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Record W2765750457

Asthma Diagnosis, Phenotypes and Severity, and Indoor Microbial Exposure among Urban and Rural Children in Saskatchewan, Canada

2018· dissertation· en· W2765750457 on OpenAlexaboutno aff
Oluwafemi Oluwole

Bibliographic record

VenueUniversity Library - University of Saskatchewan (University of Saskatchewan) · 2018
Typedissertation
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental healthAsthmaMedicineGeographyDemographyImmunology
DOInot available

Abstract

fetched live from OpenAlex

Background: Childhood asthma is less common in rural compared to urban settings. This could be linked to possible asthma under-diagnosis in rural children. Furthermore, asthma presents with multiple phenotypes and degrees of severity; and may have varied associations with indoor microbial exposures. Objectives: i) to investigate if rural children experience more asthma under-diagnosis compared to urban children; ii) to investigate the relationship between endotoxin and beta-(1→3)-D-glucan (BDG) with atopic asthma and exercise-induced bronchospasm (EIB); and iii) to examine the associations between endotoxin and BDG with asthma severity. Methods: In 2015, following a 2013 cross-sectional study, we approached those who gave consent for further testing and repeated the survey and completed clinical assessments. The 2015 study included 335 schoolchildren (aged 7–17 years) in Saskatchewan, Canada. Play and mattress area settled dust sample collection was also completed. Asthma was identified based on survey responses and then based on a validated asthma algorithm. Children with confirmed asthma using the asthma algorithm (n = 116) formed the study population for the second (asthma phenotypes) and third (asthma severity) objectives. We evaluated asthma phenotypes based on skin prick testing and exercise challenge testing and asthma severity based on standard guidelines. Endotoxin and BDG were measured from dust samples using limulus amoebocyte lysate assay. Results: The study population was comprised of 73.4% (large urban, LU), 13.7% (small urban, SU) and 12.8% (rural, R). The proportions of participants with survey-based vs. algorithm-based asthma classification were: 28.5% vs. 33.3% (LU), 34.8% vs. 41.3% (SU), and 20.9% vs. 34.9% (R). Among the algorithm-based asthma cases, 71.1% were atopic, 22.4% had EIB, 75.9% had mild asthma, and 24.1% had moderate/severe asthma. Play area endotoxin was inversely associated with atopic asthma while mattress endotoxin was positively associated with EIB. Furthermore, mattress endotoxin was positively associated with moderate/severe asthma and decreased lung function while play area BDG was inversely association with moderate/severe asthma. Conclusion: The study revealed evidence of asthma under-diagnosis in rural children. Furthermore, the study provided evidence of varied associations between indoor microbial exposures and asthma phenotypes as well as asthma severity.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.020
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.004
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.002
GPT teacher head0.145
Teacher spread0.142 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2018
Admission routes1
Has abstractno

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