Risk prediction model of in-hospital mortality in heart failure with preserved ejection fraction and mid-range ejection fraction: a retrospective cohort study

2021 ◽  
Vol 15 (14) ◽  
pp. 1223-1232
Author(s):  
Chuan-he Wang ◽  
Su Han ◽  
Fei Tong ◽  
Ying Li ◽  
Zhi-chao Li ◽  
...  

Aim: To develop and validate internally a multivariate risk model for predicting the in-hospital mortality of patients with heart failure with preserved ejection fraction (HFpEF) and heart failure with mid-range ejection fraction (HFmrEF). Methods & results: The clinical data of 8172 inpatients with HFpEF and HFmrEF was used to establish a retrospective database. These patients, among whom 307 in-hospital deaths (3.8%) occurred, were randomly assigned to derivation and verification cohort. Among the extracted data from the derivation cohort were nine variables significantly related to in-hospital mortality, which were scored 0–4, for a total score of 24, which allowed formation of a risk predictive model. The verification cohort was then used to validate the discrimination and calibration capacities of this predictive model: the area under curve equaled 0.8575 (0.8285, 0.8865) for the derivation cohort, and 0.8323 (0.7999, 0.8646) for the verification cohort. According to this risk score, we divided patients into four risk classes (low-, medium-, high- and extremely high-risk) and revealed that the risk of in-hospital mortality increased with increasing risk class with an obvious linear relationship between actual and predicted mortality (r = 0.998, p < 0.001). Conclusion: The model based on nine common clinical variables should provide an accurate prediction of in-hospital mortality and appears to be a reliable risk classification system for patients with HFpEF and HFmrEF.

2021 ◽  
Vol 77 (18) ◽  
pp. 802
Author(s):  
Vicente Morales Oyarvide ◽  
Donald Richards ◽  
Nicholas Hendren ◽  
Katherine Michelis ◽  
Thanat Chaikijurajai ◽  
...  

2021 ◽  
Author(s):  
Yohei Sotomi ◽  
Katsuomi Iwakura ◽  
Shungo Hikoso ◽  
Koichi Inoue ◽  
Toshinari Onishi ◽  
...  

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