Attribution of menopause symptoms in human immunodeficiency virus-infected or at-risk drug-using women
Bibliographic record
Abstract
In Brief Objective: To examine the relationship of human immunodeficiency virus (HIV) and attribution of menopausal symptoms. Design: Peri- and postmenopausal women participating in a prospective study of HIV-infected and at-risk midlife women (the Ms. Study) were interviewed to determine whether they experienced hot flashes and/or vaginal dryness and to what they attributed these symptoms. Results: Of 278 women, 70% were perimenopausal; 54% were HIV-infected; and 52% had used crack, cocaine, heroin, and/or methadone within the past 5 years. Hot flashes were reported by 189 women and vaginal dryness was reported by 101 women. Overall, 69.8% attributed hot flashes to menopause and 28.7% attributed vaginal dryness to menopause. In bivariate analyses, age 45 years and older was associated with attributing hot flashes and vaginal dryness to menopause, and postmenopausal status and at least 12 years of education were associated with attributing vaginal dryness to menopause, but HIV status was not associated with attribution to menopause. In multivariate analysis, significant interactions between age and menopause status were found for both attribution of hot flashes (P = 0.019) and vaginal dryness (P = 0.029). Among perimenopausal women, older age was independently associated with attribution to menopause for hot flashes (adjusted odds ratio = 1.2, 95% CI: 1.1-1.4, P = 0.001) and vaginal dryness (adjusted odds ratio = 1.3, 95% CI: 1.1-1.6, P = 0.011). None of the tested factors were independently associated with attribution to menopause among postmenopausal women. Conclusion: Tailored health education programs may be beneficial in increasing the knowledge about menopause among HIV-infected and drug-using women, particularly those who are perimenopausal. In a cross-sectional study of human immunodeficiency virus-infected and drug-using middle-aged women of low socioeconomic status, it was found that 69.8% of women with hot flashes attributed the hot flashes to menopause and 28.7% of women with vaginal dryness attributed the symptom to menopause. Postmenopausal status and having at least 12 years of education were associated with attributing vaginal dryness to menopause.
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 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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".