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Diagnostic classification of shoulder disorders: interobserver agreement and determinants of disagreement
A F de Winter1, M P Jans, R J Scholten
1Institute for Research in Extramural Medicine, Vrije Universiteit, Amsterdam, the Netherlands.
Objectives:
To assess the interobserver agreement on the diagnostic classification of shoulder disorders, based on history taking and physical examination, and to identify the determinants of diagnostic disagreement.
Methods:
Consecutive eligible patients with shoulder pain were recruited in various health care settings in the Netherlands. After history taking, two physiotherapists independently performed a physical examination and subsequently the shoulder complaints were classified into one of six diagnostic categories: capsular syndrome (for example, capsulitis, arthritis), acute bursitis, acromioclavicular syndrome, subacromial syndrome (for example, tendinitis, chronic bursitis), rest group (for example, unclear clinical picture, extrinsic causes) and mixed clinical picture. To quantify the interobserver agreement Cohen's kappa was calculated. Multivariate logistic regression analysis was applied to determine which clinical characteristics were determinants of diagnostic disagreement.
Results:
The study population consisted of 201 patients with varying severity and duration of complaints. The kappa for the classification of shoulder disorders was 0.45 (95% confidence intervals (CI) 0.37, 0.54). Diagnostic disagreement was associated with bilateral involvement (odds ratio (OR) 1.9; 95% CI 1.0, 3.7), chronic complaints (OR 2.0; 95% CI 1.1, 3.7), and severe pain (OR 2.7; 95% CI 1.3, 5.3).
Conclusions:
Only moderate agreement was found on the classification of shoulder disorders, which implies that differentiation between the various categories of shoulder disorders is complicated. Especially patients with high pain severity, chronic complaints and bilateral involvement represent a diagnostic challenge for clinicians. As diagnostic classification is a guide for treatment decisions, unsatisfactory reproducibility might affect treatment outcome. To improve the reproducibility, more insight into the reproducibility of clinical findings and the value of additional diagnostic procedures is needed.