Prediction of cerebral blood flow and perfusion with arterial pulse wave applied machine learning

Recruiting

• Conditions: Cerebrale autoregulatie onder algehele narcose; Cerebral autoregulation; control mechanisms of brain blood flow

• Registration Number: NL-OMON54402
• Lead Sponsor: Academisch Medisch Centrum

Brief Summary

Not available

Detailed Description

Not available

Study Timeline

• Last Update Posted: 26 August 2024

Recruitment & Eligibility

• Status: Recruiting
• Sex: Not specified
• Target Recruitment: 240

Inclusion Criteria

- >=18 years of age
- Informed consent
- Planned for any type of elective surgery/Requiring intubation/Requiring
tracheostomy

Exclusion Criteria

- Any right-sided structural pathology or reduced function (Tapse <1.5cm)
- Severe cardiac arrhythmias (with high heart rate), including atrial
fibrillation
- Abnormal anatomy of the fingers
- Allergy for medication used in study protocol

Study & Design

• Study Type: Observational non invasive
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
<p>The primary aim of this study is data collection of continuous noninvasive<br /><br>arterial pressure waveform signals with the CS finger cuff, continuous invasive<br /><br>arterial pressure waveform signals when an arterial cannula is already<br /><br>available due to standard of care, continuous noninvasive cerebral oximetry<br /><br>signals, transcranial Doppler ultrasound, capnography and clinical data from<br /><br>patients EMR in surgical patients. These data will be used to predict the<br /><br>likelihood of derangement of physiologic parameters in awake patients before<br /><br>induction of anesthesia and to predict cerebral blood flow using machine<br /><br>learning.</p><br>

Secondary Outcome Measures

Name	Time	Method
<p>Not applicable.</p><br>