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

Recruiting

• Conditions: Cerebral Autoregulation

• Registration Number: NL-OMON28924
• Lead Sponsor: Amsterdam UMC

Brief Summary

Not available

Detailed Description

Not available

Study Timeline

• Results First Posted: 1900-01-01
• Last Update Posted: 28 February 2024

Recruitment & Eligibility

• Status: Recruiting
• Sex: Not specified
• Target Recruitment: 100

Inclusion Criteria

=18 years of age
- Informed consent
- Planned for any type of elective surgery under anesthesia.

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
- Emergency surgery
- Allergy for medication used in study protocol
- Subjects will be excluded if both noninvasive blood pressure (with the finger cuff) and invasive blood pressure (with an arterial cannula already available due to standard of care) cannot be measured according to the Instructions for Use of the CS/EV1000/HemoSphere system.
- Unability to record transcranial Doppler ultrasound due to anatomical variance (~5% of population)

Study & Design

• Study Type: Interventional
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Prediction of cerebral blood flow and autoregulation during anaesthesia using machine learning