Using Machine Learning and Biomarkers for Early Detection of Delayed Cerebral Ischemia
Condition(s) studied
Investigational drug(s) / intervention(s)
No intervention, observational study: No intervention
Study summary
The overall goal of this project is to determine if machine learning and analysis of neurospecific biomarkers can enable early detection of upcoming or ongoing cerebral ischaemia in patients suffering from subarachnoid haemorrhage with altered consciousness due to cerebral injury or sedation. Analyses of heart rate variability, electroencephalgraphy,nearinfrared spectroscopy, cerebral autoregulation, and brain injury specific biomarkers in blood and cerebrospinal fluid will be performed.
Eligibility
Primary outcome measure(s)
- Early warning system — 2023-2033
To develop a machine learning-based model that can identify patterns in signals obtained from HRV, NIRS, and EEG monitoring, which are consistent with upcoming cerebral ischemia and provide a warning about this to attending physicians. To define the specificity and time relation of neurospecific biomarkers in blood and cerebrospinal fluid in patients with subarachnoid haemorrhage with and without delayed cerebral ischemia to evaluate if any of these biomarkers can be used as an indicator for ongoing cerebral ischemia. To assess the prognostic value of changes in physiological and neurospecific biomarkers changes during the acute phase after subarachnoid hemorrhage on long-term outcome. - Autoregulation — 2023-2033
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Trial sites (1)
| Facility | City | Region | Status |
|---|---|---|---|
| Sahlgrenska University Hospital | Gothenburg | Sweden | Recruiting |
More Sahlgrenska University Hospital trials in Sweden
Other trials for the same condition
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
View NCT06069973 on ClinicalTrials.gov ↗ ← All trials in Sweden