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Record W2322879294 · doi:10.1097/pec.0b013e31821314b0

Seasonality Patterns in Croup Presentations to Emergency Departments in Alberta, Canada

2011· article· en· W2322879294 on OpenAlexafffundabout
Rhonda J. Rosychuk, Terry P. Klassen, Donald C. Voaklander, Ambikaipakan Senthilselvan, Brian H. Rowe

Bibliographic record

VenuePediatric Emergency Care · 2011
Typearticle
Languageen
FieldMedicine
TopicOtolaryngology and Infectious Diseases
Canadian institutionsUniversity of ManitobaChildren's Hospital Research Institute of ManitobaWomen and Children’s Health Research InstituteUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsCroupMedicineSeasonalityMedical emergencyEmergency medicinePediatrics

Abstract

fetched live from OpenAlex

INTRODUCTION: Croup is a common pediatric respiratory illness presenting to the emergency department (ED) in the fall and winter months. Most cases are caused by parainfluenza viruses. We examine the monthly patterns of young children who made croup-related visits to EDs in Alberta, Canada. METHODS: Emergency department visits were identified in provincial administrative databases to obtain all ED encounters for croup made by young children (aged ≤2 years) during 6 years (April 1, 1999, to March 30, 2005). Time series models (seasonal autoregressive integrated moving average) were developed to capture temporal and seasonal trends and predict future presentations. RESULTS: Overall, 27,355 croup-related ED visits were made during the study period. More males (62%) than females presented, and most (43%) were younger than 1 year. Differences were observed in the number of visits made in odd and even years. Peak visits occurred in November for odd years and in February for other years. Strong seasonal patterns at 12 months were detected and included in the modeling. CONCLUSIONS: We observed the presence of a clear biennial pattern of croup ED visits. The seasonal autoregressive moving average models and predictions offer insights into the epidemiology of croup-related visits to EDs and may be helpful in planning both research and resource needs.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.017
GPT teacher head0.279
Teacher spread0.262 · 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 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

Citations21
Published2011
Admission routes3
Has abstractyes

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