Persistent digestive disorders in the tropics: causative infectious pathogens and reference diagnostic tests
Bibliographic record
Abstract
BACKGROUND: Persistent digestive disorders account for considerable disease burden in the tropics. Despite advances in understanding acute gastrointestinal infections, important issues concerning epidemiology, diagnosis, treatment and control of most persistent digestive symptomatologies remain to be elucidated. Helminths and intestinal protozoa are considered to play major roles, but the full extent of the aetiologic spectrum is still unclear. We provide an overview of pathogens causing digestive disorders in the tropics and evaluate available reference tests. METHODS: We searched the literature to identify pathogens that might give rise to persistent diarrhoea, chronic abdominal pain and/or blood in the stool. We reviewed existing laboratory diagnostic methods for each pathogen and stratified them by (i) microscopy; (ii) culture techniques; (iii) immunological tests; and (iv) molecular methods. Pathogen-specific reference tests providing highest diagnostic accuracy are described in greater detail. RESULTS: Over 30 pathogens may cause persistent digestive disorders. Bacteria, viruses and parasites are important aetiologic agents of acute and long-lasting symptomatologies. An integrated approach, consisting of stool culture, microscopy and/or specific immunological techniques for toxin, antigen and antibody detection, is required for accurate diagnosis of bacteria and parasites. Molecular techniques are essential for sensitive diagnosis of many viruses, bacteria and intestinal protozoa, and are increasingly utilised as adjuncts for helminth identification. CONCLUSIONS: Diagnosis of the broad spectrum of intestinal pathogens is often cumbersome. There is a need for rapid diagnostic tests that are simple and affordable for resource-constrained settings, so that the management of patients suffering from persistent digestive disorders can be improved.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".