The risk for scurvy in children with neurodevelopmental disorders
Bibliographic record
Abstract
BACKGROUND: Scurvy, the disease resulting from vitamin C deficiency, is perceived as being rare and occurring predominantly in the past. However, scurvy continues to exist and may be encountered in children with medical/developmental conditions and/or restricted diet. Diagnosis can be challenging given the perceived rarity of the condition and nonspecific symptoms, including gingival disease. METHODS: We present a series of two cases of scurvy in which the affected children presented to medical attention with dental complaints. Additional cases of scurvy are described, based on the literature review of case reports/series published in the last 10 years. RESULTS: Literature review yielded 77 relevant case reports published in the English language since 2009. Most affected children had a previous diagnosis of a medical or developmental condition (especially autism spectrum disorder). Intraoral features (gingival swelling, pain, and bleeding) were noted in most of the identified cases of scurvy. Improvement in the oral features of scurvy occurred within days of vitamin C therapy initiation. CONCLUSIONS: Recognizing classic signs and symptoms of scurvy enables prompt diagnosis and avoids invasive investigations. Dentists may be in a unique position to facilitate prompt and accurate diagnosis of a condition that is relatively easy and safe to treat once identified.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".