Recovery and relapse from severe acute malnutrition after treatment: a prospective, observational cohort trial in Pakistan
Bibliographic record
Abstract
OBJECTIVE: Millions of children suffer from severe acute malnutrition (SAM) in low- and middle- income countries. Much is known about the effectiveness of community treatment programmes (CMAM) but little is known about post-discharge outcomes after successful treatment. The present study aimed to evaluate post-discharge outcomes of children cured of SAM. DESIGN: Prospective, observational cohort study. Children with SAM who were discharged as cured were followed monthly for 6 months or until they experienced relapse to SAM. 'Cure' was defined as a child achieving a mid-upper arm circumference (MUAC) of ≥115 mm with ≥15 % weight gain after loss of oedema. Relapse was defined as a child with MUAC<115 mm and/or oedema at any monthly visit. SETTING: Save the Children CMAM programme in Swabi, Pakistan, from January 2012 to December 2014. SUBJECTS: Children aged 6-59 months (n 117) discharged as cured from the CMAM programme were eligible for the study and followed for 6 months. RESULTS: One hundred children (92·6 %) remained free of SAM, eight (7·4 %) relapsed to SAM, nine (8·3 %) were lost to follow-up and none died. Most relapses occurred within 3 months of discharge (mean time to relapse 73·4 (sd 36·2) d). At enrolment, 90 % had moderate acute malnutrition (MAM) and 10 % were not malnourished. By the end of 6 months, 35 % persisted with MAM and the remaining were not malnourished. CONCLUSIONS: In rural Pakistan, fewer than 10 % of children cured of SAM relapsed. The first 3 months is the most vulnerable time.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".