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Tong J, Shen Y, Xu A, He X, Luo C, Edmondson M, Zhang D, Lu Y, Yan C, Li R, Siegel L, Sun L, Shenkman EA, Morton SC, Malin BA, Bian J, Asch DA, Chen Y. Evaluating site-of-care-related racial disparities in kidney graft failure using a novel federated learning framework. J Am Med Inform Assoc 2024:ocae075. [PMID: 38713006 DOI: 10.1093/jamia/ocae075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 01/09/2024] [Accepted: 03/26/2024] [Indexed: 05/08/2024] Open
Abstract
OBJECTIVES Racial disparities in kidney transplant access and posttransplant outcomes exist between non-Hispanic Black (NHB) and non-Hispanic White (NHW) patients in the United States, with the site of care being a key contributor. Using multi-site data to examine the effect of site of care on racial disparities, the key challenge is the dilemma in sharing patient-level data due to regulations for protecting patients' privacy. MATERIALS AND METHODS We developed a federated learning framework, named dGEM-disparity (decentralized algorithm for Generalized linear mixed Effect Model for disparity quantification). Consisting of 2 modules, dGEM-disparity first provides accurately estimated common effects and calibrated hospital-specific effects by requiring only aggregated data from each center and then adopts a counterfactual modeling approach to assess whether the graft failure rates differ if NHB patients had been admitted at transplant centers in the same distribution as NHW patients were admitted. RESULTS Utilizing United States Renal Data System data from 39 043 adult patients across 73 transplant centers over 10 years, we found that if NHB patients had followed the distribution of NHW patients in admissions, there would be 38 fewer deaths or graft failures per 10 000 NHB patients (95% CI, 35-40) within 1 year of receiving a kidney transplant on average. DISCUSSION The proposed framework facilitates efficient collaborations in clinical research networks. Additionally, the framework, by using counterfactual modeling to calculate the event rate, allows us to investigate contributions to racial disparities that may occur at the level of site of care. CONCLUSIONS Our framework is broadly applicable to other decentralized datasets and disparities research related to differential access to care. Ultimately, our proposed framework will advance equity in human health by identifying and addressing hospital-level racial disparities.
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Affiliation(s)
- Jiayi Tong
- The Center for Health AI and Synthesis of Evidence (CHASE), Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA 19104, United States
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Yishan Shen
- The Center for Health AI and Synthesis of Evidence (CHASE), Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA 19104, United States
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA 19104, United States
- Applied Mathematics and Computational Science, The University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Alice Xu
- The Center for Health AI and Synthesis of Evidence (CHASE), Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA 19104, United States
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA 19104, United States
- Washington University in St. Louis, St. Louis, MO 63130, United States
| | - Xing He
- Department of Health Outcomes & Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32611, United States
| | - Chongliang Luo
- Division of Public Health Sciences, Department of Surgery, Washington University in St. Louis, St. Louis, MO 63110, United States
| | | | - Dazheng Zhang
- The Center for Health AI and Synthesis of Evidence (CHASE), Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA 19104, United States
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Yiwen Lu
- The Center for Health AI and Synthesis of Evidence (CHASE), Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA 19104, United States
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Chao Yan
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, United States
| | - Ruowang Li
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States
| | - Lianne Siegel
- Division of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, MN 55414, United States
| | - Lichao Sun
- Department of Computer Science and Engineering, Lehigh University, Bethlehem, PA 18015, United States
| | - Elizabeth A Shenkman
- Department of Health Outcomes & Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32611, United States
| | - Sally C Morton
- School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ 85287, United States
| | - Bradley A Malin
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, United States
- Department of Computer Science, Vanderbilt University, Nashville, TN 37212, United States
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN 37203, United States
| | - Jiang Bian
- Department of Health Outcomes & Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32611, United States
| | - David A Asch
- Division of General Internal Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
- Leonard Davis Institute of Health Economics, Philadelphia, PA 19104, United States
| | - Yong Chen
- The Center for Health AI and Synthesis of Evidence (CHASE), Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA 19104, United States
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA 19104, United States
- Applied Mathematics and Computational Science, The University of Pennsylvania, Philadelphia, PA 19104, United States
- Leonard Davis Institute of Health Economics, Philadelphia, PA 19104, United States
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2
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Ledermann JA, Shapira-Frommer R, Santin AD, Lisyanskaya AS, Pignata S, Vergote I, Raspagliesi F, Sonke GS, Birrer M, Provencher DM, Sehouli J, Colombo N, González-Martín A, Oaknin A, Ottevanger PB, Rudaitis V, Kobie J, Nebozhyn M, Edmondson M, Sun Y, Cristescu R, Jelinic P, Keefe SM, Matulonis UA. Molecular determinants of clinical outcomes of pembrolizumab in recurrent ovarian cancer: Exploratory analysis of KEYNOTE-100. Gynecol Oncol 2023; 178:119-129. [PMID: 37862791 DOI: 10.1016/j.ygyno.2023.09.012] [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: 06/22/2023] [Revised: 09/15/2023] [Accepted: 09/23/2023] [Indexed: 10/22/2023]
Abstract
OBJECTIVE This prespecified exploratory analysis evaluated the association of gene expression signatures, tumor mutational burden (TMB), and multiplex immunohistochemistry (mIHC) tumor microenvironment-associated cell phenotypes with clinical outcomes of pembrolizumab in advanced recurrent ovarian cancer (ROC) from the phase II KEYNOTE-100 study. METHODS Pembrolizumab-treated patients with evaluable RNA-sequencing (n = 317), whole exome sequencing (n = 293), or select mIHC (n = 125) data were evaluated. The association between outcomes (objective response rate [ORR], progression-free survival [PFS], and overall survival [OS]) and gene expression signatures (T-cell-inflamed gene expression profile [TcellinfGEP] and 10 non-TcellinfGEP signatures), TMB, and prespecified mIHC cell phenotype densities as continuous variables was evaluated using logistic (ORR) and Cox proportional hazards regression (PFS; OS). One-sided p-values were calculated at prespecified α = 0.05 for TcellinfGEP, TMB, and mIHC cell phenotypes and at α = 0.10 for non-TcellinfGEP signatures; all but TcellinfGEP and TMB were adjusted for multiplicity. RESULTS No evidence of associations between ORR and key axes of gene expression was observed. Negative associations were observed between outcomes and TcellinfGEP-adjusted glycolysis (PFS, adjusted-p = 0.019; OS, adjusted-p = 0.085) and hypoxia (PFS, adjusted-p = 0.064) signatures. TMB as a continuous variable was not associated with outcomes (p > 0.05). Positive associations were observed between densities of myeloid cell phenotypes CD11c+ and CD11c+/MHCII-/CD163-/CD68- in the tumor compartment and ORR (adjusted-p = 0.025 and 0.013, respectively). CONCLUSIONS This exploratory analysis in advanced ROC did not find evidence for associations between gene expression signatures and outcomes of pembrolizumab. mIHC analysis suggests CD11c+ and CD11c+/MHCII-/CD163-/CD68- phenotypes representing myeloid cell populations may be associated with improved outcomes with pembrolizumab in advanced ROC. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov, NCT02674061.
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Affiliation(s)
- Jonathan A Ledermann
- Department of Oncology, UCL Cancer Institute, University College London, London, United Kingdom.
| | - Ronnie Shapira-Frommer
- The Ella Lemelbaum Institute for Immuno-Oncology, Sheba Medical Center, Tel HaShomer Hospital, Ramat Gan, Israel
| | - Alessandro D Santin
- Department of Obstetrics, Gynecology, and Reproductive Sciences, Yale University, New Haven, CT, United States
| | - Alla S Lisyanskaya
- Department of Oncogynecology, St. Petersburg City Clinical Oncology Dispensary, St. Petersburg, Russia
| | - Sandro Pignata
- Department of Urology and Gynecology, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale, Naples, Italy
| | - Ignace Vergote
- Department of Obstetrics and Gynaecology, Division of Gynecologic Oncology, University Hospital Leuven, Leuven, Belgium
| | | | - Gabe S Sonke
- Department of Medical Oncology, Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Michael Birrer
- UAMS Winthrop P. Rockefeller Cancer Institute, Little Rock, AR, United States
| | - Diane M Provencher
- Centre Hospitalier de l'Université de Montréal (CHUM), Institut du Cancer de Montréal, Montreal, Canada
| | - Jalid Sehouli
- Gynecology with Center of Oncological Surgery, Charité-Medical University of Berlin, Berlin, Germany
| | - Nicoletta Colombo
- Department of Medicine and Surgery, University of Milan-Bicocca, Milan, Italy; European Institute of Oncology, IRCCS, Milan, Italy
| | - Antonio González-Martín
- Department of Medical Oncology and Program in Solid Tumors-Cima, Cancer Center Clínica Universidad de Navarra, Madrid, Spain
| | - Ana Oaknin
- Vall d'Hebron University Hospital, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | - P B Ottevanger
- Medical Oncology, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Vilius Rudaitis
- Clinic of Obstetrics and Gynecology, Vilnius University Institute of Clinical Medicine, Vilnius, Lithuania
| | - Julie Kobie
- Merck & Co., Inc., Rahway, NJ, United States
| | | | | | - Yuan Sun
- Merck & Co., Inc., Rahway, NJ, United States
| | | | | | | | - Ursula A Matulonis
- Division of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States
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3
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Hoyos-Jaramillo A, Palomares R, Bittar J, Divers S, Chamorro M, Berghaus R, Kirks S, Rush J, Edmondson M, Rodriguez A, Gonzalez-Altamiranda E. Clinical status and endoscopy of the upper respiratory tract of dairy calves infected with Bovine viral diarrhea virus 2 and Bovine herpes virus 1 after vaccination and trace minerals injection. Res Vet Sci 2022; 152:582-595. [DOI: 10.1016/j.rvsc.2022.09.026] [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] [Received: 05/31/2022] [Revised: 09/19/2022] [Accepted: 09/23/2022] [Indexed: 11/24/2022]
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Luo C, Islam MN, Sheils NE, Buresh J, Reps J, Schuemie MJ, Ryan PB, Edmondson M, Duan R, Tong J, Marks-Anglin A, Bian J, Chen Z, Duarte-Salles T, Fernández-Bertolín S, Falconer T, Kim C, Park RW, Pfohl SR, Shah NH, Williams AE, Xu H, Zhou Y, Lautenbach E, Doshi JA, Werner RM, Asch DA, Chen Y. DLMM as a lossless one-shot algorithm for collaborative multi-site distributed linear mixed models. Nat Commun 2022; 13:1678. [PMID: 35354802 PMCID: PMC8967932 DOI: 10.1038/s41467-022-29160-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 03/03/2022] [Indexed: 12/21/2022] Open
Abstract
Linear mixed models are commonly used in healthcare-based association analyses for analyzing multi-site data with heterogeneous site-specific random effects. Due to regulations for protecting patients’ privacy, sensitive individual patient data (IPD) typically cannot be shared across sites. We propose an algorithm for fitting distributed linear mixed models (DLMMs) without sharing IPD across sites. This algorithm achieves results identical to those achieved using pooled IPD from multiple sites (i.e., the same effect size and standard error estimates), hence demonstrating the lossless property. The algorithm requires each site to contribute minimal aggregated data in only one round of communication. We demonstrate the lossless property of the proposed DLMM algorithm by investigating the associations between demographic and clinical characteristics and length of hospital stay in COVID-19 patients using administrative claims from the UnitedHealth Group Clinical Discovery Database. We extend this association study by incorporating 120,609 COVID-19 patients from 11 collaborative data sources worldwide. A lossless, one-shot and privacy-preserving distributed algorithm was revealed for fitting linear mixed models on multi-site data. The algorithm was applied to a study of 120,609 COVID-19 patients using only minimal aggregated data from each of 14 sites.
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Affiliation(s)
- Chongliang Luo
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA.,Division of Public Health Sciences, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | | | | | | | - Jenna Reps
- Janssen Research and Development LLC, Titusville, NJ, USA
| | | | - Patrick B Ryan
- Janssen Research and Development LLC, Titusville, NJ, USA
| | - Mackenzie Edmondson
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Rui Duan
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA.,Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jiayi Tong
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Arielle Marks-Anglin
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Jiang Bian
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Zhaoyi Chen
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Talita Duarte-Salles
- Fundacio Institut Universitari per a la recerca a l'Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Sergio Fernández-Bertolín
- Fundacio Institut Universitari per a la recerca a l'Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Thomas Falconer
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - Chungsoo Kim
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Republic of Korea
| | - Rae Woong Park
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Republic of Korea.,Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Republic of Korea
| | - Stephen R Pfohl
- Stanford Center for Biomedical Informatics Research, Stanford, CA, USA
| | - Nigam H Shah
- Stanford Center for Biomedical Informatics Research, Stanford, CA, USA
| | - Andrew E Williams
- Institute for Clinical Research and Health Policy Studies, Tufts University School of Medicine, Boston, MA, USA
| | - Hua Xu
- School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Yujia Zhou
- School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Ebbing Lautenbach
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA.,Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jalpa A Doshi
- Division of General Internal Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Leonard Davis Institute of Health Economics, Philadelphia, PA, USA
| | - Rachel M Werner
- Division of General Internal Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Leonard Davis Institute of Health Economics, Philadelphia, PA, USA.,Cpl Michael J Crescenz VA Medical Center, Philadelphia, PA, USA
| | - David A Asch
- Division of General Internal Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Leonard Davis Institute of Health Economics, Philadelphia, PA, USA
| | - Yong Chen
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA.
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5
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Ngo V, Chan G, Edmondson M. 470 Financial and Efficacy Analysis of a Centralised Neck of Femur Fracture Service. Br J Surg 2021. [DOI: 10.1093/bjs/znab259.991] [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]
Abstract
Abstract
Aim
Osteoporotic fractures are rising in incidence, costing the National Health Service up to £1.1 billion for hospital care. The implementation of the Best Practice Tariff (BPT) of fragility fractures in 2010 created a financial incentive to achieve standards of best practice. In June 2015, a dedicated hip fracture unit (HFU) was set up at Princess Royal Hospital (PRH). The aim of this study is (A) to assess changes in performance to the BPT after the introduction of a dedicated HFU, and (B) whether the performance of a HFU is affected by direct/indirect presentation to the HFU.
Method
The performance of Brighton and Sussex University Hospitals (BSUH) to BPT pre and post HFU was assessed by a retrospective review of BPT performance data between 2015 and 2016. 870 patients who were treated for NOFF at BSUH were reviewed to assess whether the performance of the HFU was impacted by patients presenting either directly (PRH) to the HFU or indirectly (presentation to Royal Sussex County Hospital). Appropriate statistical tests were used to analyse the significant differences between these outcome measures.
Results
The comparison between pre and post HFU showed there was a significant increase in the time between A&E admission to ward, theatre or orthogeriatric (OG) assessment (P < 0.001) in patients presenting indirectly to HFU compared to direct presentations.
Conclusions
Having a HFU is cost neutral, and advantages of HFU include focusing NOFF care which improves in patient care. BPT achievements could be improved by increasing the direct admission of NOFF to the HFU.
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Affiliation(s)
- V Ngo
- Brighton and Sussex University Hospital, Brighton, United Kingdom
| | - G Chan
- Brighton and Sussex University Hospital, Brighton, United Kingdom
| | - M Edmondson
- Brighton and Sussex University Hospital, Brighton, United Kingdom
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Quayle J, Barakat A, Klasan A, Mittal A, Chan G, Gibbs J, Edmondson M, Stott P. Management of peri-prosthetic joint infection and severe bone loss after total hip arthroplasty using a long-stemmed cemented custom-made articulating spacer (CUMARS). BMC Musculoskelet Disord 2021; 22:358. [PMID: 33863329 PMCID: PMC8052787 DOI: 10.1186/s12891-021-04237-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 04/09/2021] [Indexed: 02/02/2023] Open
Abstract
Background There is little evidence on techniques for management of peri-prosthetic infection (PJI) in the context of severe proximal femoral bone loss. Custom-made articulating spacers (CUMARS) utilising cemented femoral stems as spacers was described providing better bone support and longer survival compared to conventional articulating spacers. We retrospectively report our experience managing PJI by adaptation of this technique using long cemented femoral stems where bone loss precludes use of standard stems. Methods Patients undergoing 1st stage revision for infected primary and revision THA using a cemented long stem (> 205 mm) and standard all-polyethylene acetabulum between 2011 and 2018 were identified. After excluding other causes of revision (fractures or aseptic loosening), Twenty-one patients remained out of total 721 revisions. Medical records were assessed for demographics, initial microbiological and operative treatment, complications, eradication of infection and subsequent operations. 2nd stage revision was undertaken in the presence of pain or subsidence. Results Twenty-one patients underwent 1st stage revision with a cemented long femoral stem. Mean follow up was 3.9 years (range 1.7–7.2). Infection was eradicated in 15 (71.4%) patients. Two patients (9.5%) required repeat 1st stage and subsequently cleared their infection. Three patients (14.3%) had chronic infection and are on long term suppressive antibiotics. One patient (4.8%) was lost to follow up before 2 years. Complications occurred in seven patients (33%) during or after 1st stage revision. Where infection was cleared, 2nd stage revision was undertaken in 12 patients (76.5%) at average of 9 months post 1st stage. Five (23.8%) CUMARS constructs remained in-situ at an average of 3.8 years post-op (range 2.6–5.1). Conclusions Our technique can be used in the most taxing of reconstructive scenarios allowing mobility, local antibiotic delivery, maintenance of leg length and preserves bone and soft tissue, factors not afforded by alternative spacer options.
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Affiliation(s)
- J Quayle
- Brighton and Sussex University Hospitals, Brighton, UK.
| | - A Barakat
- Brighton and Sussex University Hospitals, Brighton, UK
| | - A Klasan
- Department for Orthopaedics and Traumatology, Kepler University Hospital GmbH, Krankenhausstrasse 9, 4020, Linz, Austria.,Johannes Kepler University Linz, Altenberger Strasse 69, 4040, Linz, Austria
| | - A Mittal
- Brighton and Sussex University Hospitals, Brighton, UK
| | - G Chan
- Brighton and Sussex University Hospitals, Brighton, UK
| | - J Gibbs
- Brighton and Sussex University Hospitals, Brighton, UK
| | - M Edmondson
- Brighton and Sussex University Hospitals, Brighton, UK
| | - P Stott
- Brighton and Sussex University Hospitals, Brighton, UK
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7
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Walton TJ, Bellringer SF, Edmondson M, Stott P, Rogers BA. Does a dedicated hip fracture unit improve clinical outcomes? A five-year case series. Ann R Coll Surg Engl 2019; 101:215-519. [PMID: 30602304 PMCID: PMC6400913 DOI: 10.1308/rcsann.2018.0220] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/04/2018] [Indexed: 11/22/2022] Open
Abstract
INTRODUCTION The aim of the study was to establish whether a dedicated hip fracture unit, geographically separate from the local major trauma centre, could improve clinical outcomes for patients sustaining proximal femoral fragility fractures. MATERIALS AND METHODS This study was a retrospective case series, using data collected from Brighton and Sussex University Hospitals NHS Trust's submissions to the National Hip Fracture Database between 1 April 2011 and 16 September 2016. The outcomes measured were mortality, length of hospital stay, time from admission to surgical intervention and return to premorbid residence. Patients were compared before and after reconfiguration of services into a separate dedicated hip fracture unit geographically distinct from the major trauma centre. RESULTS A total of 2117 patients (2178 injuries) were managed before the existence of the hip fracture unit, while 660 patients (673 injuries) were treated within the hip fracture unit. During the five-year study period, the 30-day mortality rate (pre-hip fracture unit 5.47% vs hip fracture unit 3.13%, P = 0.014), variance in the length of hospital stay (P < 0.001), mean time to surgical intervention (P = 0.044) and return to premorbid residence were significantly improved. An immediate 12-month comparison demonstrated significantly improved variance in length of hospital stay (P = 0.020) and return to premorbid residence (P = 0.015). DISCUSSION The reconfiguration of services significantly reduced variance in length of stay, enabling accurate resource planning in future. Multiple incremental improvements in service provision, in addition to the hip fracture unit, may explain the lower mortality observed. CONCLUSION While further research is required, replication of the hip fracture unit service model may potentially afford significant clinical and financial gains.
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Affiliation(s)
- TJ Walton
- Trauma and Orthopaedics, Brighton and Sussex University Hospitals NHS Trust, Brighton, UK
| | - SF Bellringer
- Trauma and Orthopaedics, Brighton and Sussex University Hospitals NHS Trust, Brighton, UK
| | - M Edmondson
- Trauma and Orthopaedics, Brighton and Sussex University Hospitals NHS Trust, Brighton, UK
| | - P Stott
- Trauma and Orthopaedics, Brighton and Sussex University Hospitals NHS Trust, Brighton, UK
| | - BA Rogers
- Trauma and Orthopaedics, Brighton and Sussex University Hospitals NHS Trust, Brighton, UK
- Brighton and Sussex Medical School, Brighton, UK
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8
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Morley R, Edmondson M, Dovell G, Blencowe N, Main B, Blazeby J, Hinchliffe R. #16 The introduction and evolution of an innovative endovascular device for venous arterialisation: A systematic analysis of current practice (poster presentation). Int J Surg 2018. [DOI: 10.1016/j.ijsu.2018.10.017] [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: 10/27/2022]
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9
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Edmondson M, Atrey A, East D, Ellens N, Miles K, Goddard R, Apthorp H, Butler-Manuel A. Survival analysis and functional outcome of the Oxford unicompartmental knee replacement up to 11 years follow up at a District General Hospital. J Orthop 2015; 12:S105-10. [PMID: 26719619 DOI: 10.1016/j.jor.2013.12.007] [Citation(s) in RCA: 9] [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: 09/12/2013] [Accepted: 12/07/2013] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND There have been several large originator studies reporting excellent results with this prosthesis but far fewer large independent studies. We present, to our knowledge, the largest independent series documenting excellent survivorship rates and good functional outcomes at a mean follow up of 5.5 years post implantation of the Oxford unicompartmental knee replacement. METHODS Our prospective study looks at the survivorship and the functional outcome of 364 Oxford UKRs performed in a district general hospital at a mean follow up of 5.5 years (range 5-11 years). Post operatively knees were assessed in a research clinic using the Oxford knees score (as well as the American Knee Society Score and the Hospital for Special Surgery Score). Maximal flexion was also measured. RESULTS There were 26 revisions of 364 knees giving a survivorship, with revision as the end point, of 93% at a mean of 5.5 years post op (range 5-11 years). We achieved an Oxford score of 37.5, a mean AKSS of 161 (divided as American knee functional score 75.75/American knee objective score 85.4 (excellent)). The mean HSS score was 84.5. We achieved 'Excellent' Oxford knee scores in 137 knees (48%), 'Good' in 75 (26%), 'Moderate' in 51 (17%) and 'Poor' in only 27 (9%) of knees. Mean improvement in functional scores were: Oxford score (14.4), AKSS (71) and HSS (26.3). Mean maximal flexion was 123° range (110-140). CONCLUSIONS We have confirmed that good medium to long-term function and survival can be obtained following Oxford medial knee replacement for treating anteromedial osteoarthritis, in our large independent series.
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Affiliation(s)
| | - A Atrey
- Conquest Hospital, East Sussex TN37 7RD, UK
| | - D East
- Conquest Hospital, East Sussex TN37 7RD, UK
| | - N Ellens
- Conquest Hospital, East Sussex TN37 7RD, UK
| | - K Miles
- Conquest Hospital, East Sussex TN37 7RD, UK
| | - R Goddard
- Conquest Hospital, East Sussex TN37 7RD, UK
| | - H Apthorp
- Conquest Hospital, East Sussex TN37 7RD, UK
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Davey RJ, Hilton AM, Garside J, de la Fuente M, Edmondson M, Rainsford P. Crystallisation of oil-in-water emulsions. Amphiphile directed nucleation in aqueous emulsions of m-chloronitrobenzene. ACTA ACUST UNITED AC 1996. [DOI: 10.1039/ft9969201927] [Citation(s) in RCA: 19] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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Abstract
The number of surgical procedures being performed as day cases is increasing. In an attempt to ensure that patients are given the chance to present their views of this developing service, one unit has set up an innovative project to allow patients to voice any dissatisfactions directly to the staff. The project has led to several changes being made and increased satisfaction for both staff and patients.
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Edmondson M. A short stopover. Nurs Times 1988; 84:31-2. [PMID: 3205788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
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Milam H, Evans JW, Elliott JP, Platt LO, Gordon JO, Brasfield D, Trapp J, Edmondson M. Percutaneous renal calculi removal. J Miss State Med Assoc 1984; 25:287-90. [PMID: 6502702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
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Edmondson M, Rambo M. Child restraints: the name of the game is saving children's lives. Ky Nurse 1984; 32:15-6. [PMID: 6565127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 04/05/2023]
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