Bibliographic record
Abstract
Introduction: Malnutrition in childhood is related to mortality, mainly from infections, and has long-term health consequences. The impact of an acute illness on subsequent growth of malnourished children has been poorly described and there is limited understanding of the acute and long-term metabolic changes in these children. Aims: This thesis aimed to understand the growth recovery processes and metabolic disturbances linked to acute illness and malnutrition and whether these differ between children with severe wasting (SW) versus nutritional oedema (NO). Methods: Growth was measured in children hospitalised in low- and middle- income countries with classic anthropometry or with bio-impedance analysis (BIA) for body composition. Blood glucose was tracked with continuous glucose monitoring, and the recovery dynamics of hundreds of metabolites was investigated over short and longer-term convalescence to identify metabolic pathways with rapid or delayed recovery. Results: Most children had sub-optimal growth post-discharge but children with NO had a distinct weight-recovery pattern. While BIA did not add prognostic value, continuous glucose monitoring revealed that half the children experience severe glucose dysregulation, including severe hypoglycemia that can led to death. Metabolomics analysis showed that while amino acids normalise, large panels of specialised lipids show delayed recovery. Conclusion: Enhancing metabolism by optimizing therapeutic feeds or developing adjuvant therapy could improve glucose regulation and replenish lipids needed for cellular repair. Since metabolic distress is linked to mortality in malnourished children, developing tailored interventions could broaden the treatment approaches and improve not only growth but also mortality in children with acute illnesses and malnutrition.
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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 | 0.001 |
| 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 | 0.000 | 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".