Bibliographic record
Abstract
BACKGROUND: The single most important risk factor for postpartum maternal infection is Cesarean delivery. OBJECTIVES: The objective of this review was to assess the effects of prophylactic antibiotic treatment on infectious complications in women undergoing Cesarean delivery. SEARCH STRATEGY: We searched the Cochrane Pregnancy and Childbirth Group trials register and the Cochrane Controlled Trials Register. SELECTION CRITERIA: Randomised trials comparing antibiotic prophylaxis or no treatment for both elective and non-elective Cesarean section. DATA COLLECTION AND ANALYSIS: Two reviewers assessed trial quality and extracted data. MAIN RESULTS: Sixty-six trials were included. Use of prophylactic antibiotics in women undergoing Cesarean section substantially reduced the incidence of episodes of fever, endometritis, wound infection, urinary tract infection and serious infection after Cesarean section. The reduction in the risk of endometritis with antibiotics was similar across different patient groups. The relative risk for elective Cesarean section was 0.24, 95% confidence interval 0.11 to 0.48. The relative risk for non-elective Cesarean section was 0.30, 95% confidence interval 0.25 to 0.35. The relative risk for undefined or all patients together was 0.29, 95% confidence interval 0.26 to 0.33. Despite the large number of trials, different populations and different antibiotic regimens, there was no statistically significant heterogeneity. REVIEWER'S CONCLUSIONS: The reduction of endometritis by two thirds to three quarters justifies a policy of administering prophylactic antibiotics to women undergoing elective or non-elective Cesarean section.
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 | 0.004 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".