The QT and Corrected QT Interval in Recovery After Exercise in Children
Bibliographic record
Abstract
BACKGROUND: Prolongation of the QT interval after exercise can be used to help diagnose long-QT syndrome, especially when the resting QT interval is borderline. The aim of this study was to determine the normal ranges for QT and corrected QT in the recovery phase after exercise in children. METHODS AND RESULTS: Ninety-four volunteer boys and girls aged 8 to < 17 years without any history of heart disease underwent exercise testing and had a 12-lead ECG performed in the supine position for 10 minutes of recovery. The QT was measured using a standardized tangent method, with the baseline defined as the Q-Q line. The recovery QT was maximally short at 1 minute of recovery in 93 of 94 children then lengthened and stabilized at 4 to 5 minutes recovery. The recovery QT lengthens as heart rate decreases in an approximately linear fashion with a mean increase of 15 ms per 10-beat decrease in heart rate. The 98 th percentiles for the corrected QT using the Bazett formula during minutes 4 to 6 in recovery were from 482 to 491 ms. There was excellent intraobserver and interobserver reliability, with intraclass correlation coefficients of 0.95 and 0.88, respectively. CONCLUSIONS: There is substantial individual variability of the normal repolarization process in the postexercise recovery period in children. The study provides a reference for normal responses for similar populations using a specific measurement protocol that can be easily applied.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".