Heart rate variability and amplitude-integrated electroencephalography measured shortly after birth and time to reach clinical milestones: a pilot study in late preterm infants
Bibliographic record
Abstract
Background Among late preterm (LPT) infants, there is significant variability in reaching milestones for safe discharge. We examined the associations of early measures of heart rate variability (HRV) and amplitude-integrated electroencephalogram (aEEG) with time to wean to an open-air cot and to achieve full oral feeds. Methods This is a prospective, multicenter observational cohort study that enrolled infants between 340/7 and 346/7 weeks gestational age (GA). Infants with growth restriction and major congenital anomalies were excluded. Electrocardiogram (ECG) for 1 h and cross-cerebral aEEG for 6 h were recorded within 96 h after birth. Correlations of HRV and aEEG parameters with outcomes were evaluated using stepwise linear regression. Results Of the 26 infants from three centers, 23 were included for analysis for time to an open-air cot. The analysis for time to full oral feeds was limited to 19 infants from two centers with similar feeding policies. Including HRV parameters (time domain, median and standard deviation of R-wave to R-wave interval; frequency domain, ratio of the low frequency to high frequency power and their interaction) and aEEG parameters (total and immature cycles/hour) strengthened associations with time to open-air cot (adjusted R2 = 0.72) and time to full oral feeds (adjusted R2 = 0.53) compared with each parameter alone. Conclusions Early measurements of HRV and aEEG parameters correlate with time to an open-air cot and to achieve full oral feeds in LPT infants born between 340/7 and 346/7 weeks GA.
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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".