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Evaluation of the Accuracy, Safety and Robustness of a Single-input-single-output (SISO) Model-based Predictive Closed-loop System to Guide Patient-individualized ICU Sedation

This study has been completed.
Sponsor:
Collaborator:
Agentschap voor Innovatie door Wetenschap en Technologie
Information provided by (Responsible Party):
University Hospital, Ghent
ClinicalTrials.gov Identifier:
NCT00735631
First received: August 14, 2008
Last updated: December 6, 2011
Last verified: December 2011

August 14, 2008
December 6, 2011
June 2008
September 2009   (final data collection date for primary outcome measure)
The propofol and remifentanil dose needed to keep the BIS within the target range [ Time Frame: During sedation ] [ Designated as safety issue: No ]
Same as current
Complete list of historical versions of study NCT00735631 on ClinicalTrials.gov Archive Site
The hemodynamic stability of the patient, being defined as: - mean arterial blood pressure between 65 and 85 - heart rate around 80 beats'/min - diuresis 0.5 - 1 ml/kg/hour - normal pH - normal cardiac index as defined by a CI > 2.2 - Sv02 > 60 % [ Time Frame: During sedation ] [ Designated as safety issue: No ]
Same as current
Not Provided
Not Provided
 
Evaluation of the Accuracy, Safety and Robustness of a Single-input-single-output (SISO) Model-based Predictive Closed-loop System to Guide Patient-individualized ICU Sedation
Evaluation of the Accuracy, Safety and Robustness of a Single-input-single-output (SISO) Model-based Predictive Closed-loop System to Guide Patient-individualized ICU Sedation.

The aim of this study is to investigate the accuracy, safety and robustness of a single-input-single output (SISO) model-based predictive closed-loop system to guide patient-individualized ICU sedation.

Not Provided
Interventional
Phase 4
Endpoint Classification: Efficacy Study
Intervention Model: Single Group Assignment
Masking: Open Label
Primary Purpose: Treatment
Coronary Artery Disease
Device: SISO model-based predictive closed-loop system
The single-input-single-output (SISO) model-based predictive closed-loop system will be used to guide patient-individualized ICU sedation with propofol
Experimental: 1
The single-input-single-output (SISO) model-based predictive closed-loop system will be used to guide patient-individualized ICU sedation with propofol
Intervention: Device: SISO model-based predictive closed-loop system
Not Provided

*   Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
 
Completed
36
October 2009
September 2009   (final data collection date for primary outcome measure)

Inclusion Criteria:

  • patients in the immediate post-operative phase after an coronary artery reconstruction surgery.
  • age >= 18 years
  • informed consent obtained before the surgery

Exclusion Criteria:

  • severe renal failure defined by the RIFLE Classification levels Risk, Failure and End-stage Kidney Failure
  • severe hepatic failure defined by a bilirubin level of >= 3 mg/dl and/or a prothrombin level of < 50% before the surgery
  • low ejection fraction defined as < 40%
  • age < 18 years
  • postoperative bleeding so that a new surgery is necessary
  • history of cardiovascular accident (CVA)
  • history of COPD
  • age > 75 years
  • postoperative cardiac index < 2.2 for more than 2 hours
  • SvO2 < 60% for more than 2 hours
  • hypotension with a MAP < 60 mmHg for more than 2 hours
  • sedation agents other than remifentanyl and propofol including also Catapressan, Risperdal, Etumine
  • Remifentanyl dose exceeding 0.5 µg/kg/min.
  • absence of informed consent
Both
18 Years to 75 Years
No
Contact information is only displayed when the study is recruiting subjects
Belgium
 
NCT00735631
2007/489
No
University Hospital, Ghent
University Hospital, Ghent
Agentschap voor Innovatie door Wetenschap en Technologie
Principal Investigator: Michel Struys, MD, PhD University Hospital, Ghent
Principal Investigator: Annick De Wolf, MD University Hospital, Ghent
Principal Investigator: Johan Decruyenaere, MD, PhD UIniversity Hospital Ghent
University Hospital, Ghent
December 2011

ICMJE     Data element required by the International Committee of Medical Journal Editors and the World Health Organization ICTRP