Can We Predict Severity of Osteoarthritis of Knees and Compartmental Involvement Based on a Set of Predefined Clinical Questions in Patients of Knee Pain?

Background We investigated whether the severity of Osteoarthritis (OA) knees can be predicted based on a set of predefined clinical questions (PCQs) about activities of daily living (ADL). We studied the association of demographic factors and advanced radiographic OA (KL 3 and 4) and the relationship between various physical activities and radiographic involvement of knee joint compartments based on PCQs. Materials and Methods Demographic data, radiographic grading of knee OA and PCQs score, were obtained prospectively. Patients’ responses to PCQs were marked as scores—that were predefined and graded according to the severity of knee pain. Radiographic knee OA grades were dichotomized and patients were classified as either negative (KL grade 1, 2) or positive (KL grade 3, 4). Multivariate logistic regression was performed to obtain the adjusted odds for total PCQs score in relation with positive radiographic OA considering confounders like age, gender and BMI in the model. Log odds score (LOS) were obtained and ROC analysis was performed on scores to obtain the cut-off value for the screening of knee OA in patients of knee pain. Results Age and BMI were significantly negatively correlated with PCQs score ( r = − 0.473; P