A Systematic Review of Assisted and Third-Party Reproduction Guidelines Regarding Management of Donors
Bibliographic record
Abstract
Abstract Background: Gamete and embryo donors face complex challenges affecting their health and quality of life. Healthcare providers need to access well-structured, evidence-based, and needs-based guidance to care for gamete and embryo donors. Therefore, this systematic review aimed to synthesize current assisted and third-party reproduction guidelines regarding management of donors. Methods: The databases of ISI, PubMed, and Scopus and websites of organizations related to the assisted reproduction were searched using the keywords of "third party reproduction", "gamete donation", "embryo donation", "guidelines", "committee opinion", and "best practice", without time limit up to July 2023. All the clinical or ethical guidelines and best practice statements regarding management for gamete and embryo donors, written in the English language were included in the study. Quality assessment was carried using AGREE II tool. Included documents were reviewed and extracted data were qualitatively synthesized. Results: In this systematic review 14 related documents were reviewed of which eight were guidelines, three were practice codes and three were committee opinions. Five documents were developed in the United States, three in Canada, two in the United Kingdom, one in Australia, and one in Australia and New Zealand. Also, two guidelines developed by the European Society of Human Reproduction and Embryology were found. Management provided for donors were classified into four categories including screening, counseling, information provision, and ethical considerations. Conclusion: In order to inform current practices by developing evidence-based guidelines, it is needed to conduct robust and well-designed research studies to fill the knowledge gap about gamete and embryo donors' needs, psychosocial and long-term effects of donation on donors, their follow-up cares, and ethical aspects of donation.
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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 | 0.037 | 0.150 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.020 | 0.019 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".