基于神经递质的风险模型在评估急性大动脉闭塞性脑梗死机械取栓患者神经功能预后中的价值

doi:10.3969/j.issn.1006-6233.2025.01.029

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Abstract Objective: To construct a risk model for neurological function prognosis in patients with acute large artery occlusion cerebral infarction after mechanical thrombectomy based on brain neurotransmitters, and to verify the predictive efficiency of this model, guiding the formulation of clinical disease management regimens. Methods: One hundred and sixty patients with acute large artery occlusion cerebral infarction who underwent mechanical thrombectomy and visited our hospital from January 2021 to December 2023 were selected as research subjects. They were randomly assigned to a modeling set (n=112) and a validation set (n=48) in a 7∶3 ratio. Based on the neurological function prognosis of patients after mechanical thrombectomy in the modeling set, they were divided into a group with deteriorating neurological function (n=43) and a group with improved neurological function (n=69). Clinical data of the two groups were compared. Univariate and multivariate logistic regression analyses were conducted to identify risk factors affecting the neurological function prognosis of patients with acute large artery occlusion cerebral infarction after mechanical thrombectomy. A neurological function prognosis risk model for patients with acute large artery occlusion cerebral infarction after mechanical thrombectomy was constructed based on the identified risk factors, and the predictive performance of the model was evaluated using the C-index, receiver operating characteristic (ROC) curve, standard curve, and decision curve analysis (DCA). Results: There were no statistical differences in clinical data between the modeling set and the validation set (P>0.05), and comparisons between the modeling set and the overall level, as well as between the validation set and the overall level, revealed no statistical differences (P>0.05). Both data sets were representative of the total population. Univariate and multivariate logistic regression analyses showed that age, history of hypertension, history of diabetes, baseline NIHSS score, SBP, LP(a), brain neurotransmitters DA, GABA, Glu EEG S spectrum values were risk factors for deterioration of neurological function prognosis in patients with acute cerebral infarction caused by large artery occlusion after mechanical thrombectomy (P<0.05). The constructed risk model was verified by ROC curve analysis, which showed that the areas under the curves of the training set and the validation set were 0.897 (95%CI: 0.767-0.943) and 0.902 (95%CI: 0.788-0.954), respectively, indicating good discrimination. Calibration curve verification revealed that the predicted values of the model obtained from the training set and the validation set were in good agreement with the actual values. DCA analysis indicated that the model of the training set and validation set had high clinical application value. Conclusion: Neurotransmitter levels are influencing factors of prognosis in patients with acute large artery occlusion cerebral infarction with mechanical thrombectomy. It is valuable to construct a risk model based on neurotransmitters to evaluate the risk of neurological function prognosis in patients after mechanical thrombectomy.

Key words： Acute large artery occlusion cerebral infarction Mechanical thrombectomy Neurological function prognosis Brain neurotransmitters

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http://www.hbyxzzs.cn/EN/10.3969/j.issn.1006-6233.2025.01.029 OR http://www.hbyxzzs.cn/EN/Y2025/V31/I1/155

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