The Global aHUS Registry: Characteristics of 826 Patients with Atypical Hemolytic Uremic Syndrome
Notice bibliographique
Résumé
Abstract Background: Atypical hemolytic uremic syndrome (aHUS) is a rare, genetic, life-threatening disease predominantly caused by chronic, uncontrolled complement activation that leads to thrombotic microangiopathy and renal and other end-organ damage. The aHUS Registry, established in April 2012, is an observational, noninterventional, multicenter, global initiative to collect information on patient outcomes regardless of treatment approach. It facilitates availability of follow-up data for eculizumab. Methods: Patients with clinical diagnoses of aHUS (irrespective of identified complement abnormality or treatment) are eligible. Demographic, medical/disease history, and treatment outcomes data are collected at enrollment and prospectively thereafter. Results: By June 30, 2015, 826 patients enrolled (Table). Overall, 54.7% of patients, including 45.1% of pediatric and 62.7% of adult patients, were female. Patients were most commonly enrolled after their first TMA event. Thrombosis occurred more frequently in adult than pediatric patients. Nonrenal conditions, including gastrointestinal, cardiovascular, central nervous system, and pulmonary, were common in both age groups and occurred in 11.0%‒20.3% overall. Eculizumab was administered to 57.3% of patients, of whom 87.3% were treated prior to enrollment. Conclusions: Registry baseline characteristics demonstrate differences between pediatric and adult patients with aHUS, notably frequencies of thrombosis. Nonrenal conditions are frequent in both age groups. Ongoing and future analyses will further enhance understanding of aHUS history and progression. Additional clinical sites are encouraged to enroll patients to facilitate knowledge acquisition and optimization of patient care and quality of life. Disclosures Licht: Alexion Pharmaceuticals: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Achillon: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Ardissino:Alexion Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees. Ariceta:Alexion Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees. Cohen:Astellas: Consultancy; Alexion Pharmaceuticals: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy; Merck: Consultancy; Genentech: Research Funding. Gasteyger:Alexion Pharma International SàRL: Employment, Equity Ownership. Greenbaum:Alexion Pharmaceuticals: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Ogawa:Alexion Pharmaceuticals: Employment, Equity Ownership. Kupelian:Alexion Pharmaceuticals: Employment, Equity Ownership. Schaefer:Alexion Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees. Vande Walle:Alexion Pharmaceuticals: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Frémeaux-Bacchi:Alexion Pharmaceuticals: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».