Zygote intrafallopian transfer (ZIFT)
Bibliographic record
Abstract
The ability of tubal transfer of embryos to produce pregnancy and live birth was first demonstrated in a non-human primate model by Balmaceda et al.1 Soon thereafter, Devroey et al described the first successful zygote intrafallopian transfer (ZIFT) in humans.2 Early reports on ZIFT were encouraging, showing superior results over uterine embryo transfer (UET), mainly for the treatment of male factor and unexplained infertility. Despite its technical complexity and high cost compared with UET, ZIFT was gradually incorporated into clinical practice. In 1991, ZIFT comprised 6.4% of all ART cycles in the US and Canada.3 Subsequently, with the publication of randomized clinical trials that failed to show a clear advantage for ZIFT compared with UET, along with the introduction of intracytoplasmic sperm injection (ICSI) as a powerful clinical tool for the treatment of male factor infertility,4 the use of ZIFT has declined (Fig 49.1). In 1996, ZIFT comprised only 1.8% of ART cycles in the US, corresponding to 1,200 procedures.5 Nevertheless, throughout 1989-96, delivery rates per retrieval in North America have been consistently superior with ZIFT compared with UET (Fig 49.2).3,5-11 In 1996, for example, 30.9% of all ZIFT cycles resulted in delivery, Fig 49.1 Percentage of ZIFT of all ART cycles in the United States and Canada, 1989-1996* (data from references 3, 5-11). * 1996, US only Fig 49.2 Delivery rates per retrieval after IVFET and IVF-ZIFT in the US and Canada, 1989-1996* (data from references 3, 511). * 1996, US only compared with only 26% of retrievals followed by UET. It should be stated, however, that information from national statistics is difficult to evaluate. It is compiled from data originating from different operators and laboratories, and from heterogeneous patient profiles that may differ by age distributions, diagnostic categories, treatment protocols, and the number and stage of zygotes/embryos transferred per patient. Nevertheless, the consistently higher delivery rates observed with ZIFT simply suggest that “there is something about ZIFT” that should be explored further. Our objective in this chapter is to summarize the world experience with ZIFT, and to try to clarify the current role and indications for ZIFT among the assisted reproductive technologies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.006 |
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".