Combined deficiencies of 25-hydroxyvitamin D and anemia in preschool children with severe early childhood caries: A case–control study
Bibliographic record
Abstract
BACKGROUND: Severe early childhood caries (S-ECC) is common and has adverse affects on children's health. Children with S-ECC have been shown to have anemia or vitamin D deficiency. No studies have assessed the presence of combined deficiencies with S-ECC. The purpose of our study was to examine whether those with S-ECC had a higher prevalence of combined anemia and low 25-hydroxyvitamin D (25(OH)D) compared to controls. Covariates associated with elevated parathyroid hormone (PTH), previously noted in S-ECC, were examined. METHODS: This is a re-analyses of a previously described cross-sectional case-control study; data were collected between 2009 and 2011. Children with S-ECC were recruited on the day of dental surgery and controls from the community. Blood was drawn for complete blood count, ferritin, 25(OH)D and PTH. Families completed a questionnaire. RESULTS: 25(OH)D < 50 nmol/L; controls 0/114 versus S-ECC 15/140 (P<0.001). In an adjusted regression model, PTH was negatively associated with 25(OH)D (P<0.001) and higher income (P<0.02); it was positively associated with less regular milk consumption (P=0.001). CONCLUSIONS: Combined deficiencies of vitamin D and anemia are more prevalent in children with S-ECC; the etiology remains unclear. A detailed diet history is key in those with S-ECC to assess risks for deficiencies.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".