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Record W4411748681 · doi:10.1093/humrep/deaf097.995

P-689 Impact of dyslipidaemia on the probability of pregnancy in women undergoing IVF: a systematic review and meta-analysis

2025· review· en· W4411748681 on OpenAlexaboutno aff
Julia Κ. Bosdou, Panagiotis Anagnostis, Christos Venetis, E Katsika, P Ioannidou, Theoni B Tarlatzi, Kokkoni I Kiose, George T. Lainas, Leonidas Zepiridis, Grigoris Grimbizis, Efstratios M. Κolibianakis

Bibliographic record

VenueHuman Reproduction · 2025
Typereview
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisMedicinePregnancyObstetricsGynecologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Abstract Study question Is the probability of pregnancy different in women with and without dyslipidaemia undergoing in vitro fertilization (IVF)? Summary answer Women with dyslipidaemia demonstrate lower probability of achieving pregnancy compared to those without dyslipidaemia when undergoing IVF. What is known already Dyslipidaemia, including high concentrations of total cholesterol (TC) or low-density lipoprotein cholesterol (LDL-C) or triglycerides (TG), as well as low levels of high-density lipoprotein cholesterol (HDL-C) may affect fertility. Although the exact pathogenetic mechanisms have not been fully elucidated, dyslipidaemia-induced endothelial dysfunction may be identified. However, its specific impact on IVF outcomes remains inadequately studied. Study design, size, duration This systematic review and meta-analysis included cohort studies which evaluated the impact of dyslipidaemia on IVF outcomes. A comprehensive literature search of PubMed, Scopus and Google Scholar was conducted until January 2024. The primary outcome was live birth rates, while secondary outcomes included clinical pregnancy, cumulative live birth and miscarriage rates. Participants/materials, setting, methods Data from identified studies were independently extracted by two reviewers, including demographic, methodological and clinical information. Study quality was assessed using the Newcastle-Ottawa Scale. Statistical heterogeneity was evaluated using the I² statistic, and meta-analyses were conducted using random- or fixed-effects models, depending on the presence of significant heterogeneity. Results were expressed as relative risks (RR) or weighted mean differences (WMD) with 95% confidence intervals (CIs) and were analysed using an intention-to-treat principle. Main results and the role of chance Six retrospective studies (n = 11,685) published between 2018 and 2024 with moderate-to-low risk of bias were analysed. Sample size ranged from 127 to 3,372 patients. • Clinical pregnancy rates were lower in patients with dyslipidaemia compared to those without (RR 0.85, 95% CI 0.74–0.99; random effects model; I² 73.4%; five studies, 5,477 patients). • Dyslipidaemia was associated with higher miscarriage rate (RR 1.24, 95% CI 1.01–1.53; fixed effects model, I²: 0%; four studies, 5,019 patients) compared with normal lipid profile. • Patients with dyslipidaemia had lower live birth rates compared to those without (RR 0.82, 95% CI 0.68–0.99; random effects model; I² 89.4%; three studies, 4,972 patients). • No differences were noted in cumulative live birth rates between the two groups (RR 0.98, 95% CI 0.94–1.02; fixed effects model, I² 0%; two studies, 5,834 patients). Limitations, reasons for caution This analysis included a limited number of retrospective studies with moderate-to-low risk of bias due to methodological limitations. Considerable heterogeneity in terms of the population studied, criteria for dyslipidaemia definition and embryo transfer types necessitates cautious interpretation of findings. Wider implications of the findings This systematic review and meta-analysis is the first performed so far on this topic, showing decreased pregnancy outcomes in women with dyslipidaemia compared to those without. This underscores the importance of lipid profile screening before infertility treatment and necessitates prompt lifestyle intervention to reduce this effect. Trial registration number No

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.451
Threshold uncertainty score0.789

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0080.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.134
GPT teacher head0.388
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

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Citations1
Published2025
Admission routes1
Has abstractyes

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