Effect of food intake during labour on obstetric outcome: randomised controlled trial
Bibliographic record
Abstract
OBJECTIVE: To investigate the effect of feeding during labour on obstetric and neonatal outcomes. DESIGN: Prospective randomised controlled trial. SETTING: Birth centre in London teaching hospital. PARTICIPANTS: 2426 nulliparous, non-diabetic women at term, with a singleton cephalic presenting fetus and in labour with a cervical dilatation of less than 6 cm. INTERVENTION: Consumption of a light diet or water during labour. MAIN OUTCOME MEASURES: The primary outcome measure was spontaneous vaginal delivery rate. Other outcomes measured included duration of labour, need for augmentation of labour, instrumental and caesarean delivery rates, incidence of vomiting, and neonatal outcome. RESULTS: The spontaneous vaginal delivery rate was the same in both groups (44%; relative risk 0.99, 95% confidence interval 0.90 to 1.08). No clinically important differences were found in the duration of labour (geometric mean: eating, 597 min v water, 612 min; ratio of geometric means 0.98, 95% confidence interval 0.93 to 1.03), the caesarean delivery rate (30% v 30%; relative risk 0.99, 0.87 to 1.12), or the incidence of vomiting (35% v 34%; relative risk 1.05, 0.9 to 1.2). Neonatal outcomes were also similar. CONCLUSIONS: Consumption of a light diet during labour did not influence obstetric or neonatal outcomes in participants, nor did it increase the incidence of vomiting. Women who are allowed to eat in labour have similar lengths of labour and operative delivery rates to those allowed water only. TRIAL REGISTRATION: Current Controlled Trials ISRCTN33298015.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".