Literature DB >> 33592506

Trends in ischemic stroke outcomes in a rural population in the United States.

Durgesh Chaudhary1, Ayesha Khan1, Shima Shahjouei1, Mudit Gupta2, Clare Lambert3, Venkatesh Avula4, Clemens M Schirmer5, Neil Holland6, Christoph J Griessenauer5, M Reza Azarpazhooh7, Jiang Li8, Vida Abedi9, Ramin Zand10.   

Abstract

INTRODUCTION: The stroke mortality rate has gradually declined due to improved interventions and controlled risk factors. We investigated the associated factors and trends in recurrence and all-cause mortality in ischemic stroke patients from a rural population in the United States between 2004 and 2018.
METHODS: This was a retrospective cohort study based on electronic health records (EHR) data. A comprehensive stroke database called "Geisinger NeuroScience Ischemic Stroke (GNSIS)" was built for this study. Clinical data were extracted from multiple sources, including EHR and quality data.
RESULTS: The cohort included in the study comprised of 8561 consecutive ischemic stroke patients (mean age: 70.1 ± 13.9 years, men: 51.6%, 95.1% Caucasian). Hypertension was the most prevalent risk factor (75.2%). The one-year recurrence and all-cause mortality rates were 6.3% and 16.1%, respectively. Although the one-year stroke recurrence increased during the study period, the one-year stroke mortality rate decreased significantly. Age > 65 years, atrial fibrillation or flutter, heart failure, and prior ischemic stroke were independently associated with one-year all-cause mortality in stratified Cox proportional hazards model. In the Cause-specific hazard model, diabetes, chronic kidney disease and age < 65 years were found to be associated with one-year ischemic stroke recurrence.
CONCLUSION: Although all-cause mortality after stroke has decreased, stroke recurrence has significantly increased in stroke patients from rural population between 2004 and 2018. Older age, atrial fibrillation or flutter, heart failure, and prior ischemic stroke were independently associated with one-year all-cause mortality while diabetes, chronic kidney disease and age less than 65 years were predictors of ischemic stroke recurrence.
Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  All-cause mortality; Ischemic stroke; Outcomes; Recurrent stroke; Trends

Mesh:

Year:  2021        PMID: 33592506     DOI: 10.1016/j.jns.2021.117339

Source DB:  PubMed          Journal:  J Neurol Sci        ISSN: 0022-510X            Impact factor:   3.181


  7 in total

1.  Predicting mortality among ischemic stroke patients using pathways-derived polygenic risk scores.

Authors:  Jiang Li; Durgesh Chaudhary; Christoph J Griessenauer; David J Carey; Ramin Zand; Vida Abedi
Journal:  Sci Rep       Date:  2022-07-19       Impact factor: 4.996

2.  Machine Learning-Enabled 30-Day Readmission Model for Stroke Patients.

Authors:  Negar Darabi; Niyousha Hosseinichimeh; Anthony Noto; Ramin Zand; Vida Abedi
Journal:  Front Neurol       Date:  2021-03-31       Impact factor: 4.003

3.  Comparison of Long-Term Outcomes and Associated Factors between Younger and Older Rural Ischemic Stroke Patients.

Authors:  Durgesh Chaudhary; Michelle Anyaehie; Francis Demiraj; Shreya Bavishi; Shima Shahjouei; Jiang Li; Vida Abedi; Ramin Zand
Journal:  J Clin Med       Date:  2022-03-05       Impact factor: 4.241

4.  Predictors of Post-Stroke Depression: A Retrospective Cohort Study.

Authors:  Durgesh Chaudhary; Isabel Friedenberg; Vishakha Sharma; Pragyan Sharma; Vida Abedi; Ramin Zand; Jiang Li
Journal:  Brain Sci       Date:  2022-07-27

5.  The prevention of stroke by statins: A meta-analysis.

Authors:  Xiaoxu San; Zhiguo Lv; Peng Xu; Jian Wang; Tianye Lan
Journal:  Medicine (Baltimore)       Date:  2022-09-23       Impact factor: 1.817

6.  Predicting short and long-term mortality after acute ischemic stroke using EHR.

Authors:  Vida Abedi; Venkatesh Avula; Seyed-Mostafa Razavi; Shreya Bavishi; Durgesh Chaudhary; Shima Shahjouei; Ming Wang; Christoph J Griessenauer; Jiang Li; Ramin Zand
Journal:  J Neurol Sci       Date:  2021-06-29       Impact factor: 4.553

7.  Prediction of Long-Term Stroke Recurrence Using Machine Learning Models.

Authors:  Vida Abedi; Venkatesh Avula; Durgesh Chaudhary; Shima Shahjouei; Ayesha Khan; Christoph J Griessenauer; Jiang Li; Ramin Zand
Journal:  J Clin Med       Date:  2021-03-20       Impact factor: 4.241

  7 in total

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