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ORIGINAL RESEARCH article

Front. Neurol.
Sec. Endovascular and Interventional Neurology
Volume 16 - 2025 | doi: 10.3389/fneur.2025.1475956
This article is part of the Research Topic State of the Art in Antithrombotic Therapy View all 5 articles

A new score for predicting intracranial hemorrhage in patients using anticoagulant drugs

Provisionally accepted
Jinhua Zhang Jinhua Zhang 1*Fuxin Ma Fuxin Ma 1Zhiwei Zeng Zhiwei Zeng 1Jiana Chen Jiana Chen 1Chengfu Guan Chengfu Guan 1Wenlin Xu Wenlin Xu 1Chunhua Wang Chunhua Wang 2
  • 1 Department of Pharmacy, Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University , Fuzhou, China, Fuzhou, China
  • 2 Department of Neurosurgery, Fujian Medical University Union Hospital, Fuzhou, China, Fuzhou, Fujian Province, China

The final, formatted version of the article will be published soon.

    The use of anticoagulants in patients increases the risk of intracranial hemorrhage (ICH). Our aim was to identify factors associated with cerebral hemorrhage in patients using anticoagulants and to develop a predictive model that would provide an effective tool for the clinical assessment of cerebral hemorrhage.Methods: In our study, indications for patients receiving anticoagulation included AF， VTE, stroke/TIA, arteriosclerosis, peripheral vascular diseases (PVD), prosthetic mechanical valve replacement, etc. Data were obtained from the patient record hospitalization system. Logistic regression, area under the curve (AUC), and bar graphs were used to build predictive models in the development cohort. The models were internally validated, analytically characterized, and calibrated using AUC, calibration curves, and the Hosmer-Lemeshow test.Results: This single-center retrospective study included 617 patients treated with anticoagulants. Multifactorial analysis showed that male, leukoaraiosis, high risk of falls, APTT ≥45.4 s, and FIB ≥4.2 g/L were independent risk factors for cerebral hemorrhage, and β -blockers were protective factors. The model was constructed using these six factors with an AUC value of 0.883. In the validation cohort, the model had good discriminatory power (AUC = 0.801) and calibration power.Five-fold cross-validation showed Kappa of 0.483.Predictive models based on a patient's medical record hospitalization system can be used to identify patients at risk for cerebral hemorrhage. Identifying people at risk can provide proactive interventions for patients.

    Keywords: intracranial hemorrhage, Anticoagulant, prediction, score, Risk factors

    Received: 04 Aug 2024; Accepted: 06 Jan 2025.

    Copyright: © 2025 Zhang, Ma, Zeng, Chen, Guan, Xu and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Jinhua Zhang, Department of Pharmacy, Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University , Fuzhou, China, Fuzhou, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.