How fertility preservation guidelines have progressed worldwide: Potential implications and inspiration
Bibliographic record
Abstract
Abstract To summarize fertility preservation (FP) guidelines and consensus provided by medical facilities worldwide. Five reference databases (PubMed/Embase, China BioMedical Literature Database, ClinicalKey, Wanfang Data, and China Knowledge Resource Integrated) and 7 guideline databases (Guideline International Network, National Collaborating Centre for Women's and Children's Health, National Guideline Clearinghouse, The National Institute for Health and Care Excellence, Scottish Intercollegiate Guidelines Network, New Zealand Guideline Group, and Canadian Medical Association infobase) were searched. Official websites of societies were searched to find relevant guidelines and consensus, and guidelines and published systematic reviews and consensus were reviewed from inception through May 2021. A literature search was performed regarding guidance offered in professional facilities, and 304 records (including 4 in Chinese) of existing guidelines for full-text review were found. Moreover, 55 guidelines were identified after a manual search. The literature review demonstrated that FP guidance and options were unevenly distributed worldwide for women who wanted to post-pone pregnancy or had impaired fertility after gonadal toxicity. With promising cancer survival rates and diversified family decisions, more attention should be paid to the improvement and update of accessible guidelines and regulatory infrastructure to inform patients about the available options and empower them to make informed choices. Restrictions to such services can be gradually eased due to the efficacy and safety of certain FP techniques for the right candidates to initiate pregnancy conception.
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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 | 0.069 | 0.249 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.018 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".