Skip to content
2000
  1. Home
  2. A-Z Publications
  3. Current Neurovascular Research
  4. Volume 21, Issue 2
  5. Article
Volume 21, Issue 2
  • ISSN: 1567-2026
  • E-ISSN: 1875-5739

Abstract

Background

The annualized recurrent stroke rate in patients with Embolic Stroke of Undetermined Source (ESUS) under antiplatelet therapy is around 4.5%. Only a fraction of these patients will develop atrial fibrillation (FA), to which a stroke can be attributed retrospectively. The challenge is to identify patients at risk of occult AF during follow-up.

Objectives

This work aims to determine clinical factors and electrocardiographic and ultrasound parameters that can predict occult AF in patients with ESUS and build a simple predictive score applicable worldwide.

Methods

This is a single-center, registry-based retrospective study conducted at the stroke unit of Sahloul University Hospital, Sousse, Tunisia, between January 2016 and December 2020. Consecutive patients meeting ESUS criteria were monitored for a minimum of one year, with a standardized follow-up consisting of outpatient visits, including ECG every three months and a new 24-hour Holter monitoring in case of palpitations. We performed multivariate stepwise regression to identify predictors of new paroxysmal AF among initial clinical, electrocardiographic (ECG and 24-hour Holter monitoring) and echocardiographic parameters. The coefficient of each independent covariate of the fitted multivariable model was used to generate an integer-based point-scoring system.

Results

Three hundred patients met the criteria for ESUS. Among them, 42 (14%) patients showed at least one episode of paroxysmal AF during a median follow-up of two years. In univariate analysis, age, gender, coronary artery disease, history of ischemic stroke, higher NIHSS at admission and lower NIHSS at discharge, abnormal wave axis, prolonged wave duration, premature atrial contractions (PAC) frequency of more than 500/24 hours, and left atrial (LA) mean area of more than 20 cm2 were associated with the risk of occurrence of paroxysmal AF. We proposed an AF predictive score based on (1.771 x NIHSS score at admission) + (10.015 x wave dispersion; coded 1 if yes and 0 if no) + (9.841x PAC class; coded 1 if ≥500 and 0 if no) + (9.828x LA class surface; coded 1 if ≥20 and 0 if no) + (0.548xNIHSS score at discharge) + 0.004. A score of ≥33 had a sensitivity of 76% and a specificity of 93%.

Conclusion

In this cohort of patients with ESUS, NIHSS at both admission and discharge, wave dispersion, PAC≥500/24h on a 24-hour Holter monitoring, and LA surface area≥20 cm2 provide a simple AF predictive score with very reasonable sensitivity and specificity and is applicable almost worldwide. An external validation of this score is ongoing.

© 2024 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/cnr/10.2174/0115672026301430240201094411
2024-02-06
2025-01-24

  • From This Site

    /content/journals/cnr/10.2174/0115672026301430240201094411
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. FeiginV.L. MensahG.A. NorrvingB. MurrayC.J.L. RothG.A. Atlas of the global burden of stroke (1990-2013): The GBD 2013 study.Neuroepidemiology201545323023610.1159/000441106 26505985
     [Google Scholar]
  2. MarkusH. Personalising secondary prevention: Different treatments for different strokes.Pract. Neurol.20202013438 31484793
     [Google Scholar]
  3. HartR.G. DienerH.C. CouttsS.B. Embolic strokes of undetermined source: The case for a new clinical construct.Lancet Neurol.201413442943810.1016/S1474‑4422(13)70310‑7 24646875
     [Google Scholar]
  4. BhatA. MahajanV. ChenH.H.L. GanG.C.H. Pontes-NetoO.M. TanT.C. Embolic stroke of undetermined source: Approaches in risk stratification for cardioembolism.Stroke20215212e820e83610.1161/STROKEAHA.121.034498 34706562
     [Google Scholar]
  5. DienerH.C. SaccoR.L. EastonJ.D. Dabigatran for prevention of stroke after embolic stroke of undetermined source.N. Engl. J. Med.2019380201906191710.1056/NEJMoa1813959 31091372
     [Google Scholar]
  6. HartR.G. SharmaM. MundlH. Rivaroxaban for stroke prevention after embolic stroke of undetermined source.N. Engl. J. Med.2018378232191220110.1056/NEJMoa1802686 29766772
     [Google Scholar]
  7. DilaverisP.E. KennedyH.L. Silent atrial fibrillation: Epidemiology, diagnosis, and clinical impact.Clin. Cardiol.201740641341810.1002/clc.22667 28273368
     [Google Scholar]
  8. SposatoL.A. CiprianoL.E. SaposnikG. VargasE.R. RiccioP.M. HachinskiV. Diagnosis of atrial fibrillation after stroke and transient ischaemic attack: A systematic review and meta-analysis.Lancet Neurol.201514437738710.1016/S1474‑4422(15)70027‑X 25748102
     [Google Scholar]
  9. SpenceJ.D. Cardioembolic stroke: Everything has changed.Stroke Vasc. Neurol.201832768310.1136/svn‑2018‑000143 30022801
     [Google Scholar]
  10. HaeuslerK.G. TütüncüS. SchnabelR.B. Detection of atrial fibrillation in cryptogenic stroke.Curr. Neurol. Neurosci. Rep.201818106610.1007/s11910‑018‑0871‑1 30090997
     [Google Scholar]
  11. KhurshidR. AwaisM. MalikJ. Electrophysiology practice in low- and middle-income countries: An updated review on access to care and health delivery.Heart Rhythm2023416977
     [Google Scholar]
  12. KwongC. LingA.Y. CrawfordM.H. ZhaoS.X. ShahN.H. A clinical score for predicting atrial fibrillation in patients with cryptogenic stroke or transient ischemic attack.Cardiology2017138313314010.1159/000476030 28654919
     [Google Scholar]
  13. BahitM.C. SaccoR.L. EastonJ.D. MeyerhoffJ. CroninL. KleineE. Predictors of atrial fibrillation development in patients with embolic stroke of undetermined source: An analysis of the RE-SPECT ESUS trial.Circulation20211442217381746
     [Google Scholar]
  14. HealeyJ.S. GladstoneD.J. SwaminathanB. Recurrent stroke with rivaroxaban compared with aspirin according to predictors of atrial fibrillation.JAMA Neurol.201976776477310.1001/jamaneurol.2019.0617 30958508
     [Google Scholar]
  15. JohnerN. NamdarM. ShahD. [ECG: Interpretation and clinical significance of P-wave abnormalities ].Rev. Med. Suisse2018146081078108129797853
     [Google Scholar]
  16. LangR.M. BadanoL.P. Mor-AviV. Recommendations for cardiac chamber quantification by echocardiography in adults: An update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging.J. Am. Soc. Echocardiogr.2015281139.e1410.1016/j.echo.2014.10.003 25559473
     [Google Scholar]
  17. HindricksG. PotparaT. DagresN. 2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS).Eur. Heart J.202142537349810.1093/eurheartj/ehaa612 32860505
     [Google Scholar]
  18. Al KhathaamiA.M. Al BdahB. AlnosairA. Embolic stroke of undetermined source in Saudi Arabia: Prevalence, patient characteristics, and outcomes.J. Stroke Cerebrovasc. Dis.2019281210439010.1016/j.jstrokecerebrovasdis.2019.104390 31607440
     [Google Scholar]
  19. KhorvashF. KhaliliM. Rezvani HabibabadiR. Comparison of acute ischemic stroke evaluation and the etiologic subtypes between university and nonuniversity hospitals in Isfahan, Iran.Int. J. Stroke201914661361910.1177/1747493019828648 30860455
     [Google Scholar]
  20. PereraK.S. VanasscheT. BoschJ. Embolic strokes of undetermined source: Prevalence and patient features in the ESUS Global Registry.Int. J. Stroke201611552653310.1177/1747493016641967 27256472
     [Google Scholar]
  21. von FalkenhausenA.S. FeilK. SinnerM.F. Atrial fibrillation risk assessment after embolic stroke of undetermined source.Ann. Neurol.202393347948810.1002/ana.26545 36373166
     [Google Scholar]
  22. RubieraM. AiresA. AntonenkoK. European Stroke Organisation (ESO) guideline on screening for subclinical atrial fibrillation after stroke or transient ischaemic attack of undetermined origin.Eur. Stroke J.202273CVIICXXXIX10.1177/23969873221099478 36082257
     [Google Scholar]
  23. DilaverisP.E. AntoniouC.K. CaianiE.G. ESC working group on e-cardiology position paper: Accuracy and reliability of electrocardiogram monitoring in the detection of atrial fibrillation in cryptogenic stroke patients.EHJDH20223334135810.1093/ehjdh/ztac026 36712155
     [Google Scholar]
  24. SinhaA.M. DienerH.C. MorilloC.A. Cryptogenic stroke and underlying atrial fibrillation (CRYSTAL AF): Design and rationale.Am. Heart J.201016013641.e110.1016/j.ahj.2010.03.032 20598970
     [Google Scholar]
  25. CarringtonM ProvidênciaR ChahalCAA RicciF EpsteinAE GallinaS Monitoring and diagnosis of intermittent arrhythmias: Evidence-based guidance and role of novel monitoring strategies.Eur Heart J Open202226oeac072
     [Google Scholar]
  26. CameronA. ChengH.K. LeeR.P. Biomarkers for atrial fibrillation detection after stroke.Neurology20219718e1775e178910.1212/WNL.0000000000012769 34504030
     [Google Scholar]
  27. SuissaL. BertoraD. LachaudS. MahagneM.H. Score for the targeting of atrial fibrillation (STAF): A new approach to the detection of atrial fibrillation in the secondary prevention of ischemic stroke.Stroke20094082866286810.1161/STROKEAHA.109.552679 19461041
     [Google Scholar]
  28. UphausT. Weber-KrügerM. GrondM. Development and validation of a score to detect paroxysmal atrial fibrillation after stroke.Neurology2019922e115e12410.1212/WNL.0000000000006727 30530796
     [Google Scholar]
  29. YoshiokaK. WatanabeK. ZeniyaS. A score for predicting paroxysmal atrial fibrillation in acute stroke patients: iPAB score.J. Stroke Cerebrovasc. Dis.201524102263226910.1016/j.jstrokecerebrovasdis.2015.06.019 26190307
     [Google Scholar]
  30. LeeJ.D. KuoY.W. LeeC.P. HuangY.C. LeeM. LeeT.H. Development and validation of a novel score for predicting paroxysmal atrial fibrillation in acute ischemic stroke.Int. J. Environ. Res. Public Health20221912727710.3390/ijerph19127277 35742524
     [Google Scholar]
  31. RicciB. ChangA.D. HemendingerM. A simple score that predicts paroxysmal atrial fibrillation on outpatient cardiac monitoring after embolic stroke of unknown source.J. Stroke Cerebrovasc. Dis.20182761692169610.1016/j.jstrokecerebrovasdis.2018.01.028 29501269
     [Google Scholar]
  32. ZhaoS.X. ZieglerP.D. CrawfordM.H. KwongC. KoehlerJ.L. PassmanR.S. Evaluation of a clinical score for predicting atrial fibrillation in cryptogenic stroke patients with insertable cardiac monitors: Results from the CRYSTAL AF study.Ther. Adv. Neurol. Disord.20191112175628641984269810.1177/1756286419842698
     [Google Scholar]
  33. KneihslM. BispingE. ScherrD. Predicting atrial fibrillation after cryptogenic stroke via a clinical risk score-a prospective observational study.Eur. J. Neurol.202229114915710.1111/ene.15102 34519135
     [Google Scholar]
  34. DoganU. DoganE.A. TekinalpM. P-wave dispersion for predicting paroxysmal atrial fibrillation in acute ischemic stroke.Int. J. Med. Sci.20129110811410.7150/ijms.9.108 22211098
     [Google Scholar]
  35. Pérez-RieraA.R. de AbreuL.C. Barbosa-BarrosR. GrindlerJ. Fernandes-CardosoA. BaranchukA. P-wave dispersion: An update.Indian Pacing Electrophysiol. J.201616412613310.1016/j.ipej.2016.10.002 27924760
     [Google Scholar]
  36. Chávez-GonzálezE. DonoiuI. Utility of P-wave dispersion in the prediction of atrial fibrillation.Curr. Health Sci. J.2017431511 30595848
     [Google Scholar]
  37. GladstoneD.J. DorianP. SpringM. Atrial premature beats predict atrial fibrillation in cryptogenic stroke: Results from the EMBRACE trial.Stroke201546493694110.1161/STROKEAHA.115.008714 25700289
     [Google Scholar]
  38. MiyazakiY. ToyodaK. IguchiY. Atrial fibrillation after ischemic stroke detected by chest strap-style 7-day holter monitoring and the risk predictors: EDUCATE-ESUS.J. Atheroscler. Thromb.202128554455410.5551/jat.58420 32801289
     [Google Scholar]
  39. OvervadT.F. NielsenP.B. LarsenT.B. SøgaardP. Left atrial size and risk of stroke in patients in sinus rhythm. A systematic review.Thromb. Haemost.20161162206219 27075168
     [Google Scholar]
  40. XuY. ZhaoL. ZhangL. HanY. WangP. YuS. Left atrial enlargement and the risk of stroke: A meta-analysis of prospective cohort studies.Front. Neurol.2020112610.3389/fneur.2020.00026 32117002
     [Google Scholar]
  41. TsangT.S.M. AbhayaratnaW.P. BarnesM.E. Prediction of cardiovascular outcomes with left atrial size: Is volume superior to area or diameter?J. Am. Coll. Cardiol.20064751018102310.1016/j.jacc.2005.08.077 16516087
     [Google Scholar]
/content/journals/cnr/10.2174/0115672026301430240201094411
Loading
A Simple Score for Predicting Paroxysmal Atrial Fibrillation in Patients with Embolic Stroke of Undetermined Source in a Tunisian Cohort Study
Curr Neurovasc Res 21, 116 (2024); https://doi.org/10.2174/0115672026301430240201094411
/content/journals/cnr/10.2174/0115672026301430240201094411
/content/journals/cnr/10.2174/0115672026301430240201094411
Loading

Data & Media loading...

Supplements

Supplementary material is available on the publisher’s website along with the published article.

file format download Download

  • Article Type:     Research Article
Keyword(s): 12-lead ECG; anticoagulants; Cryptogenic embolism stroke; echocardiography transthoracic; holter ECG; paroxysmal atrial fibrillation

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test