Emerging concepts in the diagnosis, treatment, and prevention of travelers’ diarrhea
Bibliographic record
Abstract
PURPOSE OF REVIEW: Traveller's diarrhea, though not life-threatening. is often a vexing problem, which impacts overall function of the traveller while on holiday. Increasing data is available regarding molecular diagnostic techniques, which may help obtain an early etiologic diagnosis. Use of antibiotics for traveller's diarrhea is controversial in this era of multidrug resistance and microbiome disruption. RECENT FINDINGS: Travel to the tropics promotes gut colonization with drug-resistant bacteria and this risk increases after treatment with antibiotics, leading to potential ecological impacts in the country of residence. SUMMARY: Traveller's diarrhea is common and can impact a traveller's itinerary leading to significant inconvenience, and occasional longer term sequelae. Though bacterial causes predominate, recommended treatment is conservative in mild-to-moderate cases. Molecular techniques for early diagnosis of traveller's diarrhea may help with appropriate management. Treatment with antibiotics is sometimes required but is associated with gut colonization by multidrug-resistant bacteria.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".