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Record W1974308284 · doi:10.3109/02770900903350473

The Added Burden of Comorbidity in Patients with Asthma

2009· article· en· W1974308284 on OpenAlexafffundabout
Tingting Zhang, Bruce Carleton, Robert J. Prosser, Anne Marie Smith

Bibliographic record

VenueJournal of Asthma · 2009
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversity of British Columbia
FundersMichael Smith Health Research BC
KeywordsMedicineAsthmaComorbidityIntensive care medicinePsychiatryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Compare the prevalence of comorbidities in adults with and without asthma in Canada and investigate the association between comorbidities in patients with asthma and the occurrence of asthma symptoms or attacks. METHODS: Survey data from the 2005 Canadian Community Health Survey (CCHS) were analyzed. A total of 132,221 Canadians participated in the national survey; 10,089 adult respondents from 10 Canadian provinces and 3 territories reported having asthma. Analyses focused on 11 major chronic comorbidities. RESULTS: Respondents with asthma were more likely to have comorbidities except cancer; 31% of respondents with asthma and comorbidities reported their health status to be fair or poor. For respondents with asthma, non-asthma chronic respiratory disease, mental illness, and allergy were significantly associated with having asthma symptoms or attacks. CONCLUSIONS: Many Canadians with asthma report a high comorbidity burden. These patients will likely require more health services and more complex health management strategies. Comorbid conditions should be clearly identified with particular emphasis on management of mood disorders and anxiety because these conditions are likely to increase asthma symptomatology and may be unrecognized by clinicians.

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 score0.400
Threshold uncertainty score0.205

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 head0.007
GPT teacher head0.246
Teacher spread0.239 · 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

Citations61
Published2009
Admission routes3
Has abstractyes

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