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Record W2086908717 · doi:10.1002/ppul.10307

Hospital readmissions for asthma in children and young adults in Canada

2003· article· en· W2086908717 on OpenAlexafffundabout
Yue Chen, Robert Dales, Paula Stewart, Helen Johansen, Geoffroy Scott, Gregory Taylor

Bibliographic record

VenuePediatric Pulmonology · 2003
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsStatistics CanadaHealth CanadaUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsMedicineAsthmaIncidence (geometry)PediatricsDemographyAge groupsMultivariate analysisInternal medicine

Abstract

fetched live from OpenAlex

To examine the incidence rate of hospital readmission for asthma in relation to sex and age among Canadian children and young adults, we used data from 86,863 subjects under age 20 years when they had a first admission for asthma as 1 of first 5 diagnoses in Canada between April 1, 1994 and March 31, 1997. We calculated age- and sex-specific incidence rates, and used the Cox proportional hazards model for multivariate analysis. Of these subjects, 20,277 (23.3%) were readmitted to hospital for asthma during the study period. After adjusting for length of stay for first admission and province, the rate ratio for females vs. males was 0.86 for those under age 1 year, and close to unity for the 1-4-year and 5-9-year age groups, whereas it was 1.47 and 1.35 for the 10-14-year and 15-19-year age groups, respectively. The data showed similar trends for rehospitalization asthma as a primary diagnosis. The incidence rate of rehospitalization showed little sex difference between ages 1-9 years, but was markedly higher in females than in males 10-19 years of age. Airway size, female hormonal changes, increased use of cosmetic products, and cigarette smoking among adolescent girls may contribute to the age- and sex-differences in adolescence.

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 score0.103
Threshold uncertainty score0.851

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 head0.004
GPT teacher head0.216
Teacher spread0.212 · 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

Citations36
Published2003
Admission routes3
Has abstractyes

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