A Case Series of Third‐Trimester Raltegravir Initiation: Impact on Maternal HIV‐1 Viral Load and Obstetrical Outcomes
Bibliographic record
Abstract
OBJECTIVE: To describe the impact of initiating raltegravir (RAL)-containing combination antiretroviral therapy (cART) regimens on HIV viral load (VL) in pregnant women who have high or suboptimal VL suppression late in pregnancy. METHODS: HIV-infected pregnant women who started RAL-containing cART after 28 weeks' gestation from 2007 to 2013 were identified in two university hospital centres. RESULTS AND DISCUSSION: Eleven HIV-infected women started RAL at a median gestational age of 35.7 weeks (range 31.1 to 38.0 weeks). Indications for RAL initiation were late presentation in pregnancy (n=4) and suboptimal VL suppression secondary to poor adherence or viral resistance (n=7). Mean VL at the time of RAL initiation was 73,959 copies/mL (range <40 to 523,975 copies/mL). Patients received RAL for a median of 20 days (range one to 71 days). The mean decline in VL from the time of RAL initiation to delivery was 1.93 log, excluding one patient who received only one RAL dose and one patient with undetectable VL at the time of RAL initiation. After eight days on RAL, 50% of the women achieved a VL <1000 copies/mL (the threshold for recommended Caesarean section to reduce the risk for perinatal transmission). There were no cases of perinatal HIV transmission. CONCLUSION: The present study provides preliminary data to support the use of RAL-containing cART to expedite HIV-1 VL reduction in women who have a high VL or suboptimal VL suppression late in pregnancy, and to decrease the risk of HIV perinatal transmission while avoiding Caesarean section. Further assessment of RAL safety during pregnancy is warranted.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".