Purpose: A previously developed machine-learning approach with Kalman-filtering technology accurately predicted disease trajectory for patients with various glaucoma types and severities using clinical trials data. This study assesses performance of the KF approach with real-world data.
Design: Retrospective cohort study.
Background: Acute myocardial infarction-related cardiogenic shock (AMICS) is a severe complication associated with exceedingly high mortality rates. While mechanical circulatory support (MCS) has emerged as a potential intervention, the evidence base for independent MCS use remains weak. In contrast, systematic reviews of observational studies have revealed significant mortality reduction when a combination of MCS was used: VA-ECMO in conjunction with a left ventricular (LV) unloading device (Impella or IABP).
View Article and Find Full Text PDFBackground: Non-tuberculous mycobacteria (NTM) are environmental agents that can cause opportunistic pulmonary disease in humans and animals, often misdiagnosed as tuberculosis (TB). In this study, we describe the cases of NTM identified during the first national anti-TB drug resistance survey conducted in Mali and explore associated risk factors.
Methods: Sputum was collected from people presenting for pulmonary TB diagnosis from April to December 2019, regardless of age.