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Record W2901794969 · doi:10.1097/aci.0000000000000494

Asthma, obesity and targeted interventions: an update

2018· review· en· W2901794969 on OpenAlexaff
Helen Clare Ricketts, Douglas C. Cowan

Bibliographic record

VenueCurrent Opinion in Allergy and Clinical Immunology · 2018
Typereview
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsMedicineAsthmaWeight lossObesityQuality of life (healthcare)Pulmonary rehabilitationPhysical therapyPsychological interventionRehabilitationIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Obese asthma is now widely recognized as a phenotype of difficult asthma that is common and less responsive to traditional asthma treatments, so identifying specific treatments is increasingly important. RECENT FINDINGS: Obesity can lead to asthma through a complex relationship of causes including mechanical, inflammatory, metabolic and genetic factors. Exercise programmes including pulmonary rehabilitation, weight loss via dietary restriction, exercise and bariatric surgery, or combinations of all of these can improve quality of life, symptoms, and exercise capacity, with reductions in medication use and exacerbations, and represent tailored treatment for this phenotype of severe difficult to treat asthmatic patients. SUMMARY: Exercise programmes and pulmonary rehabilitation, weight loss programmes targeting 5-10% weight loss and bariatric surgery are effective treatments for the obese asthma phenotype.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.002

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 head0.151
GPT teacher head0.475
Teacher spread0.323 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations16
Published2018
Admission routes1
Has abstractyes

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