Nasal Continuous Positive Airway Pressure Inhibits Gastroesophageal Reflux in Newborn Lambs
Bibliographic record
Abstract
BACKGROUND: Using esophageal pHmetry, nasal CPAP (nCPAP) has been shown to decrease acid gastroesophageal reflux (GER) in adult humans. Although both GER (mainly non-acid) and nCPAP use are very frequent in newborns, the effect of nCPAP on GER in early life is unknown. Having recently shown that the newborn lamb is a unique model for studying neonatal GER, our main objective was to assess the effect of nCPAP on GER in newborn lambs. METHODS: Eight newborn lambs, aged 2-3 days, were studied. Continuous esophageal pH-Impedance monitoring and polysomnography were performed for six hours during both spontaneous breathing and nCPAP application at 6 cmH2O (nCPAP(6)), in a randomized order. Results were compared in the two experimental conditions, as well as without CPAP during the following 6 hours. RESULTS: i) nCPAP(6) virtually abolished GER [mean ± SD reflux number for 6 h = 9.1 ± 8.6 without nCPAP(6) vs. 0.6 ± 1 with nCPAP(6), P<0.05]; ii) GER number was also reduced during the 6 h-period following nCPAP(6) application (18 ± 16 without nCPAP(6) vs. 7 ± 8.1 with nCPAP(6), P<0.05); iii) nCPAP(6) decreased the depth and duration of lower esophageal sphincter relaxation. CONCLUSIONS: nCPAP inhibits GER in the newborn lamb. Further clinical studies using different levels of nasal CPAP are needed to confirm this result in human infants.
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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 | 0.000 | 0.001 |
| 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".