Malnourishment in a population of young children with severe early childhood caries.
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to describe the nutritional status of children with severe early childhood caries (S-ECC) using several clinical measurements. METHODS: Children aged 2 to 6 years with S-ECC were measured for height, weight, triceps skinfolds (TSF), and measurement of upper mid-arm circumference (MAC). Blood samples assessed: (1) hemoglobin; (2) mean corpuscular volume (MCV); (3) serum ferritin; and (4) serum albumin. Weight-for-height was converted into ideal body weight (IBW) percentiles. Body mass index (BMI) was calculated as kg/m2. TSF and MAC were converted into measurement of arm muscle circumference (MAMC). All measurements were compared with population reference values. RESULTS: Using weight for height centiles, 17% were diagnosed as being malnourished and 66% as within normal limits. Using BMI centiles, only 4% were identified as being malnourished and 75% as being normal. Conversely, the body fat of 24% was assessed as low (<10th percentile). Serum albumin was low for 16%. The majority had evidence of inadequate iron intake with low serum ferritin (80%), iron depletion (24%), iron deficiency (6%), or iron deficiency anemia (11%). CONCLUSIONS: All tests detected levels of malnutrition, with blood tests finding the most severe cases. The results suggest that severe Early Childhood Caries may be a risk marker for iron deficiency anemia. Since iron deficiency has permanent effects on growth and development, pediatric dentists should recommend assessment of iron levels in S-ECC patients regardless of their anthropometric appearance.
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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 | 0.001 | 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) | 0.001 | 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".