A clinical prediction rule for meniscal tears in primary care: development and internal validation using a multicentre study

In primary care, meniscal tears are difficult to detect. A quick and easy clinical prediction rule based on patient history and a single meniscal test may help physicians to identify high-risk patients for referral for magnetic resonance imaging (MRI). The study objective was to develop and internally validate a clinical prediction rule (CPR) for the detection of meniscal tears in primary care. In a cross-sectional multicentre study, 121 participants from primary care were included if they were aged 18-65 years with knee complaints that existed for <6 months, and who were suspected to suffer from a meniscal tear. One diagnostic physical meniscal test and 14 clinical variables were considered to be predictors of MRI outcome. Using known predictors for the presence of meniscal tears, a 'quick and easy' CPR was derived. The final CPR included the variables sex, age, weight-bearing during trauma, performing sports, effusion, warmth, discolouration, and Deep Squat test. The final model had an AUC of 0.76 (95% CI = 0.72 to 0.80). A cut-point of 150 points yielded an overall sensitivity of 86.1% and a specificity of 45.5%. For this cut-point, the positive predictive value was 55.0%, and the negative predictive value was 81.1%. A scoring system was provided including the corresponding predicted probabilities for a meniscal tear. The CPR improved the detection of meniscal tears in primary care. Further evaluation of the CPR in new primary care patients is needed, however, to assess its usefulness