Fatigue Links Sociodemographic Risk to Pain Intensity and Spread in Two Surgical Cohorts

Abstract Why some surgical patients develop pain that extends beyond the original site of injury while others do not remains poorly understood. The recently proposed Risk of Pain Spread (ROPS) framework integrates multiple psychosocial risk factors associated with widespread pain, but its generalizability to surgical populations has not been established. Using two large pre-surgical cohorts of participants undergoing total knee arthroplasty or thoracic surgery, we evaluated the generalizability of the ROPS framework and examined relationships among psychosocial and sociodemographic factors, surgical-site pain, nonsurgical-site pain, and widespread pain using complementary latent-variable, regression, Bayesian network, and mediation analyses. Across cohorts and analytical approaches, fatigue emerged as the most consistent correlate of pain outcomes, independent of other measured risk factors. Fatigue also occupied a central position within the conditional dependency structure of psychosocial and pain variables and accounted for substantial shared variance linking sleep disturbance, depressive symptoms, neuroticism, adverse childhood experiences, and socioeconomic disadvantage with pain intensity. Nonsurgical-site pain consistently occupied a position linking pain intensity with widespread pain across complementary analyses. Together, these findings externally validate the ROPS framework in clinically relevant surgical populations and identify fatigue as a central correlate linking biopsychosocial vulnerability with pain burden. Author Note This work was funded by an administrative supplement from the National Institutes of Health as part of grant 5U54DA049110-04 (FOA RFA-RM-18-031). Data was provided by the A2CPS Consortium funded by the National Institutes of Health (NIH) Common Fund, which is managed by the Office of the Director (OD)/ Office of Strategic Coordination (OSC). Consortium components and their associated funding sources include Clinical Coordinating Center (U 24NS112873), Data Integration and Resource Center (U54DA049110), Omics Data Generation Centers (U54DA049116, U54DA049115, U54DA049113), Multi-site Clinical Center 1 (MCC1) (UM1NS112874), and Multi-site Clinical Center 2 (MCC2) (UM1NS118922). Conflicts of Interest Chad Brummett serves as a consultant for Vertex Pharmaceuticals and Merck Pharmaceuticals and provides expert medicolegal testimony. Tor Wager serves on the scientific advisory board of Curable Health. All other authors declare no competing interests.