Nomogram for predicting early neurological deterioration in Anterior Circulation acute ischemic stroke patients treated with Mechanical Thrombectomy

Background The importance of early detection of patients at risk of early neurological deterioration (END) after mechanical thrombectomy (MT) at the time of prognosis provision is paramount. Methods This retrospective study not only sought to determine the predictive variables of post-MT END but also created a prognostic model in the form of a nomogram. A predictive model based on END occurrence (≥ 4 points of NIHSS score increase or death) within 72 hours after the event was created through multivariate logistic regression analysis of the possible risk factors. Results Total that 161 AIS patients undergoing MT were gathered as training cohort and 69 as validation cohort. Multivariate analysis revealed three independent predictors: atherogenic index of plasma (AIP) (OR = 1.239, 95% CI: 1.015–1.513, P = 0.035), systemic immune-inflammation index (SII)(OR = 1.086, 95% CI: 1.007–1.172, P = 0.032), and smoking history(OR = 2.558, 95% CI: 1.030–6.348, P = 0.043). The predictive model based on the three variables achieved an AUC of 0.842 (95% CI: 0.763–0.922), with its calibration curve nearly aligning with the ideal diagonal. Conclusions These results showed that the nomogram has a strong discriminative ability and calibration level, which suggests that it can be used as a viable clinical tool to predict END among acute stroke patients with ischemia and who receive MT.