Healthy Singleton Pregnancies From Restorative Reproductive Medicine (RRM) After Failed IVF
Bibliographic record
Abstract
Objectives: To determine the live birth rate for patients who chose to undergo treatment with Restorative Reproductive Medicine (RRM) after previous IVF (includes ICSI). To look at birth outcomes with RRM after IVF, particularly rates of twin and higher order pregnancies, premature birth, low birth weight and predicted cost savings achieved with RRM. Setting: Two outpatient clinics in Ireland providing advanced RRM treatment of infertility. Materials and methods: All patients presenting between January 2004 and January 2010, with a history of infertility and previous IVF treatment were included if they proceeded beyond the initial consultation and began treatment. Results: 403 patients met the study criteria, with 74 live births. These women had significant negative predictive characteristics for successful outcome including: advanced reproductive age (average 37.2 years), an average of 5.8 years of infertility with 2.1 (range 1-9) previous IVF attempts, with only 5% having achieved success with ART. Despite these undesirable prognostic indicators, the overall RRM live birth rate was 32.1% (crude 18.4%). Women aged 35 – 38 had a live birth rate of 37.5% (crude 23.6%) and older women over 40 had a live birth rate of 27.4% (crude 16.0%). The average birth weight was 3374g (7lb 7oz) with 92% being born at 37+ weeks and no very low birth weight babies. There was only one twin pregnancy in the study population; the calculated health care savings for avoidable multiple pregnancies in these patients was estimated at £205 672 (USD$284 915). Conclusions: Patients who have already tried IVF can achieve comparable live birth outcomes with RRM compared to another cycle of IVF. RRM has a low risk of twin or multiple births, and very good neonatal outcomes with predicted cost savings to the health care system.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".