Evaluation of the PROMIS Physical Function Computer Adaptive Test in Patients Undergoing Knee Surgery.
Megan MilesVidushan NadarajahJulio J JaureguiAndrew G DubinaMichael P SmudaCraig H BennettJonathan D PackerR Frank HennPublished in: The journal of knee surgery (2019)
A cross-sectional analysis of data derived from patients undergoing knee surgery at a single institution was conducted. The objectives of the study were to (1) compare how the Patient-Reported Outcomes Measurement Information System physical function (PROMIS PF) computer adaptive test performs against the International Knee Documentation Committee (IKDC) Subjective Knee Form in evaluating functional status, and (2) to determine demographic, clinical, and psychosocial correlates of each outcome measure in an urban population undergoing a variety of knee surgeries. We hypothesized that there would be a strong correlation between PROMIS PF and IKDC, with minimal floor and ceiling effects, and similar clinical correlates. The sample consisted of 412 patients undergoing knee surgery. Bivariate and multivariable statistical analyses were performed to identify significant independent predictors. The PROMIS PF and IKDC scores were strongly correlated (r s = 0.71, p < 0.001), and neither exhibited floor nor ceiling effects. Lower body mass index, no preoperative opioid use, lower Charlson comorbidity index score, employment, and lower income were found to be significant independent predictors for better scores on both PROMIS PF and IKDC. Patients undergoing total knee arthroplasty had significantly lower PROMIS PF and IKDC scores (p < 0.05). Potential explanations for these findings are presented, and clinical implications are discussed.
Keyphrases
- total knee arthroplasty
- patient reported outcomes
- patients undergoing
- total hip
- minimally invasive
- knee osteoarthritis
- body mass index
- coronary artery bypass
- anterior cruciate ligament
- anterior cruciate ligament reconstruction
- mental health
- electronic health record
- deep learning
- weight gain
- acute coronary syndrome
- mental illness
- weight loss
- climate change
- sleep quality
- risk assessment