Optimizing intrauterine insemination: A systematic review and meta‐analysis of the effectiveness and safety of clinical treatment add‐ons
Bibliographic record
Abstract
Abstract Introduction Intrauterine insemination (IUI) is one of the most widespread fertility treatments. However, IUI protocols vary significantly amongst fertility clinics. Various add‐on interventions have been proposed to boost success rates. These are mostly chosen arbitrarily or empirically. The aim of this systematic review and meta‐analysis is to assess the effectiveness and safety of add‐on interventions to the standard IUI protocol and to provide evidence‐based recommendations on techniques used to optimize the clinical outcomes of IUI treatment. Material and Methods Systematic review and meta‐analyses were performed in accordance with PRISMA guidelines. A computerized literature search was performed from database inception to May 2023. Randomized controlled trials (RCTs) were included reporting on couples/single women undergoing IUI with any protocol for any indication using partner's or donor sperm. A meta‐analysis based on random effects was performed for each outcome and add‐on. Three authors independently assessed the trials for quality and risk of bias and overall certainty of evidence. Uncertainties were resolved through consensus. Primary outcomes were ongoing pregnancy rate (OPR) or live birth rate (LBR) per cycle/per woman randomized. Registration number PROSPERO: CRD42022300857. Results Sixty‐six RCTs were included in the analysis (16 305 participants across 20 countries). Vaginal progesterone as luteal phase support in stimulated cycles was found to significantly increase LBR/OPR (RR 1.37, 95% CI 1.09–1.72, I 2 = 4.9%) (moderate/low certainty of the evidence). Endometrial scratch prior/during stimulated IUI cycles may increase LBR/OPR (RR 1.44, 95% CI 1.03–2.01, I 2 = 1.8%), but evidence is very uncertain. Results from two studies suggest that follicular phase ovarian stimulation increases LBR/OPR (RR 1.39, 95% CI 1.00–1.94, I 2 = 0%) (low certainty of evidence). No significant difference was seen for the primary outcome for the other studied interventions. Conclusions The findings of this systematic review and meta‐analysis suggest that vaginal luteal phase progesterone support probably improves LBR/OPR in stimulated IUI treatments. In view of moderate/low certainty of the evidence more research is needed for solid conclusions. Further research is also recommended for the use of endometrial scratch and ovarian stimulation. Future studies should report on results according to subfertility background as it is possible that different add‐ons could benefit specific patient groups.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.003 |
| Bibliometrics | 0.001 | 0.003 |
| 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".