Southern Alberta Vasculitis Patient Registry: Creation and Utility
Notice bibliographique
Résumé
INTRODUCTION Vasculitides encompass a group of rare diseases where inflammation of vessels causes multisystem organ damage. Incidence, currently estimated to be 10-20/million/year, shows an increasing trend in both children and adults [1]. Due to the nature of the disease, patients need ongoing follow-up to prevent relapse, avert organ damage, and control factors associated with increased mortality. However, vasculitides can be difficult to diagnose due to the diversity of presentation and lack of disease-specific diagnostic tools. As with other rare diseases, the limited number of patients impairs recruitment into clinical trials, impedes research, and hinders the generation of evidence-based treatment recommendations and protocols [2]. Moreover, the low patient numbers provide a barrier to obtaining reliable rare disease prevalence statistics and to gaining a clear understanding of the natural history of specific vasculitides. To address some of these limitations, we propose to generate a prospective vasculitis registry for patients in Southern Alberta. This initial registry will serve as a foundation for collaboration with other centres at the provincial, national, and international levels (Figure 1). The establishment of such a registry will create a framework for knowledge translation, discovery, and best practice management. METHODS Recruitment will initially be limited to patients with vasculitis residing in Southern Alberta referred to the Rheumatology division in Calgary through the central triage system. Ethics approval was obtained in May 2012. Patients complete written informed consent at their baseline visit. Upon consenting, the patients are examined yearly by Dr. Aurore Fifi-Mah, a Rheumatologist at the South Health Campus in Calgary, Alberta. Patients also complete yearly clinical case report forms and a Patient Quality of Life form (SF-36). Patient consent also extends to the collection of de-identified sera for storage in the Mitogen Advanced Diagnostics Laboratory in Calgary, Alberta, under the direction of Dr. Fritzler. These sera will be analyzed for the presence of new target antibodies and proteins to enhance understanding of the pathogenesis and prognosis of vasculitis. As this is an observational study, no power calculation is involved. Descriptive analysis will be used to summarize participant characteristics and comorbid conditions. RESULTS The initial project infrastructure has been successfully established. To date, 107 patients have been recruited with the following diagnosis (patient numbers are in brackets): ANCA-associated Vasculitis (12), Behcet’s Disease (7), Connective Tissue Disease (6), CNS Vasculitis (4), Cryoglobulinemia (1), Giant Cell Arteritis (9), IgA Vasculitis (5), Leukoclastic Angiitis (11), Neurosarcoidosis (1), NMDA Receptor Encephalitis (1), Polyarteritis Nodosa (11), Polymyalgia Rheumatica (13), Takayasu’s Arteritis (6), and Vasculitis Associated with Other Disease (20). DISCUSSION AND CONCLUSIONS The establishment of a Southern Alberta Vasculitis Patient Registry addresses the pervasive issues of inaccurate rare disease statistics, inadequate understanding of disease natural history, and limited diagnostic and treatment regimes. Through systematic collection and analysis of data, the registry will create a foundation of knowledge on which to build informed, standardized models of care. Moreover, the additional benefit of serum analysis may permit the discovery of specific biomarkers and prognostic factors to classify and predict the future course of different vasculitis subtypes. This will permit individualized, patient-centred treatment. The extension of this project to include centres provincially, nationally, and internationally would magnify the utility of the initial project. The previous establishment of provincially-based vasculitis research centres through CanVasc expedites project expansion.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,009 | 0,020 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,006 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,005 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».