Diagnostic Accuracy of McMurray’s Test for Meniscal Injury of the Knee Joint Taking Arthroscopy as Gold Standard: A Prospective Observational Study

Abstract

Meniscal tears are a common knee injury that may result in pain, instability, and chronic disability. Although McMurray’s test is a general clinical test that can be used to indicate meniscus injury, its diagnostic accuracy is still controversial. This paper assesses the diagnostic accuracy of McMurray's test, versus arthroscopy as the reference standard for meniscal tears. A total of 150 patients are included in this prospective observational study, presenting with painful knee and suspicion of meniscal injury. McMurray’s test is performed on all patients as a clinical diagnosis, and is verified by arthroscopy of whether a meniscal tear is actually present. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for McMurray’s test are determined. According to the research, 150 patients diagnosed with arthroscopy were observed, in whom 90 patients were confirmed of meniscal tears. McMurray's test is true positive in 70 of these patients, false positive in 20 patients who do not have meniscal tears, and false negative in 15 patients who with meniscal tears. The diagnostic accuracy values are as follows: Sensitivity = 77.8%, Specificity = 83.3%, PPV = 77.0%, NPV = 84.0 %. Meet McMurray's test is a relatively reliable diagnostic test to detect meniscal lesions, and is, therefore, a useful test in the initial evaluation of patients presenting with knee pain. McMurray’s test has its limitations: with low-to-moderate sensitivity and false positives, but nonetheless the test becomes an essential in clinical setups as it is simple, inexpensive and easy. It is hoped that future studies will evaluate the additive value of both McMurray’s test and imaging modalities such as MRI to improve diagnostic accuracy.

Keywords: Mcmurray’s Test, Meniscal Tears, Diagnostic Accuracy, Arthroscopy, Knee Pain, Sensitivity, Specificity, Positive Predictive Value, Negative Predictive Value