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Enregistrement W2149415552 · doi:10.1186/1710-1492-6-s4-a2

Knowledge translation opportunities in allergic disease and asthma

2010· article· en· W2149415552 sur OpenAlexaffvenueabout
Diana Royce

Notice bibliographique

RevueAllergy Asthma and Clinical Immunology · 2010
Typearticle
Langueen
DomaineMedicine
ThématiqueAsthma and respiratory diseases
Établissements canadiensMcMaster University
Organismes subventionnairesnon disponible
Mots-clésAsthmaExcellenceAllergyMedicineDiseaseFood allergyAllergen immunotherapyFamily medicineAllergenEnvironmental healthImmunologyPolitical science

Résumé

récupéré en direct d'OpenAlex

AllerGen NCE Inc., the Allergy, Genes and Environment Network, is a national, multi-disciplinary, multi-sectoral network for research and discovery, knowledge translation and capacity building. AllerGen is dedicated to improving the quality of life for allergy asthma and related immune disease sufferers by supporting research that leads to new diagnostic tests, better medications, more effective public policies and an increase in the number of medical professionals researching and practicing in this area. The Networks of Centres of Excellence (NCE) program, of which AllerGen is a part, is a strategic initiative aligned with Canada’s Science and Technology strategy. The NCE program aims to close the ‘development-to-delivery’ gap, and accelerate the rate at which research results contribute to new, evidence-based, cost-effective policies, products and services that generate social and economic benefits for Canadians. The burden of allergy, asthma and related immune disease is significant and growing world-wide, and while the underlying causes of these diseases are actively being studied, the origins of these diseases are still not well understood. According to the results of the International Study of Asthma and Allergies in Childhood (ISAAC) Study, Phase III (2003) results, 47% of Canadian children have suffered from allergic rhinitis; 39% have experienced wheezing; 22.4% have been diagnosed with asthma; and, 19% have experienced atopic eczema [1]. According to Health Canada, non-food allergies are now the most common chronic condition in Canadians 12 years of age and older [2]. The economic impact of these diseases in Canada is in excess of $15 billion annually, when one includes the cost of ambulatory care, in-patient stays, emergency department visits, physician and facility payments, prescribed medications and productivity losses at school, work and at home as a direct result of these diseases [3]. This annual cost is comparable to the economic impact of arthritis and other chronic conditions. Ontario data show that 14% of all asthma-related emergency department visits occur in children between birth and 4 years of age, and that 21% of asthma prevalent cases were children and adolescents up to 19 years of age [4]. However, hospital admissions for asthma have decreased for both children and adults since 1996, and asthma as a cause of death is relatively uncommon and decreasing among all age groups in the developed world. Globally, asthma is more prevalent among the developed countries and in major city centres [5]. Among the countries with somewhat lower prevalence rates, such as India and China, which represent 37% of the global population, recent research suggests that as these countries industrialize, allergy, asthma and related immune disease prevalence rates are rising rapidly, mirroring the experience of more developed countries. Given the Canadian Institutes of Health Research’s strategic vision to position Canada as a world leader in the creation and use of knowledge derived from health research that benefits Canadians and the global community, Canadian researchers and their international partners have a significant opportunity to work in collaborative networks to accelerate the translation of research into practice, and knowledge to action, to improve allergic disease and asthma awareness, education, management and control. A recent analysis by Teresa To, from The Hospital for Sick Children [6], reveals that for Ontarians, the lifetime risk of developing chronic asthma is 1 in 3 - the same as the risk of developing cancer and diabetes. However, unlike cancer and diabetes, the substantial lifetime risk of asthma begins at an early stage in life and persists throughout the life span, triggering heightened disease burden, potential productivity loss and other economic costs. Building upon the work done in 2004 by a team led by Rejean Landry, AllerGen developed a publicly available KT planning tool called Knowledge Translation Planning Tools for Allergic Disease Researchers. This tool provides a guide for researchers, their stakeholders and partners to collaboratively develop translational strategies and tactics that will help accelerate the rate of dissemination, uptake and application of allergy, asthma and related immune disease research to improve the quality of life for patients, facilitate optimal care by health providers and reduce the economic drag resulting from the burden of these diseases [7]. Working with national and international partners, such as the Karolinska Institute in Sweden, AllerGen is committed to facilitating efforts to improve allergic disease and asthma management and control, discover the root causes of these diseases and accelerate the application of research findings and KT activities for social and economic benefits nationally and globally.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,027
score de la tête « metaresearch » (Gemma)0,058
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: aucune
Score de désaccord entre enseignants0,032
Score d'incertitude au seuil0,145

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0270,058
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0040,005
Études des sciences et des technologies0,0040,010
Communication savante0,0130,014
Science ouverte0,0030,012
Intégrité de la recherche0,0080,007
Charge utile insuffisante (le modèle a refusé de juger)0,0320,004

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,066
Tête enseignante GPT0,346
Écart entre enseignants0,279 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2010
Routes d'admission3
Résumé présentoui

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