Researchers at Children's Hospital of Philadelphia (CHOP) have developed a novel computational algorithm to track the epidemiology of pediatric sepsis, allowing for the collection of more accurate ...

A machine-learning algorithm has the capability to identify hospitalized patients at risk for severe sepsis and septic shock using data from electronic health records (EHRs), according to a new study.

In marketing materials and internal documents, national electronic health record vendor Epic Systems has touted the ability of its sepsis algorithm to crunch dozens of variables to detect the ...

For a patient with sepsis—which kills more Americans every year than AIDS and breast and prostate cancer combined—hours can make the difference between life and death. The quest for early diagnosis of ...

Each year, sepsis affects more than 30 million people worldwide, causing an estimated six million deaths. Sepsis is the body's extreme response to an infection and is often life-threatening. Since ...

The most popular data are vital signs, which include such things as blood pressure, heart rate, respiration rate, temperature, oxygen saturation and so forth. Often these data are fed into the EHR ...

Early recognition of sepsis in hospitalized patients and timely, protocol-driven interventions are spelled out for critical care nurses in new international guidelines. "Critical care nurses play an ...

Each year, sepsis affects more than 30 million people worldwide, causing an estimated six million deaths. Sepsis is the body's extreme response to an infection and is often life-threatening. Since ...

The results of the present study show that after implementation of a PCT-guided algorithm in 2005 length of antibiotic therapy in surgical patients with severe sepsis or septic shock was reduced by an ...

Researchers then validated the algorithm on suspected or confirmed sepsis cases seen at CHOP between July 1, 2018 and January 31, 2019. Once researchers had developed and validated the algorithm, they ...