A meta-analysis and systematic review of advanced maternal age patients in IVF
Bibliographic record
Abstract
BACKGROUND: There has been an increase in the average age of patients seeking fertility treatments over the past decades, with a significantly higher rate of advanced maternal age (AMA) patients undergoing IVF. It is unclear if different treatment strategies in IVF improve outcomes in AMA patients. OBJECTIVE AND RATIONALE: The aim of this systematic review was to assess the efficacy of different interventions employed in IVF in patients of AMA. SEARCH METHODS: A comprehensive search in Embase, Medline, and the Cochrane Library was performed. The search strategy included keywords related to IVF and AMA. We included all original peer-reviewed articles published in English, from January 1985 to September 2024, primarily designed to assess the efficacy of different interventions in IVF on clinical outcomes in AMA patients. Meta-analyses were performed for interventions for which sufficient randomized controlled trials existed. OUTCOMES: A total of 151 studies were included in the review. AMA was not consistently defined in all studies reviewed, although common to all studies was an age above 35 years. For the majority of evidence, there appeared to be no clear advantage to any stimulation protocol in AMA patients. There also appeared to be no advantage to any specific FSH medication, while a meta-analysis performed for the addition of LH to follicular stimulating hormone in stimulation demonstrated similar clinical pregnancy and live birth rates. No good evidence was found to support the routine implementation of ICSI in AMA patients, while a meta-analysis performed for assisted hatching (AH) pointed to decreased live birth rates with its implementation. Low-quality evidence demonstrated an increase in live birth rates with multiple embryos transferred with an increase in multiple pregnancies delivered. Finally, a meta-analysis performed for preimplantation genetic testing for aneuploidy (PGT-A) pointed to similar live birth rates as for no testing. WIDER IMPLICATIONS: This review failed to find an advantage to the routine implementation of treatment strategies such as specific stimulation protocols and gonadotropins, ICSI, and PGT-A, and a potential harmful effect for AH. Future high-quality randomized controlled trials are needed to affirm the majority of this review's conclusions. REGISTRATION NUMBER: PROSPERO ID: CRD42022335889.
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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 | 0.019 | 0.049 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.040 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".