COMPARATIVE STUDY OF INTRACERVICAL CATHETER AND TABLET PROSTAGLANDIN FOR INDUCTION OF LABOUR IN POSTDATED PREGNANCY
Bibliographic record
Abstract
Background: Induction of labour is an essential obstetric intervention for postdated pregnancies (?41 weeks), with higher perinatal risks. There are several methods of induction, including pharmacological agents such as prostaglandins and mechanical devices such as intracervical catheters. Their relative efficacy is controversial. Methods: This randomized controlled trial was undertaken at Qazi Hussain Ahmad Medical Complex, Nowshera, between March 25 and September 25, 2023, among 76 postdated pregnant women. Randomization was done to Group A (n=38), who were given an intracervical Foley catheter, and Group B (n=38), who were given 3 mg vaginal dinoprostone. The successful labour induction within 24 hours was the primary outcome. Data was analyzed with SPSS. Results: Successful labour induction was much greater in the prostaglandin group (68.4%) than in the catheter group (42.1%) (p=0.021). Prostaglandins allowed earlier cervical ripening and a shorter induction-delivery interval. They did, however, carry a greater risk of uterine hyperstimulation, for which vigilance and monitoring are necessary. Both procedures were associated with good maternal and neonatal outcomes. Conclusion: Prostaglandins were more effective in the induction of labour than intracervical catheters. Nevertheless, mechanical techniques are still an acceptable alternative, especially in women with contraindications to pharmacologic induction. The method should be tailored to the patient, taking efficacy as well as safety into consideration. Larger sample size studies should be conducted to look at long-term maternal and neonatal outcomes.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".