2017
DOI: 10.1002/ejhf.785
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Development and validation of multivariable models to predict mortality and hospitalization in patients with heart failure

Abstract: A small number of variables, which are usually readily available in the routine clinical setting, provide useful prognostic information for patients with HF. Predictors of mortality were remarkably different from predictors of hospitalization owing to HF.

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Cited by 210 publications
(287 citation statements)
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“…[21][22][23][24][25] Calculated PVS might be prognostic because it truly reflects fluid retention that could be a marker or mediator of CHF progression. Moreover, it did so after adjustment for treatment allocation implying that the associations elucidated here were not simply driven by FCM.…”
Section: Discussionmentioning
confidence: 99%
“…[21][22][23][24][25] Calculated PVS might be prognostic because it truly reflects fluid retention that could be a marker or mediator of CHF progression. Moreover, it did so after adjustment for treatment allocation implying that the associations elucidated here were not simply driven by FCM.…”
Section: Discussionmentioning
confidence: 99%
“…The BIOSTAT‐CHF risk models used for adjustment throughout these analyses have been published and validated …”
Section: Methodsmentioning
confidence: 99%
“…All parameters were previously found to be independently associated with the outcomes in the BIOSTAT cohort and were used to build the risk models derived from this cohort (URL: https://biostat-chf.shinyapps.io/calc/). 9 …”
Section: Methodsmentioning
confidence: 99%