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Record W1988631473 · doi:10.2147/jaa.s14420

Current recommendations for the treatment of mild asthma

2010· article· en· W1988631473 on OpenAlexafffund
Neal Shahidi, Mark Fitzgerald

Bibliographic record

VenueJournal of Asthma and Allergy · 2010
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchGenentechAstraZenecaPfizer
KeywordsMedicineAsthmaExacerbationIntensive care medicineDiseaseAsthma managementPhysical therapyPediatricsInternal medicine

Abstract

fetched live from OpenAlex

Patients suffering from mild asthma are divided into intermittent or persistent classes based on frequency of symptoms and reliever medication usage. Although these terms are used as descriptors, it is important to recognize the approach of focusing on asthma control in managing asthma patients. Beta-agonists are considered first-line therapy for intermittent asthmatics. If frequent use of beta-agonists occurs more than twice a week, controller therapy should be considered. For persistent asthma, low-dose inhaled corticosteroids are recommended in addition to reliever medication. Compliance to regular therapy can pose problems for disease management, and while intermittent controller therapy regimens have been shown to be effective, it is imperative to stress the value of regular therapy especially if an exacerbation occurs. It is also important when such an approach is adopted that there is regular re-evaluations of asthma control. This is because regular anti-inflammatory therapy may become necessary if symptoms become more persistent. Other therapies are seldom needed. Antileukotrienes can be considered an option for mild asthma; however, studies have shown that they are not as effective as inhaled corticosteroids. Aside from therapy, patient education, which includes a written action plan, should be a component of the patient's strategy for disease management.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.977
Threshold uncertainty score0.190

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.027
GPT teacher head0.323
Teacher spread0.296 · 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 designNot applicable
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

Citations30
Published2010
Admission routes2
Has abstractyes

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