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Stepwise strategy on the cost of risk stratification after acute myocardial infarction: a retrospective simulation
M Oliveira1, A Staunton, A J Camm
1Department of Cardiological Sciences, St George's Hospital Medical School, London, United Kingdom.
Insights
Combining multiple prognostic markers improves risk stratification for post-heart attack patients. A stepwise strategy using Holter monitoring and signal-averaged electrocardiography is the most cost-effective for identifying high-risk individuals.
Area of Science:
- Cardiology
- Health Economics
Background:
- Accurate risk stratification of post-myocardial infarction patients is crucial for improving outcomes.
- Existing data on the cost-effectiveness of multimarker risk stratification strategies are limited.
Purpose of the Study:
- To evaluate the cost-effectiveness of different multimarker risk stratification strategies for post-myocardial infarction patients.
- To identify the optimal sequence of prognostic markers for identifying high-risk individuals.
Main Methods:
- A comprehensive search of a post-myocardial infarction database was conducted.
- A statistical computer model simulated stepwise risk stratification strategies using left ventricular ejection fraction, signal-averaged electrocardiography, Holter monitoring, and heart rate variability.
- Cost estimates were derived from European and American centers.
Main Results:
- Cardiac mortality was 5.8% within 1 year post-myocardial infarction.
- A stepwise strategy combining all four parameters, starting with Holter monitoring and ending with signal-averaged electrocardiography, was the most cost-effective.
- Costs ranged from $96 to $510 per patient using stepwise strategies, compared to $398-$1,887 for performing all tests.
Conclusions:
- A stepwise risk stratification approach is more cost-effective than performing all tests.
- Combining Holter monitoring and signal-averaged electrocardiography in a stepwise manner is the most appropriate and least expensive strategy for identifying high-risk cardiac patients.
Abstract:
Stratification of postinfarction patients at high risk of mortality and/or other adverse events can be improved by combining several prognostic markers. As the clinical impact of risk stratification has only recently emerged in prospective trials, there are a lack of data regarding the cost-effectiveness of multimarker strategies. This study performed a comprehensive search of a postinfarction database and simulated different risk stratification strategies involving left ventricular ejection fraction, signal-averaged electrocardiography, Holter monitoring, and heart rate variability, The parameters were assessed before discharge in 417 survivors of acute myocardial infarction followed-up for 1 year. Cardiac mortality was used as the clinical endpoint. A statistical computer model of a stepwise strategy using every feasible sequence of the four tests was used and, based on prices derived from European and American centers, the cost estimates of all possible combinations were compared. During the 1 year after myocardial infarction there were 24 cardiac deaths (5.8%). In all the population, 6% had all four tests positive (cardiac mortality 20%); 25% had at least three tests positive (cardiac mortality 12.5%); 58% had at least two tests positive (cardiac mortality 8.3%); and 92% presented with at least one test positive (cardiac mortality 6.3%). The cost of performing all the tests ranged between $398 and $1,887 for each patient. However, by selecting patients according to a step wise strategy, the costs ranged from $96 (> or = 1 test positive) to $510 (for the least expensive sequences of four tests positive). For each of the centers considered, the costs resulting from the risk stratification protocol were determined by the number of variables combined and sequences of tests adopted. Thus, a step wise strategy using the combination of all four parameters, starting with analysis of Holter variables and finishing with signal-averaged electrocardiography, appears to be the most appropriate and the least expensive approach for selecting patients at high risk of cardiac death.