Objective Surveillance algorithms that predict patient decompensation are increasingly
integrated with clinical workflows to help identify patients at risk of in-hospital deterioration …

Introduction Physiological signs of clinical deterioration are known to occur in the hours
preceding a serious adverse event. As a result, track and trigger systems known as early …

Background: Prompt recognition of sepsis is critical to improving patients' outcomes. We
compared the performance of NEWS and qSOFA scores as sepsis detection tools in patients …

Background In China, clinical deterioration events present a real problem for every clinical
nurse. Patient deterioration is determined in part by nurses' attitudes toward early …

The article cites information about current technology that could potentially evolve into
hypothetical future technology described in the article. Such references do not constitute …

Background Threshold-based early warning systems (EWS) are used to predict adverse
events (Aes). Machine learning (ML) algorithms that incorporate all EWS scores prior to an …

Background Clinical early warning scoring systems, have improved patient outcomes in a
range of specializations and global contexts. These systems are used to predict patient …

Background: Telehealth programs and wearable sensors that enable patients to monitor
their vital signs have expanded due to the COVID-19 pandemic. The electronic National …

The inability of the healthcare team to identify and report Early Warning System (EWS)
patient events can result in further patient deterioration and delays in providing needed care …

Objetivo: Avaliar a ef etividade de um algoritmo para identificar precocemente a
deterioração clínica em unidades de internação adulto. Método: Estudo de coorte …