To develop and validate a nomogram incorporating postoperative blood pressure and other multifactorial predictors for the risk of delayed cerebral ischemia(DCI) following surgical clipping in patients with aneurysmal subarachnoid hemorrhage(aSAH).

This retrospective cohort study consecutively enrolled 272 aSAH patients who underwent aneurysm clipping at the Department of Neurosurgery, Second Affiliated Hospital of Chongqing Medical University from January 2018 to January 2022. Demographic, clinical, and imaging data were collected. Predictors were screened using LASSO regression, and a multifactorial logistic regression-based nomogram was constructed. The dataset was randomly divided into training(n=190) and validation(n=82) sets at a 7∶3 ratio. Model discrimination, calibration, and clinical utility were evaluated using the area under the receiver operating characteristic curve(AUC), calibration curves, and decision curve analysis(DCA), respectively.

Among 272 enrolled patients, 98(36%) developed DCI. Multivariate analysis identified age(OR=0.97; 95%CI: 0.94~0.99; P=0.036), World Federation of Neurological Surgeons(WFNS) grade(OR=1.36; 95%CI: 1.02~1.82; P=0.038), Fisher grade(OR=1.44; 95%CI: 1.01~2.05; P=0.048), and mean arterial pressure on postoperative day 2(OR=1.06; 95%CI: 1.03~1.09; P<0.001) as independent risk factors for DCI. The model achieved C-indices of 0.739 (95%CI : 0.668~0.810) in the training set and 0.760 (95%CI: 0.647~0.872) in the validation set. Calibration curves demonstrated high agreement between predicted and observed probabilities(mean absolute error=0.027), while DCA confirmed significant net clinical benefit at threshold probabilities of 15%~65%.

We successfully developed a predictive model incorporating age, WFNS grade, Fisher grade, and postoperative day 2 mean arterial pressure, with elevated postoperative blood pressure identified as an early critical indicator for DCI development.