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Author Spotlight: Unveiling Prognostic Indicators in Heart Failure - The Role of Phase Angle and Bioelectrical Impedance Analysis
Published on: June 30, 2023
A Multivariate Model to Predict Chronic Heart Failure after Acute ST-Segment Elevation Myocardial Infarction:
Valentin Elievich Oleynikov1, Elena Vladimirovna Averyanova1, Anastasia Aleksandrovna Oreshkina1
1Department of Therapy, Medical Institute, Penza State University, 440026 Penza, Russia.
Insights
A new model predicts chronic heart failure (CHF) risk after myocardial infarction. This tool helps identify high-risk patients early for better management.
Area of Science:
- Cardiology
- Medical Prognostics
Background:
- ST-segment elevation myocardial infarction (STEMI) survivors face a significant risk of developing decompensated chronic heart failure (CHF).
- Early identification of patients at high risk for CHF progression post-STEMI is crucial for timely intervention and improved outcomes.
Purpose of the Study:
- To develop and validate a multivariate model for predicting the risk of decompensated CHF within 48 weeks following STEMI.
- To assess the diagnostic efficiency of the developed predictive model.
Main Methods:
- The study involved 173 STEMI patients, utilizing 2D speckle-tracking echocardiography (STE) and 24-hour ECG monitoring for parameters including global longitudinal strain (GLS) and heart rate turbulence (HRT).
- A multivariate model was constructed using data from 113 patients (Group M) and validated on 60 patients (Group T).
Main Results:
- The predictive model incorporated HRT, left ventricular end-systolic dimension (ESD), and GLS.
- The model demonstrated significant predictive value for CHF progression, with HRT (RR 3.92), ESD (RR 1.04), and GLS (RR 0.9) as key factors.
- Validation showed high diagnostic performance: 83.3% specificity, 95.8% sensitivity, and 93.3% accuracy.
Conclusions:
- The developed multivariate model effectively predicts CHF progression in STEMI patients within 48 weeks.
- The model exhibits high diagnostic efficiency and can be utilized in the early stages post-myocardial infarction for patient risk stratification.
Abstract:
A multivariate model for predicting the risk of decompensated chronic heart failure (CHF) within 48 weeks after ST-segment elevation myocardial infarction (STEMI) has been developed and tested.
Methods:
The study included 173 patients with acute STEMI aged 51.4 (95% confidence interval (CI): 42-61) years. Two-dimensional (2D) speckle-tracking echocardiography (STE) has been performed on the 7th-9th days, and at the 12th, 24th, and 48th weeks after the index event with the analysis of volumetric parameters and values for global longitudinal strain (GLS), global circumferential strain (GCS), and global radial strain (GRS). A 24-h ECG monitoring (24 h ECG) of the electrocardiogram (ECG) to assess heart rate turbulence (HRT) has been performed on the 7th-9th days of STEMI. The study involved two stages of implementation. At the first stage, a multivariate model to assess the risk of CHF progression within 48 weeks after STEMI has been built on the basis of examination and follow-up data for 113 patients (group M). At the second stage, the performance of the model has been assessed based on a 48-week follow-up of 60 patients (group T).
Results:
A multivariate regression model for CHF progression in STEMI patients has been created based on the results of the first stage. It included the following parameters: HRT, left ventricular (LV) end-systolic dimension (ESD), and GLS. The contribution of each factor for the relative risk (RR) of decompensated CHF has been found: 3.92 (95% CI: 1.66-9.25) (p = 0.0018) for HRT; 1.04 (95% CI: 1.015-1.07) (p = 0.0027) for ESD; 0.9 (95% CI: 0.815-0.98) (p = 0.028) for GLS. The diagnostic efficiency of the proposed model has been evaluated at the second stage. It appeared to have a high specificity of 83.3%, a sensitivity of 95.8%, and a diagnostic accuracy of 93.3%.
Conclusion:
The developed model for predicting CHF progression within 48 weeks after STEMI has a high diagnostic efficiency and can be used in early stages of myocardial infarction to stratify the risk of patients.
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