Timely treatment is crucial for sepsis, as only 20% of cases yield positive blood cultures, and nearly half of the cases have no identifiable pathogen.

Dr. Anand Viswanathan, a hospitalist at NYU Langone Health, encountered a challenging case involving a patient with unexplained abdominal pain and a declining white blood cell count, which raised his suspicion of sepsis.

Current sepsis management strategies often rely on outdated data that primarily focus on patients who acquired sepsis outside the hospital, highlighting the necessity for new guidelines tailored to hospital-acquired cases.

Sepsis is a critical health issue in the U.S., affecting 1.7 million hospitalizations and causing approximately 270,000 deaths annually, making it a leading cause of hospital mortality.

Hospital-onset sepsis is particularly concerning, with a mortality rate that is twice that of community-acquired sepsis, underscoring the urgent need for targeted research and guidelines for in-hospital cases.

While most sepsis cases originate outside of hospitals, about 10%-15% develop during hospitalization, where hospitalists play a vital role in identification and management.

To enhance rapid response capabilities, specialized sepsis teams are being deployed in hospitals, yet there remains a pressing need for refined detection methods, including the potential integration of AI.

The Centers for Medicare and Medicaid Services introduced sepsis care bundles in 2015 to standardize rapid response protocols, but experts argue that these may not always be beneficial and could divert resources from more effective treatments.

Emerging AI tools for sepsis management are being developed, but their use remains controversial due to concerns about accuracy and alert fatigue, indicating a need for further research to validate their effectiveness.

Despite initiating antibiotic treatment based on his suspicion, the patient unfortunately passed away the following day, highlighting the rapid progression of sepsis.