SUPPLEMENTATION WITH LONG CHAIN POLYUNSATURATED FATTY ACIDS REDUCES MARKERS OF INFLAMMATION IN CHILDREN WITH LOW DHA INTAKES
Bibliographic record
Abstract
Aim: To identify from Avon Longitudinal Study of 14,000 Parents and Children (ALSPAC) children who had been formally diagnosed as Coeliac Disease (CD) and compare this with serological screeing data.Background: 5470 children randomly selected from a total of 14,000 were screened using Tissue Transglutaminase (TTG) and IgA endomysial antibodies (EMA).54 children proved positive for CD suggesting a prevalence of 1% (1).ALSPAC is an anonymous study and hence these children have not been referred for biopsy or told the results.Within Avon all children with suspected or serologically positive CD are referred to just one centre, Bristol Children`s Hospital, for small bowel biopsies.Methods: Since 1990, data has been prospectively collected on all children having endoscopic small bowel biopsy for CD.This data and centralised computer and dietetic records within Avon have been analysed to identify ALSPAC children with CD (date of birth 01.04.1991Y31.12.1992 and Avon postcodes).Results: 12 children from Avon diagnosed with CD since 1.4.91,have birthdays concordant with ALSPAC.This gives a prevalence rate of 1/1,100.All had symptoms.Four had a family history.At time of diagnosis all were aged over 2 years, 3 were 2Y5 yr, 6 were 5Y10 yr and 3 were aged 10Y14 yrs.Discussion: Based on screening data, 140 children from Avon would be expected to have CD.However only 12 of these children have been diagnosed with CD.This suggests that 90% of children with possible CD may be being missed.The screening data also recorded that children with positive screening tests were lagging behind in growth by 9 months.There are other well documented long term health hazards of untreated CD.Our data suggests all children should be screened for CD.
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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 | 0.000 | 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) | 0.002 | 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".