Clinical features of pneumonia in severely malnourished children with diarrhoea compared to those without diarrhoea
Bibliographic record
Abstract
Introduction: Pneumonia and diarrhoea are amongst the most common causes for hospital admission for children in low- and middle-income countries such as Bangladesh. Undernourished children often have more severe infections and a higher morbidity and mortality. Objective: The objective of this study was to determine the clinical features and outcomes of pneumonia in severely malnourished children with and without diarrhoea. Methodology: A retrospective chart analysis was carried out on children under 5 years of age who were admitted in intensive care unit of the Dhaka hospital of International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b). A total of 245 severe acute malnourished children with pneumonia and diarrhoea (PD group) were compared with 89 children with pneumonia only (PO group). Results: A significantly higher number of children from the PD group had some/severe dehydration (16.3% vs. 1.1%; p < 0.005) when compared with children from the PO group. The PD group showed less cough (83.3% vs. 100%; p < 0.001), lower chest wall indrawing (40.4% vs. 60.7%; p = 0.001), and crackles (62.4% vs. 87.6%; p < 0.001) compared to the PO group at the time of admission. Conclusion: Early diagnosis and treatment of some/severe dehydration in addition to WHO recommended other routine treatment of diarrhoea, pneumonia and severe acute malnutrition in children may help to reduce childhood morbidity and mortality especially in low- and middle-income countries.
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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 | 0.002 |
| 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 | 0.000 |
| 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".