Development and internal validation of a nomogram for predicting postoperative hypotension after carotid endarterectomy

Objectives Postoperative hypotension is one of the common and serious complications following carotid endarterectomy (CEA). Early identification of high-risk patients is significance for improving perioperative management. This study aims to develop and validate a nomogram model for predicting post-CEA hypotension. Methods This single-center retrospective study included 527 patients with carotid artery stenosis who underwent CEA. They were randomly divided into a training cohort ( n = 369) and an internal validation cohort ( n = 158) at a ratio of 7:3. The demographic characteristics, clinical data and perioperative data of patients were collected in the hospital medical record system. The least absolute shrinkage and selection operator (LASSO) regression was used for predictor selection, and a postoperative hypotension risk prediction model was developed based on multivariable logistic regression, which was then visualized as a nomogram. The discrimination, calibration, and clinical utility of the model were evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results Postoperative hypotension occurred in 88 of 527 patients (17%). Eight predictors were included in the nomogram model, including plaque length above the carotid bifurcation, diabetes mellitus, hypertension, symptomatic stenosis, contralateral carotid stenosis, homocysteine, operation duration, and surgical treatment. The model achieved good discrimination in the training and internal validation cohorts, with AUCs of 0.864 (95% CI, 0.814–0.914) and 0.868 (95% CI, 0.792–0.944), respectively, and showed good calibration and clinical utility. Conclusion This study developed and validated a nomogram model for predicting post-CEA hypotension, which can provide a reference for patient risk assessment and individualized perioperative management.