Manual vs Automated Anesthesia : Impact On The Incidence Of POCD

NCT ID: NCT03148730

Last Updated: 2020-01-28

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 90 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2017-05-10
• Study Completion Date: 2017-11-21

Brief Summary

This study will be the first study to report the combined use of three independent closed-loop systems together to assist clinicians in titrating anesthesia, analgesia, fluid and optimize ventilation in frailty old patients undergoing moderate to high risk surgery. The potential benefits of optimizing the control of these variables by advanced closed loop systems are two-fold. Firstly, this will likely decrease the variance of delivered care and reduce deviation from the established standards, resulting in improved post operative cognitive outcomes in elderly patients. Secondly, this would establish a precedent that automated intraoperative systems have strong clinical significance and are more than "complicated toys", which is unfortunately how they are perceived now.

Hypothesis: Automated control of anesthetic depth (minimal episodes of overly deep or light anesthesia) and hemodynamics (via improved volume administration) can decrease the occurrence of postoperative cognitive dysfunction in elderly patients undergoing moderate to high risk surgery (Better MOCA test in the postoperative period compared to the manual group [+ two points in average])

Detailed Description

Elderly patients comprise more than 40% of all surgical patients in the USA per year and generate an even larger proportion of total healthcare costs with a sizable amount occurring during the postoperative period 1.. Therefore, reducing postoperative morbidity and mortality is a major concern in clinical practice and medical research moving forward. Cognitive dysfunction and dependence on caregivers represents two major risk factors in the elderly, especially following general anesthesia. The current literature indicates that POCD results in a mortality rate of 10% at 6 months for patients at least 70 years old and causes loss of functional capacity in an additional 20%. Overall, this results in an approximately 1 of 3 patients experiencing a negative cognitive impact following general anesthesia without optimization of anesthetic depth. In this context, continuous monitoring of the depth of anesthesia using a bispectral index (BIS) sensor may reduce the occurrence of postoperative impairments by via improved control of the anesthetic depth, especially over-sedation.

Despite steady improvements in surgical safety throughout recent years, the application of perioperative therapies still has the potential to be improved, especially regarding compliance to evidence-based recommendations.2, 3 Specifically, simply being surrounded by established monitors does not ensure that proper therapies are delivered most effectively or consistently to all patients - there must also be appropriate and timely interventions. Concordantly, large variations in patient care still exist and have been correlated with large variations in patient outcomes.4 Looking at the safety record that automation has achieved in fields ranging from manufacturing to commercial flight, medical researchers have developed devices utilizing self-contained feedback technologies (CLS) in an attempt to decrease the variability in treatment delivery with the ultimate goal of improving patient care. This development has flourished within anesthesiology, mainly via physiological closed-loop controlled devices. These systems are able to automatically adjust a therapeutic intervention based on continuous feedback from various physiological sensors.5 The best described systems have been closed-loop delivery of anesthetics, analgesics,6-11 volatile agents, insulin, and most recently, fluids 5, 12-14 and vasopressors.15-17 Overall, these systems have been shown to improve the consistency of intervention when compared to manual administration.10, 18, 19 Additionally, computer-assistance for clinical care will allow anesthesia providers to increase their accuracy and consistency, improve their awareness, and allow them to instead focus on more complex tasks.

Over the past years, members of our group have developed a dual closed-loop controller allowing the automated titration of propofol and remifentanil guided by the bispectral index (BIS).11, 20-22 The investigators also have created an adaptative closed-loop system for fluid titration using goal directed fluid therapy (GDFT) strategies guided by a minimally invasive cardiac output monitor.5 The investigator has previously demonstrated the superiority of a controller versus human-guided anesthesia in maintaining a target of BIS between 40 and 60 while limiting the incidence of overly deep anesthesia, which is often associated with the occurrence of a cognitive dysfunction in the elderly 23 Very recently, the principal investigator submitted research evaluating the simultaneous use of 2 closed-loop system (anesthesia, analgesia and fluid management) in a pilot study of high risk vascular patients.

Objectives: The main objective of this prospective randomized single-blinded controlled study is to compare manual versus automated administration of anesthesia, analgesia, fluid and ventilation with regard to the incidence of postoperative cognitive dysfunction (POCD) in elderly patients undergoing high risk surgery. POCD will be assessed by a psychiatrist and/or a psychologist preoperatively, on postoperative day 3-10 (depending on the type of surgery) and at 3-months postoperatively. Additionally, quality of life and quality of recovery will also be self-assessed before surgery, before hospital discharge and at 3 month post-surgery.

Conditions

Postoperative Delirium

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: SUPPORTIVE_CARE
• Blinding Strategy: DOUBLE

Study Groups

manual group

This group will have a standard of care anesthesia. All the drugs, fluid and adjustement of ventilation settings will be done manually by the supervising anesthesiologist using the same drugs and fluids as the closed-loop group

Group Type: NO_INTERVENTION

No interventions assigned to this group

automated closed-loop group

This group will have a fully automated anesthesia, analgesia , ventilation and fluid management using 3 indenpendent closed-loop systems same drugs used in both groups ( propofol and remifentanil, Plasmalyte and /or Voluven)

Group Type: EXPERIMENTAL

closed-loop group

Intervention Type: DEVICE

Use of 3 indenpendent closed-loop systems to deliver the propofol, remifentanil, fluid and to adjust ventilation

Interventions

closed-loop group

Use of 3 indenpendent closed-loop systems to deliver the propofol, remifentanil, fluid and to adjust ventilation

Intervention Type: DEVICE

Eligibility Criteria

Inclusion Criteria

• Adult patients > or equal 60 years old
• ASA score I-III
• Scheduled for non cardiac surgery under total intravenous anesthesia
• Self sufficient (living at home or in non medical institution)
• MOCA test preop > 23/30
• No Stroke, alzeihmer, Parkinson disease
• Written informed consent signed

Exclusion Criteria

• Allergy to propofol or remifentanil
• MOCA test < 23/30
• Visual or hearing deficiency
• Atrial fibrillation, or other Contra indication to the use of dynamic parameters of fluid responsiveness.
• Chronic renal failure ( creatinin level maximum at 2 mg/ml; no dialysis)
• Large liver resection : our center has a strict fluid /CVP fluid restriction in place

• Minimum Eligible Age: 60 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Erasme University Hospital

OTHER

Sponsor Role: lead

Responsible Party

Alexandre Joosten, MD PhD

Principal Investigator

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Alexandre Joosten, M.D

Role: PRINCIPAL_INVESTIGATOR

Erasme

Locations

Erasme

Brussels, , Belgium

Countries

Belgium

Other Identifiers

P2015/539 / B406201526591

Identifier Type: -

Identifier Source: org_study_id