Human Immunodeficiency Virus Viral Load Rebound Near Delivery in Previously Suppressed, Combination Antiretroviral Therapy–Treated Pregnant Women
Bibliographic record
Abstract
OBJECTIVE: To assess the stability of human immunodeficiency virus (HIV) viral load suppression within 1 month before birth in pregnant women receiving antenatal combination antiretroviral therapy (CART). METHODS: This is a retrospective cohort study of a Canadian provincial perinatal HIV database from 1997 to 2015. Inclusion criteria were live birth and CART received for at least 4 weeks. Viral load rebound, defined as viral load greater than 50 copies/mL (or greater than 400 copies/mL for 1997-1998) and measured within 1 month before delivery, was identified in women who had at least one previous undetectable viral load during pregnancy. Logistic regressions were conducted to identify the risk factors for viral load rebound. RESULTS: Among the 470 women in the database, 318 met inclusion criteria. Viral load rebound was experienced by 19 women (6.0%, 95% CI 3.7-9.3%) with a mean log10 viral load near delivery of 2.71 copies/mL (=513 copies/mL). Six (32%) had a viral load above 1,000 copies/mL. The rebound was detected within 1 day before delivery in 50% of the women. Aboriginal ethnicity, cocaine use, and hepatitis C virus polymerase chain reaction positivity were significantly associated with viral load rebound. There were no HIV vertical transmissions. CONCLUSION: Even women attending for HIV care and achieving viral suppression in pregnancy can experience viral load rebound predelivery.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".