Nutritional rehabilitation of malnourished children detected by Screening Tool for Assessment of Malnutrition in Pediatric: Urban versus rural settings
Bibliographic record
Abstract
BACKGROUND: Malnutrition presents a major global health burden. In Egypt, it remains an important issue in children under 5 years especially in rural communities. AIM OF THE STUDY: The aim of the study was to screen 2-5 years old children enrolled from Egyptian hospitals in rural and urban areas for the risk of malnutrition using Screening Tool for Assessment of Malnutrition in Pediatric (STAMP) and to evaluate the effectiveness of nutritional intervention programs. SUBJECTS AND METHODS: This cross-sectional study was conducted on 90 patients recruited from two hospitals in urban and rural Cairo, Dietary history and anthropometric measurements were assessed. Patients at intermediate and severe risk of malnutrition according to STAMP were given tailored nutritional programs. RESULTS: In the rural hospital, 4.4% of the screened children were underweight, 22.2% were marginally underweight, and 73.3% had normal weight. Regarding the urban hospital, 15.6% were marginally underweight, 84.4% had normal weight and no underweight patients. Among the rural group 35.6% were at high risk according to STAMP score results compared to 20% in the urban group. Nevertheless, the only significant differences were the more stunting and higher BMI in rural hospital patients. After nutritional intervention, high-risk category patients decreased in both groups coupled by significant improvement in the anthropometric parameters and nutrition data with no significant differences between them. CONCLUSION: Nutritional education and prompt implementation of nutritional rehabilitation program for malnourished children detected by screening tools result in improvement in their nutritional status disregards their location whether urban or rural.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 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".