Development and Implementation of the AIDA International Registry for Patients With Still's Disease

Objective: Aim of this paper is to present the design, construction, and modalities of dissemination of the AutoInflammatory Disease Alliance (AIDA) International Registry for patients with systemic juvenile idiopathic arthritis (sJIA) and adult-onset Still's disease (AOSD), which are the pediatric and adult forms of the same autoinflammatory disorder. Methods: This Registry is a clinical, physician-driven, population- and electronic-based instrument implemented for the retrospective and prospective collection of real-world data. The collection of data is based on the Research Electronic Data Capture (REDCap) tool and is intended to obtain evidence drawn from routine patients' management. The collection of standardized data is thought to bring knowledge about real-life clinical research and potentially communicate with other existing and future Registries dedicated to Still's disease. Moreover, it has been conceived to be flexible enough to easily change according to future scientific acquisitions. Results: Starting from June 30th to February 7th, 2022, 110 Centers from 23 Countries in 4 continents have been involved. Fifty-four of these have already obtained the approval from their local Ethics Committees. Currently, the platform counts 290 users (111 Principal Investigators, 175 Site Investigators, 2 Lead Investigators, and 2 data managers). The Registry collects baseline and follow-up data using 4449 fields organized into 14 instruments, including patient's demographics, history, clinical manifestations and symptoms, trigger/risk factors, therapies and healthcare access. Conclusions: This international Registry for patients with Still's disease will allow a robust clinical research through collection of standardized data, international consultation, dissemination of knowledge, and implementation of observational studies based on wide cohorts of patients followed-up for very long periods. Solid evidence drawn from "real-life " data represents the ultimate goal of this Registry, which has been implemented to significantly improve the overall management of patients with Still's disease. NCT 05200715 available at

Clinical and laboratory features associated with macrophage activation syndrome in Still's disease: data from the international AIDA Network Still's Disease Registry

: To characterize clinical and laboratory signs of patients with still's disease experiencing macrophage activation syndrome (MAS) and identify factors associated with MAS development. patients with still's disease classified according to internationally accepted criteria were enrolled in the autoInflammatory disease alliance (AIDA) still's disease registry. clinical and laboratory features observed during the inflammatory attack complicated by MAS were included in univariate and multivariate logistic regression analysis to identify factors associated to MAS development. A total of 414 patients with Still's disease were included; 39 (9.4%) of them developed MAS during clinical history. At univariate analyses, the following variables were significantly associated with MAS: classification of arthritis based on the number of joints involved (p = 0.003), liver involvement (p = 0.04), hepatomegaly (p = 0.02), hepatic failure (p = 0.01), axillary lymphadenopathy (p = 0.04), pneumonia (p = 0.03), acute respiratory distress syndrome (p < 0.001), platelet abnormalities (p < 0.001), high serum ferritin levels (p = 0.009), abnormal liver function tests (p = 0.009), hypoalbuminemia (p = 0.002), increased LDH (p = 0.001), and LDH serum levels (p < 0.001). at multivariate analysis, hepatomegaly (OR 8.7, 95% CI 1.9-52.6, p = 0.007) and monoarthritis (OR 15.8, 95% CI 2.9-97.1, p = 0.001), were directly associated with MAS, while the decade of life at Still's disease onset (OR 0.6, 95% CI 0.4-0.9, p = 0.045), a normal platelet count (OR 0.1, 95% CI 0.01-0.8, p = 0.034) or thrombocytosis (OR 0.01, 95% CI 0.0-0.2, p = 0.008) resulted to be protective. clinical and laboratory factors associated with MAS development have been identified in a large cohort of patients based on real-life data

Clinical and laboratory features associated with macrophage activation syndrome in Still's disease : data from the international AIDA Network Still's Disease Registry

Abstract: To characterize clinical and laboratory signs of patients with Still's disease experiencing macrophage activation syndrome (MAS) and identify factors associated with MAS development. Patients with Still's disease classified according to internationally accepted criteria were enrolled in the AutoInflammatory Disease Alliance (AIDA) Still's Disease Registry. Clinical and laboratory features observed during the inflammatory attack complicated by MAS were included in univariate and multivariate logistic regression analysis to identify factors associated to MAS development. A total of 414 patients with Still's disease were included; 39 (9.4%) of them developed MAS during clinical history. At univariate analyses, the following variables were significantly associated with MAS: classification of arthritis based on the number of joints involved (p = 0.003), liver involvement (p = 0.04), hepatomegaly (p = 0.02), hepatic failure (p = 0.01), axillary lymphadenopathy (p = 0.04), pneumonia (p = 0.03), acute respiratory distress syndrome (p < 0.001), platelet abnormalities (p < 0.001), high serum ferritin levels (p = 0.009), abnormal liver function tests (p = 0.009), hypoalbuminemia (p = 0.002), increased LDH (p = 0.001), and LDH serum levels (p < 0.001). At multivariate analysis, hepatomegaly (OR 8.7, 95% CI 1.9-52.6, p = 0.007) and monoarthritis (OR 15.8, 95% CI 2.9-97.1, p = 0.001), were directly associated with MAS, while the decade of life at Still's disease onset (OR 0.6, 95% CI 0.4-0.9, p = 0.045), a normal platelet count (OR 0.1, 95% CI 0.01-0.8, p = 0.034) or thrombocytosis (OR 0.01, 95% CI 0.0-0.2, p = 0.008) resulted to be protective. Clinical and laboratory factors associated with MAS development have been identified in a large cohort of patients based on real-life data