Bibliographic record
Abstract
OBJECTIVE: There is conflicting literature to support a link between HIV and amenorrhea. Here, we conduct a meta-analysis to summarize the results from landmark studies in this area and shed light on this important clinical association. METHODS: Using a search of Ovid Medline and Embase, a total of 322 articles were screened for controlled matched observational studies of amenorrhea in premenopausal women living with HIV (WLWH). For inclusion, amenorrhea was defined as absence of menses for 3 months or longer. The meta-analysis used a random-effects model with an I2 calculated to assess heterogeneity. RESULTS: Six studies from 1996 to 2010 were included in our analysis for a total of 8925 women (6570 WLWH). There was a significant association between HIV status and amenorrhea (OR 1.68, P value 0.0001) without evidence of heterogeneity (I2: 0.0%). In the majority of studies, there was no significant difference in substance use, smoking, or socioeconomic status between WLWH and controls. Additionally, in the majority of studies, amenorrhea in the setting of low BMI was significantly more frequent in WLWH than controls. CONCLUSION: This meta-analysis provides a large population assessment of amenorrhea in HIV to suggest increased prevalence of menstrual disturbances in WLWH. It lends evidence suggestive that this relation is independent of substance use and socioeconomic status, but may be related to low BMI. Our findings reinforce the importance of routine assessment of reproductive health and time of last menstrual period as part of the health assessment of women, especially those living with HIV.
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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.011 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".