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Record W4403673662 · doi:10.1093/pch/pxae067.054

55 Post-pandemic paediatric asthma admissions: Clinical characteristics and outcomes of children hospitalized with asthma in 2022: The READAPT-Kids study cohort

2024· article· en· W4403673662 on OpenAlexaboutno aff
Min Jung Kim, Peter J. Gill, Haifa Mtaweh, Gabrielle Freire, Connie Yang, Jonathan H. Rayment, Sanjay Mahant, Shaun K. Morris, Claire Seaton

Bibliographic record

VenuePaediatrics & Child Health · 2024
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsnot available
Fundersnot available
KeywordsAsthmaMedicineCohortPandemicCohort studyPediatricsEmergency medicineCoronavirus disease 2019 (COVID-19)Internal medicineDisease

Abstract

fetched live from OpenAlex

Abstract Background Asthma exacerbations triggered by acute respiratory infections (ARIs) are a major cause of hospitalizations in children. There were large reductions in asthma admission during the SARS-CoV2 pandemic. Following the relaxation of public health interventions, there was a resurgence in admissions for ARIs. The effect of this rebound in ARIs on asthma management practices and outcomes is not well understood. Objectives To describe sociodemographic characteristics, etiology, management, and clinical outcomes of children and youth under the age of 18 years admitted to a tertiary care paediatric hospital with an acute asthma exacerbation from July 1, 2022 to Dec 31, 2022. Design/Methods An observational cohort study of children and youth less than 18 years, hospitalized with an acute asthma exacerbation from July 1, 2022 to Dec 31, 2022 at a single large Canadian children’s hospital. This was a subgroup analysis of the READAPT-Kids study cohort (Clinical chaRacteristics and outcomEs of hospitAlized children with Acute resPiratory infecTions.) Cases were identified using ICD-10-CA codes, then manually screened for inclusion. Detailed clinical and demographic information was extracted. Results Among 551 patients hospitalized with an ARI, 29.2% (n=161) were diagnosed with an asthma exacerbation. 99 were male (61.5%) with a median age of 3.8 years (IQR 2.2-6.3). 41.3% (n=64) had a previously documented asthma history, and of those, only 16.9% were taking any form of asthma therapy at admission. In hospital, 91.4% were given systemic corticosteroids, 86.5% had at least 1 viral pathogen identified, 72.2% had a chest x ray, 42.1% received antibiotics, and 23.7% had high flow nasal cannula oxygen outside of the paediatric intensive care (PICU). 22.4% (n=36), were admitted to the PICU, and 3.7% required invasive mechanical ventilation, there were no patient deaths. Median length of stay was 2.6 days (IQR 1.7–4.6 days). At discharge, 79.5% were prescribed regular inhaled corticosteroid therapy. Conclusion Asthma admissions accounted for a significant proportion of children hospitalized with ARIs in the post-pandemic era, with one fifth requiring transfer to PICU. CXR and antibiotic usage were high. Over 80% of those with a previous diagnosis of asthma were not taking inhaled corticosteroids at the time of admission.

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 score0.227
Threshold uncertainty score0.452

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.380
Teacher spread0.356 · 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
Published2024
Admission routes1
Has abstractyes

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