Urinary Organic Acids Increase After Clinical Stabilization of Hospitalized Children With Severe Acute Malnutrition
Bibliographic record
Abstract
Background: Despite a reduction of child mortality in low-income countries, acutely ill undernourished children still have an elevated risk of death. Those at highest risk are children with severe acute malnutrition (SAM) who often show metabolic dysregulation that remains poorly understood. Objective: We performed a pilot study to examine changes in urinary organic acids during nutritional rehabilitation of children with SAM, and to identify metabolites associated with the presence of edema or with mortality. Methods: This study included 76 children aged between 6 and 60 months, hospitalized for SAM at the Moyo Nutritional Rehabilitation and Research Unit in Blantyre, Malawi. Urine was collected at admission and 3 days after clinical stabilization and metabolomics were performed using gas chromatography–mass spectrometry. Metabolite concentrations were evaluated with both uni- and multivariate approaches. Results: Most metabolites increased 3 days after clinical stabilization, and total urinary concentration changed from 1.2 mM (interquartile range [IQR], 0.78-1.7) at admission to 3.8 mM (IQR, 2.1-6.6) after stabilization ( P < .0001). In particular, 6 metabolites showed increases: 3-hydroxybutyric, 4-hydroxyhippuric, p-hydroxyphenylacetic, oxoglutaric, succinic, and lactic acids. Urinary creatinine was low at both time points, but levels did increase from 0.63 mM (IQR, 0.2-1.2) to 2.6 mM (IQR,1.6-4.4; P < .0001). No differences in urinary profiles were found between children who died versus those who survived, nor between children with severe wasting or edematous SAM. Conclusions: Total urinary metabolites and creatinine increase after stabilization and may reflect partial recovery of overall metabolism linked to refeeding. The use of urinary metabolites for risk assessment should be furthered explored. Trial registration: TranSAM study (ISRCTN13916953).
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".