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Patient Characteristics Independently Associated With Knee Osteoarthritis Symptom Severity at Initial Orthopedic Consultation

J Clin Rheumatol. 2021 Mar 5. doi: 10.1097/RHU.0000000000001726. Online ahead of print.

ABSTRACT

BACKGROUND/OBJECTIVE: The objective of this study was to identify patient and disease characteristics associated with the symptomatic severity of knee osteoarthritis (OA) at the time of initial knee OA diagnosis by an orthopedist.

METHODS: This medical records review included patients initially diagnosed with knee OA during 2016 to 2017 by a single orthopedic surgeon in a university-based tertiary care setting. All variables were assessed at first OA diagnosis. Main outcomes were subscales of the Knee Injury and Osteoarthritis Outcome Score-Pain, other Symptoms, knee-related quality of life, and function in daily living. Multivariable regression analyses examined the following predictors of main outcomes: sex, race, age, insurance type, body mass index, Charlson comorbidity index, and radiographic OA severity (Kellgren-Lawrence grade).

RESULTS: Of the 559 patients included in the study, most were African American (52.1%), female (71.7%), and had severe radiographic OA (Kellgren-Lawrence grade, 4; 68.7%). Female sex, African American racial/ethnic group, Medicaid insurance, younger age, and severe radiographic OA were independently statistically significantly associated with worse symptoms, pain, and function (p < 0.05 for all). Body mass index and Charlson comorbidity index were not statistically significant predictors of any outcome.

CONCLUSIONS: This study identified disparities in the perception of knee OA problems at initial orthopedist diagnosis based on sex, age, race, insurance, and radiographic OA severity. Because most of these variables are also associated with more rapid progression of OA, identifying their biopsychosocial underpinnings may help determine which interventions are most likely to redress these disparities and delay progression to end-stage knee OA.

PMID:33657591 | DOI:10.1097/RHU.0000000000001726

By Nevin Manimala

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