Reply: Intravenous immunoglobulin and idiopathic secondary recurrent miscarriage: methodological problems
Bibliographic record
Abstract
Sir, We would like to address and clarify Dr Clark's comments. This study was designed to show a treatment effect, based on prior publications which suggested evidence of benefit. Since this recent randomized controlled trial (RCT) (Stephenson et al., 2010), the largest to date, found that intravenous immunoglobulin (IVIG) was of no significant benefit, the next step would be an equivalency RCT, although obtaining adequate funding would be difficult due to the large sample size required. Our RCT revealed that despite a history of 3–16 consecutive miscarriages, a clinical live birth rate of 94% can be achieved with preconception care and close first trimester monitoring in women with idiopathic secondary recurrent miscarriage, and without the addition of experimental drugs or blood derivatives. IVIG, a fractionated blood product, is expensive and not without risk, therefore, its use should be based on the best evidence available. With our meta-analysis, no significant effect of treatment with IVIG was found, which was confirmed by a subsequent systematic review of IVIG for recurrent miscarriage (Ata et al., 2011). In addition to IVIG, a systematic review of randomized trials found no significant beneficial effect of paternal or third party mononuclear cell immunization, and trophoblast membranes over placebo in improving the live birth rate in idiopathic recurrent miscarriage (Porter et al., 2006). Presently, mononuclear cell immunization requires Food and Drug Administration approval under an investigational new drug application.
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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 | 0.041 | 0.273 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.024 | 0.027 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".