Prediction of Hemodynamic Instability in Patients Undergoing Surgery
1 other identifier
observational
507
0 countries
N/A
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.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Apr 2015
Typical duration for all trials
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
April 1, 2015
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 1, 2016
CompletedFirst Submitted
Initial submission to the registry
April 26, 2018
CompletedStudy Completion
Last participant's last visit for all outcomes
April 26, 2018
CompletedFirst Posted
Study publicly available on registry
May 23, 2018
CompletedMay 23, 2018
May 1, 2018
1.7 years
April 26, 2018
May 22, 2018
Conditions
Outcome Measures
Primary Outcomes (2)
Sensitivity of the HPI algorithm
Sensitivity
three minutes prior to the hypotensive event
Specifity of the HPI algorithm
Specifity
three minutes prior to the hypotensive event
Secondary Outcomes (24)
Predictive positive value of the HPI algorithm
one minute prior to the hypotensive event
Predictive positive value of the HPI algorithm
two minutes prior to the hypotensive event
Predictive positive value of the HPI algorithm
three minutes prior to the hypotensive event
Predictive positive value of the HPI algorithm
four minutes prior to the hypotensive event
Predictive positive value of the HPI algorithm
five minutes prior to the hypotensive event
- +19 more secondary outcomes
Interventions
The accurary of the Hypotension Probability Indicator (HPI) is tested in the created offline database. This means data was prospectively collected but the HPI algorithm was not tested prospectively but after collection in the offline database.
Eligibility Criteria
All adult patients undergoing surgery in the AMC were included in the study. Subjects were only excluded when technical problems or strong local vasoconstriction (i.e., cold fingers) prevented the Nexfin® non-invasive blood pressure finger cuff measurement. Subjects were not excluded for any other reason besides technical failure.
You may qualify if:
- all adult patients undergoing surgery
You may not qualify if:
- none
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Related Publications (1)
Wijnberge M, van der Ster BJP, Geerts BF, de Beer F, Beurskens C, Emal D, Hollmann MW, Vlaar APJ, Veelo DP. Clinical performance of a machine-learning algorithm to predict intra-operative hypotension with noninvasive arterial pressure waveforms: A cohort study. Eur J Anaesthesiol. 2021 Jun 1;38(6):609-615. doi: 10.1097/EJA.0000000000001521.
PMID: 33927105DERIVED
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- MD PhD
Study Record Dates
First Submitted
April 26, 2018
First Posted
May 23, 2018
Study Start
April 1, 2015
Primary Completion
December 1, 2016
Study Completion
April 26, 2018
Last Updated
May 23, 2018
Record last verified: 2018-05