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OpenTrials
Completed

NCT Number: NCT03533205

Prediction of Hemodynamic Instability in Patients Undergoing Surgery

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.

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Key information

Conditions

Blood Pressure Hemodynamic Instability Machine Learning Prediction Models

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • all adult patients undergoing surgery

Exclusion criteria

  • none

Treatment and study plan

Hypotension Probability Indicator

Diagnostic Test

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.

Primary outcomes

  1. Sensitivity of the HPI algorithm

    Time frame: three minutes prior to the hypotensive event

    Sensitivity

  2. Specifity of the HPI algorithm

    Time frame: three minutes prior to the hypotensive event

    Specifity

Secondary outcomes

  1. Predictive positive value of the HPI algorithm

    Time frame: one minute prior to the hypotensive event

    Predictive positive value

  2. Predictive positive value of the HPI algorithm

    Time frame: two minutes prior to the hypotensive event

    Predictive positive value

  3. Predictive positive value of the HPI algorithm

    Time frame: three minutes prior to the hypotensive event

    Predictive positive value

  4. Predictive positive value of the HPI algorithm

    Time frame: four minutes prior to the hypotensive event

    Predictive positive value

  5. Predictive positive value of the HPI algorithm

    Time frame: five minutes prior to the hypotensive event

    Predictive positive value

  6. Predictive positive value of the HPI algorithm

    Time frame: ten minutes prior to the hypotensive event

    Predictive positive value

  7. Predictive positive value of the HPI algorithm

    Time frame: 15 minutes prior to the hypotensive event

    Predictive positive value

  8. Negative predictive value of the HPI algorithm

    Time frame: one minute prior to the hypotensive event

    Negative predictive value

  9. Negative predictive value of the HPI algorithm

    Time frame: two minutes prior to the hypotensive event

    Negative predictive value

  10. Negative predictive value of the HPI algorithm

    Time frame: four minutes prior to the hypotensive event

    Negative predictive value

  11. Negative predictive value of the HPI algorithm

    Time frame: five minutes prior to the hypotensive event

    Negative predictive value

  12. Negative predictive value of the HPI algorithm

    Time frame: ten minutes prior to the hypotensive event

    Negative predictive value

  13. Negative predictive value of the HPI algorithm

    Time frame: 15 minutes prior to the hypotensive event

    Negative predictive value

  14. Time from HPI alarm to hypotensive event during surgery

    Time frame: 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)

    Time from HPI alarm to hypotensive event, this can range from 0,1 min to a high number such as 30 or even 40 minutes.

  15. Sensitivity of the HPI algorithm

    Time frame: one minute prior to the hypotensive event

    Sensitivity

  16. Sensitivity of the HPI algorithm

    Time frame: two minutes prior to the hypotensive event

    Sensitivity

  17. Sensitivity of the HPI algorithm

    Time frame: five minutes prior to the hypotensive event

    Sensitivity

  18. Sensitivity of the HPI algorithm

    Time frame: ten minutes prior to the hypotensive event

    Sensitivity

  19. Sensitivity of the HPI algorithm

    Time frame: 15 minutes prior to the hypotensive event

    Sensitivity

  20. Specifity of the HPI algorithm

    Time frame: one minute prior to the hypotensive event

    Specifity

  21. Specifity of the HPI algorithm

    Time frame: two minutes prior to the hypotensive event

    Specifity

  22. Specifity of the HPI algorithm

    Time frame: five minutes prior to the hypotensive event

    Specifity

  23. Specifity of the HPI algorithm

    Time frame: ten minutes prior to the hypotensive event

    Specifity

  24. Specifity of the HPI algorithm

    Time frame: 15 minutes prior to the hypotensive event

    Specifity

Sponsors and collaborators

Lead sponsor

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

Other

Registry information

Important dates

Study start
2015
Primary completion
2016
Study completion
2018
First posted
May 23, 2018
Registry last updated
May 23, 2018

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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