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Record W2155068501 · doi:10.1186/1710-1492-4-3-125

Evaluating the Safety of Intranasal Steroids in the Treatment of Allergic Rhinitis

2008· article· en· W2155068501 on OpenAlexvenueno aff
Ketan Sheth

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2008
Typearticle
Languageen
FieldMedicine
TopicAllergic Rhinitis and Sensitization
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineNasal administrationAsthmaIntensive care medicineSafety profileInhaled corticosteroidsAdverse effectImmunologyInternal medicine

Abstract

fetched live from OpenAlex

: Given that intranasal corticosteroids (INCs) are widely considered first-line therapies for treatment of rhinitis, it is important for the clinician to be comfortable with the side-effect profile and be able to discuss potential safety concerns regarding these therapies. Among the safety concerns with the use of INCs are the potential for growth suppression both short and long term, the potential for hypothalamic-pituitary-adrenal axis suppression, ocular safety, and the use of INCs concomitantly with inhaled corticosteroids in asthma patients. As all clinicians are aware, each patient can have individual responses to both efficacy and safety; however, the data reviewed suggest that the benefits outweigh the potential risks. Understanding the potential concerns and the data behind these concerns should give clinicians the information to be able to discuss this with patients and parents to incorporate appropriate therapy for those with allergic rhinitis.

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)0.010
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.015
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 head0.073
GPT teacher head0.367
Teacher spread0.294 · 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 designSystematic review
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

Citations21
Published2008
Admission routes1
Has abstractyes

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