Jonathan P Evans1, Chris D Smith2, Nicola F Fine2, Ian Porter3, Jaheeda Gangannagaripalli3, Victoria A Goodwin4, Jose M Valderas3. 1. Royal Devon and Exeter NHS Foundation Trust, Exeter, UK; Health Services and Policy Research Group, University of Exeter, Exeter, UK; National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) South West Peninsula, University of Exeter Medical School, Exeter, UK. Electronic address: j.evans3@exeter.ac.uk. 2. Royal Devon and Exeter NHS Foundation Trust, Exeter, UK. 3. Health Services and Policy Research Group, University of Exeter, Exeter, UK. 4. National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) South West Peninsula, University of Exeter Medical School, Exeter, UK.
Abstract
BACKGROUND: Clinical rating systems are used as outcome measures in clinical trials and attempt to gauge the patient's view of his or her own health. The choice of clinical rating system should be supported by its performance against established quality standards. METHODS: A search strategy was developed to identify all studies that reported the use of clinical rating systems in the elbow literature. The strategy was run from inception in Medline Embase and CINHAL. Data extraction identified the date of publication, country of data collection, pathology assessed, and the outcome measure used. RESULTS: We identified 980 studies that reported clinical rating system use. Seventy-two separate rating systems were identified. Forty-one percent of studies used ≥2 separate measures. Overall, 54% of studies used the Mayo Elbow Performance Score (MEPS). For arthroplasty, 82% used MEPS, 17% used Disabilities of Arm, Shoulder and Hand (DASH), and 7% used QuickDASH. For trauma, 66.7% used MEPS, 32% used DASH, and 23% used the Morrey Score. For tendinopathy, 31% used DASH, 23% used Patient-Rated Tennis Elbow Evaluation (PRTEE), and 13% used MEPS. Over time, there was an increased proportional use of the MEPS, DASH, QuickDASH, PRTEE, and the Oxford Elbow Score. CONCLUSIONS: This study identified a wide choice and usage of clinical rating systems in the elbow literature. Numerous studies reported measures without a history of either a specific pathology or cross-cultural validation. Interpretability and comparison of outcomes is dependent on the unification of outcome measure choice. This was not demonstrated currently.
BACKGROUND: Clinical rating systems are used as outcome measures in clinical trials and attempt to gauge the patient's view of his or her own health. The choice of clinical rating system should be supported by its performance against established quality standards. METHODS: A search strategy was developed to identify all studies that reported the use of clinical rating systems in the elbow literature. The strategy was run from inception in Medline Embase and CINHAL. Data extraction identified the date of publication, country of data collection, pathology assessed, and the outcome measure used. RESULTS: We identified 980 studies that reported clinical rating system use. Seventy-two separate rating systems were identified. Forty-one percent of studies used ≥2 separate measures. Overall, 54% of studies used the Mayo Elbow Performance Score (MEPS). For arthroplasty, 82% used MEPS, 17% used Disabilities of Arm, Shoulder and Hand (DASH), and 7% used QuickDASH. For trauma, 66.7% used MEPS, 32% used DASH, and 23% used the Morrey Score. For tendinopathy, 31% used DASH, 23% used Patient-Rated Tennis Elbow Evaluation (PRTEE), and 13% used MEPS. Over time, there was an increased proportional use of the MEPS, DASH, QuickDASH, PRTEE, and the Oxford Elbow Score. CONCLUSIONS: This study identified a wide choice and usage of clinical rating systems in the elbow literature. Numerous studies reported measures without a history of either a specific pathology or cross-cultural validation. Interpretability and comparison of outcomes is dependent on the unification of outcome measure choice. This was not demonstrated currently.
Authors: A Papen; T Schöttker-Königer; A Schäfer; F Morrison; B Hollinger; K J Burkhart; R Nietschke; A Zimmerer; N Maffulli; F Migliorini; Marco M Schneider Journal: J Orthop Surg Res Date: 2022-06-25 Impact factor: 2.677
Authors: Phoebe Parker; Nicholas D Furness; Jonathan P Evans; Timothy Batten; William J White; Christopher D Smith Journal: Shoulder Elbow Date: 2020-02-25
Authors: Marcus Bateman; Jonathan P Evans; Viana Vuvan; Val Jones; Adam C Watts; Joideep Phadnis; Leanne Bisset; Bill Vicenzino Journal: Trials Date: 2021-05-10 Impact factor: 2.279
Authors: Marcus Bateman; Jonathan P Evans; Viana Vuvan; Val Jones; Adam C Watts; Joideep Phadnis; Leanne M Bisset; Bill Vicenzino Journal: Br J Sports Med Date: 2022-02-08 Impact factor: 18.473
Authors: Sara Padovani; Maurizia Capuzzo; Leo Massari; Gaetano Caruso; Paolo Arrigoni; Carlo Zaolino; Davide Cucchi; Giorgia Valpiani; Alessandra Colozza Journal: JSES Int Date: 2021-02-06
Authors: Arno A Macken; Ante Prkić; Niels Vermeulen; Iris van Oost; Koen L M Koenraadt; Bertram The; Denise Eygendaal Journal: JSES Int Date: 2021-04-16