A10: Younger Age and Severity of Renal Presentation Distinguishes Microscopic Polyangiitis From Granulomatosis With Polyangiitis in Children: An ARChiVe Study
Notice bibliographique
Résumé
Background/Purpose: Comparisons of pediatric ANCA‐associated vasculitis subtypes (AAV) are limited by the paucity of reported cases, standardized definitions, and overlapping classification criteria. Published work from ARChiVe (A Registry for Childhood Vasculitis) demonstrated modifications of validated classification algorithms applied to pediatric patients with AAV can classify each patient to mutually exclusive diagnostic categories. We compared presenting features of children with microscopic polyangiitis (MPA) and granulomatosis with polyangiitis (GPA) classified according to this methodology. Methods: A pediatric modification of the European Medicines Agency (EMA) algorithm for classifying AAV and polyarteritis nodosa (incorporating the EULAR/PRINTO/PRES pediatric classification criteria for GPA) was applied to patients in ARChiVe censored to April 2012. We compared characteristics of patients classified as having MPA and GPA. STATA (Statcorp, 2013) was used to calculate frequencies, percentages, and chi‐squared with fisher's exact for categorical variables and means, standard deviations, and t‐tests for continuous variables. Results: One hundred fifty‐two of 227 children in ARChiVe met criteria for diagnosis of MPA (n = 22) or GPA (n = 130). Characteristics and presenting features are shown in Table . Children with MPA were younger at diagnosis (mean diff. 2.7y, p = <0.01). Renal involvement was predominant in both groups. Renal biopsies in 40% of both groups were consistent with pauci‐immune, necrotizing glomerulonephritis. Children with MPA had higher rates of nephrosis, renal failure requiring dialysis, and abnormal creatinine clearance (Table ). Upper and lower airway involvement was more prevalent among those with GPA largely in accordance with surrogate GPA features used to differentiate GPA and MPA in the EMA algorithm. The majority of patients presented with constitutional symptoms, however, other organ systems were less frequently involved. Most patients received combination therapy corticosteroids and cytoxan (64% MPA, 81% GPA) with additional plasmapheresis (29% MPA, 21% GPA), rituximab (14% MPA, 3% GPA) or methotrexate (7% MPA, 1% GPA). The remainder of children received combination corticosteroids and methotrexate or rituximab, without cytoxan (12% MPA, 11% GPA). A larger proportion of patients with MPA received antihypertensive agents and/or ACE inhibitors (64% vs 35%, p = 0.01). Characteristics & Presenting Clinical Features of children with microscopic polyangiitis or granulomatosis with polyangiitis in the ARChiVe cohort (n = 152) Algorithm‐derived diagnosis Characteristic/Feature MPA (n = 22) GPA (n = 130) p‐value Female, n(%) 15 (68) 83 (64) 0.81 Caucasian, n (%) 11 (50) 85 (66) 0.231 Age at diagnosis, yrs, mean (sd) 11.6 (5) 14.2 (3) <0.01* Median (range) 12.8 (9–15) 14.9 (4–19) Symptom duration prior to diagnosis, mos, mean (sd) 4.4 (9) 5.2 (10) 0.72 Median (range) 3.4 (0–35.8) 4.8 (0–66.8) MD‐assigned diagnosis (clinical diagnosis) MPA or isolated MPA 8 (36) 18 (14) 0.027* WG or limited WG 7 (32) 107 (82) <0.01* ANCA 3 (14) 1 (1) 0.01* Unclassified 4 (18) 4 (3) 0.02* General Features Fatigue 19 (86) 113 (87) 1.00 Fever 10 (46) 71 (55) 0.49 Weight loss 10 (46) 60 (46) 1.00 Renal 18 (82) 103 (79) 1.00 Hypertension 8 (36) 28 (22) 0.17 Hematuria and proteinuria with red blood cell casts 16 (73) 97 (75) 0.80 Nephrotic range proteinuria with edema 6 (27) 14 (11) 0.04* Renal failure requiring dialysis 7 (32) 17 (13) 0.05* Creatinine clearance >25% lower limit of normal 8 (89) 18 (36) <0.01* Biopsy‐proven glomerulonephritis 6 (27) 28 (22) 0.58 Pulmonary 9 (41) 105 (81) <0.01* Chronic cough 6 (27) 79 (61) <0.01* Shortness of breath 4 (18) 63 (49) 0.01* Hemoptysis/alveolar hemorrhage 3 (14) 54 (42) 0.02* Fixed pulmonary infiltrates ± cavitations, nodules 4 (18) 99 (76) <0.01* Head, Ear, Nose, & Throat 4 (18) 97 (75) <0.01* Bloody nasal discharge ± crusting 0 (0) 68 (52) <0.01* Chronic sinusitis, otitis, or mastoiditis 0 (0) 63 (48) <0.01* Subglottic involvement 0 (0) 16 (12) 0.13 Cranial bone ± cartilage destruction 0 (0) 10 (8) 0.36 Acute hearing loss 0 (0) 15 (12) 0.13 Red ± painful eye conditions 2 (9) 34 (26) Gastrointestinal/Abdominal 15 (68) 51 (39) 0.01* Chronic nausea 9 (41) 17 (13) <0.01* Skin 10 (45) 71 (55) 0.49 Musculoskeletal 80 (62) 14 (64) 1.00 Nervous System 35 (27) 6 (27) 1.00 Cardiovascular 9 (7) 1 (5) 1.00 ANCA Serology pANCA or anti‐MPO 14 (70) 35 (29) <0.01 cANCA or anti‐PR3 6 (30) 86 (71) <0.01 Conclusion: Children with AAV had predominantly renal and constitutional manifestations. Younger age and a more severe renal disease phenotype may characterize MPA with patients requiring additional treatment for the consequences of kidney disease. The wide variations in time to diagnosis continue to suggest that pediatric AAV is poorly recognized. Ongoing biomarker‐driven studies may complement systems for subclassifying patients with
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 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 ».