Caffeine for Persistent Intermittent Hypoxia in Newborns With and Without Chronic Lung Disease
Bibliographic record
Abstract
ABSTRACT Objectives To assess the caffeine response in preterm and term newborns with persistent intermittent hypoxia (IH) as they approach discharge, with particular focus on newborns with chronic lung disease of prematurity (CLD). To identify factors associated with a lack of response to caffeine. Design/Settings Retrospective cohort study across two neonatal intensive care units between 2015 and 2022. Main Outcomes Following Caffeine Administration Normal oximetry; no need for respiratory support; resolution of hypercapnia. Results A total of 132 infants received caffeine for persistent IH. Normal oximetry was achieved post‐caffeine in 81% (46/57) of newborns with CLD, in 96% (46/48) of preterm with no CLD, in 96% (26/27) of term newborns. Caffeine reduced the % time with SpO 2 < 90% from 6.8% (interquartile range, 3.8%–12.2%), to 0.8% (0.4%–1.6%, p < 0.0001). The desaturation index < 80% dropped from 5.3 events/hour (0.9–14.6 events/hour) to 0.2 events/hour (0–0.78 events/hour, p < 0.0001) and the desaturation index ≥ 10% lasting > 10 s went from 6.6 events/hour (3.3–10.7 events/hour) to 1.4 events/hour (0.7–2.4 events/hour, p < 0.0001). Of the 61 infants on respiratory support, 74% (45/61) were weaned within a few days following caffeine. Caffeine normalized PCO 2 in 63% (41/65) of newborns with elevated PCO 2 pre‐caffeine. Infants failing caffeine were more likely to have CLD compared to responders (79% vs. 39%, p < 0.005). Caffeine was successfully discontinued (first attempt, normal oximetry) in 101 infants (88%) at postmenstrual age of 46.1 weeks (45.3–48.3 weeks). Conclusion Caffeine improved respiratory outcomes in the majority of preterm and term born infants with persistent IH, including those with CLD.
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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 | 0.003 |
| 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) | 0.001 | 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".