Association of intestinal pathogens with faecal markers of environmental enteric dysfunction among slum‐dwelling children in the first 2 years of life in Bangladesh
Bibliographic record
Abstract
OBJECTIVE: Environmental Enteric Dysfunction (EED) can be assessed by faecal biomarkers such as Myeloperoxidase (MPO), Neopterin (NEO) and Alpha-1 anti-trypsin (AAT). We aimed to test the association of intestinal pathogens with faecal markers of EED among slum-dwelling children in first 2 years of life. METHODS: The MAL-ED birth cohort data of Bangladesh site were used to conduct this analysis. Multivariable analyses using Generalized Estimating Equations (GEE) were performed to test the association between intestinal pathogens and faecal markers of EED. RESULTS: Giardiasis, ascariasis and trichuriasis were the most frequent parasitic infections and Campylobacter spp., Enteroaggregative Escherichia coli (EAEC) and Enterotoxigenic Escherichia coli (ETEC) were the common bacterial pathogens observed in stool samples of the children. Overall, 71%, 97% and 58% of stool samples were above values considered normal in non-tropical settings for MPO, NEO and AAT respectively. Giardiasis was found to be significantly associated with MPO (Coefficient = 0.55; 95% CI = 0.15, 0.95; P-value = 0.008) and AAT concentrations (Coefficient = 0.34; 95% CI = 0.04, 0.63; P-value = 0.03). A significant association was found between trichuriasis and NEO (Coefficient = 0.90; 95% CI = 0.19, 1.61; P-value = 0.01). Trichuriasis (Coefficient = 1.71; 95% CI = 0.32, 3.11; P-value = 0.02) and giardiasis (Coefficient = 1.51; 95% CI = 0.79, 2.23; P-value <0.001) were significantly associated with EED score. Children with EAEC had significantly higher MPO concentrations (Coefficient = 0.33; 95% CI = 0.06, 0.61; P-value = 0.02). CONCLUSION: The study results imply the importance of intestinal pathogens in contributing to intestinal inflammation and increased intestinal permeability in young children.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".