Development and validation of a predictive model for the efficacy of ropivacaine lumbar-square muscle block for analgesia after cesarean delivery

Abstract Background Effective postoperative analgesia is essential in the clinical management of cesarean sections, with the lumbar square muscle block (Quadratus Lumborum Block, QLB) recognized as a viable analgesic option. Nonetheless, the development of a predictive model for its analgesic efficacy postoperatively remains underexplored. Objective This study aims to establish a predictive model for the postoperative analgesic effects of QLB through retrospective analysis, thereby offering a scientific foundation for clinical practice. Methods A total of 338 patients who underwent cesarean sections under intrathecal anesthesia, accompanied by QLB, at the Second Affiliated Hospital of Xinjiang Medical University from February 2018 to December 2023 were included in this analysis. The predictive model was developed utilizing univariate analysis, Lasso regression, and multifactorial logistic regression analysis, with validation conducted through Receiver Operating Characteristic (ROC) curves, calibration curves, and the Hosmer–Lemeshow test. Results The model demonstrated high accuracy and calibration. Conclusion The predictive model developed in this study holds significant potential for early assessment of the analgesic effects of QLB, thereby equipping clinicians with a scientifically grounded and precise tool for pain management.