Brain-Wave algorithm may flag newborns needing urgent cooling
NCT ID NCT07764315
First seen Aug 13, 2026 · Last updated Aug 14, 2026 · Updated 1 time
Summary
This study tests whether a computer algorithm can analyze standard EEG recordings from full-term newborns who experienced oxygen deprivation at birth to tell apart mild brain injury from moderate or severe forms. The algorithm's readings are compared against expert review of the full EEG plus clinical information. The study uses only existing medical data from 310 babies, requiring no extra procedures or visits. If the algorithm proves reliable, it could help doctors make faster, more objective decisions about which newborns need therapeutic hypothermia.
What this could mean
Our plain-language read of the trial. This is informational only — not medical advice or a prediction.
- Active substance
- A decision-support algorithm that analyzes conventional EEG signals to classify the severity of hypoxic-ischemic encephalopathy in newborns.
- What this could lead to
- If accurate, this algorithm could help doctors quickly and objectively identify which newborns need intensive cooling therapy, potentially improving outcomes for babies with brain injury.
- What could go wrong
- This is a retrospective observational study, so the algorithm's real-world performance may differ. It also relies on existing data, which may have gaps or biases, and the algorithm's accuracy needs confirmation in prospective trials.
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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.
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