Purpose Early clinical recognition of sepsis can be challenging. With the advancement of
machine learning, promising real-time models to predict sepsis have emerged. We …

Background: Sepsis/septic shock is a life-threatening and time-dependent condition that
requires timely management to reduce mortality. This review aims to update physicians with …

Early recognition and treatment of sepsis are linked to improved patient outcomes. Machine
learning-based early warning systems may reduce the time to recognition, but few systems …

Sepsis is life-threatening organ dysfunction caused by a dysregulated host response to
infection (1). Sepsis and septic shock are major healthcare problems, impacting millions of …

Background Sepsis is life-threatening organ dysfunction due to a dysregulated host
response to infection. It is considered a major cause of health loss, but data for the global …

Objectives: To characterize the current burden, outcomes, and costs of managing sepsis
patients in US hospitals. Design: A retrospective observational study was conducted using …

Abstract Machine learning-based clinical decision support tools for sepsis create
opportunities to identify at-risk patients and initiate treatments at early time points, which is …

Objectives: Sepsis is a major public health concern with significant morbidity, mortality, and
healthcare expenses. Early detection and antibiotic treatment of sepsis improve outcomes …

Background Septic shock is the most severe form of sepsis, in which profound underlying
abnormalities in circulatory and cellular/metabolic parameters lead to substantially …

Background In 2013, New York began requiring hospitals to follow protocols for the early
identification and treatment of sepsis. However, there is controversy about whether more …