AI-driven model supports safer and more precise blood sugar management after heart surgery
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Updates every hour. Last Updated: 17-Jun-2025 13:09 ET (17-Jun-2025 17:09 GMT/UTC)
Researchers at the Icahn School of Medicine at Mount Sinai have developed a machine learning tool that can help doctors manage blood sugar levels in patients recovering from heart surgery, a critical but often difficult task in the intensive care unit (ICU). The findings were reported in the May 27 online issue of NPJ Digital Medicine. After cardiac surgery, patients are at risk for both high and low blood sugar, which can lead to serious complications. Managing these fluctuations requires careful insulin dosing, but existing protocols often fall short due to the unpredictable nature of ICU care and differences among patients, say the investigators.
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