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A score to predict the stroke recurrence of patients with embolic stroke of undetermined source

  • Original Communication
  • Published:
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Abstract

Aim

We aimed to develop a score and validate it in a prospective cohort to identify the patients with ESUS at high risk for stroke recurrence.

Methods

We assessed the stroke recurrence in ESUS patients of the Third China National Stroke Registry. We performed multivariable logistic regression analysis to identify predictors of stroke recurrence in the derivation cohort. Based on the coefficient of each covariate of the fitted multivariable model, we generated an integer-based point scoring system. We validated the score in the validation cohort assessing its discrimination and calibration.

Results

2415 patients were included: 1611 in the derivation and 804 in the validation sample. We developed a scoring system (0–15 points) by assigning 2 points for hypertension, 3 points for diabetes mellitus, 4 points for multiple stage infarction, 2 points for watershed involved infarction, 1 points for left atrial diameter index (per increasing 2.5 mm/m2) and 3 points for without statin at discharge. The rate of stroke recurrence was 5.9% per year (95% CI 4.2–7.6%) in patients with low risk(a score of 0–5), 9.4% (7.3–11.5%) in patients with intermediate risk (6–10), and 26.8% (16.5–37.1%) in patients with high risk (11–15). The AUC (area under curve of receiver operator characteristic curve) of the score in the derivation cohort and validation cohort was, respectively, 0.60 (0.55–0.65) and 0.63 (0.56–0.70). The score was well calibrated both in the derivation cohort (p = 0.36) and validation cohort (p = 0.26) with the Hosmer–Lemeshow test.

Conclusion

The developed score can improve risk stratification after ESUS in secondary care settings.

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Data availability statement

The datasets during and/or analyzed during the current study available from the corresponding author on reasonable request.

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Funding

This work was supported by grants from the Capital’s Funds for Health Improvement and Research (2020-1-2041), Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (2019-I2M-5-029), National Natural Science Foundation of China (81870905, U20A20358), and grants from National Natural Science Foundation of China (No. 82001237).

Author information

Author notes

  1. Jing Jing and Xiaomeng Yang have contributed equally to this work.

Authors and Affiliations

  1. Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China

    Jing Jing, Xiaomeng Yang, Yueyang Wu, Xia Meng, Zixiao Li, Xingquan Zhao, Yilong Wang & Yongjun Wang

  2. China National Clinical Research Center for Neurological Diseases, Beijing, China

    Jing Jing, Xiaomeng Yang, Yueyang Wu, Xia Meng, Zixiao Li, Yong Jiang, Yuesong Pan, Aoming Jin, Xingquan Zhao, Yilong Wang, Hao Li & Yongjun Wang

  3. Tiantan Neuroimaging Center of Excellence, Beijing, China

    Jing Jing

  4. Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China

    Yongjun Wang

  5. Research Unit of Artificial Intelligence in Cerebrovascular Disease, Chinese Academy of Medical Sciences, 2019RU018, Beijing, China

    Yongjun Wang

  6. Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Beijing, China

    Yongjun Wang

  7. No. 119, South Fourth Ring West Road, Fengtai District, Beijing, 100070, China

    Yongjun Wang

Authors
  1. Jing Jing
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  2. Xiaomeng Yang
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  12. Yongjun Wang
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Contributions

Study concept and design: YJW; Drafting of the manuscript: JJ and XMY; Acquisition of data: XM, ZXL and YYW; Analysis and interpretation of data: YSP, YJ and AMJ; Study supervision: LPL, XQZ, YLW and HL. All authors approved the final version of this work.

Corresponding author

Correspondence to Yongjun Wang.

Ethics declarations

Conflicts of interest

The authors declare that they have no conflict of interest.

Ethical approval

This study was approved by the by the Ethics Committee at Beijing Tiantan Hospital (IRB approval number: KY2015-001-01) and all participating centers.

Consent to participate

Informed consent was obtained from all individual participants included in the study.

Consent for publication

Informed consent included agreement to the publication of study findings.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 386 KB)

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Jing, J., Yang, X., Wu, Y. et al. A score to predict the stroke recurrence of patients with embolic stroke of undetermined source. J Neurol 269, 6428–6435 (2022). https://doi.org/10.1007/s00415-022-11277-7

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  • DOI: https://doi.org/10.1007/s00415-022-11277-7

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