Neurobehavioral Outcomes 11 Years After Neonatal Caffeine Therapy for Apnea of Prematurity
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Caffeine is effective in the treatment of apnea of prematurity. Although caffeine therapy has a benefit on gross motor skills in school-aged children, effects on neurobehavioral outcomes are not fully understood. We aimed to investigate effects of neonatal caffeine therapy in very low birth weight (500–1250 g) infants on neurobehavioral outcomes in 11-year-old participants of the Caffeine for Apnea of Prematurity trial. METHODS: Thirteen academic hospitals in Canada, Australia, Great Britain, and Sweden participated in this part of the 11-year follow-up of the double-blind, randomized, placebo-controlled trial. Measures of general intelligence, attention, executive function, visuomotor integration and perception, and behavior were obtained in up to 870 children. The effects of caffeine therapy were assessed by using regression models. RESULTS: Neurobehavioral outcomes were generally similar for both the caffeine and placebo group. The caffeine group performed better than the placebo group in fine motor coordination (mean difference [MD] = 2.9; 95% confidence interval [CI]: 0.7 to 5.1; P = .01), visuomotor integration (MD = 1.8; 95% CI: 0.0 to 3.7; P < .05), visual perception (MD = 2.0; 95% CI: 0.3 to 3.8; P = .02), and visuospatial organization (MD = 1.2; 95% CI: 0.4 to 2.0; P = .003). CONCLUSIONS: Neonatal caffeine therapy for apnea of prematurity improved visuomotor, visuoperceptual, and visuospatial abilities at age 11 years. General intelligence, attention, and behavior were not adversely affected by caffeine, which highlights the long-term safety of caffeine therapy for apnea of prematurity in very low birth weight neonates.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".