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Record W4415902040 · doi:10.1093/jsxmed/qdag063.027

(027) Genitourinary Syndrome of Lactation: Patient-Reported Survey of Symptom Burden, Care Gaps, and Treatment Utilization in the Postpartum Period

2025· article· en· W4415902040 on OpenAlexaff
Sara Perelmuter, A Drian, S. J., M Davide, Cameron Stokes, Claire Sandler B, Daniel Kurtz A, Temiloluwa Faokunla, Mohammed farith.K Kathiravan.N, Alexandra Payne, Rachael D. Sussman, Jill M. Krapf, Rachel Rubin

Bibliographic record

VenueThe Journal of Sexual Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsUniversity of OttawaMcMaster University
Fundersnot available
KeywordsGenitourinary systemPostpartum periodPopulationPeriod (music)MEDLINE

Abstract

fetched live from OpenAlex

Abstract Introduction Despite the high prevalence of lactation in the postpartum period, the genitourinary consequences of this physiologic state remain underrecognized. The hypoestrogenic and hypoandrogenic milieu induced by lactation can give rise to genitourinary symptoms such as vaginal dryness, dyspareunia, urinary incontinence, and sexual dysfunction-collectively termed Genitourinary Syndrome of Lactation (GSL). These symptoms mirror aspects of the genitourinary syndrome of menopause but remain largely absent from postpartum care algorithms. Given their substantial impact on sexual health and quality of life, GSL represents an overlooked yet modifiable contributor to postpartum morbidity, warranting attention from providers in sexual medicine, urology, and gynecology. Objective To characterize genitourinary symptoms during lactation, assess quality-of-life impact, and identify gaps in care and treatment access among postpartum individuals. Methods We conducted a cross-sectional survey study from March to May 2025 using an anonymous, 30-item online questionnaire disseminated via social media and postpartum support groups. Eligible participants were postpartum individuals up to 24 months after delivery. Exclusion criteria included nulliparity, current pregnancy, prior genitourinary disorders, and incomplete responses. Participants were stratified into exclusive, non-exclusive, and non-lactating groups. Primary outcomes included self-reported genitourinary symptoms, treatments offered and utilized, and quality of life scores (0–100). Quantitative data were analyzed using descriptive statistics, chi-square tests, and multinomial logistic regression (α = 0.05). Qualitative data were assessed using thematic analysis of open-text responses. Results Among 1446 respondents (median age 36 years), 47.65% were exclusively lactating, 14.66% mixed feeding, and 37.69% non-lactating. Vaginal dryness was the most common symptom (exclusive: 100%; non-exclusive: 100%; non-lactating: 78.72%), followed by dyspareunia (57.04%, 50.00%, and 36.33%, respectively). Quality of life was significantly affected; 76.34% of those exclusive lactating reported difficulty with sexual activity. Despite high symptom burden, 63.81% were never asked about genitourinary symptoms by their provider, and 28.42% were offered treatment. Awareness of safe, lactation-compatible therapies was limited; 60.03% were unaware treatments existed. Vaginal estrogen and pelvic floor physiotherapy were the most commonly offered treatments but were recommended to fewer than 30% of symptomatic individuals. Significant associations were observed between lactation status and menstruation onset, symptom presence, and treatment patterns (p < 0.001). Qualitative responses emphasized severe pain, disrupted intimacy, and lack of clinical support. Conclusions Genitourinary symptoms during lactation are common, under-recognized, and insufficiently treated, with significant implications for postpartum quality of life. Clinical care models should incorporate routine screening for genitourinary symptoms, increase provider education on lactation-safe treatments, and improve patient access to multidisciplinary interventions. Disclosure 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.153
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.068
GPT teacher head0.337
Teacher spread0.268 · 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 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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