Detailed analysis of the impact of age on the QT interval.
Bibliographic record
Abstract
OBJECTIVE: To analyze the effect of age on the ECG QT interval, an important predictor of cardiovascular mortality and drug-induced cardiac arrhythmias, and determine whether QT-heart rate correction formulae (QTc) have differential relationships with age and sex. METHODS: Data were examined from the US National Health and Nutrition Examination Survey (NHANES) II and III, civilian population aged 25 to 90 years. QT weighted means and standard deviations were calculated for all ages. The QTc were evaluated for six QTc: proposed by Bazett (QTcBZT), Fridericia (QTcFRD), Hodges (QTcHDG), Dmitrienko (QTcDMT), Rautaharju (QTcRTHa) and Framingham (QTcFRM). RESULTS: < 0.001) positive relationship between QTc variance and age for each QTc formula for both men and women. There were a greater proportion of individuals with longer QTc with older ages especially age 80 years and above. CONCLUSION: QTc and its variance increase with age. Prolonged QTc is more prevalent in older individuals, especially men.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".