Pain related to knee osteoarthritis (OA) is a complex phenomenon that cannot be fully explained by radiographic disease severity. We hypothesized that pain phenotypes are likely to be derived from a confluence of factors across multiple domains: knee OA pathology, psychology, and neurophysiological pain processing. The purpose of this study was to identify distinct phenotypes of knee OA, using measures from the proposed domains. Data from 3494 subjects participating in the Osteoarthritis Initiative (OAI) study was analyzed. Variables analyzed included: radiographic OA severity (Kellgren-Lawrence grade), isometric quadriceps strength, Body Mass Index (BMI), comorbidities, CES-D Depression subscale score, Coping Strategies Questionnaire Catastrophizing subscale score, number of pain sites, and knee tenderness on physical examination. Variables used for comparison across classes included pain severity, WOMAC disability score, sex and age. Latent Class Analysis was performed. Model solutions were evaluated using the Bayesian Information Criterion. One-way ANOVAs and post hoc least significance difference tests were used for comparison of classes.Introduction
Methods
Patient-reported outcome measures have become an important part of routine care. The aim of this study was to determine if Patient-Reported Outcomes Measurement Information System (PROMIS) measures can be used to create patient subgroups for individuals seeking orthopaedic care. This was a cross-sectional study of patients from Duke University Department of Orthopaedic Surgery clinics (14 ambulatory and four hospital-based). There were two separate cohorts recruited by convenience sampling (i.e. patients were included in the analysis only if they completed PROMIS measures during a new patient visit). Cohort #1 (n = 12,141; December 2017 to December 2018,) included PROMIS short forms for eight domains (Physical Function, Pain Interference, Pain Intensity, Depression, Anxiety, Sleep Quality, Participation in Social Roles, and Fatigue) and Cohort #2 (n = 4,638; January 2019 to August 2019) included PROMIS Computer Adaptive Testing instruments for four domains (Physical Function, Pain Interference, Depression, and Sleep Quality). Cluster analysis (K-means method) empirically derived subgroups and subgroup differences in clinical and sociodemographic factors were identified with one-way analysis of variance.Aims
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