Heart Rate Variability to Quantify General Anesthesia Depth

Anesthesia Awareness Clinical Trial

Official title:

Heart Rate Variability as Tool for Quantification of General Anesthesia Depth in Patients

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04788732
• Other study ID #: CAAE: 33066620.1.0000.5440
• Status: Recruiting
• Start date: January 4, 2021
• Est. completion date: August 30, 2022

Study information

• Verified date: March 2021
• Source: University of Sao Paulo
• Contact: Waynice N Paula-Garcia
• Phone: +5516981154121
• Email: wgarcia[@]fmrp.usp.br
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial 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.

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

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 200
• Est. completion date: August 30, 2022
• Est. primary completion date: May 30, 2022
• Accepts healthy volunteers: No
• Gender: All
• Age group: N/A and older

Eligibility

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.

Related Conditions & MeSH terms

• Anesthesia Awareness
• Intraoperative Awareness

Intervention

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.

Locations

Country	Name	City	State
Brazil	Waynice N. Paula-Garcia	Ribeirão Preto	Sao Paulo

Sponsors (1)

Lead Sponsor	Collaborator
University of Sao Paulo

Country where clinical trial is conducted

Brazil, 

References & Publications (7)

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. — View Citation

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

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. — View Citation

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

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. — View Citation

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. — View Citation

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

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	To create a new Depth of Anesthesia (DoA) Score based on Heart Rate Variability indices	Define a score capable of reflecting DoA, combining different indices derived from ECG, such as HRV.	12 months
Secondary	Impact of the differnet anesthetic drugs on the HRV indices (derived from ECG)	Correlate HRV indices (derived from ECG) with the concentration and final consumption of anesthetic drugs throughout the anesthetic-surgical procedure.	12 months
Secondary	Impact of the anesthesia adjuvant drugs on the HRV indices (derived from ECG)	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.	12 months
Secondary	Time to wake up	Correlate HRV indices (derived from ECG) with the time to wake up	12 months
Secondary	Time spent in PACU	Correlate HRV indices (derived from ECG) with the time spent in PACU	12 months
Secondary	Aldrete score	Correlate HRV indices (derived from ECG) with the Aldrete score	12 months
Secondary	Incidence of nausea and vomiting	Correlate HRV indices (derived from ECG) with the incidence of postoperative nausea and vomiting, .	12 months
Secondary	Incidence of delirium	Correlate HRV indices (derived from ECG) with the incidence of postoperative delirium	12 months
Secondary	Incidence of intraoperative memory.	Correlate HRV indices (derived from ECG) with the incidence of intraoperative memory.	12 months
Secondary	Impact of frailty on the HRV indexes (derived from ECG)	The impact of pre-anesthetic frailty (evaluated by the Clinical Frailty Scale) on ECG and EEG variables in the intraoperative period.	12 months
Secondary	Impact of the basal cognitive status on the HRV indexes (derived from ECG)	The impact of the basal cognitive status on ECG and EEG variables in the intraoperative period.	12 months