Intravenous immunoglobulin for patients with unexplained recurrent implantation failure: a 6-year single center retrospective review of clinical outcomes
Bibliographic record
Abstract
The effectiveness of intravenous immunoglobulin (IVIg) for patients with unexplained recurrent implantation failure (uRIF) remains debated. We retrospectively analysed outcomes of uRIF patients treated with IVIg compared to a separate control uRIF cohort within our center (01/2014-12/2021). Primary outcomes included live birth, miscarriage, or transfer failure. We documented IVIg side effects and maternal/fetal outcomes. Logistic regression analysis was used to assess for association of IVIg exposure with outcomes and adjust for confounders. The study included 143 patients, with a 2:1 ratio of controls to patients receiving IVIg treatment. Patient characteristics were similar between groups. There was higher live birth rate (LBR) in patients receiving IVIg (32/49; 65.3%) compared to controls (32/94; 34%); p < 0.001). When stratifying patients into moderate and severe uRIF (respectively 3-4 and [Formula: see text] 5 previous good quality blastocyst transfer failures), only patients with severe uRIF benefited from IVIg (LBR (20/29 (69%) versus 5/25 (20%) for controls, p = 0.0004). In the logistic regression analysis, IVIg was associated with higher odds of live birth (OR 3.64; 95% CI 1.78-7.67; p = 0.0004). There were no serious adverse events with IVIg. IVIg can be considered in well selected patients with [Formula: see text] 5 previous unexplained, high quality blastocyst transfer failures. A randomized controlled trial is needed to confirm these findings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".