ASSOCIATION BETWEEN RADIOGRAPHIC SEVERITY AND PHARMACOLOGICAL TREATMENT PATTERNS IN PATIENTS WITH KNEE OSTEOARTHRITIS
DOI:
https://doi.org/10.4238/jb9pjn86Keywords:
Knee osteoarthritis, Kellgren–Lawrence grade, Radiographic severity, Pharmacological treatment, Medication prescribingAbstract
Osteoarthritis of the knee is usually diagnosed using the Kellgren–Lawrence radiographic grading system, but this does not always align with the extent of symptoms or drug use. Understanding whether radiographic severity influences pharmacological treatment patterns may support more individualized clinical management. This study evaluated the association between radiographic severity and opioid, antidepressant, and gabapentinoid prescribing among patients with knee osteoarthritis using a retrospective cross-sectional design. Radiographic severity was classified according to Kellgren–Lawrence grades, and treatment outcomes included medication prescriptions and overall medication burden. Group comparisons were performed using appropriate statistical tests, followed by multivariable logistic regression adjusted for age, sex, body mass index, pain score, depression, diabetes mellitus, and smoking status. Sensitivity analyses were conducted using grouped radiographic severity categories. Among 322 patients with complete radiographic data, medication burden and the prevalence of opioid, antidepressant, and gabapentinoid prescribing did not differ significantly across Kellgren–Lawrence grades. Radiographic severity was not independently associated with any pharmacological treatment outcome after adjustment. Pain score and smoking independently predicted opioid prescribing, whereas depression was strongly associated with antidepressant prescribing and showed a weaker association with gabapentinoid use. Sensitivity analyses produced consistent findings. These findings suggest that treatment patterns are being driven more by clinical and psychosocial factors than by radiographic severity and justify the use of imaging in the context of patients' clinical factors when making treatment decisions.
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