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

BACKGROUND

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).

AIM

The study objective was to develop and internally validate a clinical prediction rule (CPR) for the detection of meniscal tears in primary care.

DESIGN AND SETTING

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.

METHOD

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.

RESULTS

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.

CONCLUSION

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.