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It is unclear when the synovial-based inflammatory process of gout begins. The aim of this study was to determine the percentage of patients with inter-critical gout who have chronic synovial-based inflammation as evidenced by synovial pannus on a contrast-enhanced magnetic resonance imaging (MRI) of their most involved joint and determine if the presence and/or severity correlates with their serum urate levels. All patients received a 3 T MRI of their index joint, serum urate level, CRP, and creatinine. The primary endpoint was to determine the prevalence of synovial pannus and the correlation of serum urate levels with the presence and/or severity of the synovial pannus on that same joint. MRI erosions, tophi, swelling, effusion, and osteitis were also documented. Seventy-two of 74 subjects (90 % men) completed the protocol. Fifty-three of 72 (74 %) index joints were the first metatarsophalangeal joint. Thirty-nine (54.2 %) of the patients were on urate-lowering therapy; 15 (20.8 %) and 7 (9.7 %) were taking colchicine or a NSAID daily, respectively. Of the 72 subjects, 63 (87.5 %) had synovial pannus on their MRI with good inter-reader agreement between the two radiologists. The mean serum urate level was 7.93 mg/dL. There was no correlation with the presence ( p  = 0.33) or severity ( p  = 0.34) of synovial pannus and serum urate levels. There was also no correlation with the presence or severity of synovial pannus and the secondary endpoints. The majority of patients with inter-critical gout have evidence of chronic synovial-based inflammation. However, the presence and severity of this inflammation do not appear to correlate with serum urate levels.

The COVID-19 pandemic has highlighted a need for better understanding of countries’ vulnerability and resilience to not only pandemics but also disasters, climate change, and other systemic shocks. A comprehensive characterization of vulnerability can inform efforts to improve infrastructure and guide disaster response in the future. In this paper, we propose a data-driven framework for studying countries’ vulnerability and resilience to incident disasters across multiple dimensions of society. To illustrate this methodology, we leverage the rich data landscape surrounding the COVID-19 pandemic to characterize observed resilience for several countries (USA, Brazil, India, Sweden, New Zealand, and Israel) as measured by pandemic impacts across a variety of social, economic, and political domains. We also assess how observed responses and outcomes (i.e., resilience) of the COVID-19 pandemic are associated with pre-pandemic characteristics or vulnerabilities, including (1) prior risk for adverse pandemic outcomes due to population density and age and (2) the systems in place prior to the pandemic that may impact the ability to respond to the crisis, including health infrastructure and economic capacity. Our work demonstrates the importance of viewing vulnerability and resilience in a multi-dimensional way, where a country’s resources and outcomes related to vulnerability and resilience can differ dramatically across economic, political, and social domains. This work also highlights key gaps in our current understanding about vulnerability and resilience and a need for data-driven, context-specific assessments of disaster vulnerability in the future.