Evolution of prevention of vertical <scp>HIV</scp> transmission in Uganda: 2008–2017
Bibliographic record
Abstract
OBJECTIVES: Uganda adapted its policy for prevention of vertical transmission (VT) of HIV transmission as the World Health Organization released Options A, B and B+. We assessed trends in diagnostic testing, breastfeeding practices, maternal and infant antiretroviral therapy (ART), mortality, VT and HIV-free survival (HFS) among Ugandan infants born to women living with HIV during this period of successive guideline changes. METHODS: This is is a retrospective observational study of infants attending early infant diagnosis clinics at two Ugandan hospitals. RESULTS: A total of 1885 infants (48% female) were managed from 2009 to 2017. DNA polymerase chain reaction (PCR) for early infant diagnosis was performed on 1719 infants (92%, one or more PCR tests) and 676 infants (36%, two PCR tests). HIV serology was performed on 90 infants (4.8%). Testing increased over the study period but remained suboptimal, due to high loss to follow-up (LTFU). A total of 93% of infants were breastfed, for a median of 9.5 months. The duration of breast milk exposure increased over the study period, consistent with guidelines that increasingly encouraged breastfeeding. Nine cases (0.48%) of suspected breast milk transmission were observed. The use of ART increased significantly over the study period. Mortality (3.5%, 2.7% and 1.1%; p = 0.0076) and VT (17%, 12% and 7.4%; p < 0.0001) decreased over the study period (2008-2010, 2011-2012 and 2013-2017, respectively). LTFU values were 31%, 49% and 59% at 6, 12 and 18 months of age, respectively, with only modest improvements over time. HFS could only be conclusively documented in 532 infants (28%) because of LTFU. CONCLUSIONS: From 2009 to 2017, outcomes improved among HIV-exposed infants in Uganda. LTFU remains a barrier to optimal care.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".