Deadlier than a heart attack: UAE expert reveals how AI flags sepsis before doctors can

AI-based systems can detect it 6 hours earlier than traditional assessment methods

Last updated:
Ashwani Kumar, Chief Reporter
Sepsis is the leading cause of death in intensive care units worldwide.
Sepsis is the leading cause of death in intensive care units worldwide.
Pixabay

Sepsis – a life-threatening response to infection – is one of the deadliest conditions in hospitals worldwide, claiming a life every three seconds, according to the Global Sepsis Alliance. Despite its severity, it often goes unrecognised, with many deaths attributed simply to “infection.” In the UAE, specialists are now highlighting how artificial intelligence (AI) is advancing early detection of this silent killer.

AI flags sepsis early

“AI identifies sepsis risk earlier by analysing large volumes of clinical data drawn from electronic health records, particularly in ICU settings where continuous monitoring is available,” said Dr Rajashree Ganesh, Specialist, Internal Medicine at Medcare Hospital, Shaikh Saqr Al Qasimi St, Sharjah.

She pointed out that AI can process multiple data points simultaneously – from vital signs and lab results to comorbid conditions, demographics, and hospital and ICU stay patterns.

“By integrating and analysing these variables through different models such as Sepsis Watch, Immuno Score and In Sight, the system can detect patterns suggestive of sepsis that may not yet be clinically apparent. As decision support tools, these algorithms assist clinicians by identifying early signs of deterioration based on data trends,” Dr Rajashree underlined.

AI algorithms assist in identifying early deterioration, even in situations where a patient may appear clinically stable
Dr Rajashree Ganesh

Six-hour early warning

Dr Rajashree noted that on average, AI-based systems can detect sepsis approximately six hours earlier than traditional assessment methods.
“This earlier identification provides an important window for timely intervention,” she said, noting that earlier detection helps reduce treatment time, potentially shorten hospital and ICU stays, and improve survival rates.

“By enabling earlier clinical action, these tools support improved patient outcomes.”

Designed for stability checks

Dr Rajashree highlighted that AI tools are designed to flag early deterioration even in patients who appear clinically stable.

“Current AI-based sepsis prediction models demonstrate an accuracy range of approximately 79 to 90 per cent,” she said, while cautioning that these systems require external validation to ensure consistent performance across different healthcare settings. “In real clinical scenarios, high false alarm rates may be experienced, which remains an important limitation to consider,” she said.

Sepsis still a global killer

Meanwhile, Dr Javier Perez Fernandez, President of the World Federation of Intensive and Critical Care, noted 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 worldwide,” said Dr Fernandez, adding that public awareness remains low, making timely recognition and intervention crucial.

Who is most at risk?

Sepsis can affect anyone, but certain groups are especially vulnerable. These include elderly individuals, people living with diabetes or other chronic diseases, post-surgical patients, individuals with weakened immune systems, and newborns.

Signs you must not ignore

Key symptoms include a high fever or abnormally low body temperature, rapid breathing, a fast heart rate, confusion or disorientation, extreme weakness, and reduced urine output. If left untreated, sepsis can quickly progress to septic shock, multiple organ failure, and death, underscoring the importance of seeking urgent medical care at the first signs of deterioration.

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