Associations of Early Prolonged Secondary Amenorrhea in Women With and Without HIV
Bibliographic record
Abstract
Background: The menstrual cycle is a critical indicator of women's health. Early prolonged secondary amenorrhea increases risks for morbidity and mortality. Menstrual cycle research in women with HIV is inconsistent and often lacks an adequate comparison sample. We aimed to determine whether women with HIV have a higher lifetime prevalence of amenorrhea and whether this is independently associated with HIV and/or other biopsychosocial variables. Methods: With data from 2 established HIV cohorts, participants assigned female at birth were eligible if aged ≥16 years, not pregnant/lactating, and without anorexia/bulimia nervosa history. Amenorrhea was defined by self-reported history of (1) no menstrual flow for ≥12 months postmenarche not due to pregnancy/lactation, medications, or surgery or (2) early menopause or premature ovarian insufficiency. Multivariable logistic regression models explored biopsychosocial covariates of amenorrhea. Results: Overall, 317 women with HIV (median age, 47.5 years [IQR, 39.2-56.4]) and 420 women without HIV (46.2 [32.6-57.2]) were included. Lifetime amenorrhea was significantly more prevalent among women with HIV than women without HIV (24.0% vs 13.3%). In the multivariable analysis, independent covariates of amenorrhea included HIV (adjusted odds ratio, 1.70 [95% CI, 1.10-2.64]), older age (1.01 [1.00-1.04]), White ethnicity (1.92 [1.24-3.03]), substance use history (6.41 [3.75-11.1]), and current food insecurity (2.03 [1.13-3.61]). Conclusions: Nearly one-quarter of women with HIV have experienced amenorrhea, and this is associated with modifiable risk factors, including substance use and food insecurity. Care providers should regularly assess women's menstrual health and advocate for actionable sociostructural change to mitigate risks.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".