Impact of cessation of caffeine citrate therapy on intermittent hypoxemia patterns among preterm infants born before 34 weeks
Bibliographic record
Abstract
Introduction: ) drop ≥5% from the baseline (set at 90 s preceding the event) to a level less than 90% lasting for ≥5 s. Caffeine citrate, the standard of care for apnea of prematurity, reduces IH events. IH contributes to both short and long-term adverse neurologic outcomes. Standard patient monitors cannot detect IH events due to long averaging times. Objective: Describe change in patterns of IH events in preterms <34 weeks before and after cessation of caffeine citrate and factors associated. Methods: -value <0.05 considered significant. Results: 49 patients medical records available for secondary analysis. Frequency of IH events increased from 7.94 to 40.94 events/hour (5-fold). IH events of durations lasting between 0 and 10 s, and >20 s decreased by 12.3% and 6.8%, respectively, while those lasting 10-20 s increased by 17%. The mildly severe IH events decreased by nearly half, 46.9% (78.4% to 31.5%), while both the moderately severe and severe IH events increased by 17.4% (18.5%-35.9%), and 26% (6.7% to 32.7%) respectively. The time spent in hypoxemia increased by 2.3 h/week/patient, while the cumulative time in hypoxemia increased by 1.6 h/patient. Preterms exposure to ACS (antenatal corticosteroids) was associated with decrease in IH events. Conclusion: Caffeine citrate cessation leads to worsening of IH events with increased frequency, duration, severity and cumulative time spent in hypoxemia. Exposure to ACS was associated with decrease in IH events. Recommendation: Caffeine citrate therapy use beyond 34 weeks is likely to be beneficial especially in the context of LMIC where antenatal steroid is not always administered, and monitoring of preterm babies is suboptimal. Safe cessation of caffeine therapy requires monitoring to detect IH events.
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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 | 0.004 |
| 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".