Molecular Detection of Enteropathogens from Diarrheic Stool of HIV-positive Patients in Gondar, Ethiopia
Bibliographic record
Abstract
Infectious diarrhea is a common problem in the developing world, especially among people living with HIV/AIDS. Traditional diagnostic methods such as stool culture and microscopic examination is limited by resources. The use of molecular diagnostics for enteropathogen detection in this region of sub-Saharan Africa has not been fully explored. To identify risk factors and characterize enteropathogens from diarrheic stools of HIV positive patients in Gondar, Ethiopia using multiplex molecular panels targeting key infectious agents. A cross-sectional study of 100 stool samples was performed. Samples were collected consecutively from HIV positive patients presenting with diarrhea at a local clinic in Gondar, a major center in NW Ethiopia. Genomic DNA was extracted from stool and processed in Canada using multiplex molecular panels (Allplex [Seegene Canada] and FilmArray [Biomerieux]). Correlations between patient characteristics, symptoms, public health risk factors and enteropathogen type(s) was explored using STATA (Version 14.1). Ninety-four samples were successfully analyzed by molecular methods. Six samples were excluded due to insufficient volumes. The mean age was 35 with 43% male, 17% living in a rural area, 24% with access only to well water and 74% practicing proper hand hygiene. The majority of patients (68%) were receiving HAART with 32% having CD4 counts greater than 500/µL. Multiple pathogens were detected in 95% of specimens, with 62% having 5 or more enteropathogens. Common bacteria, viruses and parasites detected were Shigella spp./enteroinvasive E. coli (80%), enterotoxigenic E. coli (72%), Norovirus (15%) and C. Parvum (8%). CD4 cell counts and use of HAART were not associated with type or number of enteropathogens detected, though the number of patients with CD4<200/µl was small (23%). Diarrheic stool from HIV-positive outpatients in Gondar, Ethiopia had on average 5 enteropathogens present in their stool. CD4 count was not predictive of pathogen type or number in this study. Shigella spp./enteroinvasive E. coli and enterotoxigenic E. coli are the major pathogens, not dissimilar to immunocompetent individuals in low income countries. All authors: No reported disclosures.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".