Iron Status in Children With Autism Spectrum Disorder
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Children with autism spectrum disorders (ASDs) often have food selectivity and restricted diets, putting them at risk for nutritional deficiencies. Previous studies have demonstrated a high prevalence of iron deficiency (ID) in children with ASDs living in Wales, Canada, and Turkey. The objectives of this study were to determine the prevalence of ID and the adequacy of iron intake in children with ASD in the United States. METHODS: Participants (age 2-11 years recruited from the Autism Treatment Network Diet and Nutrition Study) completed a 3-day diet record (n = 368) and had laboratory measures of serum ferritin (SF), complete blood count, iron, total iron binding capacity, and transferrin saturation (TS) (n = 222). RESULTS: Of the 222 participants with laboratory data, 18 (8%) had SF <12 µg/L and 2 (1%) had ID defined by both low SF and TS (3 children with low SF had missing TS data). One subject had iron deficiency anemia. Fewer than 2% of subjects had iron intake below the estimated average requirement. CONCLUSIONS: Although the determination of iron status is complex, these data do not support previous reports that children with ASD are at greater risk for ID than the general population; however, 8% percent of the sample did demonstrate low SF despite <2% of the sample demonstrating iron intake below the estimated average requirement. The prevalence of low SF may be an underestimate, because SF is an acute phase reactant and the study included no measure of inflammation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it