The effectiveness of hysteroscopy in improving pregnancy rates in subfertile women without other gynaecological symptoms: a systematic review
Bibliographic record
Abstract
BACKGROUND: Although hysteroscopy is frequently used in the management of subfertile women, a systematic review of the evidence on this subject is lacking. METHODS: We summarized and appraised the evidence for the benefit yielded by this procedure. Our systematic search was limited to randomized and controlled studies. The QUOROM and MOOSE guidelines were followed. Language restrictions were not applied. RESULTS: We identified 30 relevant publications. Hysteroscopic removal of endometrial polyps with a mean diameter of 16 mm detected by ultrasound doubles the pregnancy rate when compared with diagnostic hysteroscopy and polyp biopsy in patients undergoing intrauterine insemination, starting 3 months after the surgical intervention [relative risk (RR) = 2.3; 95% confidence interval (CI): 1.6-3.2]. In patients with one fibroid structure smaller than 4 cm, there was a marginally significant benefit from myomectomy when compared with expectant management (RR = 1.9; 95% CI: 1.0-3.7). Hysteroscopic metroplasty for septate uterus resulted in fewer pregnancies in patients with subfertility when compared with those with recurrent pregnancy loss (RR = 0.7; 95% CI: 0.5-0.9). Randomized controlled studies on hysteroscopic treatment of intrauterine adhesions are lacking. Hysteroscopy in the cycle preceding a subsequent IVF attempt nearly doubles the pregnancy rate in patients with at least two failed IVF attempts compared with starting IVF immediately (RR = 1.7; 95% CI: 1.5-2.0). CONCLUSIONS: Scarce evidence on the effectiveness of hysteroscopic surgery in subfertile women with polyps, fibroids, septate uterus or intrauterine adhesions indicates a potential benefit. More randomized controlled trials are needed before widespread use of hysteroscopic surgery in the general subfertile population can be justified.
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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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".