Citations

Heart disease has a higher fatality rate than any other disease. Increased Atrial fat on the left atrium has been discovered to cause Atrial Fibrillation (AF) in most patients. AF can put one’s life at risk and eventually lead to death. AF might worsen over time; therefore, it is crucial to have an early diagnosis and treatment. To evaluate the left atrium fat tissue pattern using Radon descriptor-based machine learning. This study developed a bridge between the Radon transform framework and machine learning to distinguish two distinct patterns. Motivated by a Radon descriptor-based machine learning approach, the patches of eight patients from CT images of the heart were used and categorized into “epicardial fat tissue” and “nonfat tissue” groups. The 10 feature vectors are extracted from each big patch using Radon descriptors and then fed into a traditional machine learning model. The results show that the proposed methodology discriminates between fat tissues and nonfat tissues clearly. KNN has shown the best performance with 96.77% specificity, 98.28% sensitivity, and 97.50% accuracy. To our knowledge, this study is the first attempt to provide a Radon transform-based machine learning method to distinguish between fat tissue and nonfat tissue on the left atrium. Our proposed research method could be potentially used in advanced interventions.

ObjectiveDuring PREVENT (NCT01892345), eculizumab significantly reduced relapse risk versus placebo in patients with aquaporin‐4 immunoglobulin G‐positive neuromyelitis optica spectrum disorder (AQP4‐IgG+ NMOSD). We report an interim analysis of PREVENT's ongoing open‐label extension (OLE; NCT02003144) evaluating eculizumab's long‐term safety and efficacy.MethodsPatients who completed PREVENT could enroll in the OLE to receive eculizumab (maintenance dose = 1,200 mg/2 weeks, after a blinded induction phase). Safety and efficacy data from PREVENT and its OLE (interim data cut, July 31, 2019) were combined for this analysis.ResultsAcross PREVENT and the OLE, 137 patients received eculizumab and were monitored for a median (range) of 133.3 weeks (5.1–276.9 weeks), for a combined total of 362.3 patient‐years (PY). Treatment‐related adverse event (AE) and serious adverse event (SAE) rates were 183.5 in 100 PY and 8.6 in 100 PY, respectively. Serious infection rates were 10.2 in 100 PY in eculizumab‐treated patients versus 15.1 in 100 PY in the PREVENT placebo group. No patient developed a meningococcal infection. At 192 weeks (3.7 years), 94.4% (95% confidence interval [CI], 88.6–97.3) of patients remained adjudicated relapse‐free. The adjudicated annualized relapse rate was 0.025 (95% CI = 0.013–0.048) in all eculizumab‐treated patients versus 0.350 (95% CI = 0.199–0.616) in the PREVENT placebo group. During the OLE, 37% of patients (44 of 119 patients) stopped or decreased background immunosuppressive therapy use.InterpretationThis analysis demonstrates that eculizumab's long‐term safety profile in NMOSD is consistent with its established profile across other indications. This analysis also demonstrated the sustained ability of long‐term eculizumab treatment to reduce relapse risk in patients with AQP4‐IgG+ NMOSD. ANN NEUROL 2021;89:1088–1098