Qualitative and Quantitative Electrocardiogram Parameters in a Large Cohort of Children with Duchenne Muscle Dystrophy in Comparison with Age-Matched Healthy Subjects: A Study from South India
Bibliographic record
Abstract
Background: Electrocardiography (ECG) remains an excellent screening tool for cardiac assessment in Duchenne muscular dystrophy (DMD), but an accurate interpretation requires comparison with age-matched healthy controls. Objective: We examined various ECG parameters in children with DMD, in comparison with age-matched controls. Methods: Standard 12-lead ECG tracings of serial patients were screened for quality and selected. Controls were healthy, age-matched school-going children. Both quantitative and qualitative ECG parameters were analyzed. Results: After screening, ECGs from 252 patients with DMD (8.32 ± 3.12 years, 2-21 years) and ECGs from 151 age-matched healthy controls (9.72 ± 2.23, 4-19 years) were included. A significantly higher heart rate, shorter R-R interval, and taller R wave in V1 were seen across all age group of DMD in comparison to controls, with the difference increasing with age. While QT prolongation was seen in all age groups of DMD, QTc prolongation was seen only at 10 years or more. Incomplete right bundle branch block (RBBB) and pathological Q waves in inferolateral leads were exclusive in DMD, with the latter declining with age. Evidence for left ventricular (LV) pathology, such as tall R in V5/V6, increase in SV1 + RV6 height, and QRS complex duration, were seen only in the age group of 10 years or more. Conclusion: Stratification based on age and comparison with age-matched healthy subjects showed that several ECG parameters were influenced by age, and it also identified age-dependent evidence for LV pathology and QTc prolongation in DMD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".