Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Advertisement

Scientific Reports
  • View all journals
  • Search
  • My Account Login
  • Content Explore content
  • About the journal
  • Publish with us
  • Sign up for alerts
  • RSS feed
  1. nature
  2. scientific reports
  3. articles
  4. article
Ischemic stroke prediction model of sick sinus syndrome patients without atrial fibrillation: insights from atrial myopathy
Download PDF
Download PDF
  • Article
  • Open access
  • Published: 17 March 2026

Ischemic stroke prediction model of sick sinus syndrome patients without atrial fibrillation: insights from atrial myopathy

  • Yiheng Yang1 na1,
  • Haoyu Dong1 na1,
  • Shihao Wang1,
  • Yushan Wei1,
  • Rongfeng Zhang1,
  • Xiaomeng Yin1,
  • Lianjun Gao1,
  • Yingxue Dong1,
  • Xiaolei Yang1 &
  • …
  • Yunlong Xia1 

Scientific Reports , Article number:  (2026) Cite this article

  • 400 Accesses

  • Metrics details

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Cardiology
  • Diseases
  • Medical research
  • Neurology

Abstract

Sick Sinus Syndrome (SSS) has been identified as a risk factor for ischemic stroke. Thrombus assessment in SSS patients without atrial fibrillation (AF) or atrial flutter (AFL) remains underexplored. We aims to develop a predictive model for ischemic stroke risk specifically in SSS patients without AF/AFL. Patients diagnosed with SSS and without AF/AFL were consecutively enrolled from single center. Incident AF/AFL cases were excluded during follow-up period. Symptomatic ischemic stroke was confirmed by reviewing the all available medical records. After a median follow-up of 1215 days, 187 out of 1645 (11.9%) patients experienced symptomatic ischemic stroke. Key predictors identified via multivariable Cox regression included age, left atrial diameter (LAD), prolonged P-wave duration (PWD), neutrophil-lymphocyte ratio (NLR), non-AF atrial tachyarrhythmias, and prior thrombotic events. These variables were incorporated into our nomogram prediction model, which demonstrated superior calibration and performance compared to the CHA2DS2-VASc score. The incidence of new-onset ischemic stroke in SSS patients is notably high, warranting focused attention in clinical practice. We developed the model evaluate the risk for ischemic stroke of SSS patients without AF/AFL and internally validated. This risk score performs better than CHA2DS2-VASC score and may providing evidence of thrombus assessment in patients with atrial myopathy.

Data availability

The data presented in this study are available upon request from the corresponding author.

References

  1. Hindricks, G. et al. 2020 ESC guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European association for Cardio-Thoracic surgery (EACTS): the task force for the diagnosis and management of atrial fibrillation of the European society of cardiology (ESC) developed with the special contribution of the European heart rhythm association (EHRA) of the ESC. Eur. Heart J. 42 (5), 373–498 (2021).

    Google Scholar 

  2. Goldberger, J. J. et al. Evaluating the atrial myopathy underlying atrial fibrillation: Identifying the arrhythmogenic and thrombogenic substrate. Circulation 132 (4), 278–291 (2015).

    Google Scholar 

  3. Piccini, J. P. & Daubert, J. P. Atrial fibrillation and stroke: It’s not necessarily all about the rhythm. Heart Rhythm 8 (9), 1424–1425 (2011).

    Google Scholar 

  4. Shen, M. J., Arora, R. & Jalife, J. Atrial myopathy. JACC Basic Transl. Sci. 4 (5), 640–654 (2019).

    Google Scholar 

  5. Kottkamp, H. Fibrotic atrial cardiomyopathy: A specific disease/syndrome supplying substrates for atrial fibrillation, atrial tachycardia, sinus node disease, AV node disease, and thromboembolic complications. J. Cardiovasc. Electrophysiol. 23 (7), 797–799 (2012).

    Google Scholar 

  6. Sanders, P. et al. Electrophysiological and electroanatomic characterization of the Atria in sinus node disease: evidence of diffuse Atrial remodeling. Circulation 109 (12), 1514–1522 (2004).

    Google Scholar 

  7. Bodin, A. et al. Ischemic stroke in patients with sinus node disease, atrial fibrillation, and other cardiac conditions. Stroke 51 (6), 1674–1681 (2020).

    Google Scholar 

  8. Dong, H. et al. Refining prediction of stroke in sinus node dysfunction patients without atrial fibrillation using a P-combined score: A multi-centre study. Eur. J. Prev. Cardiol. 31 (5), 507–518 (2024).

    Google Scholar 

  9. Halvorsen, S. et al. Efficacy and safety of Apixaban compared with warfarin according to age for stroke prevention in atrial fibrillation: Observations from the ARISTOTLE trial. Eur. Heart J. 35 (28), 1864–1872 (2014).

    Google Scholar 

  10. Mahaffey, K. W. et al. Ischaemic cardiac outcomes in patients with atrial fibrillation treated with vitamin K antagonism or factor Xa inhibition: Results from the ROCKET AF trial. Eur. Heart J. 35 (4), 233–241 (2014).

    Google Scholar 

  11. Mo, B. F. et al. Value of combining left atrial diameter and amino-terminal pro-brain natriuretic peptide to the CHA2DS2-VASc score for predicting stroke and death in patients with sick sinus syndrome after pacemaker implantation. Chin. Med. J. (Engl). 130 (16), 1902–1908 (2017).

    Google Scholar 

  12. Dong, H., Chen, H., Hidru, T. H., Xia, Y. & Yang, X. Sinus node dysfunction and stroke risk: A systematic review and meta-analysis. BMJ Open. 13 (11), e076499 (2023).

    Google Scholar 

  13. Benz, A. P. et al. Outcomes of patients with atrial fibrillation and ischemic stroke while on oral anticoagulation. Eur. Heart J. 44 (20), 1807–1814 (2023).

    Google Scholar 

  14. Lau, C. P. et al. Prospective randomized study to assess the efficacy of site and rate of atrial pacing on long-term progression of atrial fibrillation in sick sinus syndrome: septal pacing for atrial fibrillation suppression evaluation (SAFE) study. Circulation 128 (7), 687–693 (2013).

    Google Scholar 

  15. Alonso, A. et al. Association of sick sinus syndrome with incident cardiovascular disease and mortality: The atherosclerosis risk in communities study and cardiovascular health study. PLoS One. 9 (10), e109662 (2014).

    Google Scholar 

  16. Goette, A. et al. EHRA/HRS/APHRS/SOLAECE expert consensus on atrial cardiomyopathies: Definition, characterization, and clinical implication. Heart Rhythm. 14 (1), e3–e40 (2017).

    Google Scholar 

  17. North, B. J. & Sinclair, D. A. The intersection between aging and cardiovascular disease. Circ. Res. 110 (8), 1097–1108 (2012).

    Google Scholar 

  18. Lekkala, S. P. et al. Association between preablation and postablation neutrophil-lymphocyte ratio and atrial fibrillation recurrence: A meta-analysis. J. Arrhythm. 40 (2), 214–221 (2024).

    Google Scholar 

  19. Shao, Q. et al. Usefulness of neutrophil/lymphocyte ratio as a predictor of atrial fibrillation: A meta-analysis. Arch. Med. Res. 46 (3), 199–206 (2015).

    Google Scholar 

  20. Yilmaz, A., Can, S., Perincek, G. & Kahraman, F. Atrial electromechanical delay, neutrophil-to-lymphocyte ratio, and echocardiographic changes in patients with acute and stable chronic obstructive pulmonary disease. J. Res. Med. Sci. 27, 64 (2022).

    Google Scholar 

  21. Binici, Z., Intzilakis, T., Nielsen, O. W., Kober, L. & Sajadieh, A. Excessive supraventricular ectopic activity and increased risk of atrial fibrillation and stroke. Circulation 121 (17), 1904–1911 (2010).

    Google Scholar 

  22. Larsen, B. S., Kumarathurai, P., Falkenberg, J., Nielsen, O. W. & Sajadieh, A. Excessive atrial ectopy and short atrial runs increase the risk of stroke beyond incident atrial fibrillation. J. Am. Coll. Cardiol. 66 (3), 232–241 (2015).

    Google Scholar 

  23. Ogata, T. et al. Left atrial size and long-term risk of recurrent stroke after acute ischemic stroke in patients with nonvalvular atrial fibrillation. J. Am. Heart Assoc. 6 (8), e006402 (2017).

    Google Scholar 

  24. Zhou, D. et al. Left atrial dysfunction May precede left atrial enlargement and abnormal left ventricular longitudinal function: A cardiac MR feature tracking study. BMC Cardiovasc. Disord. 22 (1), 99 (2022).

    Google Scholar 

  25. Kelmanson, I. A. Increased P-wave dispersion in patients with obstructive sleep apnea syndrome: A meta-analysis. Sleep Breath. 27 (1), 291–301 (2023).

    Google Scholar 

  26. Kamel, H. et al. Atrial cardiopathy biomarkers and atrial fibrillation in the ARCADIA trial. Eur. Stroke J. 10 (2), 495–501 (2025).

    Google Scholar 

Download references

Acknowledgements

We are grateful to all the physicians involved in patients management and device programming.

Funding

This work was supported by National Key Research and Development Program of China (Grant number 2022YFC2405002).

Author information

Author notes
  1. Yiheng Yang and Haoyu Dong contributed equally to this work.

Authors and Affiliations

  1. Department of Cardiology, First Affiliated Hospital of Dalian Medical University, No. 222. Zhongshan Road, Dalian, Liaoning Province, China

    Yiheng Yang, Haoyu Dong, Shihao Wang, Yushan Wei, Rongfeng Zhang, Xiaomeng Yin, Lianjun Gao, Yingxue Dong, Xiaolei Yang & Yunlong Xia

Authors
  1. Yiheng Yang
    View author publications

    Search author on:PubMed Google Scholar

  2. Haoyu Dong
    View author publications

    Search author on:PubMed Google Scholar

  3. Shihao Wang
    View author publications

    Search author on:PubMed Google Scholar

  4. Yushan Wei
    View author publications

    Search author on:PubMed Google Scholar

  5. Rongfeng Zhang
    View author publications

    Search author on:PubMed Google Scholar

  6. Xiaomeng Yin
    View author publications

    Search author on:PubMed Google Scholar

  7. Lianjun Gao
    View author publications

    Search author on:PubMed Google Scholar

  8. Yingxue Dong
    View author publications

    Search author on:PubMed Google Scholar

  9. Xiaolei Yang
    View author publications

    Search author on:PubMed Google Scholar

  10. Yunlong Xia
    View author publications

    Search author on:PubMed Google Scholar

Contributions

Conceptualization: Yiheng Yang and Yunlong Xia; Data curation: Haoyu Dong and Yiheng Yang; Methodology and formal Analysis: Yiheng Yang and Haoyu Dong; Statistical Analysis, Haoyu Dong and Yiheng Yang; Investigation: Haoyu Dong, Shihao Wang and Rongfeng Zhang; Resource: Yingxue Dong, Xiaomeng Yin; Software: Yushan Wei; Writing—Original Draft Preparation: Haoyu Dong; Writing—Review and Editing: Yiheng Yang and Xiaolei Yang ; Validation: Lianjun Gao. Supervision: Yunlong Xia and Xiaolei Yang . Funding acquisition: Yunlong Xia; Visualization: Xiaolei Yang and Yiheng Yang. Project administration: Xiaolei Yang and Yiheng Yang. All authors have reviewed and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Yunlong Xia.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics approval

All patient information in the database is anonymized and therefore does not require informed consent according to the regulations of Ethics committee of First affiliated hospital of Dalian Medical University. Study protocol adheres to the principles of Declaration of Helsinki, and has been approved by the Ethics committee of First affiliated hospital of Dalian Medical University (PJ-KS-KY-2022-306).

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, Y., Dong, H., Wang, S. et al. Ischemic stroke prediction model of sick sinus syndrome patients without atrial fibrillation: insights from atrial myopathy. Sci Rep (2026). https://doi.org/10.1038/s41598-026-39742-7

Download citation

  • Received: 06 September 2025

  • Accepted: 06 February 2026

  • Published: 17 March 2026

  • DOI: https://doi.org/10.1038/s41598-026-39742-7

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Keywords

  • Sick sinus syndrome
  • Atrial myopathy
  • Ischemic stroke
  • Prediction model
Download PDF

Advertisement

Explore content

  • Research articles
  • News & Comment
  • Collections
  • Subjects
  • Follow us on Facebook
  • Follow us on X
  • Sign up for alerts
  • RSS feed

About the journal

  • About Scientific Reports
  • Contact
  • Journal policies
  • Guide to referees
  • Calls for Papers
  • Editor's Choice
  • Journal highlights
  • Open Access Fees and Funding

Publish with us

  • For authors
  • Language editing services
  • Open access funding
  • Submit manuscript

Search

Advanced search

Quick links

  • Explore articles by subject
  • Find a job
  • Guide to authors
  • Editorial policies

Scientific Reports (Sci Rep)

ISSN 2045-2322 (online)

nature.com footer links

About Nature Portfolio

  • About us
  • Press releases
  • Press office
  • Contact us

Discover content

  • Journals A-Z
  • Articles by subject
  • protocols.io
  • Nature Index

Publishing policies

  • Nature portfolio policies
  • Open access

Author & Researcher services

  • Reprints & permissions
  • Research data
  • Language editing
  • Scientific editing
  • Nature Masterclasses
  • Research Solutions

Libraries & institutions

  • Librarian service & tools
  • Librarian portal
  • Open research
  • Recommend to library

Advertising & partnerships

  • Advertising
  • Partnerships & Services
  • Media kits
  • Branded content

Professional development

  • Nature Awards
  • Nature Careers
  • Nature Conferences

Regional websites

  • Nature Africa
  • Nature China
  • Nature India
  • Nature Japan
  • Nature Middle East
  • Privacy Policy
  • Use of cookies
  • Legal notice
  • Accessibility statement
  • Terms & Conditions
  • Your US state privacy rights
Springer Nature

© 2026 Springer Nature Limited

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing