A Practical Nomogram for Predicting the Bleeding Risk in Patients with a History of Myocardial Infarction Treating...

Area of Science:

• Cardiology
• Pharmacology
• Medical Informatics

Background:

• Aspirin is a key antiplatelet drug for cardiovascular event prevention.
• Balancing aspirin's benefits against bleeding risks is crucial for patient care.
• Predicting aspirin-induced bleeding in myocardial infarction (MI) patients requires effective tools.

Purpose of the Study:

• To develop a practical nomogram for predicting bleeding risk.
• To aid healthcare providers in managing aspirin therapy for MI patients.
• To improve the risk-benefit assessment of aspirin in secondary prevention.

Main Methods:

• 2099 MI patients on aspirin were enrolled for model development and validation.
• Boruta analysis identified significant bleeding risk factors.
• A logistic regression model and visual nomogram were constructed.

Main Results:

• Four independent risk factors identified: hemoglobin, platelet count, previous bleeding, and sex.
• The nomogram achieved high predictive accuracy (AUC 0.888 in training and test sets).
• The model demonstrated excellent calibration and clinical utility.

Conclusions:

• A validated nomogram effectively predicts bleeding risk in MI patients on aspirin.
• The model offers outstanding performance in discrimination, calibration, and clinical benefit.
• This tool can support personalized aspirin treatment strategies.