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A clinical score to predict mortality in patients after acute heart failure from Japanese registry

AIMS: Clinical scores that consider physical and social factors to predict long‐term observations in patients after acute heart failure are limited. This study aimed to develop and validate a prediction model for patients with acute heart failure at the time of discharge. METHODS AND RESULTS: This s...

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Autores principales: Takabayashi, Kensuke, Okada, Yohei, Iwatsu, Kotaro, Ikeda, Tsutomu, Fujita, Ryoko, Takenaka, Hiroyuki, Kitamura, Tetsuhisa, Kitaguchi, Shouji, Nohara, Ryuji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8712813/
https://www.ncbi.nlm.nih.gov/pubmed/34687170
http://dx.doi.org/10.1002/ehf2.13664
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author Takabayashi, Kensuke
Okada, Yohei
Iwatsu, Kotaro
Ikeda, Tsutomu
Fujita, Ryoko
Takenaka, Hiroyuki
Kitamura, Tetsuhisa
Kitaguchi, Shouji
Nohara, Ryuji
author_facet Takabayashi, Kensuke
Okada, Yohei
Iwatsu, Kotaro
Ikeda, Tsutomu
Fujita, Ryoko
Takenaka, Hiroyuki
Kitamura, Tetsuhisa
Kitaguchi, Shouji
Nohara, Ryuji
author_sort Takabayashi, Kensuke
collection PubMed
description AIMS: Clinical scores that consider physical and social factors to predict long‐term observations in patients after acute heart failure are limited. This study aimed to develop and validate a prediction model for patients with acute heart failure at the time of discharge. METHODS AND RESULTS: This study was retrospective analysis of the Kitakawachi Clinical Background and Outcome of Heart Failure Registry database. The registry is a prospective, multicentre cohort of patients with acute heart failure between April 2015 and August 2017. The primary outcome to be predicted was the incidence of all‐cause mortality during the 3 years of follow‐up period. The development cohort derived from April 2015 to July 2016 was used to build the prediction model, and the test cohort from August 2016 to August 2017 was used to evaluate the prediction model. The following potential predictors were selected by the least absolute shrinkage and selection operator method: age, sex, body mass index, activities of daily living at discharge, social background, comorbidities, biomarkers, and echocardiographic findings; a risk scoring system was developed using a logistic model to predict the outcome using a simple integer based on each variable's β coefficient. Out of 1253 patients registered, 1117 were included in the analysis and divided into the development (n = 679) and test (n = 438) cohorts. The outcomes were 246 (36.2%) in the development cohort and 143 (32.6%) in the test cohort. Eleven variables including physical and social factors were set into the logistic regression model, and the risk scoring system was created. The patients were divided into three groups: low risk (score 0–5), moderate risk (score 6–11), and high risk (score ≥12). The observed and predicted mortality rates were described by the Kaplan–Meier curve divided by risk group and independently increased (P < 0.001). In the test cohort, the C statistic of the prediction model was 0.778 (95% confidence interval: 0.732–0.824), and the mean predicted probabilities in the groups were low, 6.9% (95% confidence interval: 3.8–10%); moderate, 30.1% (95% confidence interval: 25.4%–34.8%); and high, 79.2% (95% confidence interval: 72.6%–85.8%). The predicted probability was well calibrated to the observed outcomes in both cohorts. CONCLUSIONS: The Kitakawachi Clinical Background and Outcome of Heart Failure score was helpful in predicting adverse events in patients with acute heart failure over a long‐term period. We should evaluate the physical and social functions of such patients before discharge to prevent adverse outcomes.
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spelling pubmed-87128132022-01-04 A clinical score to predict mortality in patients after acute heart failure from Japanese registry Takabayashi, Kensuke Okada, Yohei Iwatsu, Kotaro Ikeda, Tsutomu Fujita, Ryoko Takenaka, Hiroyuki Kitamura, Tetsuhisa Kitaguchi, Shouji Nohara, Ryuji ESC Heart Fail Original Articles AIMS: Clinical scores that consider physical and social factors to predict long‐term observations in patients after acute heart failure are limited. This study aimed to develop and validate a prediction model for patients with acute heart failure at the time of discharge. METHODS AND RESULTS: This study was retrospective analysis of the Kitakawachi Clinical Background and Outcome of Heart Failure Registry database. The registry is a prospective, multicentre cohort of patients with acute heart failure between April 2015 and August 2017. The primary outcome to be predicted was the incidence of all‐cause mortality during the 3 years of follow‐up period. The development cohort derived from April 2015 to July 2016 was used to build the prediction model, and the test cohort from August 2016 to August 2017 was used to evaluate the prediction model. The following potential predictors were selected by the least absolute shrinkage and selection operator method: age, sex, body mass index, activities of daily living at discharge, social background, comorbidities, biomarkers, and echocardiographic findings; a risk scoring system was developed using a logistic model to predict the outcome using a simple integer based on each variable's β coefficient. Out of 1253 patients registered, 1117 were included in the analysis and divided into the development (n = 679) and test (n = 438) cohorts. The outcomes were 246 (36.2%) in the development cohort and 143 (32.6%) in the test cohort. Eleven variables including physical and social factors were set into the logistic regression model, and the risk scoring system was created. The patients were divided into three groups: low risk (score 0–5), moderate risk (score 6–11), and high risk (score ≥12). The observed and predicted mortality rates were described by the Kaplan–Meier curve divided by risk group and independently increased (P < 0.001). In the test cohort, the C statistic of the prediction model was 0.778 (95% confidence interval: 0.732–0.824), and the mean predicted probabilities in the groups were low, 6.9% (95% confidence interval: 3.8–10%); moderate, 30.1% (95% confidence interval: 25.4%–34.8%); and high, 79.2% (95% confidence interval: 72.6%–85.8%). The predicted probability was well calibrated to the observed outcomes in both cohorts. CONCLUSIONS: The Kitakawachi Clinical Background and Outcome of Heart Failure score was helpful in predicting adverse events in patients with acute heart failure over a long‐term period. We should evaluate the physical and social functions of such patients before discharge to prevent adverse outcomes. John Wiley and Sons Inc. 2021-10-22 /pmc/articles/PMC8712813/ /pubmed/34687170 http://dx.doi.org/10.1002/ehf2.13664 Text en © 2021 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Original Articles
Takabayashi, Kensuke
Okada, Yohei
Iwatsu, Kotaro
Ikeda, Tsutomu
Fujita, Ryoko
Takenaka, Hiroyuki
Kitamura, Tetsuhisa
Kitaguchi, Shouji
Nohara, Ryuji
A clinical score to predict mortality in patients after acute heart failure from Japanese registry
title A clinical score to predict mortality in patients after acute heart failure from Japanese registry
title_full A clinical score to predict mortality in patients after acute heart failure from Japanese registry
title_fullStr A clinical score to predict mortality in patients after acute heart failure from Japanese registry
title_full_unstemmed A clinical score to predict mortality in patients after acute heart failure from Japanese registry
title_short A clinical score to predict mortality in patients after acute heart failure from Japanese registry
title_sort clinical score to predict mortality in patients after acute heart failure from japanese registry
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8712813/
https://www.ncbi.nlm.nih.gov/pubmed/34687170
http://dx.doi.org/10.1002/ehf2.13664
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