Management of HIV positive pregnancies in Ontario: current status.
Bibliographic record
Abstract
BACKGROUND: AIDS is one of the biggest health crises we face today. With nearly 20 million women infected with the virus that causes it, HIV, maternal transmission of HIV is increasingly becoming a serious concern and hindrance in stemming the proliferation of the disease. While an ever increasing number of pregnant women are being administered anti-retrovirals to mitigate the vertical transmission of the virus, little is known about the changing trends in the type of agents used and the duration of therapy. OBJECTIVES: This paper attempts to identify any changes in the pattern of HIV management in pregnant women for the period of time spanning 1998 to 2005. METHODS: Data from the charts of 183 patients were reviewed. A retrospective, longitudinal and cross-sectional patient chart review was employed to obtain data. Parameters such as therapeutic management of HIV, class of drugs used and duration of treatment were assessed to identify any evolving patterns over the course of the study. RESULTS: It was seen that over time, the number of women receiving adequate therapeutic interventions has steadily increased. We also identified evolving trends in terms of the classes of anti-retrovirals employed and the duration of prophylaxis. CONCLUSION: The strategies employed in the management of HIV positive pregnancies in Ontario, while evolving over time, were found to be in line with the guidelines in place. The information delivered by this study might enable the medical community to assess the progress in dealing with this challenge thus far and further fine tune the current strategy.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".