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Record W2416433336 · doi:10.20452/pamw.446

Does early intervention with inhaled corticosteroids alter the natural history of mild persistent asthma?

2008· article· en· W2416433336 on OpenAlexaff
Parameswaran Nair, Marcel Tunks

Bibliographic record

VenuePolskie Archiwum Medycyny Wewnętrznej · 2008
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsSt. Joseph’s Healthcare Hamilton
Fundersnot available
KeywordsMedicineInhaled corticosteroidsAsthmaLeukotriene receptorNatural historyMontelukastIntensive care medicineFluticasoneSputumEosinophilInhalationB2 receptorPediatricsAnesthesiaInternal medicineReceptorPathology

Abstract

fetched live from OpenAlex

In most patients, both adults and children, who have a new diagnosis of asthma and whose symptoms are mild but persistent, treatment with inhaled corticosteroids (ICS) should be recommended as soon as the diagnosis is made. This is a cost-effective and safe treatment. Patients should be cautioned that their asthma will not be cured with short-term treatment and that their symptoms may recur and their lung function may decline again if treatment is discontinued. If patients are reluctant to use ICS daily for long periods of time, it would be reasonable to delay the onset of treatment with ICS. They could subsequently be managed with intermittent therapy with either ICS or in combination with other medications, such as long-acting beta-agonists. Initial therapy with leukotriene receptor antagonist is not likely to be as effective as initial therapy with ICS. Since treatment adjustments based on eosinophil counts in sputum can reliably predict short-term responses to corticosteroids and help identify the appropriate add-on therapy, it may be useful to use this measurement, when available, to guide intermittent therapy.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.240
Teacher spread0.224 · 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 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

Citations0
Published2008
Admission routes1
Has abstractyes

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