Development of a diagnostic scoring system for gouty arthritis of the knee: A retrospective case–control study

Abstract

Background: Gouty knee arthritis (GKA) is a frequent yet often under-recognised cause of knee pain, especially where synovial crystal analysis or advanced imaging is not readily available. This study aimed to design and validate a practical scoring system to aid the diagnosis of GKA in patients presenting with knee pain, by identifying key associated risk factors and supporting earlier clinical recognition. Methods: A retrospective case-control study was conducted involving 77 adults experiencing knee pain, with 38 cases of GKA and 39 controls. Risk factors for GKA were identified and analyzed through statistical methods to develop a predictive scoring system. Results: The analysis revealed several key risk factors associated with GKA. Older age showed a trend toward higher likelihood of GKA in univariable analysis (odd ratio (OR) = 1.08, 95% confidence interval (CI): 0.96–1.21), whereas in multivariable analysis only higher serum uric acid levels remained an independent predictor of GKA. Elevated serum uric acid levels were another strong predictor, with those having higher uric acid levels showing 2.48 times higher likelihood of developing GKA (OR = 2.48, 95% CI: 1.29-4.77). On the receiver operating characteristic (ROC) analysis, gender and history of medication did not show any discrimination towards GKA. The scoring system developed from variables such as age, serum uric acid, leukocyte count, erythrocyte sedimentation rate, periarthricular tophi, history of chronic diseases, history of alcohol consumption, and knee joint bilaterality showed excellent diagnostic performance. Additionally, the area under the curve (AUC) in the ROC analysis was 0.969 (0.933-1.000), which indicates a high level of accuracy in predicting GKA. When compared to traditional diagnostic method such as serum uric acid level (AUC = 0.938), the predictive model was superior. Conclusion: The newly developed scoring system offers an effective, non-invasive method for early detection of GKA, potentially improving clinical management and patient outcomes. For rehabilitation and physiotherapy practice, earlier recognition of gouty knee using this non-invasive score may support appropriate protection during inflammatory flares, guide progression of loading programmes, and help prioritize rheumatology or orthopaedic referral in patients with knee pain.

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