• Christopher R Abrecht, Marise Cornelius, Albert Wu, Robert N Jamison, David Janfaza, Richard D Urman, Claudia Campbell, Michael Smith, Jennifer Haythornthwaite, Robert R Edwards, and Kristin L Schreiber.
• Department of Anesthesia and Perioperative Care, University of California San Francisco, San Francisco, California.
• Pain Med. 2019 Jan 1; 20 (1): 161-171.

ObjectiveTo identify factors associated with pain severity and opioid consumption in the early perioperative period.DesignProspective observational cohort study.SettingTertiary academic medical center.SubjectsPatients with osteoarthritis older than age 45 years undergoing primary total knee replacement at Brigham and Women's Hospital. A total of 126 patients enrolled.MethodsPreoperatively, pain questionnaires and quantitative sensory testing were performed on patients to develop a psychosocial and psychophysical profile. Postoperatively, pain scores and opioid consumption were measured as primary end points. Univariate and multiple linear regression analyses were performed to determine the predictive value of these characteristics on perioperative pain scores and opioid consumption.ResultsRegression analysis revealed several predictors of acute postoperative pain scores including temporal summation of pain (TSP; P = 0.001), body mass index (BMI; P = 0.044), number of previous knee surgeries (P = 0.006), and female gender (P = 0.023). Similarly, predictors of opioid utilization included TSP (P = 0.011), BMI (P = 0.02), age (P = <0.001), and tourniquet time (P = 0.003).ConclusionsThe only significant, unique predictors of both pain and opioid consumption were TSP, an index of central pain facilitatory processes, and BMI. Interestingly, psychosocial factors, such as catastrophizing and somatization, although correlated with postoperative pain scores and opioid consumption, generally did not independently explain substantial variance in these measures. This study suggests that BMI and quantitative sensory testing, specifically the temporal summation of pain, may provide value in the preoperative assessment of patients undergoing total knee arthroplasty and other surgeries via predicting their level of risk for adverse pain outcomes.

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