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Record W3094257749 · doi:10.1159/000512493

ARIA 2019 Care Pathways for Allergic Rhinitis in the Kuwait Health Care System

2020· review· en· W3094257749 on OpenAlexaff
Mona Al‐Ahmad, Jasmina Nurkić, Claus Bachert, Oliver Pfaar, Holger J. Schünemann, Anna Bedbrook, Jean Bosquet

Bibliographic record

VenueMedical Principles and Practice · 2020
Typereview
Languageen
FieldMedicine
TopicAllergic Rhinitis and Sensitization
Canadian institutionsMcMaster UniversityImpact
Fundersnot available
KeywordsMedicineHealth careAsthmaHealthcare systemIntegrated carePharmacotherapyIntensive care medicineFamily medicineMedical emergencyNursingImmunology

Abstract

fetched live from OpenAlex

A worldwide increase in prevalence of allergic diseases has led to adaptations in national and international health care systems. ARIA (Allergic Rhinitis and Its Impact on Asthma) initiative develops internationally applicable guidelines for allergic respiratory diseases. In collaboration with international initiatives, ARIA offers updates of real-life integrated care pathways (ICPs) for digitally assisted, integrated, and individualized treatment of allergic rhinitis (AR). This article presents certain aspects of the health care system in Kuwait with reference to the management of AR and the objective of introducing ICPs and adopting the latest ARIA recommendations. Guidelines for ICPs include aspects of patients and health care providers and cover key areas of management of AR. This model of guidelines supports real-life health care better than traditional models. ARIA recommendations will be locally integrated in the health care system with the aim of improving both pharmacotherapy and allergy immunotherapy.

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)0.002
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 score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.093
GPT teacher head0.374
Teacher spread0.281 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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