Methylxanthine for the prevention and treatment of apnea in preterm infants
Bibliographic record
Abstract
BACKGROUND: Very preterm infants often require respiratory support and are therefore exposed to an increased risk of chronic lung disease and later neurodevelopmental disability. Although methylxanthines are widely used to prevent and treat apnea associated with prematurity and to facilitate extubation, there is uncertainty about the benefits and harms of different types of methylxanthines. OBJECTIVES: To assess the effects of methylxanthines on the incidence of apnea, death, neurodevelopmental disability, and other longer-term outcomes in preterm infants (1) at risk for or with apnea, or (2) undergoing extubation. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, two other databases, and three trial registers (November 2022). SELECTION CRITERIA: We included randomized trials in preterm infants, in which methylxanthines (aminophylline, caffeine, or theophylline) were compared to placebo or no treatment for any indication (i.e. prevention of apnea, treatment of apnea, or prevention of re-intubation). DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods and GRADE to assess the certainty of evidence. MAIN RESULTS: = 69%; NNTB 4, 95% CI 2 to 6; 6 studies, 197 infants; moderate-certainty evidence). AUTHORS' CONCLUSIONS: Caffeine probably reduces the risk of death, major neurodevelopmental disability at 18 to 24 months, and the composite outcome DMND at 18 to 24 months. Administration of any methylxanthine to preterm infants for any indication probably leads to a reduction in the risk of any apneic episodes, failed apnea reduction after two to seven days, cerebral palsy, developmental delay, and may reduce receipt of positive-pressure ventilation after institution of treatment. Methylxanthine used for any indication reduces chronic lung disease (defined as the use of supplemental oxygen at 36 weeks' postmenstrual age).
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".