Related Experiment Video
Updated: Sep 6, 2025
Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions
Published on: June 5, 2019
Heart rate variability as a biomarker in patients with Chronic Chagas Cardiomyopathy with or without concomitant
Luiz Eduardo Virgilio Silva1, Henrique Turin Moreira1, Marina Madureira de Oliveira1
1Division of Cardiology, Department of Internal Medicine, Ribeirão Preto Medical School, University of São Paulo, Av. Bandeirantes, 3900, Ribeirão Preto, São Paulo, 14048-900, Brazil.
Insights
Heart rate variability (HRV) analysis helps predict Chagas heart disease (CCC) prognosis. Increased heart rate fragmentation indicates a worse outlook, especially in patients with digestive involvement.
Area of Science:
- Cardiology
- Autonomic Nervous System Research
- Medical Data Analysis
Background:
- Dysautonomia contributes to Chronic Chagas Cardiomyopathy (CCC) pathogenesis and digestive issues.
- Heart rate variability (HRV) is crucial for risk stratification in CCC.
- Investigating HRV differences in isolated CCC versus mixed (CCC + digestive) forms is essential.
Purpose of the Study:
- To assess HRV's ability to stratify death risk in CCC patients.
- To compare HRV alterations in isolated CCC versus mixed CCC forms.
- To develop machine learning models for CCC risk prediction.
Main Methods:
- 31 CCC patients were categorized into low, intermediate, and high-risk groups based on Rassi score.
- 10-20 minute single-lead ECGs were recorded to generate RR series and calculate 31 HRV indices.
- Four machine learning models were developed to predict patient risk class.
Main Results:
- High-risk CCC patients showed decreased phase entropy and increased inflection points compared to low-risk.
- Mixed form patients exhibited reduced RR histogram triangular interpolation and low-frequency power.
- Support vector machine model achieved the highest predictive accuracy (F1-score of 0.61).
Conclusions:
- The mixed form of Chagas disease is linked to diminished slow HRV components.
- Worse CCC prognosis correlates with increased heart rate fragmentation.
- Combining HRV indices improves risk stratification accuracy; mixed form may involve sympathetic and parasympathetic impairment.
Background:
Dysautonomia plays an ancillary role in the pathogenesis of Chronic Chagas Cardiomyopathy (CCC), but is the key factor causing digestive organic involvement. We investigated the ability of heart rate variability (HRV) for death risk stratification in CCC and compared alterations of HRV in patients with isolated CCC and in those with the mixed form (CCC + digestive involvement). Thirty-one patients with CCC were classified into three risk groups (low, intermediate and high) according to their Rassi score. A single-lead ECG was recorded for a period of 10-20 min, RR series were generated and 31 HRV indices were calculated. The HRV was compared among the three risk groups and regarding the associated digestive involvement. Four machine learning models were created to predict the risk class of patients.
Results:
Phase entropy is decreased and the percentage of inflection points is increased in patients from the high-, compared to the low-risk group. Fourteen patients had the mixed form, showing decreased triangular interpolation of the RR histogram and absolute power at the low-frequency band. The best predictive risk model was obtained by the support vector machine algorithm (overall F1-score of 0.61).
Conclusions:
The mixed form of Chagas' disease showed a decrease in the slow HRV components. The worst prognosis in CCC is associated with increased heart rate fragmentation. The combination of HRV indices enhanced the accuracy of risk stratification. In patients with the mixed form of Chagas disease, a higher degree of sympathetic autonomic denervation may be associated with parasympathetic impairment.
More Related Videos
06:24Examining Changes in HRV and Emotion Following Artmaking with Three Different Art Materials
Published on: January 11, 2020
12:45Benefits of Cardiac Resynchronization Therapy in an Asynchronous Heart Failure Model Induced by Left Bundle Branch Ablation and Rapid Pacing
Published on: December 11, 2017
Related Concept Videos
01:30Factors Influencing Heart Rate
Let us explore the significant factors affecting heart rate, including age, body temperature, posture, acute pain, chemical influences,...
01:22Rheumatic Heart Disease II: Clinical Manifestations and Diagnostic Studies
01:19Blood Studies for Cardiovascular System II: CRP, Hcy, and Cardiac Natriuretic Peptide Markers
These markers indicate stress or strain on the heart muscle:
Natriuretic Peptides (BNP)
Cardiac myocytes produce these hormones in response to ventricular stretching...
01:29Cardiomyopathy IV: Restrictive Cardiomyopathy
01:20Blood Studies for Cardiovascular System I: Cardiac Biomarkers
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
Troponins
Troponins, particularly cardiac troponins I and T, are the most precise and sensitive markers of myocardial injury. They are detectable within 4-6 hours of myocardial injury and remain...
01:30Pulse rhythm
Conversely, an irregular pulse pattern is termed dysrhythmia, stemming from disruptions in cardiac...