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Record W4229030731 · doi:10.1016/j.jaip.2022.04.034

Cigarette Smoking and Asthma

2022· review· en· W4229030731 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Journal of Allergy and Clinical Immunology In Practice · 2022
Typereview
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
FundersSandozMerck Sharp and DohmeUniversità di CataniaBoehringer IngelheimForest LaboratoriesGlaxoSmithKlineNovartisPfizerCanada Research ChairsAstraZenecaAmerican Academy of Allergy Asthma and Immunology
KeywordsAsthmaMedicineSmoking cessationIntensive care medicinePopulationClinical trialCigarette smokingEosinophilicCOPDAirwayImmunologyEnvironmental healthPathologyInternal medicineSurgery

Abstract

fetched live from OpenAlex

Globally, around half the adult asthma population are current or former cigarette smokers. Cigarette smoking and asthma interact to induce an "asthma-smoking phenotype(s)," which has important implications for diagnosis, pathogenic mechanisms, and management. The lack of progress in understanding the effects of smoking on adults with asthma is due in part to their exclusion from most investigative studies and large clinical trials. In this review, we summarize the adverse clinical outcomes associated with cigarette smoking in asthma, highlight challenges in diagnosing asthma among cigarette smokers with chronic respiratory symptoms, particularly in older individuals with a long-standing smoking history, and review pathogenic mechanisms involving smoking- and asthma-related airway inflammation, tissue remodeling, corticosteroid insensitivity, and low-grade systemic inflammation. We discuss the key components of management including the importance of smoking cessation strategies, evidence for the effectiveness of the Global Initiative for Asthma recommendations on treatment in cigarette smokers, and the role of treatable traits such as type 2 eosinophilic airway inflammation. Lastly, we provide an algorithm to aid clinicians to manage current and former smokers with asthma. In the future, controlled and pragmatic trials in real-world populations should include cigarette smokers with asthma to provide an evidence base for treatment recommendations.

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.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
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 integrity0.0000.003
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 head0.064
GPT teacher head0.413
Teacher spread0.348 · 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