Subjective Crepitus as a Risk Factor for Incident Symptomatic Knee Osteoarthritis: Data From the Osteoarthritis Initiative.

OBJECTIVE: Subjective crepitus is the reporting of hearing grating, cracking, or popping sounds in and/or around a joint. We aimed to evaluate whether there is an association between crepitus and incident symptomatic knee osteoarthritis (OA) in the Osteoarthritis Initiative (OAI), a multicenter longitudinal US cohort.

METHODS: Knees without baseline symptomatic OA were included. Crepitus frequency was assessed using a question from the Knee Injury and Osteoarthritis Outcome Score at baseline and at 12, 24, and 36 months. Frequent knee pain and radiographs were assessed at baseline and at annual visits up to 48 months. Radiographic OA was defined as a tibiofemoral Kellgren/Lawrence grade ≥2. Symptomatic OA was defined as a knee with both frequent symptoms and radiographic OA. We performed a repeated-measures analysis with a predictor of crepitus and outcome of incident symptomatic OA, adjusting for age, sex, and body mass index (BMI), with those never reporting crepitus as the referent group.

RESULTS: There were a total of 3,495 participants (42.2% male), with mean ± SD age of 61.1 ± 9.2 years and a mean ± SD BMI of 28.2 ± 4.7 kg/m². The odds of incident symptomatic OA were higher with greater frequency of crepitus (never, rarely, sometimes, often, and always, with adjusted odds ratios of (referent), 1.5, 1.8, 2.2, and 3.0, respectively; P < 0.0001 for trend). The group with radiographic OA at OAI baseline but without symptoms contributed 26% of the observations but more than 75% of the incident symptomatic OA cases.

CONCLUSION: In those without symptomatic OA, subjective knee crepitus predicts incident symptomatic OA longitudinally, with most cases occurring in those with preexisting tibiofemoral radiographic OA but without frequent knee pain. However, an important limitation is that patellofemoral OA was not systematically evaluated within the OAI. Subjective crepitus offers utility for the identification of at-risk individuals, predictive modeling, and future research.