We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
ARAB HEALTH - INFORMA

Download Mobile App




Novel Breakthrough AI Technology Recognizes Sepsis Patients in Real-Time

By HospiMedica International staff writers
Posted on 21 Nov 2023
Print article
Image: The FDA has granted KATE AI breakthrough device designation for early sepsis detection (Photo courtesy of 123RF)
Image: The FDA has granted KATE AI breakthrough device designation for early sepsis detection (Photo courtesy of 123RF)

Sepsis, a critical and often fatal condition, is the leading cause of mortality in U.S. hospitals, as well as the primary reason for hospital readmissions and a major contributor to hospitalization costs. Early detection is key in managing sepsis effectively, as delays in treatment can significantly increase the risk of adverse outcomes. Now, a groundbreaking technology could transform the early detection of sepsis.

Mednition’s (Burlingame, CA, USA) KATE Sepsis system is an AI-powered tool designed to detect sepsis early and accurately in real-time. It analyzes over 600 clinical data elements from a patient's medical record, incorporating both structured data and unstructured clinical notes, to aid nurses in timely intervention. A critical hurdle in implementing AI for sepsis detection has been balancing high sensitivity with specificity to avoid excessive false positives and alert fatigue. KATE Sepsis has excelled in this area, showing a 74% improvement in detecting sepsis, 80% in severe sepsis, and an impressive 118% in septic shock compared to conventional screening methods, all while maintaining a high specificity rate of 95%.

The U.S. Food and Drug Administration (FDA) has awarded KATE Sepsis the Breakthrough Device Designation, acknowledging its significant role in enhancing early sepsis detection. This recognition comes from KATE Sepsis's demonstrated capability to surpass standard screening protocols in the early detection of sepsis at Emergency Department (ED) Triage by up to 118%, and importantly, achieving this level of detection before any laboratory diagnostic results are available.

“We are deeply honored to receive the FDA Breakthrough Device Designation for KATE Sepsis. This recognition underscores our commitment to advancing equitable care, improving patient outcomes, and reducing risk for patients,” said Steven Reilly, chief executive officer at Mednition. “We believe every second counts in the fight against sepsis. KATE Sepsis represents a significant leap forward in detecting sepsis earlier and enabling clinicians to provide more effective and timely treatment.”

Related Links:
Mednition 

Gold Member
SARS‑CoV‑2/Flu A/Flu B/RSV Sample-To-Answer Test
SARS‑CoV‑2/Flu A/Flu B/RSV Cartridge (CE-IVD)
Gold Member
12-Channel ECG
CM1200B
New
3-Channel ECG
ECG-1003p
New
Oxygen Concentrator
Nuvo 8

Print article

Channels

Surgical Techniques

view channel
Image: Application of Pericelle to the porcine model of femoral arterio-venous fistula (Photo courtesy of Bioactive Materials, DOI:10.1016/j.bioactmat.2024.10.005)

Nanotechnology-Based Drug Delivery System Could Help Dialysis and Heart Patients Avoid Repeat Surgeries

Revascularization procedures are essential for treating cardiovascular disease by restoring the necessary blood flow. For instance, a surgeon may transfer a vein from the leg to the heart to help patients... Read more

Patient Care

view channel
Image: The portable biosensor platform uses printed electrochemical sensors for the rapid, selective detection of Staphylococcus aureus (Photo courtesy of AIMPLAS)

Portable Biosensor Platform to Reduce Hospital-Acquired Infections

Approximately 4 million patients in the European Union acquire healthcare-associated infections (HAIs) or nosocomial infections each year, with around 37,000 deaths directly resulting from these infections,... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.