The impact of laparoscopic ovarian drilling on AMH and ovarian reserve: a meta-analysis
Bibliographic record
Abstract
Abstract Laparoscopic ovarian drilling (LOD) has been widely used as an effective treatment of anovulatory women with polycystic ovarian syndrome (PCOS). However, there has been a growing concern over a possible damaging effect of this procedure on ovarian reserve. The objective of this study was to investigate the hypothesis that LOD compromises ovarian reserve as measured by post-operative changes in circulating anti-Müllerian hormone (AMH). This meta-analysis included all cohort studies as well as randomised controlled trials (RCTs) investigating serum AMH concentrations and other ovarian reserve markers in women with PCOS undergoing LOD. Various databases were searched including MEDLINE, EMBASE, Dynamed Plus, ScienceDirect, TRIP database, ClinicalTrials.gov and Cochrane Library from January 2000 to December 2016. Sixty studies were identified, of which seven were deemed eligible for this review. AMH data were extracted from each study and entered into the RevMan software to calculate the weighted mean difference (WMD) between pre- and post-operative values. Pooled analysis of all studies (n = 442) revealed a statistically significant decline in serum AMH concentration after LOD (WMD −2.13 ng/mL; 95% confidence interval (CI) −2.97 to −1.30). Subgroup analysis based on duration of follow-up, AMH kit, laterality of surgery and amount of energy applied during LOD consistently showed a statistically significant fall in serum AMH concentration. In conclusion, although LOD seems to markedly reduce circulating AMH, it remains uncertain whether this reflects a real damage to ovarian reserve or normalisation of the high pre-operative serum AMH levels. Further long-term studies on ovarian reserve after LOD are required to address this uncertainty.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.041 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".