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Clinical Use of CathPCI Registry Risk Score and Its Validation to Predict Long-Term Mortality
Majeed Zahalka1, Erick Sanchez-Jimenez1, Yaniv Levi1
1Cardiology Department, Hillel Yaffe Medical Center, Hadera, Israel; Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel.
Insights
A new risk score accurately predicts mortality after percutaneous coronary intervention (PCI) in high-risk patients. This validated model improves upon existing tools for acute coronary ischemia, offering broader applicability for in-hospital, 30-day, and 1-year outcomes.
Area of Science:
- Cardiology
- Clinical Risk Prediction
- Health Outcomes Research
Background:
- Existing risk models for percutaneous coronary intervention (PCI) mortality have limited utility in complex, high-risk patient populations.
- A recent bedside model utilizing the American College of Cardiology CathPCI Registry data demonstrated improved prediction of in-hospital mortality.
Purpose of the Study:
- To validate the American College of Cardiology (ACC) CathPCI Registry risk score in a distinct population of patients admitted with acute coronary ischemia.
- To assess the model's ability to predict in-hospital, 30-day, and 1-year mortality.
Main Methods:
- The CathPCI risk score was applied to the Acute Coronary Syndrome Israeli Survey (ACSIS) cohort, comprising 1,155 patients admitted with acute myocardial infarction who underwent PCI.
- Data included in-hospital, 30-day, and 1-year mortality outcomes.
Main Results:
- The CathPCI risk score demonstrated high predictive accuracy for in-hospital mortality (AUC 0.96) and 30-day mortality (AUC 0.96), and good accuracy for 1-year mortality (AUC 0.88).
- The ACSIS cohort included high-risk patients with conditions such as frail status, aortic stenosis, refractory shock, and post-cardiac arrest, indicating the model's applicability in complex cases.
Conclusions:
- The ACC CathPCI Registry risk score is validated in the ACSIS cohort, confirming its effectiveness in predicting mortality for patients with acute coronary ischemia.
- The model shows a wider scope of application than previous tools, including its utility for predicting 30-day and 1-year mortality in diverse, high-risk patient groups.
Abstract:
Risk models to estimate percutaneous coronary intervention (PCI) mortality have limited value in complex high-risk patients. However, it was improved by a recently developed bedside model to predict in-hospital mortality using data from the American College of Cardiology CathPCI Registry that included 706,263 patients. The median risk-standardized in-hospital mortality rate was 1.9%. In an attempt to validate this model in patients admitted because of acute coronary ischemia to predict in-hospital, 30-day, and 1-year mortality, we applied the proposed risk score to the study population of the Acute Coronary Syndrome Israeli Survey (ACSIS). This study was conducted for 2 months in 2018 and included all patients admitted to 25 coronary care units and cardiology departments in Israel. The ACSIS included 1,155 patients admitted because of acute myocardial infarction and who underwent PCI. In-hospital, 30-day, and 1-year mortality were 2.3%, 3.1%, and 6.2%, respectively. The CathPCI risk score yielded an area under the receiver operating characteristic curve of 0.96 (95% confidence interval [CI] 0.94 to 0.99) for in-hospital mortality; 0.96 (95% CI 0.94 to 0.98) for the 30-day mortality, and 0.88 (95% CI 0.83 to 0.93) for the 1-year mortality. The current model also included frail patients, and those with aortic stenosis, refractory shock, and after cardiac arrest. In conclusion, the CathPCI Registry risk score was validated using data from the ACSIS. Because the ACSIS population comprised patients with acute ischemia including those with high-risk features this model demonstrates a wider scope of application compared with previous ones. In addition, the model seems to be suitable to predict also the 30-day and 1-year mortality.
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