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用于预测应激性心肌病患者院内死亡率的简单整数风险评分的开发与验证

Development and validation of a simple integer risk score for prediction of in-hospital mortality following Takotsubo syndrome.

作者信息

Mahmoud Ahmed N, Al-Ani Mohammad, Saad Marwan, Elgendy Akram Y, Elgendy Islam Y

机构信息

Division of Cardiovascular Medicine, Department of Medicine, University of Florida, Gainesville, FL, USA.

Division of Cardiovascular Medicine, Department of Medicine, University of Florida, Gainesville, FL, USA.

出版信息

Heart Lung. 2016 Nov-Dec;45(6):510-514. doi: 10.1016/j.hrtlng.2016.08.009. Epub 2016 Sep 24.

DOI:10.1016/j.hrtlng.2016.08.009
PMID:27679934
Abstract

BACKGROUND

Data regarding the characteristics associated with worse outcomes in Takotsubo syndrome (TTS) patients is lacking.

METHODS AND OBJECTIVES

The National Inpatient Sample (NIS) 2012 database was utilized to calculate a risk score for in-hospital mortality following TTS that was internally and externally validated in both 2012 and 2013 databases, respectively.

RESULTS

The incidences of in-hospital mortality in the 2012 development sample were 0.2%, 3.2% and 15.6% in the low risk (≤2), intermediate risk (3-4) and high-risk (≥5) score groups, respectively. The risk score C-statistics were 0.86 and 0.88 in the development and external validation samples, respectively (p < 0.001). Age ≥ 80 year was associated with the highest odds ratio (OR) of mortality (OR 8.07, 95% confidence interval (CI) 5.79-11.25). Other important predictors were acute cerebrovascular accident and acute respiratory failure.

CONCLUSIONS

The risk of in-hospital mortality following TTS could be predicted using a simple risk score, which could aid in identifying and proper management of a higher risk group.

摘要

背景

关于应激性心肌病(TTS)患者预后较差相关特征的数据尚缺乏。

方法与目的

利用2012年全国住院患者样本(NIS)数据库计算TTS患者院内死亡风险评分,并分别在2012年和2013年数据库中进行内部和外部验证。

结果

在2012年的开发样本中,低风险(≤2)、中风险(3 - 4)和高风险(≥5)评分组的院内死亡率分别为0.2%、3.2%和15.6%。开发样本和外部验证样本的风险评分C统计量分别为0.86和0.88(p < 0.001)。年龄≥80岁与最高的死亡比值比(OR)相关(OR 8.07,95%置信区间(CI)5.79 - 11.25)。其他重要的预测因素是急性脑血管意外和急性呼吸衰竭。

结论

可使用简单的风险评分预测TTS患者的院内死亡风险,这有助于识别和妥善管理高风险组。

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