Literature DB >> 22621797

A new scoring system for evaluating the risk of heart failure events in Japanese patients with atrial fibrillation.

Shinya Suzuki1, Koichi Sagara, Takayuki Otsuka, Shunsuke Matsuno, Ryuichi Funada, Tokuhisa Uejima, Yuji Oikawa, Junji Yajima, Akira Koike, Kazuyuki Nagashima, Hajime Kirigaya, Hitoshi Sawada, Tadanori Aizawa, Takeshi Yamashita.   

Abstract

Risk stratification for heart failure (HF) in patients with atrial fibrillation (AF) has not been well established. The aim of this study was to identify the predictors of HF events in patients with AF, consequently developing a new risk-scoring system that stratifies the risk for HF events. In this prospective, single hospital-based cohort, all patients who presented from July 2004 to March 2010 were registered (Shinken Database 2004-2009). Follow-up was maintained by being linked to the medical records or by sending study documents of prognosis. Of the 13,228 patients in the Shinken Database 2004-2009, 1,942 patients with AF were identified. Of the patients with AF, HF events (hospitalization or death from HF) occurred in 147 patients (7.6%) during a mean follow-up period of 776 ± 623 days. After identifying the parameters that were independently associated with the incidence of HF events (coexistence of organic heart diseases, anemia [hemoglobin level <11 g/dl], renal dysfunction [estimated glomerular filtration rate <60 ml/min/m(2)], diabetes mellitus, and the use of diuretics), a new scoring system was developed, the H(2)ARDD score (heart diseases = 2 points, anemia = 1 point, renal dysfunction = 1 point, diabetes = 1 point, and diuretic use = 1 point; range 0 to 6 points). This scoring system discriminated the low- and high-risk populations well (incidence in patients scoring 0 and 6 points of 0.2% and 40.8% per patient-year, respectively) and showed high predictive ability (area under the curve 0.840, 95% confidence interval 0.803 to 0.876). In conclusion, the new H(2)ARDD score may help identify the population of patients with AF at high risk for HF events.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22621797     DOI: 10.1016/j.amjcard.2012.04.049

Source DB:  PubMed          Journal:  Am J Cardiol        ISSN: 0002-9149            Impact factor:   2.778


  11 in total

1.  Clinical characteristics and cardiovascular outcomes in patients with atrial fibrillation receiving rhythm-control therapy: the Fushimi AF Registry.

Authors:  Yoshimori An; Masahiro Esato; Mitsuru Ishii; Moritake Iguchi; Nobutoyo Masunaga; Hikari Tsuji; Hiromichi Wada; Koji Hasegawa; Hisashi Ogawa; Mitsuru Abe; Gregory Y H Lip; Masaharu Akao
Journal:  Heart Vessels       Date:  2018-05-24       Impact factor: 2.037

Review 2.  Global epidemiology of atrial fibrillation.

Authors:  Faisal Rahman; Gene F Kwan; Emelia J Benjamin
Journal:  Nat Rev Cardiol       Date:  2014-08-12       Impact factor: 32.419

Review 3.  Anemia: An Independent Predictor Of Adverse Outcomes In Older Patients With Atrial Fibrillation.

Authors:  Ali N Ali; Nandkishor V Athavale; Ahmed H Abdelhafiz
Journal:  J Atr Fibrillation       Date:  2016-04-30

Review 4.  Atrial fibrillation and heart failure: intersecting populations, morbidities, and mortality.

Authors:  Oana Dickinson; Lin Y Chen; Gary S Francis
Journal:  Heart Fail Rev       Date:  2014-05       Impact factor: 4.214

5.  Impact of BNP level and peak VO2 on future heart failure events: comparison between sinus rhythm and atrial fibrillation.

Authors:  Yuko Kato; Shinya Suzuki; Tokuhisa Uejima; Hiroaki Semba; Hiroto Kano; Shunsuke Matsuno; Hideaki Takai; Takayuki Otsuka; Yuji Oikawa; Kazuyuki Nagashima; Hajime Kirigaya; Koichi Sagara; Takashi Kunihara; Junji Yajima; Hitoshi Sawada; Tadanori Aizawa; Takeshi Yamashita
Journal:  Heart Vessels       Date:  2016-08-22       Impact factor: 2.037

6.  Factors associated with atrial fibrillation in Japanese patients with type 2 diabetes mellitus: a cross-sectional study.

Authors:  Natsuki Honda; Akinobu Ochi; Sadahiko Uchimoto; Yoshinori Kakutani; Yuko Yamazaki; Tomoaki Morioka; Tetsuo Shoji; Masaaki Inaba; Masanori Emoto
Journal:  Diabetol Int       Date:  2022-01-24

7.  Risk assessment for incident heart failure in individuals with atrial fibrillation.

Authors:  Renate B Schnabel; Michiel Rienstra; Lisa M Sullivan; Jenny X Sun; Carlee B Moser; Daniel Levy; Michael J Pencina; João D Fontes; Jared W Magnani; David D McManus; Steven A Lubitz; Thomas M Tadros; Thomas J Wang; Patrick T Ellinor; Ramachandran S Vasan; Emelia J Benjamin
Journal:  Eur J Heart Fail       Date:  2013-04-17       Impact factor: 15.534

8.  Incidence and Predictors of Heart Failure in Patients With Atrial Fibrillation.

Authors:  Philipp Krisai; Linda S B Johnson; Giorgio Moschovitis; Alexander Benz; Chinthanie Ramasundarahettige; William F McIntyre; Jorge A Wong; David Conen; Christian Sticherling; Stuart J Connolly; Jeff S Healey
Journal:  CJC Open       Date:  2021-08-08

9.  Risk factors for heart failure hospitalizations among patients with atrial fibrillation.

Authors:  Lucien Eggimann; Steffen Blum; Stefanie Aeschbacher; Andreas Reusser; Peter Ammann; Paul Erne; Giorgio Moschovitis; Marcello Di Valentino; Dipen Shah; Jürg Schläpfer; Nadine Mondet; Michael Kühne; Christian Sticherling; Stefan Osswald; David Conen
Journal:  PLoS One       Date:  2018-02-02       Impact factor: 3.240

10.  CHADS2 and modified CHA2DS2-VASc scores for the prediction of congestive heart failure in patients with nonvalvular atrial fibrillation.

Authors:  Yorihiko Koeda; Takashi Komatsu; Yuki Matsuura; Hidemi Morioka; Yohei Uchimura; Yuya Taguchi; Kentaro Tanaka; Jun Kawakami; Marie Nakamura; Shuko Takahashi; Yuji Takahashi; Yujiro Naganuma; Hiroshi Endo; Tatsuro Ito; Yoshihiro Morino; Motoyuki Nakamura
Journal:  J Arrhythm       Date:  2017-07-31
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