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Record W58330457

Risk factors for tuberculosis in Greenland: case-control study.

2011· article· en· W58330457 on OpenAlexaboutno aff
K. Ladefoged, Thomas Rendal, Turid Bjarnason Skifte, Martin Andersson, Bolette Søborg, Anders Koch

Bibliographic record

VenuePubMed · 2011
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDemographyPopulationTuberculosisRisk factorEnvironmental healthLogistic regressionIncidence (geometry)UnderweightEthnic groupObesityInternal medicineOverweight
DOInot available

Abstract

fetched live from OpenAlex

SETTING AND OBJECTIVE: Despite several efforts aiming at disease control, the incidence of tuberculosis (TB) remains high in Greenland, averaging 131 per 100,000 population during the period 1998-2007. The purpose of the present study was to disclose risk factors for TB. METHODS: A case-control study was performed among 146 patients diagnosed with TB in the period 2004-2006. For each patient, four healthy age- and sex-matched control persons living in the same district were included. All participants completed a questionnaire regarding socio-demographic and lifestyle factors. Risk factor analyses were carried out using logistic regression models. RESULTS: Factors associated with TB were Inuit ethnicity, living in a small settlement, unemployment, no access to tap water, no bathroom or flushing toilet, underweight, smoking, frequent intake of alcohol and immunosuppressive treatment. The multivariate model showed that Inuit ethnicity (OR 15.3), living in a settlement (OR 5.1), being unemployed (OR 4.1) and frequent alcohol use (OR 3.1) were independent determinants of risk. Unemployment was associated with the highest population-attributable risk (29%). CONCLUSION: Risk factors associated with living in a settlement should be further explored and an investigation of genetic susceptibility is warranted.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.047
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.068
GPT teacher head0.303
Teacher spread0.235 · 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

Citations43
Published2011
Admission routes1
Has abstractyes

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