New AI could predict dangerous blood pressure drops in C-Sections
NCT ID NCT06158542
First seen Mar 01, 2026 · Last updated Jun 23, 2026 · Updated 14 times
Summary
This study aimed to create an artificial intelligence algorithm that can predict which patients are at risk of low blood pressure after receiving spinal anesthesia for a cesarean section. Researchers collected data from 370 patients, including their medical history, demographics, and blood test results. They then used machine learning to develop and test an algorithm that could help doctors prepare for and prevent this common complication.
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Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
This is a summary of the original study . Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
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Contacts and locations
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Locations
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Hacettepe University Hospitals
Ankara, Altındağ, 06230, Turkey (Türkiye)
What this could mean
Our plain-language read of the trial. This is informational only — not medical advice or a prediction.
Active substance
Artificial intelligence algorithm
What this could lead to
If successful, this algorithm could help doctors identify high-risk patients before spinal anesthesia, potentially reducing complications during cesarean sections.
What could go wrong
This is a completed study, but the algorithm's accuracy and real-world usefulness need further testing in different hospitals and patient groups.
Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.