ArticleAnnals of hematology2024
A new score for predicting intracranial hemorrhage in patients using antiplatelet drugs.
Article in Annals of hematology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- Towards a prescribing monitoring system for medication safety evaluation within electronic health records: a scoping review.BMC medical informatics and decision making · 2025Article
- A new score for predicting intracranial hemorrhage in patients using anticoagulant drugs.Frontiers in neurology · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
4 authors at 1 institution in 1 country.
Funding
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.