Literature DB >> 24794758

New scoring system (APACHE-HF) for predicting adverse outcomes in patients with acute heart failure: evaluation of the APACHE II and Modified APACHE II scoring systems.

Hirotake Okazaki1, Akihiro Shirakabe2, Noritake Hata1, Masanori Yamamoto1, Nobuaki Kobayashi1, Takuro Shinada1, Kazunori Tomita1, Masafumi Tsurumi1, Masato Matsushita1, Yoshiya Yamamoto1, Shinya Yokoyama1, Kuniya Asai3, Wataru Shimizu3.   

Abstract

BACKGROUND: No scoring system for assessing acute heart failure (AHF) has been reported. METHODS AND
RESULTS: Data for 824 AHF patients were analyzed. The subjects were divided into an alive (n=750) and a dead group (n=74). We constructed a predictive scoring system based on eight significant APACHE II factors in the alive group [mean arterial pressure (MAP), pulse, sodium, potassium, hematocrit, creatinine, age, and Glasgow Coma Scale (GCS); giving each one point], defined as the APACHE-HF score. The patients were assigned to five groups by the APACHE-HF score [Group 1: point 0 (n=70), Group 2: points 1 and 2 (n=343), Group 3: points 3 and 4 (n=294), Group 4: points 5 and 6 (n=106), and Group 5: points 7 and 8 (n=11)]. A higher optimal balance was observed in the APACHE-HF between sensitivity and specificity [87.8%, 63.9%; area under the curve (AUC)=0.779] at 2.5 points than in the APACHE II (47.3%, 67.3%; AUC=0.558) at 17.5 points. The multivariate Cox regression model identified belonging to Group 5 [hazard ratio (HR): 7.764, 95% confidence interval (CI) 1.586-38.009], Group 4 (HR: 6.903, 95%CI 1.940-24.568) or Group 3 (HR: 5.335, 95%CI 1.582-17.994) to be an independent predictor of 3-year mortality. The Kaplan-Meier curves revealed a poorer prognosis, including all-cause death and HF events (death, readmission-HF), in Group 5 and Group 4 than in the other groups, in Group 3 than in Group 2 or Group 1, and in Group 2 than in Group 1.
CONCLUSIONS: The new scoring system including MAP, pulse, sodium, potassium, hematocrit, creatinine, age, and GCS (APACHE-HF) can be used to predict adverse outcomes of AHF.
Copyright © 2014 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Acute heart failure syndrome; Mortality; Prognosis; Scoring

Mesh:

Year:  2014        PMID: 24794758     DOI: 10.1016/j.jjcc.2014.03.002

Source DB:  PubMed          Journal:  J Cardiol        ISSN: 0914-5087            Impact factor:   3.159


  5 in total

1.  Decreased blood glucose at admission has a prognostic impact in patients with severely decompensated acute heart failure complicated with diabetes mellitus.

Authors:  Akihiro Shirakabe; Noritake Hata; Nobuaki Kobayashi; Hirotake Okazaki; Masato Matsushita; Yusaku Shibata; Suguru Nishigoori; Saori Uchiyama; Kazutaka Kiuchi; Fumitaka Okajima; Toshiaki Otsuka; Kuniya Asai; Wataru Shimizu
Journal:  Heart Vessels       Date:  2018-03-22       Impact factor: 2.037

Review 2.  Predicting mortality in patients with acute heart failure: Role of risk scores.

Authors:  Andrea Passantino; Francesco Monitillo; Massimo Iacoviello; Domenico Scrutinio
Journal:  World J Cardiol       Date:  2015-12-26

3.  Severity of illness scores at presentation predict ICU admission and mortality in COVID-19.

Authors:  Erin M Wilfong; Christine M Lovly; Erin A Gillaspie; Li-Ching Huang; Yu Shyr; Jonathan D Casey; Brian I Rini; Matthew W Semler
Journal:  J Emerg Crit Care Med       Date:  2021-01-25

4.  Causes and Predictors of In-Hospital Mortality in Patients Admitted with or for Heart Failure at a Tertiary Hospital in Brazil.

Authors:  André Wajner; Priccila Zuchinali; Vírgilio Olsen; Carisi A Polanczyk; Luis Eduardo Rohde
Journal:  Arq Bras Cardiol       Date:  2017-09-28       Impact factor: 2.000

5.  Blood Urea Nitrogen (BUN) is independently associated with mortality in critically ill patients admitted to ICU.

Authors:  Okan Arihan; Bernhard Wernly; Michael Lichtenauer; Marcus Franz; Bjoern Kabisch; Johanna Muessig; Maryna Masyuk; Alexander Lauten; Paul Christian Schulze; Uta C Hoppe; Malte Kelm; Christian Jung
Journal:  PLoS One       Date:  2018-01-25       Impact factor: 3.240

  5 in total

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