Prescribing patterns of antiretroviral treatments during pregnancy for women living with <scp>HIV</scp> in Canada 2004–2020: A surveillance study
Bibliographic record
Abstract
BACKGROUND: While treatment guidelines for HIV in adults have evolved rapidly with the advent of new antiretroviral (ARV) treatment, those for the prevention of vertical HIV transmission in pregnancy have evolved more slowly due to safety and efficacy concerns. Here we describe Canadian prescribing patterns for ARV treatments during pregnancy and compare them to perinatal HIV prescribing guidelines of the United States Department of Health and Human Services (HHS), that are commonly used in Canada and include recommendations for newly commercialized therapies. METHODS: The Canadian Perinatal HIV Surveillance Program (CPHSP) captures annual medical data on mothers living with HIV and their infants from 23 sites across Canada. Women from this cohort who received an ARV treatment during pregnancy and who gave birth between 2004 and 2020 were included in the study. ARV treatments were designated as 'preferred/alternative' as per HHS HIV perinatal guidelines, or 'other than preferred/alternative'. RESULTS: We identified 3673 pregnancies from 2720 women. The proportion of women that conceived while on ARV treatment increased from 29% in 2003 to 90% in 2020. Other than preferred/alternative ARV treatments were received in 1112 (30%) of pregnancies and this was significantly associated with having initiated ARV treatment before conception. CONCLUSION: In Canada during the study period, a high number of women were prescribed an other than preferred/alternative ARV treatment during pregnancy. Further optimization of ARV treatment in women of childbearing age living with HIV is warranted.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".