A recent retrospective study involving 292 patients with newly diagnosed gout highlights the potential of musculoskeletal ultrasound findings to predict carotid plaque vulnerability, a significant indicator of cerebrovascular events like stroke. The research identified three gout-related factors—presence of tophi, power Doppler signal intensity, and the frequency of gout flares—as independent predictors of plaque instability. Utilizing machine learning, a predictive model integrating these indicators along with traditional cardiovascular risk factors displayed remarkable accuracy, suggesting implications for improved cardiovascular risk stratification in gout patients. Limitations include the study's retrospective nature and incomplete lifestyle data.

Source: Frontiers