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Updated: Aug 22, 2025
An Experimental Paradigm for the Prediction of Post-Operative Pain PPOP
Published on: January 27, 2010
Prediction of postoperative respiratory depression and respiratory complications in patients on preoperative
Ryu Komatsu1,2, Michael G Nash3, Jiang Wu4
1Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA. komatsr@ccf.org.
Purpose:
We developed prediction models for postoperative respiratory depression and respiratory complications for 958 patients who were on methadone preoperatively.
Methods:
The primary outcome was postoperative respiratory depression as defined by respiratory rate < 10/min, oxygen saturation (SpO2) < 90%, or requirement of naloxone for 48 h postoperatively. Secondary outcome was the composite of postoperative respiratory complications. Prediction models for postoperative respiratory depression and respiratory complications were constructed using multivariate logistic regression with preoperative and intraoperative characteristics as the predictors.
Results:
For the multivariate logistic regression model for postoperative respiratory depression, surgery duration (P = 0.005), body mass index (BMI) (P = 0.008), surgery involving digestive system (P = 0.031), and American Society of Anesthesiologists (ASA) physical status ≥ 4 (P = 0.038) were statistically significant predictors. The area under the receiver operating characteristic curve (AUROC) of the model was 0.581 (0.558-0.601) [median (95% confidence interval (CI))] with fivefold cross-validation. For the model for postoperative respiratory complications, surgery duration (P = 0.001), history of hypertension (P = 0.028), surgery involving musculoskeletal system (P < 0.001), surgery involving integumental system (P = 0.034), surgery categorized to miscellaneous therapeutic procedures (P = 0.028), combined general and regional anesthesia (P = 0.033), ASA physical status 3 (P < 0.001), and ASA physical status ≥ 4 (P < 0.001) were statistically significant predictors, and AUROC of the model was 0.726 (0.712-0.737).
Conclusions:
Multivariate logistic regression models including preoperative, and intraoperative characteristics as the predictors performed poorly to predict postoperative respiratory depression, and moderately for postoperative respiratory complications. Neither model is accurate enough to be subject to clinical use.
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