PDF(Pubmed)
Abstract：
BACKGROUND: This study aimed to establish and validate a nomogram model for predicting 90-day mortality in patients with acute basilar artery occlusion receiving endovascular thrombectomy.
RESULTS: A total of 242 patients with basilar artery occlusion undergoing endovascular thrombectomy were enrolled in our study, in which 172 patients from 3 stroke centers were assigned to the training cohort, and 70 patients from another center were assigned to the validation cohort. Univariate and multivariate logistic regression analyses were adopted to screen prognostic predictors, and those with significance were subjected to establish a nomogram model in the training cohort. The discriminative accuracy, calibration, and clinical usefulness of the nomogram model was verified in the internal and external cohorts. Six variables, including age, baseline National Institutes of Health Stroke Scale score, Posterior Circulation-Alberta Stroke Program Early CT (Computed Tomography) score, Basilar Artery on Computed Tomography Angiography score, recanalization failure, and symptomatic intracranial hemorrhage, were identified as independent predictors of 90-day mortality of patients with basilar artery occlusion and were subjected to develop a nomogram model. The nomogram model exhibited good discrimination, calibration, and clinical usefulness in both the internal and the external cohorts. Additionally, patients were divided into low-, moderate-, and high-risk groups based on the risk-stratified nomogram model.
CONCLUSIONS: Our study proposed a novel nomogram model that could effectively predict 90-day mortality of patients with basilar artery occlusion after endovascular thrombectomy and stratify patients with high, moderate, or low risk, which has a potential to facilitate prognostic judgment and clinical management of stroke.
RESULTS: A total of 242 patients with basilar artery occlusion undergoing endovascular thrombectomy were enrolled in our study, in which 172 patients from 3 stroke centers were assigned to the training cohort, and 70 patients from another center were assigned to the validation cohort. Univariate and multivariate logistic regression analyses were adopted to screen prognostic predictors, and those with significance were subjected to establish a nomogram model in the training cohort. The discriminative accuracy, calibration, and clinical usefulness of the nomogram model was verified in the internal and external cohorts. Six variables, including age, baseline National Institutes of Health Stroke Scale score, Posterior Circulation-Alberta Stroke Program Early CT (Computed Tomography) score, Basilar Artery on Computed Tomography Angiography score, recanalization failure, and symptomatic intracranial hemorrhage, were identified as independent predictors of 90-day mortality of patients with basilar artery occlusion and were subjected to develop a nomogram model. The nomogram model exhibited good discrimination, calibration, and clinical usefulness in both the internal and the external cohorts. Additionally, patients were divided into low-, moderate-, and high-risk groups based on the risk-stratified nomogram model.
CONCLUSIONS: Our study proposed a novel nomogram model that could effectively predict 90-day mortality of patients with basilar artery occlusion after endovascular thrombectomy and stratify patients with high, moderate, or low risk, which has a potential to facilitate prognostic judgment and clinical management of stroke.
摘要：
背景：本研究旨在建立并验证用于预测接受血管内血栓切除术的急性基底动脉闭塞患者90天死亡率的列线图模型。
结果：我们的研究共纳入242例基底动脉闭塞患者进行血管内血栓切除术，其中来自3个卒中中心的172名患者被分配到训练队列中，另一个中心的70例患者被分配到验证队列.采用单因素和多因素logistic回归分析筛选预后预测因子，具有显著性的在训练队列中建立列线图模型。辨别的准确性，校准,并且在内部和外部队列中验证了列线图模型的临床有效性。六个变量,包括年龄,基线美国国立卫生研究院卒中量表评分，后循环-阿尔伯塔省卒中计划早期CT（计算机断层扫描）评分，基底动脉计算机断层造影评分,再通失败，有症状的颅内出血,被确定为基底动脉闭塞患者90天死亡率的独立预测因子,并建立列线图模型.列线图模型表现出良好的辨别力，校准,以及在内部和外部队列中的临床有用性。此外,患者被分为低，moderate-,和基于风险分层列线图模型的高危人群。
结论：我们的研究提出了一种新的列线图模型，该模型可以有效预测血管内血栓切除术后基底动脉闭塞患者的90天死亡率，并对高死亡率患者进行分层。中度,或低风险，这可能有助于中风的预后判断和临床治疗。
结果：我们的研究共纳入242例基底动脉闭塞患者进行血管内血栓切除术，其中来自3个卒中中心的172名患者被分配到训练队列中，另一个中心的70例患者被分配到验证队列.采用单因素和多因素logistic回归分析筛选预后预测因子，具有显著性的在训练队列中建立列线图模型。辨别的准确性，校准,并且在内部和外部队列中验证了列线图模型的临床有效性。六个变量,包括年龄,基线美国国立卫生研究院卒中量表评分，后循环-阿尔伯塔省卒中计划早期CT（计算机断层扫描）评分，基底动脉计算机断层造影评分,再通失败，有症状的颅内出血,被确定为基底动脉闭塞患者90天死亡率的独立预测因子,并建立列线图模型.列线图模型表现出良好的辨别力，校准,以及在内部和外部队列中的临床有用性。此外,患者被分为低，moderate-,和基于风险分层列线图模型的高危人群。
结论：我们的研究提出了一种新的列线图模型，该模型可以有效预测血管内血栓切除术后基底动脉闭塞患者的90天死亡率，并对高死亡率患者进行分层。中度,或低风险，这可能有助于中风的预后判断和临床治疗。
