Comparing the efficacy of vaginal micronized progesterone gel and capsule for prevention of preterm birth in singleton pregnancies with short cervical length at midtrimester: an indirect comparison meta-analysis
Bibliographic record
Abstract
Objective: To evaluate the effectiveness of vaginal progesterone in preventing preterm birth in women with a singleton gestation and short cervical length and to determine which of the two formulations, micronized progesterone vaginal capsule versus vaginal gel containing micronized progesterone, is more effective for preventing preterm birth. Data sources: A systematic search was performed in the following databases: EMBASE, PubMed (MEDLINE), The Cochrane Library, and the Clinical Trials Registry ( clinicaltrials.gov ). Study eligibility criteria: Randomized controlled trials (RCTs), prospective and retrospective observational studies were included. We searched for progesterone administration to prevent preterm birth in asymptomatic women with a shortened cervix (<25 mm) measured by ultrasound in the second trimester of singleton pregnancy. Study appraisal and synthesis methods: Assessments of the risk of bias of RCTs were performed by applying the Cochrane Collaboration’s Risk of Bias Tool; non-randomized control trials were evaluated with the Newcastle–Ottawa Scale (NOS). The primary outcome was preterm birth ≤33 weeks of gestation. Pooled relative risks (RR) and 95% CI’s were calculated for dichotomous outcomes. Heterogeneity of treatment effect was assessed with the I 2 statistic. We pooled results of the primary outcome for individual studies using a random-effect model. We then performed a network meta-analysis to pool indirect comparisons between the two formulations (gel vs capsule). This analysis was performed using the network meta-analysis package within the R environment. Results: Five studies met the inclusion criteria (4 RCTs, one cohort study) including 1,048 women. The meta-analysis demonstrated that vaginal micronized progesterone significantly reduces preterm birth risk, Risk Ratio = 0.63; 95% CI, 0.48–0.82; p = 0.0006; with no heterogeneity between the studies: I 2 = 0%. In the network meta-analysis, no significant difference was demonstrated (OR = 0.85; 95% CI, 0.43–1.69) between the effect of the two formulations of vaginal micronized progesterone (vaginal gel versus vaginal capsules) on the risk of PTB. Conclusion: Vaginal progesterone is associated with a decreased risk of premature birth in women with a shortened cervix in the second trimester of pregnancy. No differences were found between vaginal micronized progesterone in gel or capsule formulations. Systematic Review Registration: PROSPERO, identifier CRD42020165198.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".