A nomogram for predicting coronary artery lesions in patients with Kawasaki disease.

As an acute systemic vasculitis, Kawasaki disease (KD) could develop coronary artery lesions (CAL) sometimes. However, its etiology was still unidentified. This study was to construct a predictive model based on clinical features and laboratory parameters, and then perform a rapid risk assessment of CAL.

Case report: Aggressive progression of acute heart failure due to juvenile tuberculosis-associated Takayasu arteritis with aortic stenosis and thrombosis.

Background: Takayasu arteritis (TA) is a chronic granulomatous vasculitis with unknown pathophysiology. TA with severe aortic obstruction has a poor prognosis. However, the efficacy of biologics and appropriate timing of surgical intervention remain controversial.

Short-term effectiveness of baricitinib in children with refractory and/or severe juvenile dermatomyositis.

Objective: To determine the short-term effectiveness safety of baricitinib in children with refractory and/or severe juvenile dermatomyositis (rsJDM) in a real-world setting.

Methods: This was a single-center retrospective study, including 20 children with rsJDM. They were all treated using baricitinib combined with steroids and other immunosuppressive agents.

FCL-Net: Towards accurate edge detection via Fine-scale Corrective Learning.

Integrating multi-scale predictions has become a mainstream paradigm in edge detection. However, most existing methods mainly focus on effective feature extraction and multi-scale feature fusion while ignoring the low learning capacity in fine-level branches, limiting the overall fusion performance. In light of this, we propose a novel Fine-scale Corrective Learning Net (FCL-Net) that exploits semantic information from deep layers to facilitate fine-scale feature learning.