostering research in effort to continue post-fellowship investigations. As the number of fellowship programs and fellows continues to increase, this study attempts to identifies factors associated with postfellowship research success. A PubMed search of peer-reviewed literature authored by ACFAS recognized 1-year fellowship graduates from 2000-2018 was conducted. Demographic data including current practice type and location was collected. Research activity at the 3, 5, and 10-year postfellowship period was investigated between publication history and current practice type. Statistical significance was set at p ≤ .05. Among the 37 fellowships assessed, 132 fellows were eligible for analysis. Most fellows maintained hospital-based employment 46 (34%) followed by private 44 (33%) and orthopedic group 30 (22%) practices. The proportion of fellows that published 5 and 10 years postfellowship was associated with research productivity 3 and 5 years postfellowship (p ≤ .03). The odds of publishing 3 years post-fellowship in orthopedic groups and university-based practices were 1.62 and 4.42 times higher compared to hospital-based graduates, respectively. The odds of publishing 5 years post-fellowship in orthopedic group and university based practices were 3.5 and 6.63 times higher than hospital-based practices, respectively. Despite the growing number of fellowships, a small proportion of fellows continue publishing postfellowship. These findings support the need to provide resources to engage graduates if retaining young practitioners in scholarly activity is desired.
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Affiliation(s)
| | - John Thompson
- Fellow, Orthopedic Foot & Ankle Center, Worthington, OH
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Mehta B, Goodman S, Dicarlo E, Jannat-Khah D, Gibbons JA, Otero M, Donlin L, Pannellini T, Robinson W, Sculco P, Figgie M, Rodriguez J, Kirschmann J, Thompson J, Slater D, Frezza D, Xu Z, Wang F, Orange D. OP0223 DISTINGUISHING OSTEOARTHRITIS AND RHEUMATOID ARTHRITIS SYNOVIUM WITH MACHINE LEARNING USING AUTOMATED CELL DENSITY AND PATHOLOGIST SCORES. Ann Rheum Dis 2022. [DOI: 10.1136/annrheumdis-2022-eular.4262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
BackgroundJoint damage in the knee can be severe in both rheumatoid arthritis (RA) and osteoarthritis (OA) such that total knee replacement (TKR) is often the only management option. Pathological assessment of the extent or type of synovial tissue inflammation from joint explants or biopsies can be useful. However, an ongoing challenge in using semi-quantitative assessments of synovitis is the disagreement between human pathologist scores of the same sample. We previously developed and validated a computer vision algorithm to automatically count each cell nucleus in an H&E-stained synovial whole slide image and yield a value of cell density, defined as mean nuclei count per mm2 of tissue1.ObjectivesWe sought to develop methods to distinguish OA from RA based on machine learning analysis of histologic features on H&E-stained synovial tissue samples.MethodsWe measured 14 pathologist-scored histology features (137 RA and 152 OA patients) and computer vision quantified cell density (60 RA and 147 OA patients) in H&E stained synovial tissue samples from total knee replacement arthroplasty explants. A random forest model was trained using disease state (OA vs RA) as classifier and histology features and/or cell density as inputs, and feature importance scores for the model were calculated.ResultsSynovium from patients with RA exhibited increased lymphocytic inflammation, lining hyperplasia, neutrophils, detritus, plasma cells, Russell bodies, binucleate plasma cells, sub-lining giant cells, synovial lining giant cells, and fibrin (all p<0.001), while synovium from patients with OA had increased mast cells and fibrosis (both p<0.001). Fourteen pathologist-scored features allowed for discrimination between RA and OA samples, producing a macro-averaged area under the receiver operating curve (AUC) of 0.85. This discriminatory ability was comparable to that of the computer vision score of cell density alone (AUC = 0.88). Combining the pathologist scores with the cell density metric improved the discriminatory power of the model (AUC = 0.91). The three most important features in this combined model were mast cells followed by cell density and fibrosis (Figure 1). AUC values for each individual feature are provided in Table 1. The optimal cell density threshold to distinguish RA from OA synovium was 3,400 cells per mm2, which yielded a sensitivity of 0.82 and specificity of 0.82.Table 1.Area under receiver operating characteristic curves (AUC) of the synovial features in distinguishing RA and OA patientsFeatureAUCAutomated Cell Density0.88Fibrosis0.84Mast cells0.80Lining hyperplasia0.78Lymphocytic inflammation0.69Fibrin0.68Plasma cells0.66Detritus0.64Binucleate plasma cells0.60Neutrophils0.60Synovial giant cells0.58Sub-lining giant cells0.57Russell bodies0.56Germinal centers0.51Mucoid change0.50Figure 1.Importance of synovial features in distinguishing RA and OA synoviumFeature importance scores for supervised machine learning model including all 14 pathology scores and the computer vision-generated cell density.ConclusionH&E-stained images of RA and OA TKR explant synovium are distinct. We identified cell density, mast cells and fibrosis as the three most important features for making this distinction, with RA being characterized by increased cell density, low mast cells, and low fibrosis. Cell density greater than 3400 per mm2 of tissue yields a sensitivity of 0.82 and a specificity of 0.82 for distinguishing RA from OA. In the future, this can have clinical and research applications as this technique removes the requirement for subjective selection of a certain field of interest, is reproducible, and is scalable as it does not require technical expertise of a pathologist.References[1]Guan S, Mehta B…Orange DE. Rheumatoid Arthritis Synovial Inflammation Quantification Using Computer Vision. ACR Open Rheumatology. 2022 Jan 10;acr2.11381.AcknowledgementsThis work was supported by the C. Ronald MacKenzie Young Scientist Endowment Award, the Leon Lowenstein Foundation, and the Kellen Scholar Award supported by the Anna Marie and Stephen Kellen Foundation Total Knee Improvement Program.Disclosure of InterestsBella Mehta Paid instructor for: Novartis, Susan Goodman Consultant of: UCB, Grant/research support from: Novartis, Edward DiCarlo: None declared, Deanna Jannat-Khah Shareholder of: AstraZeneca, Cytodyn, and Walgreens, J. Alex Gibbons: None declared, Miguel Otero Consultant of: Regeneron Pharmaceuticals, Grant/research support from: Tissue Genesis, Laura Donlin Speakers bureau: Stryker, Consultant of: Stryker, Grant/research support from: Karius, Inc, Tania Pannellini: None declared, William Robinson: None declared, Peter Sculco Consultant of: Intellijoint Surgical, DePuy Synthes, Lima Corporate, Zimmer Biomet, and EOS Imaging, Grant/research support from: Intellijoint Surgical and Zimmer Biomet, Mark Figgie Shareholder of: HS2, Mekanika, and Wishbone, Consultant of: Lima and Wishbone, Jose Rodriguez Consultant of: ConforMIS, Medacta, Exactech, Inc, and Smith & Nephew, Grant/research support from: DePuy, Exactech, Inc, and Smith & Nephew, Jessica Kirschmann: None declared, James Thompson: None declared, David Slater: None declared, Damon Frezza: None declared, Zhenxing Xu: None declared, Fei Wang: None declared, Dana Orange: None declared
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Katelaris A, Browne L, Bucci J, Malouf D, Thompson J. Long term impact of LDR brachytherapy for prostate cancer on erectile function: Single centre tertiary referral outcomes with 8-year follow up. J Sex Med 2022. [DOI: 10.1016/j.jsxm.2022.03.374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Razmara A, Idlett-Ali S, Chee K, Shrestha K, Bayman E, Thompson J, Jameson L, Ojemann S, Kramer D. Transient cardiac asystole during vagus nerve stimulator implantation: A case report. Surg Neurol Int 2022; 13:131. [PMID: 35509543 PMCID: PMC9062970 DOI: 10.25259/sni_21_2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 03/18/2022] [Indexed: 11/04/2022] Open
Abstract
Background:
Vagal nerve stimulation (VNS) is a Food and Drug Administration approved therapy for seizures with a suggested mechanism of action consisting of cortical desynchronization, facilitated through broad release of inhibitory neurotransmitters in the cortex and brainstem. The vagus nerve contains visceral afferents that transmit sensory signals centrally, from locations that include the heart and the aorta. Although the vagus nerve serves a role in cardiac function, electrical stimulation with VNS has rarely resulted in adverse cardiac events. Here, we report a case of a cardiac event during left-sided VNS implantation.
Case Description:
A 22-year-old male with an 8-year history of absence seizures and a 3-year history of medically refractory generalized tonic-clonic seizure was planned for surgical implantation of a VNS device. In the operating room, the patient underwent left-sided VNS implantation. An initial impedance check was performed with subsequent wound irrigation; following a few seconds of irrigation, a 5 s complete cardiac pause was noted. A repeated impedance check, which included turning on the stimulation, did not replicate the cardiac pause. No further pauses or cardiac events were noted and the case continued to completion without issue. The patient was later activated without any further complications.
Conclusion:
This report describes the initiation of a cardiac event, unlikely resulting from VNS, but instead time linked to intraoperative irrigation directly on the vagus nerve.
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Affiliation(s)
- Ashkaun Razmara
- Department of Neurosurgery, University of Colorado School of Medicine, Aurora, United States,
| | - Shaquia Idlett-Ali
- Department of Neurosurgery, University of Colorado School of Medicine, Aurora, United States,
| | - Keanu Chee
- Department of Neurosurgery, University of Colorado School of Medicine, Aurora, United States,
| | - Keshari Shrestha
- Department of Neurosurgery, University of Colorado School of Medicine, Aurora, United States,
| | - Eric Bayman
- Department of Neurosurgery, University of Colorado School of Medicine, Aurora, United States,
| | - John Thompson
- Department of Neurosurgery, University of Colorado School of Medicine, Aurora, United States,
| | - Leslie Jameson
- Department of Anesthesiology, University of Colorado School of Medicine, Aurora, United States
| | - Steven Ojemann
- Department of Neurosurgery, University of Colorado School of Medicine, Aurora, United States,
| | - Daniel Kramer
- Department of Neurosurgery, University of Colorado School of Medicine, Aurora, United States,
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Thompson J, Widdows G, Parbat M. An audit of acute respiratory antibiotic prescribing in COPD patients during the COVID-19 pandemic. International Journal of Pharmacy Practice 2022. [PMCID: PMC9383641 DOI: 10.1093/ijpp/riac019.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Abstract
Introduction
Coronavirus-2 is the virus responsible for the COVID-19 pandemic. People with certain risk factors, such as having chronic obstructive pulmonary disease (COPD) may be more likely to develop complications. Research has identified that ~7% of patients with COVID-19 have a bacterial infection, however antibiotic prescribing rates have been found to vary from 38% to 72% (1,2). Primary care is estimated to make up 75% of antibiotic prescribing and was therefore a key target to evaluate whether antimicrobial stewardship principles were being followed during the COVID-19 pandemic.
Aim
To audit the adherence of antibiotic prescribing in people with COPD during the COVID-19 pandemic across a primary care network (PCN) in England against national and local guidelines.
Methods
The management of patients with COPD should follow NICE Guideline (NG) 114, NG168 and the local formulary. Three audit standards were created: 1) 100% of COPD patients should not be started on prophylactic antibiotics to reduce risk from COVID-19; 2) 100% of COPD patients should not be prescribed antibiotics for COVID-19 symptoms; 3) 90% of antibiotic prescription regimens should adhere to local and national guidelines. Prescribing data was collected from 12 practices linked to the PCN. Data of patients who had COPD, were prescribed an antibiotic, and had an indication for the antibiotic between 01/03/20 and the 30/06/20 were extracted and transferred into an anonymised spreadsheet. A total of 1088 data points were extracted. Random stratified sampling provided 300 data points for analysis, ensuring each GP surgery was represented proportionally; the required sample size to determine significance was 291. For each practice, the total number of antibiotics prescribed to COPD patients between March-June 2019 and March-June 2020 was extracted. Descriptive statistics were used to determine antibiotic prescribing adherence and overall rates of prescribing. Inferential statistics were used to compare rates of prescribing pre-vs-during the pandemic.
Results
Antibiotics were not prescribed for any patient for prophylaxis against COVID-19 (100% adherence to criteria 1). Two patients were prescribed antibiotics for ‘suspected disease caused by COVID-19’ (99.4% adherence to criteria 2). In only 28.7% of cases, the antibiotic was prescribed in line with the national and local guidelines (criteria 3). In most cases, treatment duration was the main reason for poor adherence, with longer courses of antibiotics being prescribed (7 rather than 5 days). Prescribing rates did not change significantly in 2020 compared to 2019 (1134 antibiotic prescriptions vs 1029 antibiotic prescriptions; p>0.05).
Conclusion
The audit was successful in determining that the COVID-19 pandemic did not significantly affect antibiotic prescribing rates across the PCN for people with COPD. Adherence to NICE and local guidelines was low, specifically concerning the duration of antibiotic treatment. This highlights an area for improvement; to ensure healthcare professionals across the PCN prescribe in-line with antimicrobial stewardship principles. Extracted data was limited to antibiotic prescribing and could have been expanded to include steroids to provide a fuller audit of prescribing in COPD exacerbations. A re-audit may be beneficial since the publication of NG191.
References
(1) Lansbury L, Lim B, Baskaran V, Lim WS. Co-infections in people with COVID-19: a systematic review and meta-analysis. J Infect. 2020 Aug;81(2):266-275.
(2) Seaton RA, Gibbons CL, Cooper L, Malcolm W, McKinney R, Dundas S, Griffith D, Jeffreys D, Hamilton K, Choo-Kang B, Brittain S, Guthrie D, Sneddon J. Survey of antibiotic and antifungal prescribing in patients with suspected and confirmed COVID-19 in Scottish hospitals. J Infect. 2020 Dec;81(6):952-960.
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Affiliation(s)
- J Thompson
- School of Pharmacy and Bioengineering, Keele University, Staffordshire, UK
| | - G Widdows
- School of Pharmacy and Bioengineering, Keele University, Staffordshire, UK
| | - M Parbat
- School of Pharmacy and Bioengineering, Keele University, Staffordshire, UK
- North Solihull Primary Care Network, UK
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Essel D, Thompson J, Chapman S. The effect of an augmented reality educational tool on the motivation towards learning in pharmacy students: an evaluative survey. International Journal of Pharmacy Practice 2022. [DOI: 10.1093/ijpp/riac019.041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Abstract
Introduction
Within the context of education, motivation relates to the desire students possess to engage in their learning environment. This quality is vital in determining the effort an individual expresses towards their learning and the desire they have to achieve higher academic performances (1). Educational technologies, particularly digital technologies, have long been used in post-secondary education to increase collaboration, critical thinking and motivation among students (2). The advancements in technology have led to the creation of novel augmented reality (AR) educational tools, however they have not been widely implemented or researched with the education of pharmacy students in the United Kingdom.
Aim
To identify changes of pharmacy students’ self-reported intrinsic motivation towards learning after using the ‘Pharma Compounds AR’ (PCAR) educational tool.
Methods
The PCAR tool was an image-based educational AR mobile application – it displayed 3-D models and animations of complex molecules when unique target images were scanned with the mobile’s camera. 118 stage two undergraduate Pharmacy students from a University in England were approached through cohort emails that contained a link to an online consent form and pre-intervention questionnaire. Participants were required to complete the pre-questionnaire before they received the PCAR tool for at least two months. Students were informed that they could use the tool to accommodate their learning in any way they felt appropriate. Once the intervention period ended, participants completed an online post-questionnaire. Changes in self-reported intrinsic motivation were determined with the use of adapted Intrinsic Motivation Inventory (IMI) Likert scale questions. The pre-questionnaire focused on motivation towards learning using conventional methods and their perceived usefulness, whereas the post-questionnaire focused on motivation towards learning with the PCAR tool and its perceived usefulness. Descriptive and inferential statistical analyses were conducted on the IMI adapted Likert scales.
Results
A total of 68 (57.6% rr) undergraduate Pharmacy students completed the pre-questionnaire. The majority were aged 18-21(82.4%), female (70.6%) and domestic (94.1%). The post-questionnaire was completed by 30 students (44.1% rr), mainly aged 18-21 (83.3%), female (70%), and domestic (86.7%). Participants ranked their agreement to each Likert statement from 1 (not true at all) to 7 (very true). Mean agreement motivation scores were increased after the use of the PCAR tool (pre-3.88 vs post-5.15), as were the mean agreement scores of the learning tools’ perceived usefulness (pre-4.69 vs post-5.29). Dependant T-tests performed on responses of students who completed both questionnaires revealed a significant increase in students’ mean pre- and post-intervention motivation towards learning scores (p=0.000). No significance was calculated between the mean pre-and post-agreement usefulness scores (p>0.05).
Conclusion
Incorporating the PCAR tool into the education of stage two Pharmacy students significantly increased their reported motivation towards learning when compared to conventional methods, it was also reported as being a more useful learning tool. The drop in post-questionnaire responses has to be acknowledge as a limitation as well as not explicitly knowing how students used the PCAR tool in their studies. Nevertheless, the incorporation of AR into schools of Pharmacy could provide students and tutors more engaging teaching and learning experiences.
References
(1) Budiman R. Developing Learning Media Based on Augmented Reality (AR) to Improve Learning Motivation. J Educ Teach Learn. 2016 Sep;1(2):89–94. Available from: https://www.learntechlib.org/p/209026
(2) Martin F, Polly D, Coles S, Wang C. Examining higher education faculty use of current digital technologies: Importance, competence, and motivation. Int J Teach Learn High Educ. 2020;32(1):73–86.
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Affiliation(s)
- D Essel
- School of Pharmacy and Bioengineering, Keele University, Stoke-on-Trent, UK
| | - J Thompson
- School of Pharmacy and Bioengineering, Keele University, Stoke-on-Trent, UK
| | - S Chapman
- School of Pharmacy and Bioengineering, Keele University, Stoke-on-Trent, UK
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Thompson J, Al-Attbi S, Patel B. Patient perceptions of clinical pharmacists in general practice. International Journal of Pharmacy Practice 2022. [DOI: 10.1093/ijpp/riac019.052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Abstract
Introduction
As a result of changes in the demands and pressures on the NHS, the role of the pharmacist has advanced from purely dispensing and compounding medicines to a more clinical and patient-centred approach to care (1). Since 2015, NHS England set a target of recruiting practice-based pharmacists into 20% of practices by 2020-2021 as a way of reducing these pressures (2). Conducting evaluations of clinical pharmacists in individual practices is essential for role integration and evolution.
Aim
To explore patient perceptions of clinical pharmacists across three general practices.
Methods
A paper-based questionnaire consisting of open and closed questions was used to gather patient perceptions on the role of a clinical pharmacist and their consultation experiences. Participants included patients over the age of 18 who had attended a face-to-face appointment with a clinical pharmacist from one of three general practice surgeries in England between November and December 2019. The clinical pharmacists were used as a gateway to recruit participants; post-consultation, the pharmacist asked patients if they would complete a questionnaire. Patients were provided with an information sheet and consent form prior to completion of the questionnaire. The questionnaire was anonymous. Data were analysed using descriptive statistics and content analysis.
Results
A total of 39 participants completed the questionnaire. Most participants were elderly (28%) and female (64%). The primary reason for the consultations was due to an acute illness (79%), and the most common outcome was the supply of a prescription (83%). Patients were predominantly unfamiliar with the role of a clinical pharmacist (56%) and 31% of patients reportedly thought their appointment had been with a doctor. All patients were positive about their experience and reported they would “be more than happy to see a pharmacist in the future” and that the role was “a very necessary addition to the practice”. All patients reported that their consultation was the same (51%) or better than they have had with a doctor (49%). Patients commented on the pharmacists’ consultation skills, making statements such as [they] “listened to me”, “asked me questions”, “were really good at explaining” and “spoke in a way I understood”. Clinical pharmacists were reported as being “very professional” and knowledgeable as “[they] knew more about my medication [than the doctor] and prescribed me something to help”. Patients reported that they would recommend the clinical pharmacist to their family and friends when seeking an appointment.
Conclusion
This research highlights patient acceptance towards consultations with a clinical pharmacist and reinforces the competence of pharmacists to undertake this role. A key finding related to the effective consultation skills of the pharmacists and involving the patients in their care. The number of patients who participated limits the generalisability of the findings, and the patient responses may have been a reaction to the individual clinical pharmacists rather than their thoughts on the role overall. Increased publicity and patient education of the role of a clinical pharmacist may promote a greater integration into the multidisciplinary team.
References
(1) Robertson R, Wenzel L, Thompson J, Charles A. Understanding NHS financial pressures. How are they affecting patient care. 2017. The Kings Fund. https://www.kingsfund.org.uk/sites/default/files/field/field_publication_file/Understanding%20NHS%20financial%20pressures%20-%20full%20report.pdf
(2) NHS England 2016. General Practice Forward View. https://www.england.nhs.uk/wp-content/uploads/2016/04/gpfv.pdf
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Affiliation(s)
- J Thompson
- School of Pharmacy and Bioengineering, Keele University, Staffordshire, UK
| | - S Al-Attbi
- School of Pharmacy and Bioengineering, Keele University, Staffordshire, UK
| | - B Patel
- Midlands Practice Pharmacy Network, UK
- Rushall Medical Centre, Walsall, West Midlands, UK
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Thompson J, Gusev V, Dervin P, Tevendale E. 712 EVALUATING AN ‘ACUTE FRAILTY TEAM’ MODEL OF CARE IN IMPROVING OUTCOMES FOR PATIENTS WITH FRAILTY ACUTELY ADMITTED TO HOSPITAL. Age Ageing 2022. [DOI: 10.1093/ageing/afac034.712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Introduction
In frailty, Comprehensive geriatric assessment (CGA) has benefit in improving patient outcomes, including hospital readmissions and institutionalisation. We looked to evaluate the effectiveness of our newly initiated multi-disciplinary, acute frailty team (AFT) in improving acute care. This team works on the Acute Medical Unit (AMU), delivering early CGA alongside the existing acute medical care.
Methods
The AFT initially targeted identification of frailty using the Rockwood clinical frailty score (CFS) through local quality improvement work. A standard operating procedure, encompassing CGA for all patients with frailty (define as a CFS 5 to 8 or, 4 with a frailty syndrome) was introduced. This assessment was additional to usual acute medical care. The impact was measured by retrospective case note review of 100 AMU admissions with frailty prior to the team being in post (Jan-March 2020) with a subsequent 100 patients seen by the AFT (March–April 2021). The 2 groups were matched for age, gender, frailty scores and pre-admission residence. These 2 cohorts were compared against key performance indices.
Results
The mean age of patients in the Pre and post AFT cohorts were 85 years and 84 years respectively with an average CFS of 6. The identification and documentation of frailty improved in the AFT intervention cohort from 31% to 100% and screening for delirium with 4AT improved from 27% to 91%. The number of patients in the AFT cohort discharged directly from AMU increased from 5% to 14% with the average length of in-patient stay reducing from 10.2 days to 7.8 days. Thirty day remission fell from 23% to 16% in the AFT cohort, and the number of patients discharge to new 24 hour care declined from 21% to 9%.
Conclusion
Our AFT alongside existing acute medical care improved outcomes including, frailty identification, delirium screening, length of stay, re-admissions and institutionalisation.
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Affiliation(s)
- J Thompson
- County Durham and Dralington Foundation Trust
| | - V Gusev
- County Durham and Dralington Foundation Trust
| | - P Dervin
- County Durham and Dralington Foundation Trust
| | - E Tevendale
- County Durham and Dralington Foundation Trust
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Jarden R, Scanlon A, Bridge N, McKeever S, Turner R, Prescott H, Thompson J, Cambridge P, Kinney S, Leong N, Gerdtz M. Coronavirus disease 2019 Critical Care Essentials course for nurses: development and implementation of an education program for healthcare professionals. AUST J ADV NURS 2022. [DOI: 10.37464/2020.391.423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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Doan P, Counter W, Sheehan-Dare G, Papa N, Ho B, Lee J, Liu V, Thompson J, Agrawal S, Roberts M, Algharzo O, Buteau J, Hofman M, Moon D, Murphy D, Stricker P, Emmett L. Diagnostic accuracy, concordance and certainty with 68Ga-PSMA-11 PET/MRI fusion compared to mpMRI and 68Ga-PSMA-11 PET/CT alone for prostate cancer diagnosis: A PRIMARY trial sub-study. Eur Urol 2022. [DOI: 10.1016/s0302-2838(22)00822-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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Doan P, Scheltema M, Amin A, Shnier R, Geboers B, Gondoputro W, Moses D, Van Leeuwen P, Haynes AM, Matthews J, Brenner P, O'Neill G, Yuen C, Delprado W, Stricker P, Thompson J. 3-year outcomes from the prospective ‘MRIAS’ trial: A novel active surveillance protocol which incorporates multiparametric MRI to reduce frequency of biopsy in men with prostate cancer. Eur Urol 2022. [DOI: 10.1016/s0302-2838(22)00359-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Geboers B, Gondoputro W, Thompson J, Reesink D, Van Riel L, Zhang D, Blazevski A, Doan P, Agrawal S, Mathews J, Haynes AM, Liu Z, Delprado W, Shnier R, De Reijke T, Lawrentschuk N, Stijns P, Yaxley J, Scheltema M, Stricker P. Multicenter validation of the diagnostic accuracy of multiparametric magnetic resonance imaging to detect residual prostate cancer in the follow-up of focal therapy with irreversible electroporation. Eur Urol 2022. [DOI: 10.1016/s0302-2838(22)00410-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Gallen C, Bignert A, Taucare G, O'Brien J, Braeunig J, Reeks T, Thompson J, Mueller JF. Temporal trends of perfluoroalkyl substances in an Australian wastewater treatment plant: A ten-year retrospective investigation. Sci Total Environ 2022; 804:150211. [PMID: 34798742 DOI: 10.1016/j.scitotenv.2021.150211] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 09/01/2021] [Accepted: 09/03/2021] [Indexed: 06/13/2023]
Abstract
Per- and poly-fluoroalkyl substances (PFAS) are a problematic group of chemicals used in various industrial and household products. They have been extensively detected in wastewater as a result of day-to-day product usage. Due to concerns about their safety, voluntary and regulatory action to limit the manufacture and use of some individual PFAS has occurred since the year 2000. The impact that this intervention has had on the use and potential exposure of Australians has not been measured. Wastewater serves as a powerful tool to assess the chemical use or consumption patterns of a population over time. We accessed a ten-year wastewater archiving program to conduct a temporal analysis of PFAS trends in an urban Australian population between the years 2010 and 2020. Results showed a decline in the concentrations for most PFAS, and a change in the PFAS profile from perfluorosulfonic acids and long-chain perfluorocarboxylic acids, to the short-chain perfluorocarboxylic acids and PFOS-replacement degradation products such as 5:3 FTCA. Intermittent pulses of PFAS that were significantly higher than 'background' levels (i.e., representing the PFAS input from primarily households) were observed, suggesting continuing industrial PFAS input within the wastewater catchment. This study highlights the long-term consequences of the diffuse use of persistent chemicals in products, and their ability to continue to enter the wastewater stream for decades.
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Affiliation(s)
- C Gallen
- Queensland Alliance for Environmental Health Sciences, 20 Cornwall St, Woolloongabba 4102, Australia.
| | - A Bignert
- Department of Environmental Research and Monitoring, Swedish Museum of Natural History, Frescativägen 40, 114 18 Stockholm, Sweden.
| | - G Taucare
- Queensland Alliance for Environmental Health Sciences, 20 Cornwall St, Woolloongabba 4102, Australia.
| | - J O'Brien
- Queensland Alliance for Environmental Health Sciences, 20 Cornwall St, Woolloongabba 4102, Australia.
| | - J Braeunig
- Queensland Alliance for Environmental Health Sciences, 20 Cornwall St, Woolloongabba 4102, Australia.
| | - T Reeks
- Queensland Alliance for Environmental Health Sciences, 20 Cornwall St, Woolloongabba 4102, Australia.
| | - J Thompson
- Queensland Alliance for Environmental Health Sciences, 20 Cornwall St, Woolloongabba 4102, Australia.
| | - J F Mueller
- Queensland Alliance for Environmental Health Sciences, 20 Cornwall St, Woolloongabba 4102, Australia.
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Anderson M, Sathe N, Polacek C, Vawter J, Fritz T, Mann M, Hernandez P, Nguyen MC, Thompson J, Penderville J, Arling M, Safo S, Christopher R. Site Readiness Framework to Improve Health System Preparedness for a Potential New Alzheimer’s Disease Treatment Paradigm. J Prev Alzheimers Dis 2022; 9:542-549. [PMID: 35841255 PMCID: PMC8978498 DOI: 10.14283/jpad.2022.32] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
New therapies that address the underlying pathophysiology of Alzheimer’s Disease (AD), coupled with the growth of the AD population, will transform the AD care pathway and present significant challenges to health systems. We explored real-world challenges health systems may face in delivering potential new AD therapies with diverse stakeholders. Key challenges in care included integrating primary care providers into assessment and management, availability of memory care specialists, understanding payment and coverage issues and training mid-level providers to help coordinate care and serve as a shared resource across the system. This input informed a novel Site Readiness Framework for AD, comprising self-assessment exercises to identify health system capabilities and gaps and a framework of core strategies and responsive tools to help prepare to integrate new AD therapies. These resources may help health systems improve readiness to modify care pathways to integrate new therapies for AD.
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Affiliation(s)
- M Anderson
- Cate Polacek, Premier Inc, Charlotte, NC, USA, E-Mail:
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Jasat H, Thompson J, Sonneborn O, Dayment J, Miller C. Prolonged use of paracetamol and the prescribing patterns on rehabilitation facilities. J Clin Nurs 2021; 31:3605-3616. [PMID: 34957612 DOI: 10.1111/jocn.16188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 12/14/2021] [Accepted: 12/16/2021] [Indexed: 11/30/2022]
Abstract
AIMS AND OBJECTIVES The study investigated: (a) the usage patterns of paracetamol, and (b) the association between paracetamol use and patient outcomes such as liver and kidney functions among older people. BACKGROUND Paracetamol is a well-known analgesic and antipyretic drug, with an excellent safety profile when used within its recommended dose. It is a commonly used drug by people aged over 65 years to treat chronic pain. Prolonged use of paracetamol in the elderly is poorly understood. As such, there is a genuine risk among older people of unintentional overdose. METHODS A retrospective analysis of medical records in rehabilitation wards was undertaken from 1 July 2016 to 30 June 2017. Patients' paracetamol use, prescribing patterns and biochemical results were analysed to assess for differences in admission and discharge biochemistry results. The TREND Statement was utilised to guide study reporting (Enhancing the QUAlity and Transparency Of health Research, 2021). RESULTS A total of 1119 patients were admitted for seven or more days in a metropolitan tertiary hospital in Melbourne. Almost three-quarters (74%) of patients were administered paracetamol; 76.1% received Immediate-Release Paracetamol (IRP), and 23.9% were given Sustained-release paracetamol (SRP). A proportion (4.5%) of patients in both the IRP and SRP groups received more than the daily recommended dose. There were limited statistically significant differences between patients' admission and discharge biochemistry results; group or time differences were observed, which were indicative of improvements within the paracetamol group. CONCLUSION Paracetamol was a commonly used medication among long-stay elderly patients. Precaution to ensure paracetamol use does not exceed recommended daily doses is required. This study suggests that paracetamol used at a therapeutic level in older patients had limited, negative associations with liver and kidney function. RELEVANCE TO CLINICAL PRACTICE The clinical practice regarding prolonged use of paracetamol is ambitious. The increased risk of paracetamol toxicity among the frail elderly is a concern. Optimising the dose adjustment in the elderly is important to avoid adverse outcomes.
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Affiliation(s)
- Homairah Jasat
- La Trobe University, Bundoora, Victoria, Australia.,Austin Health, Heidelberg, Victoria, Australia
| | - John Thompson
- Department of Nursing, The University of Melbourne, Carlton, Victoria, Australia.,Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - Olivia Sonneborn
- La Trobe University, Bundoora, Victoria, Australia.,Alfred Health, Melbourne, Victoria, Australia
| | | | - Charne Miller
- La Trobe University, Bundoora, Victoria, Australia.,Department of Nursing, The University of Melbourne, Carlton, Victoria, Australia
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Zou F, Faleck D, Thomas A, Harris J, Satish D, Wang X, Charabaty A, Ernstoff MS, Glitza Oliva IC, Hanauer S, McQuade J, Obeid M, Shah A, Richards DM, Sharon E, Wolchok J, Thompson J, Wang Y. Efficacy and safety of vedolizumab and infliximab treatment for immune-mediated diarrhea and colitis in patients with cancer: a two-center observational study. J Immunother Cancer 2021; 9:jitc-2021-003277. [PMID: 34789551 PMCID: PMC8601082 DOI: 10.1136/jitc-2021-003277] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/14/2021] [Indexed: 12/12/2022] Open
Abstract
Background Current treatment guidelines for immune-mediated diarrhea and colitis (IMDC) recommend steroids as first-line therapy, followed by selective immunosuppressive therapy (SIT) (infliximab or vedolizumab) for refractory cases. We aimed to compare the efficacy of these two SITs and their impact on cancer outcomes. Methods We performed a two-center, retrospective observational cohort study of patients with IMDC who received SITs following steroids from 2016 to 2020. Patients’ demographic, clinical, and overall survival data were collected and analyzed. Results A total of 184 patients (62 vedolizumab, 94 infliximab, 28 combined sequentially) were included. The efficacy of achieving clinical remission of IMDC was similar (89% vs 88%, p=0.79) between the two groups. Compared with the infliximab group, the vedolizumab group had a shorter steroid exposure (35 vs 50 days, p<0.001), fewer hospitalizations (16% vs 28%, p=0.005), and a shorter hospital stay (median 10.5 vs 13.5 days, p=0.043), but a longer time to clinical response (17.5 vs 13 days, p=0.012). Longer durations of immune checkpoint inhibitors treatment (OR 1.01, p=0.004) and steroid use (OR 1.02, p=0.043), and infliximab use alone (OR 2.51, p=0.039) were associated with higher IMDC recurrence. Furthermore, ≥3 doses of SIT (p=0.011), and fewer steroid tapering attempts (p=0.012) were associated with favorable overall survival. Conclusions Treatment with vedolizumab as compared with infliximab for IMDC led to comparable IMDC response rates, shorter duration of steroid use, fewer hospitalizations, and lower IMDC recurrence, though with slightly longer time to IMDC response. Higher number of SIT doses was associated with better survival outcome, while more steroid exposure resulted in worse patient outcomes.
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Affiliation(s)
- Fangwen Zou
- Department of Oncology, Second Xiangya Hospital, Changsha, Hunan, China.,Department of Gastroenterology, Hepatology & Nutrition, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - David Faleck
- Department of Gastroenterology, Hepatology and Nutrition, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Anusha Thomas
- Department of Gastroenterology, Hepatology & Nutrition, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jessica Harris
- Department of Gastroenterology, Hepatology and Nutrition, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Deepika Satish
- Department of Gastroenterology, Hepatology and Nutrition, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Xuemei Wang
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Aline Charabaty
- Department of Gastroenterology, Johns Hopkins University, Washington, DC, USA
| | - Marc S Ernstoff
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland, USA
| | - Isabella C Glitza Oliva
- Department of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Stephen Hanauer
- Department of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Jennifer McQuade
- Department of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Michel Obeid
- Department of Medicine, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
| | - Amishi Shah
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - David M Richards
- Department of Gastroenterology, Hepatology & Nutrition, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Elad Sharon
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland, USA
| | - Jedd Wolchok
- Human Oncology and Pathogenesis Program, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - John Thompson
- University of Washington, Seattle Cancer Care Alliance, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Yinghong Wang
- Department of Gastroenterology, Hepatology & Nutrition, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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Casciato DJ, Yancovitz S, Law R, Thompson J, Barron I, Hyer C. Anatomic Description of the Fourth and Fifth Tarsometatarsal Articulation: A Cadaveric Study. J Foot Ankle Surg 2021; 60:1149-1151. [PMID: 34074589 DOI: 10.1053/j.jfas.2020.11.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 08/17/2020] [Accepted: 11/02/2020] [Indexed: 02/03/2023]
Abstract
The fourth and fifth tarsometatarsal joint, consisting of the fourth and fifth metatarsal and the cuboid, imparts a significant amount of motion to the foot during ambulation. Injury to this joint complex, through chronic deformation or acute trauma, often necessitates arthroplasty, arthrodesis, or fusion. Currently, there exists no studies that investigate the anatomy of this articulation. The purpose of this study is to describe the medial and lateral anterior cuboid articulations which allows for surgical planning and the advancement of hardware design. Twenty fresh-frozen below-the-knee cadaver legs were thawed and the cuboids were excised. The width and height of the entire joint complex were measured as the longest span across the total articular surface of the anterior cuboid. The width and height of each articular facet were recorded as the span across the geometric bisection of each individual surface. The mean anterior cuboid articulation width and height was 25.62 mm and 16.74 mm, respectively. The mean medial cuboid articulation width and height was 11.7mm and 13.65 mm, respectively. The mean lateral cuboid width and height was 16.74 mm and 12.78 mm, respectively. The medial articulation maintained a larger mean height and narrower mean width than the lateral facet (p < .05). The unique anatomy of the lateral tarsometatarsal joint complex plays an important functional role and requires attention when deciding between arthrodesis or arthroplasty. Increasing the understanding of the clinical anatomy of this joint will better prepare surgeons and product designers to anticipate hardware needs.
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Affiliation(s)
| | - Sara Yancovitz
- Resident Physician, OhioHealth Grant Medical Center, Columbus, OH
| | - Rona Law
- Fellow, Mon Valley Foot and Ankle Fellowship, Belle Vernon, PA
| | - John Thompson
- Resident Physician, OhioHealth Grant Medical Center, Columbus, OH
| | - Ian Barron
- Teaching Faculty, OhioHealth Grant Medical Center, Columbus, OH
| | - Christopher Hyer
- Fellowship Co-Director, Orthopedic Foot and Ankle Center, Worthington, OH
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Casciato DJ, Thompson J, Law R, Faherty M, Barron I, Thomas R. The July Effect in Podiatric Medicine and Surgery Residency. J Foot Ankle Surg 2021; 60:1152-1157. [PMID: 34078561 DOI: 10.1053/j.jfas.2021.04.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 01/26/2021] [Accepted: 04/22/2021] [Indexed: 02/03/2023]
Abstract
The period when medical students begin residency in teaching hospitals throughout the United States heralds a period known in the medical community as the "July Effect." Though several sentinel studies associated this timeframe with an increase in medical errors, residencies since demystified this phenomenon within their respective specialty. This study aims to evaluate the presence of the July Effect in a podiatric medicine and surgery residency program. A retrospective chart review was conducted, comparing patient demographics and surgical outcomes including length of stay, operative time and readmission rate between the first (July, August, September) and fourth (April, May June) quarters of the academic year from 2014-2019. A total of 206 patients met the inclusion criteria, where 99 received care in the first, resident-naïve, quarter and 107 received care in the fourth, resident-experienced, quarter. No difference in patient demographics including sex, body mass index, or comorbidity index was appreciated between both quarters (p<0.05). Those patients who underwent soft tissue and bone debridements, digital, forefoot, midfoot and rearfoot amputations experienced no statistically significant difference in length of stay, operative time, or readmission rate between both quarters (p<0.05). The results of this study did not support the presence of the July Effect in our foot and ankle surgery residency. Future studies can further explore this phenomenon by examining patients admitted following traumatic injury or elective procedures. Moreover, this study shows the curriculum employed at our program provides sufficient support, guidance, and resources to limit errors attributed to the July Effect.
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Affiliation(s)
- Dominick J Casciato
- Resident Physician, Medical Education Department, Grant Medical Center, Columbus, OH.
| | - John Thompson
- Resident Physician, Medical Education Department, Grant Medical Center, Columbus, OH
| | - Rona Law
- Fellow, Mon Valley Foot and Ankle Fellowship, Belle Vernon, PA
| | - Mallory Faherty
- OhioHealth Research Institute, Riverside Methodist Hospital, Columbus, OH
| | - Ian Barron
- Teaching Faculty, Medical Education Department, Grant Medical Center, Columbus, OH
| | - Randall Thomas
- Teaching Faculty, Medical Education Department, Grant Medical Center, Columbus, OH
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49
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Casciato DJ, Thompson J, Yancovitz S, Chandra A, Prissel MA, Hyer CF. Research Activity Among Foot and Ankle Surgery Fellows: A Systematic Review. J Foot Ankle Surg 2021; 60:1227-1231. [PMID: 34074588 DOI: 10.1053/j.jfas.2021.04.018] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 02/02/2021] [Accepted: 04/22/2021] [Indexed: 02/03/2023]
Abstract
Surgical residents cite a number of reasons to pursue a fellowship training program including improving surgical skills, furthering medical research, pursuing an academic practice, or to generally become an overall better trained surgeon and clinician. The interest in foot and ankle surgery fellowships has increased among graduating residents as have the number of fellowship programs. Since the introduction of these programs, there has been no formal investigation of the scholarly activity among foot and ankle surgery fellows. Using PubMed, a systematic review was conducted from papers published by fellows participating in American College of Foot and Ankle Surgeons or American Podiatric Medical Association approved fellowships during 2013 to 2019. A total of 76 of the 128 identified fellows published research during or within one year of completing their fellowship. Fellows that published at least once prior to fellowship were more likely to publish during fellowship compared to those who had no publication history. Over this 6-year period, fellows contributed to 279 manuscripts where they maintained primary authorship of 34.41% of the publications, across 35 journals, with the most common being the Journal of Foot and Ankle Surgery. Results of this study provide a survey of the scholastic activity among foot and ankle surgery fellows and could be used by applicants and evaluators to stratify applicant aptitude. These results could also serve as a scholarly activity benchmark for current fellows and a method of gauging scholarly involvement for new and current fellowships.
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Affiliation(s)
- Dominick J Casciato
- Resident Physician, Medical Education Department, Grant Medical Center, Columbus, OH.
| | - John Thompson
- Resident Physician, Medical Education Department, Grant Medical Center, Columbus, OH
| | - Sara Yancovitz
- Resident Physician, Medical Education Department, Grant Medical Center, Columbus, OH
| | - Amar Chandra
- Resident Physician, Medical Education Department, Grant Medical Center, Columbus, OH
| | - Mark A Prissel
- Fellowship Co-Director, Orthopedic Foot and Ankle Center, Worthington, OH
| | - Christopher F Hyer
- Fellowship Co-Director, Orthopedic Foot and Ankle Center, Worthington, OH
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Elfadaly FG, Adamson A, Patel J, Potts L, Potts J, Blangiardo M, Thompson J, Minelli C. BIMAM—a tool for imputing variables missing across datasets using a Bayesian imputation and analysis model. Int J Epidemiol 2021. [PMCID: PMC8580266 DOI: 10.1093/ije/dyab177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Motivation Combination of multiple datasets is routine in modern epidemiology. However, studies may have measured different sets of variables; this is often inefficiently dealt with by excluding studies or dropping variables. Multilevel multiple imputation methods to impute these ‘systematically’ missing data (as opposed to ‘sporadically’ missing data within a study) are available, but problems may arise when many random effects are needed to allow for heterogeneity across studies. We show that the Bayesian IMputation and Analysis Model (BIMAM) implemented in our tool works well in this situation. General features BIMAM performs imputation and analysis simultaneously. It imputes both binary and continuous systematically and sporadically missing data, and analyses binary and continuous outcomes. BIMAM is a user-friendly, freely available tool that does not require knowledge of Bayesian methods. BIMAM is an R Shiny application. It is downloadable to a local machine and it automatically installs the required freely available packages (R packages, including R2MultiBUGS and MultiBUGS). Availability BIMAM is available at [www.alecstudy.org/bimam].
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Affiliation(s)
- Fadlalla G Elfadaly
- School of Mathematics and Statistics, The Open University, Milton Keynes, UK
| | - Alex Adamson
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Jaymini Patel
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Laura Potts
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - James Potts
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Marta Blangiardo
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - John Thompson
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Cosetta Minelli
- National Heart and Lung Institute, Imperial College London, London, UK
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