After more than a decade as an OB-GYN, Darine El-Chaâr still finds late-stage emergency C-sections to be hard. Labor can drag on for days without a baby being born, at which point the situation grows dangerous.
“Many times I walk to the operating room, and I’m like, I’m so sorry that you got so far and now this is where you are,” said El-Chaâr, a physician at the Ottawa Hospital Research Institute. “It’s nobody’s fault. It’s just … you’ve tried, and the only way to know is if you try.”
In the U.S, 30% of deliveries happen by C-section, and 10% are by emergency C-section specifically. Any C-section carries some risks, but those risks are compounded when exhausted doctors and patients have to rush to make a call at the last minute. It’s with that scramble in mind that a team of researchers at the University of Texas in Austin has developed a new machine learning model that predicts who is at risk of ending up with an emergency C-section — well before it’s time to give birth. Armed with that information, parents can consider a planned C-section instead.
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