Development and validation of a clinically available risk model for medium-to-high opioid consumption after total knee arthroplasty.

OBJECTIVES

To develop and internally validate a clinically interpretable preoperative model for predicting medium-to-high opioid consumption within 72 h after unilateral total knee arthroplasty (TKA).

METHODS

We retrospectively analyzed 806 patients who underwent primary unilateral TKA between October 2017 and September 2021. Patients were randomly divided into a training cohort (70%) and a validation cohort (30%). The primary outcome was total opioid consumption within the first 72 postoperative hours, categorized as low versus medium-to-high consumption. Baseline and perioperative variables were first compared using appropriate univariable statistical tests, and variables showing potential associations, together with clinically relevant factors, were entered into a multivariable logistic regression model with bidirectional stepwise selection. The final model was presented as a nomogram. Discrimination, calibration, and clinical utility were assessed using the area under the receiver operating characteristic curve (AUC), calibration plots with intercepts and slopes, Hosmer-Lemeshow testing, and decision curve analysis.

RESULTS

Female sex, diabetes mellitus, higher body mass index, and higher preoperative day-1 serum interleukin-6 (IL-6) levels were independent predictors of medium-to-high postoperative opioid consumption. The model showed acceptable discrimination in the training cohort (AUC 0.727) and modest discrimination in the validation cohort (AUC 0.665). Calibration was acceptable in both cohorts (training: intercept 0.012, slope 0.953; validation: intercept 0.009, slope 0.941). Decision curve analysis supported potential clinical utility across relevant threshold probabilities.

CONCLUSIONS

A simple preoperative model based on routinely available demographic, clinical, and inflammatory variables may help identify patients at increased risk of higher opioid requirements after unilateral TKA and may support individualized multimodal analgesic planning.