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Optimized Management of Endovascular Treatment for Acute Ischemic Stroke
Published on: January 18, 2018
Predicting the prognosis of acute ischemic stroke patients undergoing endovascular thrombectomy: A multicenter
Xuchen Meng1, Weijie Zhong1, Dingzhong Tang2
1Neurosurgery Department, Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Abstract:
Acute ischemic stroke (AIS) is a leading cause of mortality and long-term disability worldwide. The identification of reliable prognostic determinants and formation of a validated model for AIS is unclear. We retrospectively recruited 210 patients with stroke of anterior circulation large-vessel occlusion who underwent endovascular thrombectomy between March 2021 and March 2024. Participants were aged 18 years or older and had undergone examination and treatment for at least 90 days. We collected baseline demographic characteristics, medical records, and blood biomarkers and tracked the prognosis for 30 days. We used LASSO-logistic regression to identify potential indicators of AIS over a 90 days. After adjusting for age (P = .130), previous stroke or transient ischemic attack (P = .112), admission diastolic pressure (P = .101), glucose (P = .162), and albumin (P = .094), only male (vs female, P = .042), alcohol consumption (P = .013), hypertension (P = .007), trial of acute stroke treatment type "others" versus large artery atherosclerosis, P = .046), leukocytes (P = .013), and neutrophil-to-lymphocyte ratio (P < .001) remained significant predictors of poor clinical endpoints. The prognostic model had a classification accuracy of 77.6%, a sensitivity of 79.3%, a specificity of 73.3%, and a precision of 88.1%. This study identified modifiable risk factors such as alcohol consumption and hypertension, along with inflammatory markers such as leukocyte count and neutrophil-to-lymphocyte ratio, as significant predictors of poor outcomes in patients with AIS undergoing endovascular thrombectomy. These findings could guide clinicians in identifying high-risk patients and in tailoring treatment strategies. Further studies are needed to validate these predictors and to explore their potential roles in therapeutic interventions.
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