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Record W1532736258 · doi:10.1093/pch/17.5.e34

Prevalence of hypothalamic-pituitary-adrenal axis suppression in children treated for asthma with inhaled corticosteroid

2012· article· en· W1532736258 on OpenAlexaff
Ryan Smith, Kim Downey, Michelle Gordon, Alan Hudak, Rob Meeder, Sarah Barker, W Gary Smith

Bibliographic record

VenuePaediatrics & Child Health · 2012
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsWestern UniversityNOSM UniversityUniversity of Toronto
Fundersnot available
KeywordsCorticosteroidAsthmaMedicineHypothalamic–pituitary–adrenal axisInhaled corticosteroidsInternal medicineEndocrinologyAnesthesiaPediatricsHormone

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the prevalence of hypothalamic-pituitary-adrenal (HPA) axis suppression in asthmatic children on inhaled corticosteroids (ICS). METHODS: Clinical and demographic variables were recorded on preconstructed, standardized forms. HPA axis suppression was measured by morning serum cortisol levels and confirmed by low-dose adrenocorticotropic hormone stimulation testing. RESULTS: In total, 214 children participated. Twenty children (9.3%, 95% CI 5.3% to 13.4%) had HPA axis suppression. Odds of HPA axis suppression increased with ICS dose (OR 1.005, 95% CI 1.003 to 1.009, P<0.001). All children with HPA axis suppression were on a medium or lower dose of ICS for their age (200 μg/day to 500 μg/day). HPA axis suppression was not predicted by drug type, dose duration, concomitant use of long-acting beta-agonist or nasal steroid, or clinical features. CONCLUSION: Laboratory evidence of HPA axis suppression exists in children taking ICS for asthma. Children should be regularly screened for the presence of HPA axis suppression when treated with high-dose ICS (>500 μg/day). Consideration should be given to screening children on medium-dose ICS.

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 score0.013
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.011
GPT teacher head0.264
Teacher spread0.253 · 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

Citations45
Published2012
Admission routes1
Has abstractyes

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