Intraoperative Implementation of the Hypotension Probability Indicator
HYPE
HYPE Trial. Intraoperative Implementation of the Hypotension Probability Indicator (HPI) Algorithm: a Pilot Randomized Controlled Clinical Trial
1 other identifier
interventional
100
1 country
1
Brief Summary
Reducing intraoperative hypotension using FlotracIQ with HPI software.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P50-P75 for not_applicable
Started Nov 2017
1 active site
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
November 8, 2017
CompletedFirst Submitted
Initial submission to the registry
December 3, 2017
CompletedFirst Posted
Study publicly available on registry
December 18, 2017
CompletedPrimary Completion
Last participant's last visit for primary outcome
March 20, 2019
CompletedStudy Completion
Last participant's last visit for all outcomes
March 20, 2019
CompletedJanuary 13, 2020
January 1, 2020
1.4 years
December 3, 2017
January 9, 2020
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
TWA hypotension (measured with FlotracIQ)
Time weighted average spent in hypotension, defined as MAP \<65mmHg for ≥1min
intraoperative, starting 15 minutes after induction
Secondary Outcomes (9)
Incidence of hypotension (measured with FlotracIQ)
intraoperative, starting 15 minutes after induction
Time spent in hypotension (measured with FlotracIQ)
intraoperative, starting 15 minutes after induction
TWA hypertension (measured with FlotracIQ)
intraoperative, starting 15 minutes after induction
Percentage of time in hypertension (measured with FlotracIQ)
intraoperative, starting 15 minutes after induction
Incidence of hypertension (measured with FlotracIQ)
intraoperative, starting 15 minutes after induction
- +4 more secondary outcomes
Study Arms (2)
Conventional arm
NO INTERVENTIONInstitutional Standard of Care with intention to keep MAP\> 65 mmHg. The FlotracIQ will be connected, but fully covered.
Treatment arm
ACTIVE COMPARATORFlotracIQ with HPI algorithm.
Interventions
FlotracIQ with hypotension probability indicator (HPI) algorithm connected to arterial line. The treating anesthetist is provided with guidance by means of a flowchart suggesting when to treat and what. Timing of treatment and choice of treatment is then left to the discretion of the attending physician.
Eligibility Criteria
You may qualify if:
- Aged 18 years or older
- Planned for elective non-cardiac non-day surgery with an expected duration of more than 2 hours
- Planned to receive general anaesthesia
- Planned to receive an arterial line during surgery
- Aim for MAP of 65 mmHg during surgery
- Being able to give written informed consent prior to surgery
You may not qualify if:
- Aim for MAP other than 65 mmHg at discretion treating physician
- Significant hypotension before surgery defined as a MAP \<65
- Right- or left sided cardiac failure (e.g. LVEF\<35%)
- Known cardiac shunts (significant)
- Known aortic stenosis (severe)
- Severe cardiac arrhythmias including atrial fibrillation
- Requiring dialysis
- Liver surgery
- Vascular surgery with clamping of the aorta
- Perioperative Goal Directed Therapy (PGDT) protocol
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Academic Medical Center Amsterdam
Amsterdam, Netherlands
Related Publications (2)
Wijnberge M, Geerts BF, Hol L, Lemmers N, Mulder MP, Berge P, Schenk J, Terwindt LE, Hollmann MW, Vlaar AP, Veelo DP. Effect of a Machine Learning-Derived Early Warning System for Intraoperative Hypotension vs Standard Care on Depth and Duration of Intraoperative Hypotension During Elective Noncardiac Surgery: The HYPE Randomized Clinical Trial. JAMA. 2020 Mar 17;323(11):1052-1060. doi: 10.1001/jama.2020.0592.
PMID: 32065827DERIVEDWijnberge M, Schenk J, Terwindt LE, Mulder MP, Hollmann MW, Vlaar AP, Veelo DP, Geerts BF. The use of a machine-learning algorithm that predicts hypotension during surgery in combination with personalized treatment guidance: study protocol for a randomized clinical trial. Trials. 2019 Oct 11;20(1):582. doi: 10.1186/s13063-019-3637-4.
PMID: 31601239DERIVED
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
M.W. Hollmann, MD, PhD
Academic Medical Center (AMC), Amsterdam
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- SINGLE
- Who Masked
- PARTICIPANT
- Purpose
- TREATMENT
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Principal Investigator, Medical Doctor, PhD
Study Record Dates
First Submitted
December 3, 2017
First Posted
December 18, 2017
Study Start
November 8, 2017
Primary Completion
March 20, 2019
Study Completion
March 20, 2019
Last Updated
January 13, 2020
Record last verified: 2020-01
Data Sharing
- IPD Sharing
- Will not share