MétaCan
Menu
Back to cohort
Record W4321225259 · doi:10.1186/s13223-023-00767-6

Recommendations from a Canadian Delphi consensus study on best practice for optimal referral and appropriate management of severe asthma

2023· article· en· W4321225259 on OpenAlexafffundvenueabout
Krystelle Godbout, Mohit Bhutani, L. Connors, Charles K. Chan, C. Connors, Del Dorscheid, G. Dyck, Vanessa Foran, Alan Kaplan, Julie C. Reynolds, Susan Waserman

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsCanadian Anesthesiologists' SocietyDalhousie UniversityUniversity of TorontoMcMaster UniversitySt. Paul's HospitalCanadian Respiratory Research NetworkUniversity of AlbertaUniversité Laval
FundersAstraZeneca CanadaAstraZeneca
KeywordsMedicineAsthmaFamily medicineReferralDelphi methodHealth careInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: In Canada, severe asthma affects an estimated 5-10% of people with asthma and is associated with frequent exacerbations, poor symptom control and significant morbidity from the disease itself, as well as the high dose inhaled, and systemic steroids used to treat it. Significant heterogeneity exists in service structure and patient access to severe asthma care, including access to biologic treatments. There appears to be over-reliance on short-acting beta agonists and frequent oral corticosteroid use, two indicators of uncontrolled asthma which can indicate undiagnosed or suboptimally treated severe asthma. The objective of this modified Delphi consensus project was to define standards of care for severe asthma in Canada, in areas where the evidence is lacking through patient and healthcare professional consensus, to complement forthcoming guidelines. METHODS: The steering group of asthma experts identified 43 statements formed from eight key themes. An online 4-point Likert scale questionnaire was sent to healthcare professionals working in asthma across Canada to assess agreement (consensus) with these statements. Consensus was defined as high if ≥ 75% and very high if ≥ 90% of respondents agreed with a statement. RESULTS: A total of 150 responses were received from HCPs including certified respiratory educators, respirologists, allergists, general practitioners/family physicians, nurses, pharmacists, and respiratory therapists. Consensus amongst respondents was very high in 37 (86%) statements, high in 4 (9%) statements and was not achieved in 2 (5%) statements. Based on the consensus scores, ten key recommendations were proposed. These focus on referrals from primary and secondary care, accessing specialist asthma services, homecare provision for severe asthma patients and outcome measures. CONCLUSIONS: Implementation of these recommendations across the severe asthma care pathway in Canada has the potential to improve outcomes for patients through earlier detection of undiagnosed severe asthma, reduction in time to severe asthma diagnosis, and initiation of advanced phenotype specific therapies.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.899

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.169
GPT teacher head0.479
Teacher spread0.311 · 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 designOther design
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

Citations22
Published2023
Admission routes4
Has abstractyes

Explore more

Same venueAllergy Asthma and Clinical ImmunologySame topicDelphi Technique in ResearchFrench-language works237,207