Screening for coeliac disease in children and adults living in a slum of Dhaka, Bangladesh
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Serological screening with a confirmation through biopsy has improved the understanding of coeliac disease (CD) epidemiology worldwide. Prevalence of CD in Bangladesh is not yet explored and therefore, we aimed to assess the seroprevalence of CD in slum-dwelling malnourished children and adults in Dhaka. METHODS: ). Samples from all the participants were assessed for anti-tissue transglutaminase antibody (tTG-IgA) and total serum IgA by ELISA. Positive tTG-IgA and randomly selected low IgA values were reconfirmed using anti-tTG-IgG and gliadin IgG ELISA. CD was diagnosed when second screening tests were found positive and the participants were further investigated by small bowel biopsy. RESULTS: A total of 818 participants (240 stunted, 272 at risk of stunting children and 306 malnourished adults) were enrolled in the study. Overall, anti-tTG-IgA was positive in 5/818 (0.6%; 95% CI 0.25% to 1.46%). Of the five positive cases, anti-tTG-IgG and gliadin IgG were found positive in only one participant. Duodenal biopsy of positive participant revealed characteristic lesions of CD. Randomly selected low IgA values were found negative in tTG-IgG and gliadin IgG for all the participants. No participant was found total IgA deficient. CONCLUSION: The incidence of coeliac autoimmunity is low in malnourished slum dwellers regardless of age in Bangladesh. It is important to investigate the nationwide prevalence to reveal the definite picture.
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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) | 0.003 | 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".