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Evaluation of prognostic clinical and ECG parameters in patients after myocardial infarction by applying logistic
Grazina Urbonaviciene1, Sigitas Urbonavicius, Henrik Vorum
1Kaunas University of Medicine, Institute of Cardiology, Kaunas, Lithuania. urbograz@gmail.com
Insights
A new scoring system combining six noninvasive factors helps predict cardiac mortality risk in myocardial infarction (MI) survivors. This tool stratifies patients, identifying high-risk individuals for better post-MI cardiac event management.
Area of Science:
- Cardiology
- Preventive Medicine
- Medical Diagnostics
Background:
- Noninvasive risk stratification after myocardial infarction (MI) remains a significant clinical challenge.
- Existing single tests lack sufficient predictive power for post-MI cardiac mortality.
- A combination of noninvasive parameters is necessary for accurate risk assessment.
Purpose of the Study:
- To identify noninvasive predictors of 2-year cardiac mortality in patients post-MI.
- To develop a risk stratification model for identifying high-risk individuals.
Main Methods:
- Evaluation of clinical, electrocardiographic, and echocardiographic parameters in 180 acute MI survivors before hospital discharge.
- Follow-up for 2 years to record cardiac mortality.
- Multivariate logistic regression analysis to determine significant predictors and construct a scoring system.
Main Results:
- Six variables identified: filtered QRS duration (>114 ms), coefficient of variation (
- A scoring system with a cutoff of 10 or higher identified 'high-risk' patients (75% sensitivity, 70% specificity).
- Mortality rates were 12.5% in the low-risk group and 87.5% in the high-risk group (AUC of 0.88).
Conclusions:
- The proposed scoring system effectively predicts 2-year cardiac mortality risk in post-MI patients.
- This model allows for stratification into low- and high-risk groups, aiding clinical decision-making.
- Noninvasive assessment provides valuable insights for managing post-MI cardiac events.
Abstract:
Noninvasive risk stratification of patients who have suffered myocardial infarction (MI) is one of the greatest challenges in today's cardiology. No single test has sufficient predictive ability. Therefore, a combination of the tests must be applied for better post-MI risk stratification. The purpose of this study was to assess noninvasive predictors of 2 years cardiac mortality in post-MI patients and create a stratification model for identification of high-risk patients. Clinical, electrocardiographic, and echocardiographic parameters were evaluated before hospital discharge in 180 survivors of acute MI (mean age 57.0 +/- 9.9, male 82.2%), followed up for 2 years. A multivariate logistic regression analysis was used to determine informative predictors of cardiac mortality. A clinical score was constructed using the regression coefficient from the multivariate model. During follow-up, 16 deaths (8.8%) occurred. Multivariate analysis identified a combination of six variables that showed the strongest association with cardiac mortality. Based on the coefficients of the logistic regression, six variables were used to create a scoring system: filtered QRS duration (QRSd) >114 ms, coefficient of variation (Cv)