Gavage Feed Volume Determines the Gastric Emptying Rate in Preterm Infants
Bibliographic record
Abstract
OBJECTIVE: Feeding intolerance, manifesting as increased gastric residual, is a common finding in preterm neonates. Little is known about the regulation of gastric emptying early in life and the extent to which this plays a role in the preterm infants' feeding tolerance. The goal of this study was to evaluate clinically stable 28- to 32-week gestation neonates during the first 4 weeks of life and noninvasively determine their gastric emptying rate. STUDY DESIGN: Ultrasound measurements of gastric milk content volume were obtained from 25 neonates immediately after, 30 and/or 60 minutes following routine gavage feeds. The content emptying rate was calculated from the gastric volume data. RESULTS: Gastric emptying rate was not postnatal age-dependent, was significantly higher at 30 minutes, whenever compared with 60-minute postfeed and directly proportional to the feed volume. At any postnatal age, the gastric emptying rate was at least 6-fold greater, when comparing the lowest and highest average stomach content volumes. CONCLUSIONS: The gastric emptying rate of preterm infants is content volume-dependent and unrelated to the postnatal age. Given the present findings, further investigation on the gastric residual of preterm infants receiving larger than currently administered feed volumes at the initiation of enteral nutrition, is warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| 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".