Current Interventions to Prevent HTLV-1 Mother-to-Child Transmission and Their Effectiveness: A Systematic Review and Meta-Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Human T lymphotropic virus 1 (HTLV-1) may be transmitted from mother to child and affects at least 5−10 million individuals worldwide, with severe consequences on health. Strategies to prevent transmission are important, as there is no treatment or vaccine. This systematic review aimed to identify interventions to prevent HTLV-1 mother-to-child transmission and to determine their effectiveness. Exclusive formula feeding, short-term breastfeeding, use of freeze−thaw milk, milk pasteurization, maternal and infant antiretroviral drugs, caesarean section, early clamping of umbilical cord, screening of milk donors and avoidance of cross-breastfeeding were identified as possible strategies. Avoidance of breastfeeding is an intervention that prevents 85% of transmissions. This strategy is recommended in Japan, Brazil, Colombia, Canada, Chile, Uruguay, the USA and some regions of French Guyana. Whilst breastfeeding for <3 months does not increase the risk of transmission compared to exclusive formula-feeding, concerns remain regarding the limited number of studies outside Japan, and the lack of information on women having higher risk of HTLV-1 transmission and on the ability of women to discontinue breastfeeding. Additional interventions are plausible, but data on their effectiveness are limited. The acceptance of interventions is high. These findings may guide healthcare professionals and support policymakers in implementing policies to avoid HTLV-1 mother-to-child transmission.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it