BACKGROUND: It is unknown which combination of patient information and clinical tests might be optimal for the diagnosis of traumatic anterior shoulder instability. This study aimed to determine the diagnostic value of individual clinical tests and to develop a prediction model that combined patient characteristics, history, and clinical tests for diagnosis of traumatic anterior shoulder instability. MATERIALS AND METHODS: This prospective cohort study included 169 consecutive patients with shoulder complaints who were examined at an orthopaedic outpatient clinic. One experienced clinician conducted 25 clinical tests; of these, 6 were considered to be specific for testing of traumatic anterior shoulder instability (apprehension, relocation, release, anterior drawer, load and shift, and hyperabduction tests). Magnetic resonance arthrography was used to determine the final diagnosis. A prediction model was developed by logistic regression analysis. RESULTS: In this cohort, 60 patients (36%) were diagnosed with anterior shoulder instability on the basis of magnetic resonance arthrography. The overall accuracy of individual clinical tests was 80.5% to 86.4%. Age, previous shoulder dislocation, sudden onset of complaints, and the release test were important predictors for the diagnosis of traumatic anterior shoulder instability. The prediction model demonstrated high discriminative ability (AUC 0.95). CONCLUSION: Individual clinical shoulder tests provide good diagnostic accuracy. Young age, history of shoulder dislocation, sudden onset of complaints, and positive result of the release test were the most important predictors for traumatic anterior shoulder instability.
BACKGROUND: It is unknown which combination of patient information and clinical tests might be optimal for the diagnosis of traumatic anterior shoulder instability. This study aimed to determine the diagnostic value of individual clinical tests and to develop a prediction model that combined patient characteristics, history, and clinical tests for diagnosis of traumatic anterior shoulder instability. MATERIALS AND METHODS: This prospective cohort study included 169 consecutive patients with shoulder complaints who were examined at an orthopaedic outpatient clinic. One experienced clinician conducted 25 clinical tests; of these, 6 were considered to be specific for testing of traumatic anterior shoulder instability (apprehension, relocation, release, anterior drawer, load and shift, and hyperabduction tests). Magnetic resonance arthrography was used to determine the final diagnosis. A prediction model was developed by logistic regression analysis. RESULTS: In this cohort, 60 patients (36%) were diagnosed with anterior shoulder instability on the basis of magnetic resonance arthrography. The overall accuracy of individual clinical tests was 80.5% to 86.4%. Age, previous shoulder dislocation, sudden onset of complaints, and the release test were important predictors for the diagnosis of traumatic anterior shoulder instability. The prediction model demonstrated high discriminative ability (AUC 0.95). CONCLUSION: Individual clinical shoulder tests provide good diagnostic accuracy. Young age, history of shoulder dislocation, sudden onset of complaints, and positive result of the release test were the most important predictors for traumatic anterior shoulder instability.
Authors: Michael James; Cory A Kwong; Kristie D More; Justin LeBlanc; Ian K Y Lo; Aaron J Bois Journal: Am J Sports Med Date: 2022-03-31 Impact factor: 7.010
Authors: Henrik Eshoj; Kim Gordon Ingwersen; Camilla Marie Larsen; Birgitte Hougs Kjaer; Birgit Juul-Kristensen Journal: BMJ Open Date: 2018-03-03 Impact factor: 2.692
Authors: Derk A van Kampen; Tobias van den Berg; Henk Jan van der Woude; Rene M Castelein; Vanessa A B Scholtes; Caroline B Terwee; W Jaap Willems Journal: J Orthop Surg Res Date: 2014-08-07 Impact factor: 2.359
Authors: Hanneke Weel; Wouter Tromp; Peter R Krekel; Pietro Randelli; Michel P J van den Bekerom; Derek F P van Deurzen Journal: Arch Orthop Trauma Surg Date: 2016-03-14 Impact factor: 3.067
Authors: Sarah A Warby; Jon J Ford; Andrew J Hahne; Lyn Watson; Simon Balster; Ross Lenssen; Tania Pizzari Journal: BMJ Open Date: 2016-09-12 Impact factor: 2.692
Authors: André Couto Godinho; Pedro Couto Godinho; Elísio José Salgado Ribeiro; Daniel Carvalho de Toledo; Frederico de Menezes Figueiredo Couto Bem; Armando D'Lucca de Castro E Silva; Glaydson Gomes Godinho Journal: JSES Int Date: 2021-04-28