Carbohydrate malabsorption in acutely malnourished children and infants: a systematic review
Bibliographic record
Abstract
CONTEXT: Severe acute malnutrition (SAM) accounts for approximately 1 million child deaths per year. High mortality is linked with comorbidities, such as diarrhea and pneumonia. OBJECTIVE: The aim of this systematic review was to determine the extent to which carbohydrate malabsorption occurs in children with SAM. DATA SOURCES: The PubMed and Embase databases were searched. Reference lists of selected articles were checked. DATA EXTRACTION: All observational and controlled intervention studies involving children with SAM in which direct or indirect measures of carbohydrate absorption were analyzed were eligible for inclusion. A total of 20 articles were selected for this review. DATA SYNTHESIS: Most studies reported carbohydrate malabsorption, particularly lactose malabsorption, and suggested an increase in diarrhea and reduced weight gain in children on a lactose-containing diet. As most studies reviewed were observational, there was no conclusive scientific evidence of a causal relationship between lactose malabsorption and a worse clinical outcome among malnourished children. CONCLUSION: The combined data indicate that carbohydrate malabsorption is prevalent in children with SAM. Additional well-designed intervention studies are needed to determine whether outcomes of SAM complicated by carbohydrate malabsorption could be improved by altering the carbohydrate/lactose content of therapeutic feeds and to elucidate the precise mechanisms involved.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".