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Prediction of Hemodynamic Instability in Patients Undergoing Surgery

NCT03533205 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 507

Last updated 2018-05-23

No results posted yet for this study

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.

Conditions

  • Blood Pressure
  • Prediction Models
  • Machine Learning
  • Hemodynamic Instability

Interventions

DIAGNOSTIC_TEST

Hypotension Probability Indicator

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.

Sponsors & Collaborators

  • Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2015-04-01
Primary Completion
2016-12-01
Completion
2018-04-26

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT03533205 on ClinicalTrials.gov