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Current Neurovascular Research


ISSN (Print): 1567-2026
ISSN (Online): 1875-5739

Research Article

Determinants of Use of Long-term Continuous Electrocardiographic Monitoring for Acute Ischemic Stroke Patients without Atrial Fibrillation at Baseline

Author(s): Jiann-Der Lee, Yen-Chu Huang, Meng Lee, Tsong-Hai Lee, Ya-Wen Kuo, Ya-Han Hu* and Bruce Ovbiagele

Volume 17, Issue 3, 2020

Page: [224 - 231] Pages: 8

DOI: 10.2174/1567202617666200423092025

Price: $65


Background: Atrial fibrillation (AF) is the most common cardiac rhythm disorder associated with stroke. Increased risk of stroke is the same regardless of whether the AF is permanent or paroxysmal. However, detecting paroxysmal AF is challenging and resource intensive. We aimed to develop a predictive model for AF in patients with acute ischemic stroke, which could improve the detection rate of paroxysmal AF.

Methods: We analyzed 10,034 adult patients with acute ischemic stroke. Differences in clinical characteristics between the patients with and without AF were analyzed in order to develop a predictive model of AF. The associated factors for AF were analyzed using multivariate logistic regression and classification and regression tree (CART) analyses. We used another dataset, which enrolled 860 acute ischemic stroke patients without AF at baseline, to test whether the developed model could improve the detection rate of paroxysmal AF. Among the study population, 1,658 patients (16.5%) had AF.

Results: Multivariate logistic regression revealed that sex, age, body weight, hypertension, diabetes mellitus, hyperlipidemia, pulse rate at admission, respiratory rate at admission, systolic blood pressure at admission, diastolic blood pressure at admission, National Institute of Health Stroke Scale (NIHSS) score at admission, total cholesterol level, triglyceride level, aspartate transaminase level, and sodium level were major factors associated with AF. CART analysis identified NIHSS score at admission, age, triglyceride level, and aspartate transaminase level as important factors for AF to classify the patients into subgroups.

Conclusion: When selecting the high-risk group of patients (with an NIHSS score >12 and age >64.5 years, or with an NIHSS score ≤12, age >71.5 years, and triglyceride level ≤61.5 mg/dL) according to the CART model, the detection rate of paroxysmal AF was approximately double in the acute ischemic stroke patients without AF at baseline.

Keywords: Acute ischemic stroke, atrial fibrillation, classification and regression tree analyses, cardiac rhythm, CART analyses, hypertension.

Lloyd-Jones DM, Wang TJ, Leip EP, et al. Lifetime risk for development of atrial fibrillation: The framingham heart study. Circulation 2004; 110(9): 1042-6.
[] [PMID: 15313941]
Arboix A, Cendrós V, Besa M, et al. Trends in risk factors, stroke subtypes and outcome. Nineteen-year data from the Sagrat Cor Hospital of Barcelona stroke registry. Cerebrovasc Dis 2008; 26(5): 509-16.
[] [PMID: 18810238]
Marini C, De Santis F, Sacco S, et al. Contribution of atrial fibrillation to incidence and outcome of ischemic stroke: Results from a population-based study. Stroke 2005; 36(6): 1115-9.
[] [PMID: 15879330]
Camm AJ, Kirchhof P, Lip GY, et al. European Heart Rhythm Association; European Association for Cardio-Thoracic Surgery. Guidelines for the management of atrial fibrillation: The Task Force for the Management of Atrial Fibrillation of the European Society of Cardiology (ESC). Eur Heart J 2010; 31(19): 2369-429.
[] [PMID: 20802247]
Kolominsky-Rabas PL, Weber M, Gefeller O, Neundoerfer B, Heuschmann PU. Epidemiology of ischemic stroke subtypes according to TOAST criteria: Incidence, recurrence, and long-term survival in ischemic stroke subtypes: A population-based study. Stroke 2001; 32(12): 2735-40.
[] [PMID: 11739965]
Jonas DE, Kahwati LC, Yun JDY, Middleton JC, Coker-Schwimmer M, Asher GN. Screening for atrial fibrillation with electrocardiography: Evidence report and systematic review for the us preventive services task force. JAMA 2018; 320(5): 485-98.
[] [PMID: 30088015]
Hohnloser SH, Pajitnev D, Pogue J, et al. ACTIVE W Investigators. Incidence of stroke in paroxysmal versus sustained atrial fibrillation in patients taking oral anticoagulation or combined antiplatelet therapy: An ACTIVE W Substudy. J Am Coll Cardiol 2007; 50(22): 2156-61.
[] [PMID: 18036454]
Rabinstein AA. Prolonged cardiac monitoring for detection of paroxysmal atrial fibrillation after cerebral ischemia. Stroke 2014; 45(4): 1208-14.
[] [PMID: 24619396]
Seet RC, Friedman PA, Rabinstein AA. Prolonged rhythm monitoring for the detection of occult paroxysmal atrial fibrillation in ischemic stroke of unknown cause. Circulation 2011; 124(4): 477-86.
[] [PMID: 21788600]
Jauch EC, Saver JL, Adams HP Jr, et al. American Heart Association Stroke Council; Council on Cardiovascular Nursing; Council on Peripheral Vascular Disease; Council on Clinical Cardiology. Guidelines for the early management of patients with acute ischemic stroke: A guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke 2013; 44(3): 870-947.
[] [PMID: 23370205]
Lip GY, Nieuwlaat R, Pisters R, Lane DA, Crijns HJ. Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: the euro heart survey on atrial fibrillation. Chest 2010; 137(2): 263-72.
[] [PMID: 19762550]
Fauchier L, Clementy N, Pelade C, Collignon C, Nicolle E, Lip GY. Patients with ischemic stroke and incident atrial fibrillation: A nationwide cohort study. Stroke 2015; 46(9): 2432-7.
[] [PMID: 26251249]
Breiman LFJ, Olshen R, Stone CJ. Classification and regression trees. Chapman & Hall: New York 1984.
Lemon SC, Roy J, Clark MA, Friedmann PD, Rakowski W. Classification and regression tree analysis in public health: Methodological review and comparison with logistic regression. Ann Behav Med 2003; 26(3): 172-81.
[] [PMID: 14644693]
Kato T, Yamashita T, Sagara K, Iinuma H, Fu LT. Progressive nature of paroxysmal atrial fibrillation. Observations from a 14-year follow-up study. Circ J 2004; 68(6): 568-72.
[] [PMID: 15170094]
Lee TH, Chang CH, Chang YJ, Chang KC, Chung J. Chang Gung Medical System Stroke Registry Group. Establishment of electronic chart-based stroke registry system in a medical system in Taiwan. J Formos Med Assoc 2011; 110(8): 543-7.
[] [PMID: 21783024]
Schaer BA, Zellweger MJ, Cron TA, Kaiser CA, Osswald S. Value of routine holter monitoring for the detection of paroxysmal atrial fibrillation in patients with cerebral ischemic events. Stroke 2004; 35(3): e68-70.
[] [PMID: 14963276]
Suissa L, Lachaud S, Mahagne MH. Optimal timing and duration of continuous electrocardiographic monitoring for detecting atrial fibrillation in stroke patients. J Stroke Cerebrovasc Dis 2013; 22(7): 991-5.
[] [PMID: 22349706]
Hsieh CY, Lee CH, Wu DP, Sung SF. Prediction of new-onset atrial fibrillation after first-ever ischemic stroke: A comparison of CHADS2, CHA2DS2-VASc and HATCH scores and the added value of stroke severity. Atherosclerosis 2018; 272: 73-9.
[] [PMID: 29571030]
Norby FL, Soliman EZ, Chen LY, et al. Trajectories of cardiovascular risk factors and incidence of atrial fibrillation over a 25-year follow-up: The ARIC Study (Atherosclerosis Risk in Communities). Circulation 2016; 134(8): 599-610.
[] [PMID: 27550968]
Guo Y, Tian Y, Wang H, Si Q, Wang Y, Lip GYH. Prevalence, incidence, and lifetime risk of atrial fibrillation in China: New insights into the global burden of atrial fibrillation. Chest 2015; 147(1): 109-19.
[] [PMID: 24921459]
Alonso A, Yin X, Roetker NS, et al. Blood lipids and the incidence of atrial fibrillation: The multi-ethnic study of atherosclerosis and the framingham heart study. J Am Heart Assoc 2014; 3(5)e001211
[] [PMID: 25292185]
Yuan BB, Luo GG, Gao JX, et al. Variance of serum lipid levels in stroke subtypes. Clin Lab 2015; 61(10): 1509-14.
[] [PMID: 26642713]
Dahl T, Kontny F, Slagsvold CE, et al. Lipoprotein(a), other lipoproteins and hemostatic profiles in patients with ischemic stroke: The relation to cardiogenic embolism. Cerebrovasc Dis 2000; 10(2): 110-7.
[] [PMID: 10686449]
Allore H, Tinetti ME, Araujo KL, Hardy S, Peduzzi P. A case study found that a regression tree outperformed multiple linear reg-ression in predicting the relationship between impairments and Social and Productive Activities scores. J Clin Epidemiol 2005; 58(2): 154-61.
[] [PMID: 15680749]
Sinner MF, Wang N, Fox CS, et al. Relation of circulating liver transaminase concentrations to risk of new-onset atrial fibrillation. Am J Cardiol 2013; 111(2): 219-24.
[] [PMID: 23127690]
Yamagami H, Toyoda K. Timing of anticoagulation therapy in patients with acute cardioembolic stroke. Circ J 2015; 79(4): 763-5.
[] [PMID: 25753856]

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