Modeling In-Hospital Mortality Among Patients Undergoing Percutaneous Coronary Intervention with Acute Myocardial Infarction Complicated by Cardiogenic Shock Receiving Mechanical Circulatory Support
Hurley, N.; Mortazavi, B. J.; Dhruva, S.; Ross, J. S.; Ngufor, C. G.; Curtis, J. P.; Krumholz, H.; Desai, N.
Show abstract
Acute myocardial infarction complicated by cardiogenic shock (AMI-CS) is a heterogeneous clinical syndrome associated with substantial morbidity and mortality. We developed a machine learning-based mortality model to identify features and patient subgroups associated with the largest change in mortality risk when evaluating treatment with Impella devices or intra-aortic Balloon Pump (IABP). Our cohort comprised 369 sites and 15,796 patient visits to the cardiac catheterization laboratory from the National Cardiovascular Data Registry. The estimated population mean excess mortality effect of treatment with Impella devices vs IABP was 10.4 {+/-} 0.8%. However, we identified clinical subgroups of 282 patients for whom a decreased risk of mortality was associated with use of Impella as compared with IABP. Those patients were on average younger, presented with higher systolic blood pressure, higher rate of salvage percutaneous coronary intervention, higher initial creatinine, and lower hemoglobin. While Impella devices were associated with higher mortality risk overall, certain clinical profiles were associated with lower risk, illustrating heterogeneity of treatment effects.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Prognostic Value of Patient-Reported Outcomes in Predicting Long-term Mortality after Transcatheter Aortic Valve Replacement (TAVR) 95%
- Effectiveness of an Impella versus intra-aortic balloon pump in patients who received extracorporeal membrane oxygenation 95%
- Artificial intelligence of arterial Doppler waveforms to predict major adverse outcomes among patients evaluated for peripheral artery disease 95%
Similar papers in this journal
- Hemodynamic profiles by non-invasive monitoring of cardiac index and vascular tone in acute heart failure patients in the emergency department: external validation and clinical outcomes 96%
- The effect of coronary revascularization treatment timing on mortality in patients with stable ischemic heart disease in British Columbia 95%
- ChatGPT Provides Inconsistent Risk-Stratification of Patients With Atraumatic Chest Pain 95%
Similar papers in this journal
- Multiple Biomarkers to Predict Major Adverse Cardiovascular Events in Patients With Coronary Chronic Total Occlusions 95%
- Investigating Electrocardiographic Abnormalities in Patients with Coronary Microvascular Dysfunction 94%
- Ticagrelor vs Clopidogrel: the Impact of Platelet Inhibition on Cerebrovascular Microembolic Events during TAVR 94%
Similar papers in this journal
- Development and Validation of a Nomogram for Predicting Survival in Patients With Cardiogenic Shock 97%
- Predicting long-term prognosis after percutaneous coronary intervention in patients with acute coronary syndromes: a prospective nested case-control analysis for county-level health services 94%
- Autologous cardiac micrografts as support therapy to coronary artery bypass surgery 93%
Similar papers in this journal
- Impact of COVID-19 pandemic on rates of congenital heart disease procedures among children: Prospective cohort analyses of 26,270 procedures in 17,860 children using CVD-COVID-UK consortium record linkage data 94%
- Machine learning approaches to predict 30-day mortality following percutaneous coronary intervention in an Australian population 94%
- The Impact of COVID-19 Pandemic on Cardiology Services 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.