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Record W6959692766 · doi:10.11575/prism/44662

Is Universal Screening Necessary? Incidence of Tuberculosis among Tibetan Refugees Arriving in Calgary, Alberta

2016· other· en· W6959692766 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Calgary · 2016
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvances in Cucurbitaceae Research
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeIncidence (geometry)TuberculosisActive tuberculosisChest radiographCohortHistory of tuberculosisRetrospective cohort study

Abstract

fetched live from OpenAlex

Background. Canadian policy requires refugees with a history of tuberculosis (TB) or abnormal chest radiograph to be screened after arrival for TB. However, Tibetan refugees are indiscriminately screened, regardless of preimmigration assessment. We sought to determine the incidence of latent (LTBI) and active TB, as well as treatment-related outcomes and associations between preimmigration factors and TB infection among Tibetan refugees arriving in Calgary, Alberta. Design. Retrospective cohort study including Tibetan refugees arriving between 2014 and 2016. Associations between preimmigration factors and incidence of latent and active TB were determined using Chi-square tests. Results. Out of 180 subjects, 49 percent had LTBI. LTBI was more common in migrants 30 years of age or older (). Treatment initiation and completion rates were high at 90 percent and 76 percent, respectively. No associations between preimmigration factors and treatment completion were found. A case of active TB was detected and treated. Conclusion. Within this cohort, the case of active TB would have been detected through the usual postsurveillance process due to a history of TB and abnormal chest radiograph. Forty-nine percent had LTBI, compared to previously quoted rates of 97 percent. Tibetan refugees should be screened for TB in a similar manner to other refugees resettling in Canada.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.738
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.257
Teacher spread0.250 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2016
Admission routes1
Has abstractyes

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