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Record W2966179234 · doi:10.1097/qco.0000000000000581

Emerging concepts in the diagnosis, treatment, and prevention of travelers’ diarrhea

2019· review· en· W2966179234 on OpenAlexaff
Lorne Schweitzer, Bhagteshwar Singh, Priscilla Rupali, Michael Libman

Bibliographic record

VenueCurrent Opinion in Infectious Diseases · 2019
Typereview
Languageen
FieldMedicine
TopicTravel-related health issues
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersNational Institute for Health and Care Research
KeywordsMedicineDiarrheaAntibioticsTraveler's diarrheaIntensive care medicineAntibiotic resistanceMicrobiomeMultiple drug resistanceDrug resistanceMicrobiologyInternal medicineBioinformaticsBiology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.882
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.148
GPT teacher head0.482
Teacher spread0.334 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations10
Published2019
Admission routes1
Has abstractyes

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