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Record W4410242726 · doi:10.3390/life15050758

The Relationship Between Obesity, Bariatric Surgery, and Infertility: A Systematic Review

2025· review· en· W4410242726 on OpenAlexaboutno aff
Charalampos Voros, Antonia Varthaliti, Kyriakos Bananis, Despoina Mavrogianni, Diamantis Athanasiou, Antonia Athanasiou, Aikaterini Athanasiou, Anthi-Maria Papahliou, Constantinos G. Zografos, Panagiota Kondili, Menelaos Darlas, Ioannis Papapanagiotou, Maria Anastasia Daskalaki, Marianna Theodora, Panagiotis Antsaklis, G. Daskalakis, D. Loutradis

Bibliographic record

VenueLife · 2025
Typereview
Languageen
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGestational diabetesPregnancyInfertilitySystematic reviewObservational studyObesityWeight lossObstetricsCochrane LibraryRandomized controlled trialGynecologyMEDLINEGestationSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Obesity is a complicated, chronic condition that has a major impact on reproductive health, leading to infertility, anovulation, and poor pregnancy outcomes. It alters the hypothalamic-pituitary-ovarian (HPO) axis, promotes insulin resistance, and causes persistent low-grade inflammation, all of which result in hormonal abnormalities that compromise normal ovarian function. Because standard weight loss procedures frequently fail to provide significant and long-term reproductive benefits, bariatric surgery is becoming increasingly popular as a therapeutic option for obese women trying to conceive. However, continuous research is being conducted to determine the degree of its advantages and potential hazards to fertility and pregnancy outcomes. METHODS: This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards and entered into the PROSPERO database. Comprehensive searches in the PubMed, Scopus, and Web of Science databases turned up relevant studies. Studies that examined the effects of bariatric surgery on female fertility, ovulatory function, pregnancy rates, and neonatal outcomes were considered. Methodological quality and risk of bias were evaluated using the Newcastle-Ottawa Scale (NOS) for observational studies and the Cochrane Risk of Bias Tool for randomized controlled trials. RESULTS: This review comprised 34 studies. More than 75% of the studies analyzed showed improvements in ovulatory function, monthly regularity, or spontaneous pregnancy after bariatric surgery. Post-surgical pregnancies are related to a lower incidence of gestational diabetes, hypertension, and macrosomia. However, several studies raised concerns about nutritional inadequacies and the possibility of small-for-gestational-age newborns, particularly following Roux-en-Y gastric bypass. Studies suggest delaying conception for 12 to 18 months after surgery to reduce nutritional hazards and improve pregnancy outcomes. Variability in study design, follow-up duration, and surgical methods reduces the generalizability of findings, emphasizing the importance of uniform research protocols. CONCLUSIONS: Bariatric surgery is a highly effective treatment for increasing fertility and pregnancy outcomes in obese women, particularly those with PCOS. However, rigorous preconception planning, postoperative nutritional monitoring, and multidisciplinary follow-up are required to reduce the related hazards. Future research should concentrate on long-term reproductive outcomes, standardizing fertility assessment criteria, and improving clinical guidelines for managing post-bariatric pregnancies. These findings support the incorporation of bariatric surgery into fertility treatment regimens for obese women, and they may shape future revisions to clinical guidelines on reproductive care following weight loss surgery.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.008
Bibliometrics0.0090.010
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.103
GPT teacher head0.357
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 source (direct Gemma or distilled Codex), 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".

Quick stats

Citations13
Published2025
Admission routes1
Has abstractyes

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