Key result
Model combining intense early pain and central sensitization effectively predicts chronic postoperative pain risk.
Why the study?
The authors sought to develop a prediction tool and decision-making algorithm based on identified predictors to prevent chronic postoperative pain in patients undergoing cardiac and/or aortic surgery.
Does a predictive model incorporating early postoperative pain and central sensitization accurately predict chronic postoperative pain in patients undergoing cardiac surgery?
Observational
Does a predictive model incorporating early postoperative pain and central sensitization accurately predict chronic postoperative pain in patients undergoing cardiac surgery?
Effect estimate: AUC 0.78 (95% CI 0.68-0.88)
A novel predictive model using early postoperative pain intensity and central sensitization can effectively identify cardiac surgery patients at high risk for chronic postoperative pain.
May aid early risk stratification for chronic pain after cardiac surgery; leaves open prospective validation before clinical use.
Objective. To develop a tool for prediction of chronic postoperative pain based on identified predictors and decision-making algorithm for its prevention in patients undergoing cardiac and/or aortic surgery. Material and methods. An iterative logistic regression analysis was performed to identify optimal prognostic model for chronic postoperative pain. The baseline model included intense pain in early postoperative period (OR=6.3; p=0.0001). The following variables were sequentially added: central sensitization (CSI), anxiety (HADS), and pain catastrophizing (PCS). Models were compared using the AIC, BIC and likelihood ratio test (LRT). The quality of the final model was assessed by ROC analysis. Results. Inclusion of CSI (Model #2) significantly improved the model compared to baseline one (LRT: p=0.019). Inclusion of anxiety (p=0.24) or pain catastrophizing (p=0.69) did not improve prognosis. The final model included two predictors: intense pain in early postoperative period (β=1.69; p<0.001) and central sensitization (β=0.051; p=0.022). ROC analysis showed AUC 0.78 (95% CI 0.68–0.88). Sensitivity was 66.7%, and specificity was 80.0% at a threshold of 0.36. Conclusion. Original predictive model enables effective identification of patients with high risk of chronic postoperative pain after cardiac surgery and facilitates transition from reactive treatment to proactive prevention. This improves quality of life in late postoperative period.
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Tsedinova et al. (2026) conducted an observational in Chronic postoperative pain after cardiac and/or aortic surgery. Intense pain in early postoperative period and central sensitization was evaluated on Prediction of chronic postoperative pain (AUC 0.78, 95% CI 0.68-0.88). A predictive model combining intense early postoperative pain and central sensitization effectively identified patients at high risk for chronic postoperative pain (AUC 0.78; 95% CI 0.68-0.88).
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