Comparison of Dinoprostone Vaginal Tablet and Vaginal Insert in Primigravid Women for Induction of Labor
Bibliographic record
Abstract
Background: Labor of induction by use of different drugs is generally preferred for avoiding complications with prolonged pregnancy. Dinoprostone vaginal gel or insert tablets are commonly used for inducing contractions similar to normal delivery contractions. The current study compares the effectiveness of dinoprostone vaginal tablet and dinoprostone vaginal insert in induction of labor for primigravid women. Methods: The participants of the prospective cohort observational study were primigravid women. BISHOP score was used as a tool for predicting patient who required labor induction. All the participants with BISHOP score less than 6 were given either dinoprostone vaginal tablet or dinoprostone vaginal insert for induction of labor. Chi-square statistical analysis was performed using SPSS, version 17.0. Results: A total of 135 patients were studied. Post-term pregnancy was found to be most common indication among studied patients. Labor induction was executed by using dinoprostone vaginal tablet and insert in 61% and 31% patients, respectively. Statistically, no significant differences were found in the rate of cesarean section among two treatment regimens on applying Chi-square analysis. On average, two dinoprostone tablets per patient as compared to one vaginal insert were used for labor induction. Conclusion: Dinoprostone vaginal tablet and vaginal insert both have similar efficacy in induction of labor to be used in primigravid women. J Clin Gynecol Obstet. 2018;7(2):52-56 doi: https://doi.org/10.14740/jcgo471w
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".