Literature DB >> 28823956

Novel composite scoring system to predict unknown atrial fibrillation in acute ischemic stroke patients.

Rixia Liu1, Xiaomeng Yang1, Shuya Li1, Yong Jiang1, Yilong Wang1, Yongjun Wang2.   

Abstract

OBJECTIVES: The aim of the study is to ascertain whether a new risk-stratification scheme that combination of CHADS2 or CHA2DS2-VASc score and neuroimaging features could reliably predict unknown AF in patients with acute ischemic stroke.
METHODS: From October 2013 to June 2015, patients from 20 hospitals throughout China were selected from the study of Atrial Fibrillation Screening in the patients with acute ischemic stroke and transient ischemic attack (TIA). Brain imaging characteristics in prediction of AF detection were analyzed with multivariate logistic regressions. The clinical prediction of the models was examined using the C-statistic.
RESULTS: Among the 661 patients, previously undetected AF was in 53 patients (8.02%). Age, history of congestive heart failure, acute cortical involvement, acute insular cortex involvement, and prior cortical infarction were independently associated with newly detected AF. Using CHADS2 and CHA2DS2-VASc scores, C statistics for newly detected AF was 0.54 (OR 1.11, 95% CI: 0.88-1.38) and 0.58 (OR 1.17, 95% CI: 0.99-1.38), respectively; adding newly identified AF-associated imaging characteristics to the two scores, the value of C statistic was significantly improved to 0.74 (P<0.001) and 0.75 (P<0.001), respectively.
CONCLUSION: Both CHADS2 and CHA2DS2-VASc scores are useful but not optimal for predicting newly detected AF in patients with acute ischemic stroke. A newly identified embolic features combining with the CHADS2 or CHA2DS2-VASc score for predicting AF in patients with stroke is superior to the CHADS2 or CHA2DS2-VASc score alone.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Atrial fibrillation; CHA(2)DS(2)-VASc score; CHADS(2) score; Stroke

Mesh:

Year:  2017        PMID: 28823956     DOI: 10.1016/j.brainres.2017.08.005

Source DB:  PubMed          Journal:  Brain Res        ISSN: 0006-8993            Impact factor:   3.252


  2 in total

1.  Validation of Risk Scores for Predicting Atrial Fibrillation Detected After Stroke Based on an Electronic Medical Record Algorithm: A Registry-Claims-Electronic Medical Record Linked Data Study.

Authors:  Cheng-Yang Hsieh; Hsuan-Min Kao; Kuan-Lin Sung; Luciano A Sposato; Sheng-Feng Sung; Swu-Jane Lin
Journal:  Front Cardiovasc Med       Date:  2022-04-29

2.  Atrial fibrillation risk factors in patients with ischemic stroke.

Authors:  Paweł Wańkowicz; Przemysław Nowacki; Monika Gołąb-Janowska
Journal:  Arch Med Sci       Date:  2019-04-05       Impact factor: 3.318

  2 in total

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