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Published on: January 28, 2020
Prediction of long-term mortality after percutaneous coronary intervention in older adults: results from the National
William S Weintraub1, Maria V Grau-Sepulveda, Jocelyn M Weiss
1Christiana Care Health System, 4755 Ogletown-Stanton Road, Newark, DE 19718, USA. wweintraub@christianacare.org
Insights
A new model predicts long-term mortality after percutaneous coronary intervention (PCI) for ST-segment elevation myocardial infarction and stable coronary disease patients. This validated tool aids in predicting survival up to three years post-procedure.
Area of Science:
- Cardiovascular Medicine
- Medical Informatics
- Health Services Research
Background:
- Percutaneous coronary intervention (PCI) is a common procedure for coronary artery disease.
- Predicting long-term mortality after PCI is crucial for patient management and healthcare planning.
- Existing models may not adequately capture long-term outcomes across diverse patient populations.
Purpose of the Study:
- To develop and validate a predictive model for all-cause mortality up to 3 years following PCI.
- To include patients with both ST-segment elevation myocardial infarction (STEMI) and stable coronary disease.
- To utilize a large, nationally representative dataset for robust model development.
Main Methods:
- Linked American College of Cardiology Foundation CathPCI Registry data with Centers for Medicare and Medicaid Services (CMS) data.
- Used pre-procedure variables to predict 3-year mortality in patients aged ≥65 years.
- Randomly divided 343,466 linked patients into derivation (60%) and validation (40%) cohorts.
- Identified 24 mortality-associated characteristics.
Main Results:
- Achieved C-indices of 0.79 (STEMI) and 0.78 (non-STEMI) in validation cohorts, indicating excellent discrimination.
- Model demonstrated good calibration across a wide range of predicted mortality probabilities.
- Observed 3-year mortality rates of 18.7% in the overall study population.
Conclusions:
- A validated model with excellent discrimination and calibration for predicting 3-year survival post-PCI has been developed.
- The model is based on a large, nationally representative dataset, enhancing its generalizability.
- This tool can aid clinicians in risk stratification and long-term patient care planning after PCI.
Background:
The purpose of this study was to develop a long-term model to predict mortality after percutaneous coronary intervention in both patients with ST-segment elevation myocardial infarction and those with more stable coronary disease.
Methods And Results:
The American College of Cardiology Foundation CathPCI Registry data were linked to the Centers for Medicare and Medicaid Services 100% denominator file by probabilistic matching. Preprocedure demographic and clinical variables from the CathPCI Registry were used to predict the probability of death over 3 years as recorded in the Centers for Medicare and Medicaid Services database. Between 2004 and 2007, 343 466 patients (66%) of 518 195 patients aged ≥65 years undergoing first percutaneous coronary intervention in the CathPCI Registry were successfully linked to Centers for Medicare and Medicaid Services data. This study population was randomly divided into 60% derivation and 40% validation cohorts. Median follow-up was 15 months, with mortality of 3.0% at 30 days and 8.7%, 13.4%, and 18.7% at 1, 2, and 3 years, respectively. Twenty-four characteristics related to demographics, clinical comorbidity, prior history of disease, and indices of disease severity and acuity were identified as being associated with mortality. The C indices in the validation cohorts for patients with and without ST-segment elevation myocardial infarction were 0.79 and 0.78. The model calibrated well across a wide range of predicted probabilities.
Conclusions:
On the basis of the large and nationally representative CathPCI Registry, we have developed a model that has excellent discrimination, calibration, and validation to predict survival up to 3 years after percutaneous coronary intervention.
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