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Simple risk-score model for in-hospital major bleeding based on multiple blood variables in patients with acute
Yuhei Goriki1, Goro Yoshioka2, Masahiro Natsuaki2
1Department of Cardiovascular Medicine, National Hospital Organization Ureshino Medical Center, Saga, Japan; Department of Cardiovascular Medicine, Saga University, Saga, Japan.
Insights
A new risk score using routine blood tests can predict in-hospital bleeding in acute myocardial infarction (AMI) patients undergoing percutaneous coronary intervention (PCI). This simple model aids in identifying high-risk patients for better management.
Area of Science:
- Cardiology
- Hematology
- Clinical Medicine
Background:
- In-hospital bleeding is a significant predictor of poor outcomes in patients with acute myocardial infarction (AMI).
- Identifying patients at high risk for bleeding is crucial for effective management and improving prognosis.
Purpose of the Study:
- To develop and validate a predictive model for in-hospital major bleeding in AMI patients undergoing primary percutaneous coronary intervention (PCI).
- To assess the utility of routine pre-procedural blood tests in predicting bleeding events.
Main Methods:
- A total of 1684 AMI patients undergoing primary PCI were divided into derivation and validation cohorts.
- A risk-score model was created using 5 routine blood test parameters: hemoglobin, white blood cell count, platelet count, albumin, and estimated glomerular filtration rate.
- Multivariate analysis and receiver operating characteristic (ROC) curve analysis were performed to assess the model's predictive performance.
Main Results:
- The risk-score model identified 5 key predictors of in-hospital major bleeding.
- Higher risk scores were significantly associated with increased bleeding incidence in both cohorts (P < 0.001).
- The model demonstrated adequate discrimination, with an area under the curve (AUC) of 0.807 in the derivation cohort and 0.793 in the validation cohort.
Conclusions:
- A novel, laboratory-based risk model can effectively predict in-hospital major bleeding in AMI patients.
- This simple and objective model can aid clinicians in identifying high-risk individuals for targeted interventions.
Background:
In-hospital bleeding is associated with poor prognosis in patients with acute myocardial infarction (AMI). We sought to investigate whether a combination of pre-procedural blood tests could predict the incidence of in-hospital major bleeding in patients with AMI.
Methods And Results:
A total of 1684 consecutive AMI patients who underwent primary percutaneous coronary intervention (PCI) were recruited and randomly divided into derivation (n = 1010) and validation (n = 674) cohorts. A risk-score model was created based on a combination of parameters assessed on routine blood tests on admission. In the derivation cohort, multivariate analysis revealed that the following 5 variables were significantly associated with in-hospital major bleeding: hemoglobin level < 12 g/dL (odds ratio [OR], 3.32), white blood cell count >10,000/μL (OR, 2.58), platelet count <150,000/μL (OR, 2.51), albumin level < 3.8 mg/dL (OR, 2.51), and estimated glomerular filtration rate < 60 mL/min/1.73 m2 (OR, 2.31). Zero to five points were given according to the number of these factors each patient had. Incremental risk scores were significantly associated with a higher incidence of in-hospital major bleeding in both cohorts (P < 0.001). Receiver operating characteristic curve analysis of risk models showed adequate discrimination between patients with and without in-hospital major bleeding (derivation cohort: area under the curve [AUC], 0.807; 95% confidence interval [CI], 0.759-0.848; validation cohort: AUC, 0.793; 95% CI, 0.725-0.847).
Conclusions:
Our novel laboratory-based bleeding risk model could be useful for simple and objective prediction of in-hospital major bleeding events in patients with AMI.
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