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钻孔引流与开颅治疗高血压性脑出血合并脑疝失败预测模型

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目的:探讨钻孔引流与开颅治疗高血压性脑出血(HICH)合并脑疝失败预测模型.方法:选择 2020年1月至 2022年 8月本院收治的 132例HICH合并脑疝患者,根据手术治疗结果,将患者分成成功组和失败组.单因素和多因素Logistic回归分析确定HICH合并脑疝治疗失败的影响因素,建立人工神经网络图.结果:Logistic回归分析结果显示,肌红蛋白、α-羟丁酸脱氢酶、血肿量、血肿破入脑室、脑中线移位程度、受伤至开颅时间及骨孔直径是HICH合并脑疝患者治疗失败的影响因素(P<0.05).结论:临床建立预测模型可预测引流与血肿清除手术效果,提高成功率和预后.
Prediction model for failure of drilling drainage and craniotomy in the treatment of hypertensive cerebral hemorrhage combined with cerebral herniation
Objective:To study the drainage and craniotomy for hypertensive brain herniation prediction model.Methods:A total of 132 patients with hypertensive cerebral hemorrhage complicated with cerebral hernia admitted to our hospital from January 2020 to August 2022 were selected,all patients underwent burr hole drainage combined with hematoma evacuation,According to the results of surgical treatment,the patients were divided into successful group and failure group.Univariate and multivariate Logistic regression analysis was used to determine the factors influencing the treatment failure of hypertensive cerebral hemorrhage complicated with cerebral hernia.Results:Logistic regression analysis showed that myoglobin,α-hydroxybutyrate dehydrogenase,hematoma volume,hematoma penetration into the ventricle,brain line displacement degree,time from injury to craniotomy and pore diameter were the factors influencing treatment failure in patients with HICH complicated with cerebral hernia(P<0.05).Conclusion:Clinical predictive models can forecast the outcomes of drainage and hematoma removal surgeries,enhancing success rates and prognoses.

artificial neural network diagramburr hole drainagehematoma evacuationhypertensive intracerebral hemorrhagecerebral herniaprediction model

刘甲、赵丽岩、聂红峰、冯进、尹丽萍、刘宏志

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邢台医学高等专科学校第一附属医院神经外科,河北邢台 054001

邢台医学高等专科学校第一附属医院内分泌科,河北邢台 054001

邢台医学高等专科学校第一附属医院胃肠外科,河北邢台 054001

邢台医学高等专科学校第一附属医院护理部,河北邢台 054001

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人工神经网络图 颅骨钻孔引流术 开颅血肿清除术 高血压性脑出血 脑疝 预测模型

2024

现代科学仪器
中国分析测试协会

现代科学仪器

CSTPCD
影响因子:0.329
ISSN:1003-8892
年,卷(期):2024.41(5)