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Record W2333394835 · doi:10.9778/cmajo.20140082

Dermatoses among returned Canadian travellers and immigrants: surveillance report based on CanTravNet data, 2009-2012

2015· article· en· W2333394835 on OpenAlexaffvenueabout
M. S. Stevens, J Geduld, Michael Libman, Brian J. Ward, Anne McCarthy, Jean Vincelette, Wayne Ghesquière, Jan Hájek, Susan Kuhn, David O. Freedman, Kevin C. Kain, Andrea K. Boggild

Bibliographic record

VenueCMAJ Open · 2015
Typearticle
Languageen
FieldMedicine
TopicDermatological diseases and infestations
Canadian institutionsPublic Health OntarioUniversity of British ColumbiaUniversity of TorontoIsland HealthUniversity Health NetworkOttawa HospitalCentre for Global Health ResearchHôpital Saint-LucPublic Health Agency of CanadaMcGill University Health CentreToronto Public HealthAlberta Children's Hospital
Fundersnot available
KeywordsRashImmigrationMedicineCohortFamily medicineTourismPediatricsDemographyGeographyDermatologyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: There is a lack of multicentre analyses of the spectrum of dermatologic illnesses acquired by Canadian travellers and immigrants. Our objective for this study was to provide a comprehensive, Canada-specific surveillance summary of travel-related dermatologic conditions in a cohort of returned Canadian travellers and immigrants. METHODS: Data for Canadian travellers and immigrants with a primary dermatologic diagnosis presenting to CanTravNet sites between September 2009 and September 2012 were extracted and analyzed. Data were collected using the GeoSentinel data platform. This network comprises 56 specialized travel and tropical medicine clinics, including 6 Canadian sites (Vancouver, Calgary, Toronto, Ottawa and Montréal), that contribute anonymous, de-linked, clinician- and questionnaire-based travel surveillance data on all ill travellers examined to a centralized Structure Query Language database. Results were analyzed according to reason for most recent ravel: immigration (including refugee); tourism; business; missionary/volunteer/research and aid work; visiting friends and relatives; and other, which included students, military personnel and medical tourists. RESULTS: During the study period, 6639 patients presented to CanTravNet sites across Canada and 1076 (16.2%) received a travel-related primary dermatologic diagnosis. Arthropod bites (n = 162, 21.5%), rash (n = 141, 18.7%), cutaneous larva migrans (n = 98, 13.0%), and skin and soft tissue infection (n = 92, 12.2%) were the most common dermatologic diagnoses or diagnostic bundles issued to returning Canadian tourists (n = 754, 70.1% of total sample). Patients travelling for the purpose of immigration (n = 63, 5.9%) were significantly more likely to require inpatient management of their dermatologic diagnoses (p < 0.001) than those travelling for other purposes. INTERPRETATION: This analysis of surveillance data details the spectrum of travel-related dermatological conditions among returning Canadian travellers in this cohort, and provides an epidemiologic framework for Canadian physicians encountering these patients.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score0.746

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.067
GPT teacher head0.323
Teacher spread0.256 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations18
Published2015
Admission routes3
Has abstractyes

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