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Hormone Replacement Therapy Use After Bilateral Salpingo-oophorectomy for Severe Endometriosis

2025· article· en· W4408936331 on OpenAlexaff
A. Zeccola, Isabel Janmey, Ling Wang, H.‐Erich Wichmann, Caroline Heres, Nicole Donnellan, H. Pietragallo

Bibliographic record

VenueObstetrics and Gynecology · 2025
Typearticle
Languageen
FieldMedicine
TopicEndometriosis Research and Treatment
Canadian institutionsWomen's Health Research Institute
Fundersnot available
KeywordsEndometriosisMedicineHormone replacement therapy (female-to-male)Hormone therapyGynecologySurgeryInternal medicineCancerBreast cancer

Abstract

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INTRODUCTION: Definitive surgical management of severe endometriosis involves excision with hysterectomy and bilateral salpingo-oophorectomy (BSO). Women who are less than 50 years old at the time of BSO have an increased morbidity, including risk of cardiovascular disease, osteoporosis, sexual dysfunction, dementia, and overall mortality. These risks are mitigated by hormone replacement therapy (HRT) use through the average age of menopause. Previous studies show relatively low rates of HRT postoperatively when BSO is performed for all benign indications. HRT use specifically in patients with severe endometriosis is not well studied, and its rate may be lower given perceptions about risks, lack of standard prescribing guidelines, and concerns about endometriosis recurrence. OBJECTIVE: We aim to investigate the rate of HRT use among patients undergoing BSO for severe endometriosis and hypothesize that preoperative counseling increases HRT use postoperatively. Secondarily, we aim to describe rates of recurrent endometriosis symptoms and surgery in those taking postoperative HRT. METHODS: This retrospective cohort study compares patients who used HRT to those who did not after definitive surgical management of severe endometriosis. Patients were included if they were between the ages of 18 and 50 and rendered surgically menopausal for severe endometriosis. Procedures were performed by fellowship-trained minimally invasive gynecologic surgeons at an urban, tertiary care referral center between January 2016 and December 2020. We included HRT use of any systemic estrogen/progesterone combination for any postoperative duration in the HRT group. We excluded patients with medical contraindications to HRT or incomplete records. RESULTS: 140 patients met inclusion criteria. 70% (n=98) used systemic HRT at some point postoperatively, of whom the majority (58.2%, n=57) used systemic estrogen alone, whereas 41.8% (n=41) used estrogen and progesterone. Patients who used HRT were more likely to be younger (38.6±4.9 vs. 40.8±5.8 years, p=0.022) and nulliparous (54.1% vs. 33.3%, p=0.024) compared to patients who did not use HRT. Patients who used HRT were more likely to have been counseled by their surgeon about HRT (93.9% vs. 54.8%, p<0.001) and more likely to be referred to a menopause HRT specialist (69.4% vs. 23.8%, p<0.001). In our multivariable analysis, counseling by surgeon at any time remained a predictor of increased HRT use (OR=4.6, 95% CI 1.1–18.9) when controlling for postoperative menopausal symptoms and referral to a menopause HRT specialist. There were no differences in recurrence of endometriosis symptoms (21.4% vs. 16.7%) or repeat surgery (19% vs. 14%) between patients who did versus did not use HRT. CONCLUSIONS: Patients with severe endometriosis who undergo definitive surgical management with bilateral oophorectomy should be prescribed HRT to mitigate the long-term health effects of surgical menopause. A discussion of HRT perioperatively should be included in the surgeon’s counseling, and when feasible patients should be offered referral to specialists in menopause management. HRT use appears to pose minimal risk of recurrent endometriosis surgery, although more studies are needed (Tables 1 and 2).

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.000

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 head0.025
GPT teacher head0.305
Teacher spread0.279 · 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 designObservational
Domainnot available
GenreEmpirical

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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Citations0
Published2025
Admission routes1
Has abstractyes

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