Seasonal, Regional, and Clinical Factors Associated With Manipulation Under Anesthesia Following Total Knee Arthroplasty: A PearlDiver Study

Abstract Background Postoperative stiffness after total knee arthroplasty (TKA) can necessitate manipulation under anesthesia (MUA) when conservative treatments fail. While younger age and female sex have been linked to MUA risk, the impact of enviro nmental factors and systemic comorbidities is less defined. This study evaluates both patient-specific and environmental factors influencing MUA rates. We hypothesized that regional and seasonal variability influence MUA incidence and that a history of fibrotic or inflammatory pathologies would increase postoperative MUA risk. Methods Using the PearlDiver database, we retrospectively analyzed patients who underwent TKA and had active records within 90 days postoperatively (n = 1,703,407). Factors assessed included region, season, demographics (age, sex, Charlson Comorbidity Index), and various comorbidities. Multivariate regression evaluated associations between MUA and predictor variables, while chi-square assessed variation by region, season, and comorbidity. Statistical significance was set at α = 0.001. Results MUA incidence declined from 3.12% in 2011 to 2.61% in 2022. Among the 49,594 patients (2.91%) who underwent MUA, higher risk was associated with younger age, female sex, and lower Charlson Comorbidity Index scores. Musculoskeletal pathologies like arthrofibrosis, knee instability, patellar tendonitis, and previous ligamentous injury also independently increased MUA risk (P < .001). MUA rates were highest in the Midwest (3.22%, P < .001) and winter (3.07%, P < .001), and lowest in the South (2.65%, P < .001) and summer (2.82%, P < .001). Conclusions Younger age and female sex were the strongest predictors of MUA following TKA. While geographic region and season showed statistically significant associations, their impact was comparatively modest, emphasizing that patient-specific demographic factors remain the primary drivers of MUA risk.