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

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Abstract

Antiplatelet drugs in patients increase the risk of intracranial hemorrhage (ICH), which can seriously affect patients’ quality of life and even endanger their lives. Currently, there is no specific score for predicting the risk of ICH caused by antiplatelet drugs. We aimed to identify factors associated with ICH in patients on antiplatelet drugs and to construct and validate a predictive model that would provide a validated tool for the clinic. Data were obtained from the patient medical records inpatient system. Prediction models were built by logistic regression, the area under the curve (AUC), and column line plots. Internal validation, analytical identification and calibration of the model using AUC, calibration curves and Hosmer-Lemeshow test. The registration number of this study is ChiCTR2000031909, and the ethical review number is 2020KY087. This single-center retrospective study enrolled 753 patients treated with antiplatelet drugs, including 527 in the development cohort. Multifactorial analysis showed that male, headache or vomiting, hypertension, cerebrovascular disease, CT-defined white matter hypodensity, abnormal GCS, fibrinogen and D-dimer were independent risk factors for ICH, and lipid-lowering drugs was a protective factor. The model was constructed using these nine factors with an AUC value of 0.949. In the validation cohort, the model showed good discriminatory power with an AUC value of 0.943 and good calibration (Hosmer-Lemeshow test P value of 0.818). Based on 9 factors, we derived and validated a predictive model for ICH with antiplatelet drugs in patients. The model has good predictive value and may be an effective tool to reduce the occurrence of ICH.

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Data availability

The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author/s.

Abbreviations

ICH:

intracranial hemorrhage

AUC:

area under the curve

BMI:

body mass index

MT:

malignant tumor

VTE:

venous thromboembolism

AF:

atrial fibrillation

PVD:

peripheral vascular diseases

TIA:

transient ischemic attack

CT-WMH:

computed tomography-defined white matter hypodensity

NIHSS:

national institutes of health stroke scale

GCS:

glasgow coma scale

PT:

prothrombin time

INR:

international normalized ratio

APTT:

activated partial thromboplastin time

FIB:

fibrinogen

TT:

thrombin time

ROC:

receiver operating characteristic

MRI:

magnetic resonance imaging

OR:

odds ratio

CI:

confidence interval

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Acknowledgements

All authors made a substantial contribution to the concept and design of the study, interpreted the data, and reviewed the manuscript. All listed authors participated in the study and agree with the submission and subsequent revisions submitted by the corresponding author.

Funding

This work has been supported by the Science and Technology Innovation Startup Fund of Fujian Maternal and Child Health Hospital (YCXY 23 − 02).

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Author notes

  1. Fuxin Ma, Zhiwei Zeng and Jiana Chen contributed equally to this work and share first authorship.

Authors and Affiliations

  1. Department of School, Fujian Medical University, Fuzhou, China

    Fuxin Ma

  2. Department of Pharmacy, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Maternity and Child Health Hospital, Fujian Medical University, #18 Daoshan Road, Fuzhou, 350001, China

    Zhiwei Zeng, Jiana Chen & Jinhua Zhang

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  1. Fuxin Ma
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Contributions

MFX and ZJH initiated the study. ZZW, CJN, and MFX performed data extraction and analyses. ZZW drafted the first version of the manuscript. CJN, MFX and ZJH critically reviewed and revised the manuscript.

Corresponding author

Correspondence to Jinhua Zhang.

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Ethical approval

The Fujian Medical University Union Hospital Ethics Committee reviewed and approved the studies involving human participants. This study did not require informed consent for participation in accordance with the national legislation and institutional requirements.

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The authors declare no competing interests.

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Ma, F., Zeng, Z., Chen, J. et al. A new score for predicting intracranial hemorrhage in patients using antiplatelet drugs. Ann Hematol (2024). https://doi.org/10.1007/s00277-024-05734-8

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