Objective ·To explore the factors influencing 90 d poor prognosis in male patients with anterior circulation acute ischemic stroke with large vessel occlusion (AIS-LVO) after mechanical thrombectomy (MT), and to develop a predictive model based on clinical characteristics and inflammatory markers. Methods ·This retrospective study enrolled 126 male patients who received MT for anterior circulation AIS-LVO at two hospitals in Shanghai from March 2022 to June 2024. The 90-day modified Rankin Scale (mRS) score after surgery was used as the outcome measure, based on which patients were divided into a good prognosis group and a poor prognosis group. Baseline data, perioperative clinical indicators, and admission laboratory indicators were collected and compared between the two groups. Univariate Logistic regression model was used to screen variables associated with 90-day poor prognosis, and multivariate Logistic regression model was subsequently performed to identify independent predictors and construct a predictive model. Receiver operator characteristic (ROC) curve was used to evaluate the performance of the predictive model. Results ·According to the 90-day mRS score, male patients with anterior circulation AIS-LVO after MT were divided into a good prognosis group (n=50) and a poor prognosis group (n=76). Analysis of baseline data, perioperative clinical indicators, and admission laboratory indicators between the two groups showed that there were statistically significant differences in admission National Institutes of Health Stroke Scale (NIHSS) score, history of previous stroke or transient ischemic attack (TIA), and neutrophil-lymphocyte ratio multiplied by fibrinogen-to-albumin ratio (NMF) index (P<0.05). Univariate Logistic regression analysis showed that an elevated NMF index was strongly correlated with an increased risk of poor prognosis (OR=6.944, 95% CI 2.636‒22.022, P<0.001). Multivariate Logistic regression analysis further confirmed that the NMF index was an independent predictor of poor prognosis (OR=6.153, 95% CI 1.939‒24.563, P=0.004). Other independent predictors included NIHSS score (P=0.003), history of previous stroke or TIA (P=0.034), large-artery atherosclerosis subtype (P=0.032) and undetermined etiology subtype (P=0.006) in the Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification, and white blood cell count (P=0.027). ROC curve analysis showed that the model exhibited excellent performance in predicting poor prognosis, with an area under the curve (AUC) of 0.889, a sensitivity of 70%, and a specificity of 96%. Conclusion ·NMF index may serve as a potential biomarker for predicting poor prognosis in male patients with anterior circulation AIS-LVO after MT. When combined with independent predictors such as admission NIHSS score, history of previous stroke or TIA, TOAST classification, and white blood cell count, it has high accuracy in predicting poor prognosis in the specific patient population.