Heart Rate Variability to Quantify General Anesthesia Depth

• ClinicalTrials.gov Identifier: NCT04788732
• Recruitment Status: Recruiting
• First Posted: March 9, 2021
• Last Update Posted: March 9, 2021
• Sponsor: University of Sao Paulo
• Information provided by (Responsible Party): Waynice N.P. Garcia, University of Sao Paulo

Study Description

Brief Summary:

The shortage of anesthetic agents can lead to intraoperative awareness while overdosing can trigger severe intra and postoperative problems. Therefore, monitoring anesthesia's depth (DoA: Depth of Anesthesia) is a crucial but still challenging task. Although some commercial monitors are based on electroencephalogram (EEG), designed to quantify DoA, their use in clinical practice has limitations. On the other hand, heart rate variability (HRV) has valuable information about physiological states, both from the heart and the organism. Classical indices derived from HRV have been shown to be able to differentiate the different stages of anesthesia. In this study, it is proposed to create a model to monitor DoA combining several HRV indices. Patients will be divided into three groups, according to the type of anesthesia to which they will be submitted (inhalation, total or balanced intravenous) and will have the electrocardiogram recorded during the entire surgical procedure. Various HRV indices will be calculated, and machine learning techniques will be used to combine and identify the most relevant index to compose a score that reliably represents DoA. Several commercial devices have been developed to monitor the level of consciousness during anesthesia. Among the most popular tools are included: Narcotrend TM (MonitorTechnik, Bad Bramstedt, Germany); the M-Entropy TM (GE Healthcare, Helsinki, Finland); Nindex SA (Controls, Montevideo, Uruguay) and the Bi-Spectral Index (BIS, TM Medtronic-Covidien, Dublin, Ireland). In this study, BIS or Nindex will also be monitored during the entire period that the patients remain anesthetized and will later be used to compose the DoA score based on HRV. As a result, a computer program will be created to monitor DoA in real-time.

Condition or disease	Intervention/treatment
Anesthesia Awareness	Device: ECG and EEG monitoring

Detailed Description:

Anesthesia is a state of reversible unconsciousness induced by one or more pharmacological agents. The three main anesthesia components are analgesia (pain relief), amnesia (memory loss), and immobilization, including autonomic reflexes' inhibition for harmful stimuli.1 Drugs used to induce anesthesia, in general, have different effects on each of these three components mentioned above.

Anesthesia depth assessment ( DoA: from English, Depth of Anesthesia ) is essential for anesthetic practice. The DoA depends on two opposing factors: the amount of anesthetic agent administered to the patient and the stimuli produced during surgery, increasing the level of awareness, and the patient's nociception. The ideal level d the DoA involves the guaranteed unconsciousness and anti-nociception adequate during surgery without compromise the functions of vital organs. In other words, one of the main challenges for anesthetists is to identify the appropriate amount of anesthetic to be administered to avoid the unwanted effects of anesthetic shortages (leading, for example, to intraoperative awareness) or anesthetic overdose, which can cause severe problems during intra and postoperative periods. 2 Before using muscle relaxants, the appropriate level of DoA could be monitored by the absence of movements to painful stimuli; once, the surgical incision's lack of movements was a sure sign that the patient was not superficially anesthetized. However, with the muscle relaxants' adoption in the anesthetics protocols, other measures to ensure that anesthetic agents' concentrations were administered properly were necessary.

Becoming conscious during surgery is a major concern for patients and anesthesiologists. It is estimated that the incidence of consciousness during general anesthesia is low, around 0.04% to 0.3%. However, considering the high number of surgical interventions, accidental awareness during surgery represents thousands of cases worldwide. Therefore, despite being an old problem, awareness during anesthesia is still a very relevant issue in public health.

DoA inefficient may also lead to an imbalance nociception x anti-nociception intraoperatively, even without patient conscious pain. Nociceptive stimuli can substantially affect the physiological state, inducing, for example, tachycardia, hypertension, nausea, fainting, and, therefore, negatively influencing patients' postoperative period 1 Thus, careful and efficient monitoring of DoA is the key to minimizing both the possibility of accidental awareness in surgeries and the overdose of anesthetic agents. 3 However, despite the importance of monitoring d the DoA, it is not easy to quantify this parameter during general anesthesia, and several approaches have been proposed to accomplish this task.

Quantification of DoA:

The anesthetic depth could be identified by monitoring the sympathetic activity of the patient. However, many anesthetics substantially alter autonomic activity, both sympathetic and parasympathetic. The observation of autonomic responses such as sweating, tear formation, hypertension, tachycardia, and pupil dilation are also important indicators of adequate unconsciousness levels. However, these signals cannot guide the anesthetist, considering that the patient cannot react due to neuromuscular blockade. 3 On the other hand, some authors suggest monitoring the concentration of inspired and expired anesthetic gases as markers of DoA.4 However, to date, there is no standardized and universally accepted method for quantifying DoA, and the anesthesiologist's experience is still the most important and effective factor in determining DoA.

DoA's monitoring techniques have advanced considerably in recent years. The nature of changes in electroencephalographic patterns during the stages of anesthesia was studied in detail, opening up possibilities for monitoring DoA by identifying electroencephalogram (EEG) patterns with crucial clinical significance for anesthesia.5 The use of EEG devices made monitoring of DoA potentially easier and was recommended by NIH - Care Excellence.

Although the progress brought by EEG-based monitors to anesthetic practice is indisputable, they still have significant limitations: 1) the algorithms created to derive a single DoA index from the EEG are exclusive (owned by their creators) for each device; 2) The EEG obtained in these devices is limited, exclusively, to the activity of the frontal lobe, lacking the representation of deeper subcortical structures ; 3) EEG is recognized for being highly sensitive to a variety of sources of interference during monitoring; 4) it is high cost restricts the availability of such equipment. Several monitors have prices ranging from £ 4,687 to £ 10,285 for the initial purchase, followed by the acquisition of single-use sensors ranging from £ 0.56 to £ 14.08. (3) Also, recent studies have pointed to substantial divergences between the most common commercial displays at DoA, making the application of these electronic devices still controversial and not universally recommended. 4 Specific limitations to the use of BIS, such as the inconsistency of this index in some situations, have also been reported. 6 BIS's particular challenge involves the administration of ketamine, nitric oxide, and xenon, which do not produce the typical EEG patterns observed during general anesthesia with other anesthetic agents. Besides, as the BIS was created based on a database of volunteers under specific conditions, it must be revalidated whenever used with a new drug or even a unique patient population, whose characteristics differ from the original population database data.7

Study Design

• Study Type: Observational [Patient Registry]
• Estimated Enrollment: 200 participants
• Observational Model: Cohort
• Time Perspective: Prospective
• Target Follow-Up Duration: 1 Year
• Official Title: Heart Rate Variability as Tool for Quantification of General Anesthesia Depth in Patients
• Actual Study Start Date: January 4, 2021
• Estimated Primary Completion Date: May 30, 2022
• Estimated Study Completion Date: August 30, 2022

Groups and Cohorts

Group/Cohort	Intervention/treatment
1-Inhalation Anesthesia; patients in this group will be anesthetized only with an inhaled anesthetic ( Sevoflurane ).	Device: ECG and EEG monitoring; the ECG and EEG will also be monitored during the entire period that the patients remain anesthetized with various anesthetics drugs and will later be used to compose the DoA score based on HRV.
2-Total Intravenous Anesthesia; the patients in this group will be anesthetized with only intravenous drugs such as benzodiazepícos (midazolam), opioids (alfentanil, fentanyl, sufentanil, remifentanil), hypnotics ( propofol and etomidate ), associated or not to relaxing neuromuscular (nondepolarizing/depolarizing), and adjuvant drugs such as dextrocetamina, dexmedetomidine, lidocaine, and magnesium sulfate.	Device: ECG and EEG monitoring; the ECG and EEG will also be monitored during the entire period that the patients remain anesthetized with various anesthetics drugs and will later be used to compose the DoA score based on HRV.
3-Balanced anesthesia; the patients in this group will be anesthetized with blends of anesthetic inhaled (Sevoflurane) and intravenous drugs such as benzodiazepine (midazolam), opioids (alfentanil, fentanyl, sufentanil, remifentanil), hypnotics ( propofol and etomidate ), associated or not with neuromuscular relaxants (nonpolarizing/depolarizing) and adjuvant drugs such as dextrocetamine, dexmedetomidine, lidocaine, and magnesium sulfate.	Device: ECG and EEG monitoring; the ECG and EEG will also be monitored during the entire period that the patients remain anesthetized with various anesthetics drugs and will later be used to compose the DoA score based on HRV.

Outcome Measures

Primary Outcome Measures :

1. To create a new Depth of Anesthesia (DoA) Score based on Heart Rate Variability indices [ Time Frame: 12 months ]
   Define a score capable of reflecting DoA, combining different indices derived from ECG, such as HRV.

Secondary Outcome Measures :

1. Impact of the differnet anesthetic drugs on the HRV indices (derived from ECG) [ Time Frame: 12 months ]
   Correlate HRV indices (derived from ECG) with the concentration and final consumption of anesthetic drugs throughout the anesthetic-surgical procedure.
2. Impact of the anesthesia adjuvant drugs on the HRV indices (derived from ECG) [ Time Frame: 12 months ]
   Correlate HRV indices (derived from ECG) with the concentration and final consumption of adjuvant drugs (for example: lidocaine, dexmedetomedine, magnesium sulfate) throughout the anesthetic-surgical procedure.
3. Time to wake up [ Time Frame: 12 months ]
   Correlate HRV indices (derived from ECG) with the time to wake up
4. Time spent in PACU [ Time Frame: 12 months ]
   Correlate HRV indices (derived from ECG) with the time spent in PACU
5. Aldrete score [ Time Frame: 12 months ]
   Correlate HRV indices (derived from ECG) with the Aldrete score
6. Incidence of nausea and vomiting [ Time Frame: 12 months ]
   Correlate HRV indices (derived from ECG) with the incidence of postoperative nausea and vomiting, .
7. Incidence of delirium [ Time Frame: 12 months ]
   Correlate HRV indices (derived from ECG) with the incidence of postoperative delirium
8. Incidence of intraoperative memory. [ Time Frame: 12 months ]
   Correlate HRV indices (derived from ECG) with the incidence of intraoperative memory.
9. Impact of frailty on the HRV indexes (derived from ECG) [ Time Frame: 12 months ]
   The impact of pre-anesthetic frailty (evaluated by the Clinical Frailty Scale) on ECG and EEG variables in the intraoperative period.
10. Impact of the basal cognitive status on the HRV indexes (derived from ECG) [ Time Frame: 12 months ]
    The impact of the basal cognitive status on ECG and EEG variables in the intraoperative period.

Biospecimen Retention:   Samples With DNA

whole blood and plasma sample

Eligibility Criteria

• Ages Eligible for Study: Child, Adult, Older Adult
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: No
• Sampling Method: Non-Probability Sample

Study Population

Patients ASA (classification by the American Society of Anesthesiology) 1-3, of all ages, undergoing general anesthesia will be considered and divided into three groups, according to the type of anesthesia used: inhaled, total intravenous, or balanced.

Criteria

Inclusion Criteria:

• ASA patients (classification by the American Society of Anesthesiology) 1-3, of all ages, scheduled to undergo procedures under general anesthesia.

Exclusion Criteria:

• Patients with craniofacial deformities in which it is not possible to place the EEG sensors.
• Patients with severe eczema, allergy, or skin atopy.
• Patients with a history of severe autonomic dysfunction.
• Need of autonomic cardiac blockers during the intraoperative period.
• Absence of Consent.

Contacts and Locations

Contacts

Contact: Waynice N Paula-Garcia; +5516981154121; wgarcia@fmrp.usp.br

Locations

Brazil

Waynice N. Paula-Garcia; Recruiting

Ribeirão Preto, Sao Paulo, Brazil, 14.048-900

Contact: Waynice N Paula-Garcia +5516981154121 waynicegarcia@gmail.com

Contact +551636021000 ext 2211 wgarcia@fmrp.usp.br

Principal Investigator: Waynice N Paula-garcia

Principal Investigator: Rubens Fazan Junior

Principal Investigator: Luis Vicente Garcia

Sponsors and Collaborators

University of Sao Paulo

More Information

Publications:

Guignard B. Monitoring analgesia. Best Pract Res Clin Anaesthesiol. 2006 Mar;20(1):161-80. Review.

Fahy BG, Chau DF. The Technology of Processed Electroencephalogram Monitoring Devices for Assessment of Depth of Anesthesia. Anesth Analg. 2018 Jan;126(1):111-117. doi: 10.1213/ANE.0000000000002331. Review.

Smith A. Literature review: Awareness of anaesthesia. J Perioper Pract. 2017 Sep;27(9):191-195. Review.

Merry AF, Cooper JB, Soyannwo O, Wilson IH, Eichhorn JH. International Standards for a Safe Practice of Anesthesia 2010. Can J Anaesth. 2010 Nov;57(11):1027-34. doi: 10.1007/s12630-010-9381-6. Epub 2010 Sep 21.

Shander A, Lobel GP, Mathews DM. Brain Monitoring and the Depth of Anesthesia: Another Goldilocks Dilemma. Anesth Analg. 2018 Feb;126(2):705-709. doi: 10.1213/ANE.0000000000002383. Review.

Hajat Z, Ahmad N, Andrzejowski J. The role and limitations of EEG-based depth of anaesthesia monitoring in theatres and intensive care. Anaesthesia. 2017 Jan;72 Suppl 1:38-47. doi: 10.1111/anae.13739. Review.

Kissin I. Depth of anesthesia and bispectral index monitoring. Anesth Analg. 2000 May;90(5):1114-7.

• Responsible Party: Waynice N.P. Garcia, Assistant Professor, M.D, Ph.D, University of Sao Paulo
• ClinicalTrials.gov Identifier: NCT04788732
• Other Study ID Numbers: CAAE: 33066620.1.0000.5440
• First Posted: March 9, 2021
• Last Update Posted: March 9, 2021
• Last Verified: March 2021

Individual Participant Data (IPD) Sharing Statement:

• Plan to Share IPD: Undecided

• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No

Keywords provided by Waynice N.P. Garcia, University of Sao Paulo:

general anesthesia; consciousness; heart rate variability; general anaesthesia monitors; computational analysis

Additional relevant MeSH terms:

Intraoperative Awareness; Intraoperative Complications; Pathologic Processes