Diagnostic Scoring System for Atrial Fibrillation in Ischemic Stroke

  • Erick Hoetama dr. H. Marsidi Judono Hospital, Tanjung Pandan, Provinsi Bangka Belitung
  • Bambang Hermawan Hermawan dr. H. Marsidi Judono Hospital, Tanjung Pandan, Provinsi Bangka Belitung
  • I Gusti Made Sunia dr. Ben Mboi Hospital, Ruteng, Provinsi Nusa Tenggara Timur


Background & Objectives. Atrial Fibrillation (AF) is the most common arrhytmia that is found in daily practices. Patients with AF have four- to five-fold increased risk of developing ischemic stroke compared to normal population. Diagnosing AF can sometimes be quite difficult especially in the setting of paroxysmal AF. Moreover, paroxysmal AF can also increase the risk of thromboembolic complications. Some cases of cryptogenic stroke are believed to be cardioembolic in origin which caused by occult AF. This study aimed to develop a simple scoring system to detect patients with ischemic stroke most likely to have AF, so that recurrent stroke can be prevented.
Methods. We conducted diagnostic study using cross sectional design. Total 173 subjects were gathered. Those subject were patients with ischemic stroke admitted in Belitung or Ruteng General Hospital from January 2014 until August 2015. Data collected were subjects’ characteristics, hypertension, diabetes, obesity, dyslipidemia, smoking history, congestive heart failure (CHF), alcohol consumption, valvular heart disease, chronic obstructive pulmonary disease, myocardial infarct history, previous stroke, Modified National Institutes of Health Stroke Scale (mNIHSS) score, and left atrial diameter (LAD). We analyzed those data using bivariate and logistic regression multivariate analysis.
Results. Multivariate analysis showed significant relationship between AF and some of the variables, which are hypertension, diabetes, obesity, CHF, left atrial enlargement, age and mNHISS score. We developed 7-point scoring system derived from those variables. A cutoff score of 3 or higher has sensitivity 97,1% and specificity 54,3%. Also, this scoring system has Area Under the Curve (AUC) value of 88,9% (IK95% 83,1% - 94,7%).
Conclusion. This scoring system uses only clinical and echocardiographic profile that are easy to do, so it can be utilized as a simple diagnostic tool to identify ischemic stroke patient who is likely to have AF. Future studies are needed to determine another possibly related parameters.


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1. Chugh SS, Havmoller S, Narayanan K, Singh D, Rienstra M, Benjamin EJ, et al. Worldwide Epidemiology of Atrial Fibrillation: A Global Burden of Disease 2010 Study. Circulation. 2014;129:837-847.

2. Kisshore A, Vail A, Majid A, Dawson J, Lees KR, Tyrell PJ, et al. Detection of Atrial Fibrillation After Ischemic Stroke or Transient Ischemic Attack. Stroke.2014;45:520-526.

3. Saposnik G, Gladstone D, Raptis R, Zhou L, Hart GR. Atrial Fibrillation in Ischemic Stroke: Predicting Response to Thrombolysis and Clinical Outcomes. Stroke.2013;44:49-104.

4. Altieri M, Troisi P, Maesterini I, Lenzi GL. Cryptogenic Stroke: Cryptic Definition. Stroke. 2009;40:e530.

5. Kimura K, Minematsu K, Yamaguchi T. Atrial Fibrillation as a predictive factor for severe stroke and early death in 15831 patients with acute ischaemic stroke. J Neurol Neurosurg Psychiatry.2005;76:679–683.

6. Yancy CW, Jessup M, Bozkurt B, Butler J, Casey DE, Drazner MH, et al. 2013 ACCF/AHA Guideline for the Management of Heart Failure: Executive Summary. Circulation. 2013;128:1810-1852.

7. Lang RM, Bierig M, Devereux RB, et al. Recommendations for chamber quantification: a report from the American Society of Echocardiography’s Guidelines and Standards Committee and the Chamber Quantification Writing Group, developed in conjunction with the European Association of Echocardiography, a branch of the European Society of Cardiology. J Am Soc Echocardiogr.2005;18:1440–63.

8. Asia Pasific Cohort Studies Collaboration. Body mass index and cardiovascular disease in the Asia-Pacific Region: an overview of 33 cohorts involving 310 000 participants. Int. J. Epidemiol. 2004;33(4):751-758.

9. Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Ferannti SD, et al. Heart Disease and Stroke Statistics-2015 Update. Circulation.2015;131(4):e29-e32.

10. Appelros P, Stegmayer B, Terent A. Sex differences in Stroke Epidemiology. Stroke.2009;40:1082-1090.

11. Psatys BM, Manolio TA, Kuller LH, Kronmal RA, Cuhsman M,Fried LP, et al. Incidence of and Risk Factors of Atrial Fibrillation in Older Adults. Circulation.1997;96:2455-2461.

12. Healey JS, Conolly SJ. Atrial fibrillation: hypertension as a causative agent, risk factor for complications, and potential therapeutic target. Am J Cardiol.2003;91(10A):9G-14G.

13. Lau YF, Hiu KH, Siu CW, Tse HF. Hypertension and atrial fibrillation: epidemiology, pathophysiology and therapeutic implications. Journal of Human Hypertension.2012;26:563-569.

14. Sun Y, Hu D. The link between diabetes and atrial fibrillation: cause or correlation. J Cardiovasc Dis Res.2010;1(1):10–11.

15. Bandemer S. Merkel S, Doffour AN, Weber MW. Diabetes and atrial fibrillation: stratification and prevention of stroke risks. EPMA Journal.2014;5:17

16. Schoen T, Pradhan AD, Albert CM, Conen D. Type 2 Diabetes Mellitus and Risk of Incident Atrial Fibrillation in Women. J Am Coll Cardiol.2012;60(15):1421-1428.

17. Frost L, Hune LJ, Vestergaard P. Overweight and obesity as risk factors for atrial fibrillation or flutter: the Danish Diet, Cancer, and Health Study. Am J Med. 2005;118:489–495.

18. Tsang TS, Barnes ME, Miyasaka Y, Cha SS, Bailey KR, Verzosa GC, Seward JB, Gersh BJ. Obesity as a risk factor for the progression of paroxysmal to permanent atrial fibrillation: a longitudinal cohort study of 21 years. Eur Heart J. 2008;29:2227–2233.

19. Magnani JW, Hylek EM , Apovian CM. Obesity Begets Atrial Fibrillation.Circulation. 2013;128:401-405.

20. Anter E, Jessup M, Callans DJ. Atrial Fibrillation and Heart Failure. Circulation.2009; 119: 2516-2525.

21. Sanfillipo AJ, Abascal VM, Sheehan M, Oertel LB, Harrigen P, Hughes RA. Atrial enlargement as a Consequence of Atrial Fibrillation. Circulation.1990;82:792-797.

22. Yoshioka K, Watanabe K, Zeniya S, Ito Y, Kanazawa T, Tomita M. A Score for Predicting Paroxysmal Atrial Fibrillation in Acute Stroke Patients: iPAB Score. J Stroke Cerebrovasc Dis. 2015; 15:344-345.

23. Fuji S, Shibazaki K, Kimura K, Aoki J. A simple score for predicting paroxysmal atrial fibrillation in acute ischemic stroke. J Neurol Sci. 2013;328(1-2):83-6.

24. Figueiredo MM, Rodrigues AC, Alves BM, Neto MC, Silva GS. Score for atrial fibrillation detection in acute stroke and transient ischemic attack patients in a Brazilian population: The acute stroke atrial fibrillation scoring system. Clinics (Sao Paulo). 2014;69(4): 241–246.

25. Malik S, Hicks WJ, Schultz J, Penstone P, Katramandos AM, Russman AN. Development of a scoring system for atrial fibrillation in acute stroke and transient ischemic attack patients: the LADS scoring system. J Neurol Sci.2011;301(1-2):27-30.
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How to Cite
Hoetama, E., Hermawan, B. H., & Sunia, I. G. (2017). Diagnostic Scoring System for Atrial Fibrillation in Ischemic Stroke. Indonesian Journal of Cardiology, 37(1), 19-27. https://doi.org/10.30701/ijc.v37i1.552
Clinical Research