The Clinical Implications of High Rates of Intimate Partner Violence Against HIV-Positive Women
Bibliographic record
Abstract
INTRODUCTION: Intimate partner violence (IPV) is associated with increased risk of HIV infection among women, however, whether IPV affects outcomes after HIV infection is uncertain. We assess the impact of IPV on HIV-positive women. METHODS: All HIV-positive women who received outpatient HIV care in southern Alberta between March 2009 and January 2012 were screened for IPV. The associations with IPV of sociodemographic factors, health-related quality of life, clinical status, and hospitalizations were obtained from a regional database and evaluated with multivariable regression analysis. RESULTS: Of 339 women screened, 137 (40.4%) reported experiencing IPV. Those disclosing IPV had higher rates of smoking [adjusted prevalence ratio (APR) = 5.07; 95% confidence interval (CI): 2.72 to 9.43]; illicit drug use (APR = 7.58; CI: 2.45 to 23.26); a history of incarceration (APR = 4.84, CI: 1.85 to 12.68); depression (APR = 2.50, CI: 1.15 to 5.46); and anxiety disorders (APR = 5.75, CI: 2.10 to 15.63). Health-related quality of life was diminished with IPV (APR = 2.94, CI: 1.40 to 6.16) for poor/fair versus very good/excellent. IPV-exposed women were hospitalized 256 times per 1000 patient-years compared to 166/1000 patient-years among IPV-unexposed (P < 0.001) women. The relative risk was increased for HIV-unrelated hospitalizations (APR = 1.42, CI: 1.16 to 1.73) and for HIV-related hospitalizations after outpatient HIV care was initiated (APR = 2.19, CI: 1.01 to 4.85). Modifiable contributors to the poor outcomes included decreased use of antiretroviral therapy (APR = 0.55, CI: 0.34 to 0.91) and additional interruptions in care longer than 1 year (APR = 1.90, CI: 1.07 to 3.39). CONCLUSIONS: IPV is associated with deleterious HIV-related and HIV-unrelated health outcomes, of which, suboptimal engagement in care is a contributor. To improve outcomes, practitioners should aim to increase engagement in care of these women in particular.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".