Development and validation of a clinical prediction model for ischemic stroke recurrence after successful stent implantation in symptomatic intracranial atherosclerotic stenosis.

OBJECTIVE

This study aimed to analyze the risk factors for recurrent ischemic stroke in patients with symptomatic intracranial atherosclerotic stenosis (ICAS) who underwent successful stent placement and to establish a nomogram prediction model.

METHODS

We utilized data from a prospective collection of 430 consecutive patients at Jining NO.1 People's Hospital from November 2021 to November 2022, conducting further analysis on the subset of 400 patients who met the inclusion criteria. They were further divided into training (n=321) and validation (n=79) groups. In the training group, we used univariate and multivariate COX regression to find independent risk factors for recurrent stroke and then created a nomogram. The assessment of the nomogram's discrimination and calibration was performed through the examination of various measures including the Consistency index (C-index), the area under the receiver operating characteristic (ROC) curves (AUC), and the calibration plots. Decision curve analysis (DCA) was used to evaluate the clinical utility of the nomogram by quantifying the net benefit to the patient under different threshold probabilities.

RESULTS

The nomogram for predicting recurrent ischemic stroke in symptomatic ICAS patients after stent placement utilizes six variables: coronary heart disease (CHD), smoking, multiple ICAS, systolic blood pressure (SBP), in-stent restenosis (ISR), and fasting plasma glucose. The C-index (0.884 for the training cohort and 0.87 for the validation cohort) and the time-dependent AUC (>0.7) indicated satisfactory discriminative ability of the nomogram. Furthermore, DCA indicated a clinical net benefit from the nomogram.

CONCLUSIONS

The predictive model constructed includes six predictive factors: CHD, smoking, multiple ICAS, SBP, ISR and fasting blood glucose. The model demonstrates good predictive ability and can be utilized to predict ischemic stroke recurrence in patients with symptomatic ICAS after successful stent placement.