Infant feeding for people living with HIV in high resource settings: a multi-disciplinary approach with best practices to maximise risk reduction
Bibliographic record
Abstract
Shared decision making for infant feeding in the context of HIV in high-resourced settings is necessary to acknowledge patient autonomy, meet increasing patient requests and address the changing reality of perinatal HIV care. In low-to middle-income countries (LMIC), where the majority of individuals living with HIV reside, persons with HIV are recommended to breastfeed their infants. In the setting of maternal anti-retroviral therapy (ART) use throughout pregnancy, viral suppression and appropriate neonatal post-exposure prophylaxis (PEP) use, updated information indicates that the risk of HIV transmission through breastmilk may be between 0.3 and 1%. While not endorsing or recommending breastfeeding, the United States' DHHS perinatal guidelines are similarly pivoting, stating that individuals should "receive patient-centred, evidence-based counselling on infant feeding options." Similar statements appear in the British, Canadian, Swiss, European, and Australasian perinatal guidelines. We assembled a multi-disciplinary group at our institution to develop a structured shared decision-making process and protocol for successful implementation of breastfeeding. We recommend early and frequent counselling about infant feeding options, which should include well known benefits of breastfeeding even in the context of HIV and the individual's medical and psychosocial circumstances, with respect and support for patient's autonomy in choosing their infant feeding option.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".