The effect of vaginal pH on labor induction with vaginal misoprostol
Bibliographic record
Abstract
OBJECTIVE: To estimate the association of vaginal pH on the induction to vaginal delivery interval in labor induction with vaginal misoprostol. METHODS: Women presenting at term with intact membranes for labor induction were recruited. The pH of the vagina was measured during a digital examination of the cervix to determine the Bishop Score. Labor was induced with 25 microg of vaginal misoprostol placed every 6 h until spontaneous rupture of membranes or active labor occurred. The primary outcome was the induction to vaginal delivery interval in the lower pH (< 5) versus higher pH (> or = 5) group. Secondary outcomes assessed maternal and neonatal morbidities. Sample size calculated a priori estimated 120 subjects were required for a power of 95% and a 2-tailed a of 0.05. RESULTS: 120 women met inclusion criteria and had available pH data. There was no difference in the induction to vaginal delivery interval in the lower pH (1455 min) versus higher pH group (1295 minutes, Mean difference 160 [- 147,468] P = .30). No difference was observed for operative delivery rates or neonatal outcomes. CONCLUSION: The pH of the vagina may not affect the length of the induction to vaginal delivery interval in women undergoing labor induction with vaginal misoprostol. Further research is required to determine factors that may influence the efficacy of vaginal misoprostol when used for labor induction.
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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 | 0.003 | 0.028 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".