Diarrhoeal children with concurrent severe wasting and stunting compared to severe wasting or severe stunting
Bibliographic record
Abstract
OBJECTIVE: Children with both severe wasting and severe stunting (SWSS) represent an extreme form of malnutrition and are prone to develop severe infection. The study aims to demonstrate clinical features and aetiology of diarrhoea among children with SWSS compared to those with either severe wasting (SW) or severe stunting (SS), which may help in early identification of high-risk children. METHODS: Data were extracted from the database of the diarrhoeal disease surveillance system (DDSS) of Dhaka Hospital, icddr,b from 2008 to 2017. Among 14 403 under-five diarrhoeal children, 149 had concurrent SWSS (WLZ/WHZ ˂-3 with LAZ/HAZ ˂-3), 795 had SW (WLZ/WHZ ˂-3 but LAZ/HAZ ≥-3) alone, and 1000 had only SS (LAZ/HAZ ˂-3 but WLZ/WHZ ≥-3). RESULTS: In logistic regression analysis after adjusting for potential confounders, dehydrating diarrhoea and slum dwelling were independently associated with SWSS vs. SW (P < 0.05). When compared with SS, dehydration and maternal illiteracy were independently associated with SWSS (P < 0.05). In comparison with SW or SS, SWSS less often included infection with rotavirus (P < 0.05). Dehydration was independently associated with SW vs. SS after adjusting for potential confounders (P < 0.05). CONCLUSION: Children with SWSS more often presented with dehydrating diarrhoea (69%) than children who had either SW (55%) or SS (43%). However, SWSS patients less frequently presented with rotavirus-associated diarrhoeal illnesses. This result underscores the importance of early detection and prompt management of dehydrating diarrhoea in children with concomitant severe wasting and severe stunting to reduce morbidity and mortality in these children, especially in poor settings.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".