The QTc-Bazett Interval in Former Very Preterm Infants in Adolescence and Young Adulthood is Not Different from Term-Born Controls
Bibliographic record
Abstract
Although relevant for precision pharmacovigilance, there are conflicting data on whether former preterm birth is associated with QT c-Bazett prolongation in later life. To explore QT c-Bazett interval differences between former preterm and/or extremely low birth weight (ELBW) cases and term-born controls in adolescence and young adulthood, we analyzed pooled individual data after a structured search on published cohorts. To test the absence of a QT c-Bazett difference, a non-inferiority approach was applied (one-sided, upper limit of the 95% confidence interval [CI] mean QT c-Bazett difference, 5 and 10 ms). We also investigated the impact of characteristics, either perinatal or at assessment, on QT c-Bazett in the full dataset (cases and controls). Data were reported as median and range. The pooled dataset contained 164 former preterm and/or ELBW (cases) and 140 controls born full-term from three studies. The median QT c-Bazett intervals were 409 (335–490) and 410 (318–480) ms in cases and controls. The mean QT c-Bazett difference was 1 ms, with an upper 95% CI of 6 ms ( p > 0.05 and p < 0.01 for 5 and 10 ms, respectively). In the full dataset, females had a significantly longer QT c-Bazett than males (415 vs. 401 ms; p < 0.0001). QT c-Bazett intervals are not significantly different between former preterm and/or ELBW cases and term-born controls, and we rejected a potential prolongation > 10 ms in cases. When prescribing QTc-prolonging drugs, pharmacovigilance practices in this subpopulation should be similar to the general public (NCT05243537).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".