Effects of water‐based hand sanitizers and micronutrient powders along with nutrition and hygiene education to prevent infections and linear growth faltering among low birth weight infants in Bangladesh
Bibliographic record
Abstract
Objective To measure the relative efficacy of Benzalkonium Chloride containing, water‐based hand sanitizers (HS) and multiple micronutrient powder (MNP) along with nutrition and hygiene education (NHE) to prevent infections and linear growth faltering among low birth weight (LBW) infants. Methods Prospective 2×2 factorial, cluster‐randomized trial, conducted among 467 full‐term LBW infants from 0–12 months (mo) in rural Bangladesh, using 48 clusters randomly assigned as follows: from 0–6 mo, i) NHE only or ii) NHE plus HS; from 6–12 mo, i) NHE only; ii) NHE plus HS; iii) NHE plus MNP (to be provided with complementary foods); and iv) NHE plus HS and MNP. Results During 0–6mo, the proportion of LBW infants with any infection was significantly lower in the ‘NHE plus HS’ group compared to the ‘NHE only’ group (P<0.001). Mean duration of diarrhea among LBW infants was significantly lower in the ‘NHE plus HS’ group compared to ‘NHE only’ (3.4±1.2 vs. 6.0±1.6 days, P<0.01). Upper respiratory tract infections and cough were also significantly lower in the ‘NHE plus HS’ group in comparison with ‘NHE only’ (29.8% vs. 33.0% and10.6% vs. 12.2%, P<0.05, for both). Conclusions Caregiver use of hand sanitizers might effectively reduce infections among term LBW infants in the first six months of life. Grant Funding Source : Bill & Melinda Gates Foundation to FHI 360, through the Alive & Thrive Small Grants Program managed by UC Davis.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".