Establishing reference ranges for ambulatory electrocardiography parameters: meta-analysis
Bibliographic record
Abstract
OBJECTIVE: Despite the widespread and increasing use of ambulatory electrocardiography (ECG), there is no consensus on reference ranges for ambulatory electrocardiogram parameters to guide interpretation. We sought to determine population distribution-based reference ranges for parameters measured during ambulatory electrocardiogram in healthy adults, based on existing literature. METHODS: We searched multiple databases from 1950 to 2020. Articles reporting original data from ≥24-hour ambulatory electrocardiogram monitoring in healthy adults were included. Data extraction and synthesis were performed according to Meta-analysis of Observational Studies in Epidemiology guidelines. The prevalence/mean and SD for common parameters (sinus pauses, conduction abnormalities and ectopy) were extracted by age group (18-39, 40-59, 60-79 and 80+ years). RESULTS: We identified 33 studies involving 6466 patients. Sinus pauses of >3 s were rare (pooled prevalence <1%) across all ages. Supraventricular ectopy of >1000/24 hours increased with age, from 0% (95% CI 0% to 0%) in those aged 18-39 years to 6% (95% CI 0% to 17%) in those aged 60-79 years. Episodes of supraventricular tachycardia increased from 3% (95% CI 1% to 6%) in those aged 18-39 years to 28% (95% CI 9% to 52%) in those aged 60-79 years. Ventricular ectopy of >1000/24 hours also increased with age, from 1% (95% CI 0% to 2%) in those aged 18-39 years to 5% (95% CI 1% to 10%) in those aged 60-79 years. Episodes of non-sustained ventricular tachycardia ranged from 0% (95% CI 0% to 1%) in those aged 18-39 years to 2% (95% CI 0% to 5%) in those aged 60-79 years. CONCLUSION: Despite the limitations of existing published data, this meta-analysis provides evidence-based reference ranges for ambulatory electrocardiogram parameters and highlights significant age-dependent differences that should be taken into account during interpretation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.034 | 0.092 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.042 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".