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Study: AI Predicts Pediatric Sepsis 48 Hours Before Onset
The multi-center study led by Elizabeth Alpern validated AI models that predict pediatric sepsis within 48 hours, enabling early preemptive care to reduce mortality, researchers said.
- Elizabeth Alpern led a multi-center study across five PECARN health systems that developed AI models to predict pediatric sepsis using the Phoenix Sepsis Criteria, published in JAMA Pediatrics.
- Sepsis's status as a leading cause of pediatric death prompted researchers to train models on routine EHR data from the first four hours of ED visits, excluding children already septic on arrival.
- The models predict sepsis risk within 48 hours, allowing preemptive steps, and showed robust balance in risk identification, with Alpern calling them `a huge step toward precision medicine for sepsis in children`.
- Deployment enabled clinicians to start life-saving preemptive care, scientists said, and early identification allows initiation of lifesaving therapies that could reduce pediatric sepsis mortality worldwide.
- Assessing bias, Alpern said `We evaluated our models to ensure that there were no biases` and added that `Future research will need to combine EHR-based AI models with clinician judgment to make even better predictions`.
58 Articles
58 Articles
Clinical validation of an AI-based blood testing device for diagnosis and prognosis of acute infection and sepsis - Nature Medicine
Lack of reliable diagnostics for the presence, type and severity of infection in patients presenting to emergency departments with non-specific symptoms poses considerable challenges. We developed TriVerity, which uses isothermal amplification of 29 mRNAs and machine learning algorithms on the Myrna instrument to determine likelihoods of bacterial infection, viral infection and need for critical care interventions within 7 days. To validate TriV…
Study validates AI models for preemptive sepsis care in pediatrics
Sepsis, or infection causing life-threatening organ dysfunction, is a leading cause of death in children worldwide. In efforts to prevent this rare but critical condition, researchers developed and validated AI models that accurately identify children at high risk for sepsis within 48 hours, so that early preemptive care can be provided.
Watauga Democrat
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Deployment of the state-of-the-art technology allowed doctors to begin life-saving pre-emptive care.
AI models predict sepsis in children to allow preemptive care
Sepsis, or infection causing life-threatening organ dysfunction, is a leading cause of death in children worldwide. In efforts to prevent this rare but critical condition, researchers developed and validated AI models that accurately identify children at high risk for sepsis within 48 hours, so that early preemptive care can be provided.
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