Literature DB >> 28874288

Atrial fibrillation: Utility of CHADS2 and CHA2DS2-VASc scores as predictors of readmission, mortality and resource utilization.

Sopan Lahewala1, Shilpkumar Arora2, Prashant Patel3, Varun Kumar4, Nirali Patel3, Byomesh Tripathi4, Nilay Patel5, Kamala Ramya Kallur4, Harshil Shah6, Amer Syed1, Umesh Gidwani6, Juan F Viles-Gonzalez7, Abhishek Deshmukh8.   

Abstract

BACKGROUND: CHADS2 and CHA2DS2-VASc scores are widely used for thromboembolic risk assessment in Atrial Fibrillation(AF) cohort, however further utilization to predict outcomes is understudied.
METHOD: HCUP's National Readmission Data(NRD) 2013 was queried for AF admissions using ICD-9-CM code 427.31 in principal diagnosis field. Patients with mitral valve disease or repair/or replacement were excluded to estimate population with non-valvular AF only. CHADS2 and CHA2DS2-VASc were calculated for each patient. Hierarchical two-level logistic and linear models were used to evaluate study outcomes in terms of mortality, 30 or 90-day readmissions, length of stay(LOS) and cost. RESULT: Of 116,450 principal non-valvular AF admissions(50.2% female and 43.1% age≥75years) 29,179 patients were readmitted, with total 40,959 readmissions. Higher CHADS2 and CHA2DS2-VASc score were associated with increased mortality from 0.4% for CHADS2 of 0 to 3.2% for score of 6 and from 0.2% for CHA2DS2-VASc of 0 to 3.2% for score≥8. LOS increased from 2.20days for CHADS2 of 0 to 5.08days for score of 6, while cost increased from $7888 to $11,151. 30-day readmission rate increased from 8.9% for CHADS2 of 0 to 26.0% for score of 6, and 90-day readmission rate increased from 15.2% to 39%. CHA2DS2-VASc scoring similarly demonstrated a trend towards increasing readmission rate, LOS and cost for higher scores. Also, similar results were seen in hierarchical modeling with increment of CHADS2 and CHA2DS2-VASc scores.
CONCLUSION: CHADS2 and CHA2DS2-VASc scores can be used as quick surrogate markers for predicting outcomes beyond thromboembolic risk. Physician familiarity with these systems makes them easy to use bedside clinical tools to improve outcomes and resource allocation.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Atrial fibrillation; CHA(2)DS(2)-VASc; CHADS(2); Mortality; Readmission

Mesh:

Year:  2017        PMID: 28874288     DOI: 10.1016/j.ijcard.2017.06.090

Source DB:  PubMed          Journal:  Int J Cardiol        ISSN: 0167-5273            Impact factor:   4.164


  6 in total

1.  Mortality in patients with atrial fibrillation and common co-morbidities - a cohort study in primary care.

Authors:  Per Wändell; Axel C Carlsson; Martin J Holzmann; Johan Ärnlöv; Jan Sundquist; Kristina Sundquist
Journal:  Ann Med       Date:  2017-11-27       Impact factor: 4.709

2.  CHA2DS2-VASC Score Predicts the Risk of Stroke in Patients Hospitalized to the Internal Medicine Department Without Known Atrial Fibrillation.

Authors:  Karney Lahad; Elad Maor; Robert Klempfner; Chagai Grossman; Amit Druyan; Ilan Ben-Zvi
Journal:  J Gen Intern Med       Date:  2022-05-27       Impact factor: 6.473

3.  Low alanine aminotransferase levels are independently associated with mortality risk in patients with atrial fibrillation.

Authors:  Yuki Saito; Yasuo Okumura; Koichi Nagashima; Daisuke Fukamachi; Katsuaki Yokoyama; Naoya Matsumoto; Eizo Tachibana; Keiichiro Kuronuma; Koji Oiwa; Michiaki Matsumoto; Toshihiko Nishida; Toshiaki Kojima; Shoji Hanada; Kazumiki Nomoto; Kazumasa Sonoda; Ken Arima; Fumiyuki Takahashi; Tomobumi Kotani; Kimie Ohkubo; Seiji Fukushima; Satoru Itou; Kunio Kondo; Hideyuki Ando; Yasumi Ohno; Motoyuki Onikura; Atsushi Hirayama
Journal:  Sci Rep       Date:  2022-07-16       Impact factor: 4.996

4.  Functional Analysis of Serum Long Noncoding RNAs in Patients with Atrial Fibrillation.

Authors:  Qi Zhang; Jun Wang; Ying Wang; Ji-Meng Yang; Hai-Cui Dong; Di Xu
Journal:  Dis Markers       Date:  2022-05-16       Impact factor: 3.464

5.  Outcomes and Resource Utilization Associated With Readmissions After Atrial Fibrillation Hospitalizations.

Authors:  Byomesh Tripathi; Varunsiri Atti; Varun Kumar; Vamsidhar Naraparaju; Purnima Sharma; Shilpkumar Arora; Ewelina Wojtaszek; Radha Gopalan; Konstantinos C Siontis; Bernard J Gersh; Abhishek Deshmukh
Journal:  J Am Heart Assoc       Date:  2019-09-19       Impact factor: 5.501

6.  Impact of the Fibrosis-4 Index on Risk Stratification of Cardiovascular Events and Mortality in Patients with Atrial Fibrillation: Findings from a Japanese Multicenter Registry.

Authors:  Yuki Saito; Yasuo Okumura; Koichi Nagashima; Daisuke Fukamachi; Katsuaki Yokoyama; Naoya Matsumoto; Eizo Tachibana; Keiichiro Kuronuma; Koji Oiwa; Michiaki Matsumoto; Toshihiko Nishida; Toshiaki Kojima; Shoji Hanada; Kazumiki Nomoto; Kazumasa Sonoda; Ken Arima; Fumiyuki Takahashi; Tomobumi Kotani; Kimie Ohkubo; Seiji Fukushima; Satoru Itou; Kunio Kondo; Hideyuki Ando; Yasumi Ohno; Motoyuki Onikura; Atsushi Hirayama
Journal:  J Clin Med       Date:  2020-02-21       Impact factor: 4.241

  6 in total

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