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重症监护病房内医院卒中死亡率的预测

Prediction of in-hospital stroke mortality in critical care unit.

作者信息

Ho Wei-Min, Lin Jr-Rung, Wang Hui-Hsuan, Liou Chia-Wei, Chang Ku-Chou, Lee Jiann-Der, Peng Tsung-Yi, Yang Jen-Tsung, Chang Yeu-Jhy, Chang Chien-Hung, Lee Tsong-Hai

机构信息

Dementia Center and Department of Neurology, Linkou Medical Center, Chang Gung Memorial Hospital, No.5, Fuxing St., Guishan Dist., Taoyuan City, 333 Taiwan, ROC.

Clinical Informatics and Medical Statistics Research Center, Chang Gung University, No.261, Wenhua 1st Rd., Guishan Dist., Taoyuan City, 333 Taiwan, ROC.

出版信息

Springerplus. 2016 Jul 11;5(1):1051. doi: 10.1186/s40064-016-2687-2. eCollection 2016.

Abstract

BACKGROUND

Critical stroke causes high morbidity and mortality. We examined if variables in the early stage of critical stroke could predict in-hospital mortality.

METHODS

We recruited 611 ischemic and 805 hemorrhagic stroke patients who were admitted within 24 h after the symptom onset. Data were analyzed with independent t test and Chi square test, and then with multivariate logistic regression analysis.

RESULTS

In ischemic stroke, National Institutes of Health Stroke Scale (NIHSS) score (OR 1.08; 95 % CI 1.06-1.11; P < 0.01), white blood cell count (OR 1.11; 95 % CI 1.05-1.18; P < 0.01), systolic blood pressure (BP) (OR 0.49; 95 % CI 0.26-0.90; P = 0.02) and age (OR 1.03; 95 % CI 1.00-1.05; P = 0.03) were associated with in-hospital mortality. In hemorrhagic stroke, NIHSS score (OR 1.12; 95 % CI 1.09-1.14; P < 0.01), systolic BP (OR 0.25; 95 % CI 0.15-0.41; P < 0.01), heart disease (OR 1.94; 95 % CI 1.11-3.39; P = 0.02) and creatinine (OR 1.16; 95 % CI 1.01-1.34; P = 0.04) were related to in-hospital mortality. Nomograms using these significant predictors were constructed for easy and quick evaluation of in-hospital mortality.

CONCLUSION

Variables in acute stroke can predict in-hospital mortality and help decision-making in clinical practice using nomogram.

摘要

背景

重症卒中导致高发病率和死亡率。我们研究了重症卒中早期的变量是否能预测住院死亡率。

方法

我们招募了611例缺血性卒中和805例出血性卒中患者,这些患者在症状发作后24小时内入院。数据采用独立t检验和卡方检验进行分析,然后进行多因素逻辑回归分析。

结果

在缺血性卒中中,美国国立卫生研究院卒中量表(NIHSS)评分(比值比[OR]1.08;95%置信区间[CI]1.06 - 1.11;P < 0.01)、白细胞计数(OR 1.11;95% CI 1.05 - 1.18;P < 0.01)、收缩压(BP)(OR 0.49;95% CI 0.26 - 0.90;P = 0.02)和年龄(OR 1.03;95% CI 1.00 - 1.05;P = 0.03)与住院死亡率相关。在出血性卒中中,NIHSS评分(OR 1.12;95% CI 1.09 - 1.14;P < 0.01)、收缩压(OR 0.25;95% CI 0.15 - 0.41;P < 0.01)、心脏病(OR 1.94;95% CI 1.11 - 3.39;P = 0.02)和肌酐(OR 1.16;95% CI 1.01 - 1.34;P = 0.04)与住院死亡率相关。使用这些显著预测因子构建了列线图,以便于快速评估住院死亡率。

结论

急性卒中变量可预测住院死亡率,并有助于在临床实践中使用列线图进行决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf9a/4940351/c9d2cccb1c96/40064_2016_2687_Fig1_HTML.jpg

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