A Systematic Review on the Optimal Dose and Duration of Ready-to-Use Therapeutic Food (RUTF) for 6–59-Month-Old Children with Severe Wasting or Oedema
Bibliographic record
Abstract
The World Health Organisation (WHO) recommends that severe wasting and/or oedema should be treated with ready-to-use therapeutic food (RUTF) at a dose of 150-220 kcal/kg/day for 6-8 weeks. Emerging evidence suggests that variations of RUTF dosing regimens from the WHO recommendation are not inferior. We aimed to assess the comparative efficacy and effectiveness of different RUTF doses and durations in comparison with the current WHO RUTF dose recommendation for treating severe wasting and/or oedema among 6-59-month-old children. A systematic literature search identified three studies for inclusion, and the outcomes of interest included anthropometric recovery, anthropometric measures and indices, non-response, time to recovery, readmission, sustained recovery, and mortality. The study was registered with PROSPERO, CRD 42021276757. Only three studies were eligible for analysis. There was an overall high risk of bias for two of the studies and some concerns for the third study. Overall, there were no differences between the reduced and standard RUTF dose groups in all outcomes of interest. Despite the finding of no differences between reduced and standard-dose RUTF, the studies are too few to conclusively declare that reduced RUTF dose was more efficacious than standard RUTF.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".