Preterm deliveries that result from multiple pregnancies associated with assisted reproductive technologies in the USA: a cost analysis
Bibliographic record
Abstract
PURPOSE OF REVIEW: Simultaneous transfer of multiple embryos in an assisted reproductive technology (ART) cycle results in a high rate of multiple pregnancy. Besides the medical complications associated with multiple pregnancy, the financial burden of the resultant preterm infants is also substantial. The current review evaluates the costs associated with the care of preterm infants that are born as a result of ART-associated multiple pregnancies. RECENT FINDINGS: In 2006, 30% of all ART live births were multiple infant deliveries in the USA. This resulted in 48% of all ART neonates being the product of a multiple infant delivery. In the same year, 62% of ART twins and 97% of ART triplets were delivered preterm, corresponding to approximately 17 000 infants. The Board of Health Sciences Policy has estimated the mean cost of each preterm infant to be US$ 51 600. Therefore, the financial burden of ART-associated preterm deliveries is estimated to be approximately US$ 1 billion annually. This figure has remained essentially unchanged between 2001 and 2006, despite decreasing number of embryos transferred, due to increasing total number of ART cycles performed. SUMMARY: Preterm deliveries that result from ART-associated multiple pregnancies add a substantial burden to overall US healthcare expenditure annually. Policies limiting the number of embryos transferred should be considered with a perspective to increase elective single embryo transfers.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".