Prediction model of in-hospital mortality in elderly patients with acute heart failure based on retrospective study

被引:0
|
作者
Qian JIA [1 ,2 ]
YuRong WANG [1 ,2 ]
Ping HE [3 ]
XueLiang HUANG [1 ,4 ]
Wei YAN [4 ,5 ]
Yang MU [5 ]
KunLun HE [1 ,5 ]
YaPing TIAN [1 ,4 ]
机构
[1] Core Laboratory of Translational Medicine, Chinese PLA General Hospital
[2] Department of Cardiology, School of Medicine,Nankai University
[3] Department of Statistics, Peking University Health Science Center
[4] Department of Clinical Biochemistry, Chinese PLA General Hospital
[5] Department of Cardiology,Chinese PLA General
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R541.6 [血液循环衰竭];
学科分类号
摘要
Objectives The aim of this study was to develop a clinical risk model that is predictive of in-hospital mortality in elderly patients hospitalized with acute heart failure(AHF). Methods 2486 patients who were 60 years and older from intensive care units of Cardiology Department in the hospital were analyzed. Independent risk factors for in-hospital mortality were obtained by binary logistic regression and then used to establish the risk prediction score system(RPSS). The area under the curve(AUC) of receiver operator characteristic and C-statistic test were adopted to assess the performance of RPSS and to compare with previous get with the guidelines-heart failure(GWTG-HF). Results By binary logistic regression analysis, heart rate(OR: 1.043, 95% CI: 1.030-1.057, P < 0.001), left ventricular ejection fraction(OR:0.918, 95% CI: 0.833-0.966, P < 0.001), pH value(OR: 0.001, 95% CI: 0.000-0.002, P < 0.001), renal dysfunction(OR: 0.120, 95% CI:0.066-0.220, P < 0.001) and NT-pro BNP(OR: 3.463, 95% CI: 1.870-6.413, P < 0.001) were independent risk factors of in-hospital mortality for elderly AHF patients. Additionally, RPSS, which was composed of all the above-mentioned parameters, provided a better risk prediction than GWTG-THF(AUC: 0.873 vs. 0.818, P = 0.016). Conclusions Our risk prediction model, RPSS, provided a good prediction for in-hospital mortality in elderly patients with AHF.
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页码:669 / 678
页数:10
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