Knee disorders are highly prevalent and may be a disabling condition. An accurate diagnosis is necessary to guide toward a rapid and efficient management of knee disorders. However, the ability to make a valid diagnosis is often complex for clinicians and evidence is mainly focused on clinician cognitive biases or errors produced during clinical reasoning. The aim of this secondary exploratory analysis is to identify patient-specific characteristics associated with diagnostic discordance between health care providers in making a diagnosis for a new knee disorder.
We performed a secondary analysis of a diagnostic study comparing the diagnostic ability of a physiotherapist to medical musculoskeletal specialists. Patients' socio-demographic, psychosocial and clinical characteristics were compared between the concordant and discordant diagnostic groups. Psychosocial symptoms were evaluated using the validated Kessler 6 (K6) questionnaire. We performed multivariable logistic regressions using the Bayesian Information Criterion to identify the most probable model including patients' characteristics associated with diagnostic discordance. Overall probability of identified variables to explain diagnostic discordance and associated odd ratios (OR) with 95% credibility intervals (95% CrI) were calculated.
Overall, 279 participants were evaluated by a physiotherapist and medical musculoskeletal specialists. The mean age of the participants was 49.1 ± 15.8 years and 57.7% were female. The most common disorder was osteoarthritis (n = 117, 18.8% of cases were discordant). The most probable model explaining diagnostic discordance (11.13%) included having depressive symptoms, which was associated with an increased probability of diagnostic discordance (OR: 3.9; 95% CrI: 1.9 - 8.0) and having a higher number of comorbidities, which was associated with a decreased probability of diagnostic discordance (OR: 0.6; 95% CrI: 0.5 - 0.9). The depression item of the K6 questionnaire had a 99.4% chance to be included in a model explaining diagnostic discordance. Other variables taken separately had less than 50% chance to be included in a model explaining diagnostic discordance and cannot be considered significant.
Our results suggest that depressive symptoms may increase the risk of knee diagnostic discordance. Clinicians may be more likely to make diagnostic errors and should be more cautious when evaluating patients with knee disorders suffering from psychological distress.