NCT03533205
Completed
N/A
Prediction of Hemodynamic Instability in Patients Undergoing Surgery
Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)0 sites507 target enrollmentApril 1, 2015
Overview
- Phase
- N/A
- Intervention
- Not specified
- Conditions
- Blood Pressure
- Sponsor
- Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)
- Enrollment
- 507
- Primary Endpoint
- Sensitivity of the HPI algorithm
- Status
- Completed
- Last Updated
- 7 years ago
Overview
Brief Summary
Intraoperative hypotension occurs often and is associated with adverse patient outcomes such as stroke, myocardial infarction and renal injury.
The aim of this study was to test the accuracy of a physiology-based machine-learning algorithm using continuous non-invasive measurement of the blood pressure waveform with the Nexfin® finger cuff during surgery.
Investigators
D.P.Veelo
MD PhD
Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)
Eligibility Criteria
Inclusion Criteria
- •all adult patients undergoing surgery
Exclusion Criteria
- Not provided
Outcomes
Primary Outcomes
Sensitivity of the HPI algorithm
Time Frame: three minutes prior to the hypotensive event
Sensitivity
Specifity of the HPI algorithm
Time Frame: three minutes prior to the hypotensive event
Specifity
Secondary Outcomes
- Predictive positive value of the HPI algorithm(15 minutes prior to the hypotensive event)
- Negative predictive value of the HPI algorithm(15 minutes prior to the hypotensive event)
- Sensitivity of the HPI algorithm(15 minutes prior to the hypotensive event)
- Time from HPI alarm to hypotensive event during surgery(From the onset of the HPI alarm to the hypotensive event during surgery, this is in minutes. (this can range from 0,1 min to a high number such as 30 or even 40 minutes))
- Specifity of the HPI algorithm(15 minutes prior to the hypotensive event)
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