AI-based systems can identify sepsis up to six hours earlier than traditional diagnostic methods.
Sepsis—a life-threatening reaction to infection—is among the deadliest conditions in hospitals worldwide, claiming a life every three seconds, according to the Global Sepsis Alliance. Despite its severity, it often goes unrecognized, with many deaths attributed simply to “infection.” In the UAE, experts are now emphasizing how artificial intelligence (AI) is helping to detect this silent killer earlier.
AI flags sepsis early
“AI can identify sepsis risk sooner by analysing large volumes of clinical data from electronic health records, especially in ICU settings where continuous monitoring is available,” said Dr. Rajashree Ganesh, Specialist in Internal Medicine at Medcare Hospital, Shaikh Saqr Al Qasimi St, Sharjah.
She explained that AI can simultaneously process multiple data points—from vital signs and lab results to comorbidities, patient demographics, and patterns of hospital and ICU stays—allowing for earlier detection than traditional methods.
“By integrating and analysing these variables through models such as Sepsis Watch, Immuno Score, and In Sight, the system can detect patterns indicative of sepsis before they become clinically apparent. As decision-support tools, these algorithms help clinicians identify early signs of patient deterioration based on data trends,” emphasized Dr. Rajashree Ganesh.
AI algorithms help spot early deterioration
Dr. Rajashree Ganesh explained that AI systems can identify early signs of patient deterioration, even when a patient appears clinically stable.
Six-hour early warning
She noted that, on average, AI-based systems can detect sepsis around six hours earlier than traditional assessment methods. “This earlier identification provides a crucial window for timely intervention,” she said, highlighting that it can reduce treatment time, potentially shorten hospital and ICU stays, and improve survival rates. “By enabling earlier clinical action, these tools support better patient outcomes.”
Designed for stability checks
Dr. Rajashree emphasized that AI tools are specifically designed to flag deterioration in patients who seem clinically stable. “Current AI-based sepsis prediction models show an accuracy range of roughly 79–90%,” she said, while cautioning that external validation is needed to ensure consistent performance across different healthcare settings. “In real-world scenarios, high false alarm rates can occur, which is an important limitation to consider.”
Sepsis remains a global killer
Dr. Javier Perez Fernandez, President of the World Federation of Intensive and Critical Care, highlighted that sepsis consumes more than half of ICU resources worldwide, yet early detection makes it largely preventable and treatable. “Sepsis is the leading cause of death in intensive care units globally,” he said, adding that low public awareness makes timely recognition and intervention essential.
Who is most at risk?
While sepsis can affect anyone, certain groups are particularly vulnerable, including the elderly, individuals with diabetes or other chronic illnesses, post-surgical patients, those with weakened immune systems, and newborns.
Symptoms you should not ignore
Key warning signs include high fever or unusually low body temperature, rapid breathing, fast heart rate, confusion or disorientation, extreme weakness, and reduced urine output. If untreated, sepsis can quickly escalate to septic shock, multiple organ failure, and death, emphasizing the importance of seeking urgent medical care at the first signs of deterioration.
