| Autor: |
Takeshi Yagyu, Masahiro Kumada, Tsutomu Nakagawa |
| Jazyk: |
angličtina |
| Rok vydání: |
2017 |
| Předmět: |
|
| Zdroj: |
PLoS ONE, Vol 12, Iss 11, p e0187410 (2017) |
| Druh dokumentu: |
article |
| ISSN: |
1932-6203 |
| DOI: |
10.1371/journal.pone.0187410 |
| Popis: |
Patients with acute heart failure (AHF) show various clinical courses during hospitalization. We aimed to identify time course predictors of in-hospital mortality and to establish a sequentially assessable risk model.We enrolled 1,035 consecutive AHF patients into derivation (n = 597) and validation (n = 438) cohorts. For risk assessments at admission, we utilized Get With the Guidelines-Heart Failure (GWTG-HF) risk scores. We examined significant predictors of in-hospital mortality from 11 variables obtained during hospitalization and developed a risk stratification model using multiple logistic regression analysis. Across both cohorts, 86 patients (8.3%) died during hospitalization. Using backward stepwise selection, we identified five time-course predictors: catecholamine administration, minimum platelet concentration, maximum blood urea nitrogen, total bilirubin, and C-reactive protein levels; and established a time course risk score that could sequentially assess a patient's risk status. The addition of a time course risk score improved the discriminative ability of the GWTG-HF risk score (c-statistics in derivation and validation cohorts: 0.776 to 0.888 [p = 0.002] and 0.806 to 0.902 [p |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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