Feeding Post-Pyloromyotomy: A Meta-analysis
Bibliographic record
Abstract
CONTEXT: Postoperative emesis is common after pyloromyotomy. Although postoperative feeding is likely to be an influencing factor, there is no consensus on optimal feeding. OBJECTIVE: To compare the effect of feeding regimens on clinical outcomes of infants after pyloromyotomy. DATA SOURCES: Cumulative Index to Nursing and Allied Health Literature, The Cochrane Central Register of Controlled Trials, Embase, and Medline. STUDY SELECTION: Two reviewers independently assessed studies for inclusion based on a priori inclusion criteria. DATA EXTRACTION: Data were extracted on methodological quality, general study and intervention characteristics, and clinical outcomes. RESULTS: Fourteen studies were included. Ad libitum feeding was associated with significantly shorter length of stay (LOS) when compared with structured feeding (mean difference [MD] -4.66; 95% confidence interval [CI], -8.38 to -0.95; P = .01). Although gradual feeding significantly decreased emesis episodes (MD -1.70; 95% CI, -2.17 to -1.23; P < .00001), rapid feeding led to significantly shorter LOS (MD 22.05; 95% CI, 2.18 to 41.93; P = .03). Late feeding resulted in a significant decrease in number of patients with emesis (odds ratio 3.13; 95% CI, 2.26 to 4.35; P < .00001). LIMITATIONS: Exclusion of non-English studies, lack of randomized controlled trials, insufficient number of studies to perform publication bias or subgroup analysis for potential predictors of emesis. CONCLUSIONS: Ad libitum feeding is recommended for patients after pyloromyotomy as it leads to decreased LOS. If physicians still prefer structured feeding, early rapid feeds are recommended as they should lead to a reduced LOS.
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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 | 0.015 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.054 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".