A clinical practice guide: What HIV care providers need to know about HIV pregnancy planning to optimize preconception care for their patients
Bibliographic record
Abstract
This clinical practice guide has been developed to support human immunodeficiency virus (HIV) care providers' use of the 2018 Canadian HIV Pregnancy Planning Guidelines (CHPPG) in their work with people and couples affected by HIV. HIV pregnancy planning has changed considerably in the last decade and requires a multidisciplinary team, and HIV care providers are often at the forefront of the team. It is, therefore, important to have clear guidance on how to provide HIV pregnancy planning care. This Clinical Practice Guide is intended for both primary and specialty HIV care providers, including doctors, nurses, and nurse practitioners. We have repackaged the 2018 CHPPG's 36 recommendations into five standards of care for ease of use. We have also included an initial algorithm that can be used with each patient to direct discussions about their reproductive goals. Pregnancy and parenting are increasingly normalized experiences in the lives of people and couples affected by HIV. While conception used to be a complicated decision, often heavily focused on minimizing the risk of HIV transmission, the current evidence supports more universal counselling and supports for HIV pregnancy planning. HIV care providers have a responsibility to be familiar with the unique considerations for pregnancy planning when supporting their patients. This counselling is critical to optimizing reproductive health outcomes for all people affected by HIV, including those who wish to prevent pregnancy.
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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 | 0.008 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.029 | 0.024 |
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".