Cognitive Outcomes and Neuroimages Associated With Anesthesia-Related EEG Signatures
NCT ID: NCT03442179
Last Updated: 2023-08-01
Study Results
Results pending
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Basic Information
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Recruitment Status
UNKNOWN
Total Enrollment
24 participants
Study Classification
OBSERVATIONAL
Study Start Date
2019-02-13
Study Completion Date
2024-05-11
Brief Summary
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In this study, we propose to evaluate the relationship between the alpha oscillation dynamics and the signals derived from the brain images related to brain aging.
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Detailed Description
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In 1955 Bedford reported the "adverse cerebral effects of anesthesia on old people" and suggested precautions in relation to operations on the elderly. Since then, many studies have investigated the incidence of and the risk factors for postoperative cognitive dysfunction (POCD). The incidence ranges from 8.9% to 46.1% and advanced age, preoperative mild cognitive impairment, extensive surgical procedures and other factors have been identified as important risk factors. The incidence has been reported to be as high as 41.4% at hospital discharge and 12.7% at 3 months after surgery in the elderly (60 years or older). Postoperative delirium (POD) is a more acute complication of major surgery, affecting 10-70% of surgical patients 60 years and older. Some studies have shown the association between POD and early POCD, and even POD and POCD are commonly reported as being part of the same continuum. Whether this is true or not, both represent postoperative cognitive deterioration, and age is the predominant risk factor for both.
Every day in the United States, nearly 100,000 patients undergo general anesthesia and sedation for surgical and diagnostic procedures. Approximately 35% of all surgical procedures are performed on adults older than 65 years. Considering the aging surgical population, the burden of postoperative cognitive disorders will almost certainly increase over time.
Although many factors, such as surgical stress, inflammation, and other comorbidities may contribute to POCD, there is evidence that anesthetic exposure plays a major role. Pre-clinical studies have demonstrated that exposure to anesthetic drugs is neurotoxic, and that older animals are particularly vulnerable. It is also generally understood that the elderly are more sensitive to anesthetics, meaning that lower doses of anesthetic drugs are required to induce and maintain unconsciousness. This has led to age-adjusted guidelines for anesthetic dosing, which in theory could be used to mitigate potentially harmful anesthetic exposures. However, these guidelines describe the age-dependent dose-response relationships for a population of patients; individual drug requirements can vary significantly, by a factor of \~2 above or below the levels recommended by population-based models. In the absence of a means to measure and monitor individual drug responses, anesthesiologists would tend to err on the side of administering more anesthetic than required, to minimize the probability of patient awareness across the population as a whole.
Fortunately, in recent years, significant progress has been made to understand the neural mechanisms of anesthesia-induced unconsciousness, making it possible to monitor individual patients' drug responses using the electroencephalogram (EEG). Increasing concentrations of the commonly-used GABAergic anesthetic drugs, such as propofol and sevoflurane, induce a stereotyped sequence of brain oscillations with increasing drug concentration. These brain oscillations are directly related to the states of sedation and unconsciousness induced by anesthetic drugs, and readily observed using the EEG. At lower concentrations, propofol and sevoflurane, two of the most commonly used anesthetic drugs, induce beta oscillations (12-25 Hz). At concentrations producing unconsciousness for general anesthesia, these drugs produce frontal alpha (8-12 Hz) and slow (0.1 to 1 Hz) oscillations. At still higher concentrations, propofol and sevoflurane produce a pattern referred to as burst suppression, a deep state of brain inactivation in which brain activity is punctuated by long periods of neuronal and EEG silence. However, it is now known that elderly patients do not always exhibit this canonical EEG signature under general anesthesia. First, it was described that ageing was associated with a decrease in the frontal alpha power. Then, other studies suggested that older patients with poor preoperative cognitive performance also lack the alpha band under anesthesia. And finally, our group demonstrated that a low alpha power is also associated with a higher risk to develop burst suppression under anesthesia. Nonetheless, the potential mechanism related to the lower alpha power with ageing and cognitive function remains unknown. In this study, we propose to evaluate the relationship between the alpha oscillation dynamics and the signals derived from brain images related to brain aging.
We hypothesize that: 1) Brain imaging signals will correlate with the alpha power induced by anesthetics, and 2) Aging brain imaging features will be associated with postoperative cognitive recovery.
Every day in the United States, nearly 100,000 patients undergo general anesthesia and sedation for surgical and diagnostic procedures. Approximately 35% of all surgical procedures are performed on adults older than 65 years. Considering the aging surgical population, the burden of postoperative cognitive disorders will almost certainly increase over time.
Although many factors, such as surgical stress, inflammation, and other comorbidities may contribute to POCD, there is evidence that anesthetic exposure plays a major role. Pre-clinical studies have demonstrated that exposure to anesthetic drugs is neurotoxic, and that older animals are particularly vulnerable. It is also generally understood that the elderly are more sensitive to anesthetics, meaning that lower doses of anesthetic drugs are required to induce and maintain unconsciousness. This has led to age-adjusted guidelines for anesthetic dosing, which in theory could be used to mitigate potentially harmful anesthetic exposures. However, these guidelines describe the age-dependent dose-response relationships for a population of patients; individual drug requirements can vary significantly, by a factor of \~2 above or below the levels recommended by population-based models. In the absence of a means to measure and monitor individual drug responses, anesthesiologists would tend to err on the side of administering more anesthetic than required, to minimize the probability of patient awareness across the population as a whole.
Fortunately, in recent years, significant progress has been made to understand the neural mechanisms of anesthesia-induced unconsciousness, making it possible to monitor individual patients' drug responses using the electroencephalogram (EEG). Increasing concentrations of the commonly-used GABAergic anesthetic drugs, such as propofol and sevoflurane, induce a stereotyped sequence of brain oscillations with increasing drug concentration. These brain oscillations are directly related to the states of sedation and unconsciousness induced by anesthetic drugs, and readily observed using the EEG. At lower concentrations, propofol and sevoflurane, two of the most commonly used anesthetic drugs, induce beta oscillations (12-25 Hz). At concentrations producing unconsciousness for general anesthesia, these drugs produce frontal alpha (8-12 Hz) and slow (0.1 to 1 Hz) oscillations. At still higher concentrations, propofol and sevoflurane produce a pattern referred to as burst suppression, a deep state of brain inactivation in which brain activity is punctuated by long periods of neuronal and EEG silence. However, it is now known that elderly patients do not always exhibit this canonical EEG signature under general anesthesia. First, it was described that ageing was associated with a decrease in the frontal alpha power. Then, other studies suggested that older patients with poor preoperative cognitive performance also lack the alpha band under anesthesia. And finally, our group demonstrated that a low alpha power is also associated with a higher risk to develop burst suppression under anesthesia. Nonetheless, the potential mechanism related to the lower alpha power with ageing and cognitive function remains unknown. In this study, we propose to evaluate the relationship between the alpha oscillation dynamics and the signals derived from brain images related to brain aging.
We hypothesize that: 1) Brain imaging signals will correlate with the alpha power induced by anesthetics, and 2) Aging brain imaging features will be associated with postoperative cognitive recovery.
Conditions
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Elderly
General Anesthesia
Study Design
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Observational Model Type
COHORT
Study Time Perspective
PROSPECTIVE
Eligibility Criteria
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Inclusion Criteria
* 65 years old or above (male and female)
* American Society of Anesthesiologists (ASA) physical status classification of I, II or III.
* Candidates scheduled for open or laparoscopic general surgical procedures under general anesthesia
* No cognitive impairment base on Telephone Interview for Cognitive Status (TICS)
* Fluency in English Language
* American Society of Anesthesiologists (ASA) physical status classification of I, II or III.
* Candidates scheduled for open or laparoscopic general surgical procedures under general anesthesia
* No cognitive impairment base on Telephone Interview for Cognitive Status (TICS)
* Fluency in English Language
Exclusion Criteria
* Prior diagnosis of dementia
* Prior diagnosis of Alzheimer's Disease
* Prior history of psychiatric or neurological diseases including:
* Schizophrenia
* Parkinsonism
* Epilepsy or seizure
* Brain injury
* Brain tumors/metastases
* Encephalitis
* Stroke, CVA, TIA
* Drug or alcohol abuse:
* Any history of IV drug abuse
* Alcohol/drug (non-IV) abuse \<10 years
* Language impairment
* Hearing or visual impairment
* Severe obesity (BMI ≥40 kg/m2)
* MRI contraindications, such as presence of pacemakers, aneurysm clips, artificial heart valves, ear implants, metal fragments, or foreign objects in the eyes, skin, or body
* Body weight of \> 300 lbs. (weight limit of the MRI table)
* Prior diagnosis of Alzheimer's Disease
* Prior history of psychiatric or neurological diseases including:
* Schizophrenia
* Parkinsonism
* Epilepsy or seizure
* Brain injury
* Brain tumors/metastases
* Encephalitis
* Stroke, CVA, TIA
* Drug or alcohol abuse:
* Any history of IV drug abuse
* Alcohol/drug (non-IV) abuse \<10 years
* Language impairment
* Hearing or visual impairment
* Severe obesity (BMI ≥40 kg/m2)
* MRI contraindications, such as presence of pacemakers, aneurysm clips, artificial heart valves, ear implants, metal fragments, or foreign objects in the eyes, skin, or body
* Body weight of \> 300 lbs. (weight limit of the MRI table)
Minimum Eligible Age
65 Years
Eligible Sex
ALL
Accepts Healthy Volunteers
No
Sponsors
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Massachusetts General Hospital
OTHER
Sponsor Role
lead
Responsible Party
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Patrick L. Purdon
Associate Professor of Anaesthesia
Responsibility Role
PRINCIPAL_INVESTIGATOR
Principal Investigators
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Patrick L. Purdon, PhD
Role: PRINCIPAL_INVESTIGATOR
Massachusetts General Hospital
Locations
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Massachusetts General Hospital
Boston, Massachusetts, United States
Site Status
Countries
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United States
References
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Akeju O, Westover MB, Pavone KJ, Sampson AL, Hartnack KE, Brown EN, Purdon PL. Effects of sevoflurane and propofol on frontal electroencephalogram power and coherence. Anesthesiology. 2014 Nov;121(5):990-8. doi: 10.1097/ALN.0000000000000436.
Reference Type
BACKGROUND
Fournier A, Krause R, Winterer G, Schneider R. Biomarkers of postoperative delirium and cognitive dysfunction. Front Aging Neurosci. 2015 Jun 9;7:112. doi: 10.3389/fnagi.2015.00112. eCollection 2015.
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BACKGROUND
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BACKGROUND
BEDFORD PD. Adverse cerebral effects of anaesthesia on old people. Lancet. 1955 Aug 6;269(6884):259-63. doi: 10.1016/s0140-6736(55)92689-1. No abstract available.
Reference Type
BACKGROUND
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Besch G, Liu N, Samain E, Pericard C, Boichut N, Mercier M, Chazot T, Pili-Floury S. Occurrence of and risk factors for electroencephalogram burst suppression during propofol-remifentanil anaesthesia. Br J Anaesth. 2011 Nov;107(5):749-56. doi: 10.1093/bja/aer235. Epub 2011 Aug 8.
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BACKGROUND
Brice DD, Hetherington RR, Utting JE. A simple study of awareness and dreaming during anaesthesia. Br J Anaesth. 1970 Jun;42(6):535-42. doi: 10.1093/bja/42.6.535. No abstract available.
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BACKGROUND
Chemali J, Ching S, Purdon PL, Solt K, Brown EN. Burst suppression probability algorithms: state-space methods for tracking EEG burst suppression. J Neural Eng. 2013 Oct;10(5):056017. doi: 10.1088/1741-2560/10/5/056017. Epub 2013 Sep 10.
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BACKGROUND
Ching S, Cimenser A, Purdon PL, Brown EN, Kopell NJ. Thalamocortical model for a propofol-induced alpha-rhythm associated with loss of consciousness. Proc Natl Acad Sci U S A. 2010 Dec 28;107(52):22665-70. doi: 10.1073/pnas.1017069108. Epub 2010 Dec 13.
Reference Type
BACKGROUND
Flores FJ, Hartnack KE, Fath AB, Kim SE, Wilson MA, Brown EN, Purdon PL. Thalamocortical synchronization during induction and emergence from propofol-induced unconsciousness. Proc Natl Acad Sci U S A. 2017 Aug 8;114(32):E6660-E6668. doi: 10.1073/pnas.1700148114. Epub 2017 Jul 25.
Reference Type
BACKGROUND
Fritz BA, Kalarickal PL, Maybrier HR, Muench MR, Dearth D, Chen Y, Escallier KE, Ben Abdallah A, Lin N, Avidan MS. Intraoperative Electroencephalogram Suppression Predicts Postoperative Delirium. Anesth Analg. 2016 Jan;122(1):234-42. doi: 10.1213/ANE.0000000000000989.
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BACKGROUND
Guidera JA, Taylor NE, Lee JT, Vlasov KY, Pei J, Stephen EP, Mayo JP, Brown EN, Solt K. Sevoflurane Induces Coherent Slow-Delta Oscillations in Rats. Front Neural Circuits. 2017 Jul 4;11:36. doi: 10.3389/fncir.2017.00036. eCollection 2017.
Reference Type
BACKGROUND
Hussain M, Berger M, Eckenhoff RG, Seitz DP. General anesthetic and the risk of dementia in elderly patients: current insights. Clin Interv Aging. 2014 Sep 24;9:1619-28. doi: 10.2147/CIA.S49680. eCollection 2014.
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Iwakiri H, Nishihara N, Nagata O, Matsukawa T, Ozaki M, Sessler DI. Individual effect-site concentrations of propofol are similar at loss of consciousness and at awakening. Anesth Analg. 2005 Jan;100(1):107-110. doi: 10.1213/01.ANE.0000139358.15909.EA.
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Krenk L, Rasmussen LS. Postoperative delirium and postoperative cognitive dysfunction in the elderly - what are the differences? Minerva Anestesiol. 2011 Jul;77(7):742-9.
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Lewis LD, Ching S, Weiner VS, Peterfreund RA, Eskandar EN, Cash SS, Brown EN, Purdon PL. Local cortical dynamics of burst suppression in the anaesthetized brain. Brain. 2013 Sep;136(Pt 9):2727-37. doi: 10.1093/brain/awt174. Epub 2013 Jul 25.
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BACKGROUND
Lewis LD, Weiner VS, Mukamel EA, Donoghue JA, Eskandar EN, Madsen JR, Anderson WS, Hochberg LR, Cash SS, Brown EN, Purdon PL. Rapid fragmentation of neuronal networks at the onset of propofol-induced unconsciousness. Proc Natl Acad Sci U S A. 2012 Dec 4;109(49):E3377-86. doi: 10.1073/pnas.1210907109. Epub 2012 Nov 5.
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Mapleson WW. Effect of age on MAC in humans: a meta-analysis. Br J Anaesth. 1996 Feb;76(2):179-85. doi: 10.1093/bja/76.2.179.
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Marcantonio ER, Ngo LH, O'Connor M, Jones RN, Crane PK, Metzger ED, Inouye SK. 3D-CAM: derivation and validation of a 3-minute diagnostic interview for CAM-defined delirium: a cross-sectional diagnostic test study. Ann Intern Med. 2014 Oct 21;161(8):554-61. doi: 10.7326/M14-0865.
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BACKGROUND
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Purdon PL, Pavone KJ, Akeju O, Smith AC, Sampson AL, Lee J, Zhou DW, Solt K, Brown EN. The Ageing Brain: Age-dependent changes in the electroencephalogram during propofol and sevoflurane general anaesthesia. Br J Anaesth. 2015 Jul;115 Suppl 1(Suppl 1):i46-i57. doi: 10.1093/bja/aev213.
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BACKGROUND
Purdon PL, Pierce ET, Mukamel EA, Prerau MJ, Walsh JL, Wong KF, Salazar-Gomez AF, Harrell PG, Sampson AL, Cimenser A, Ching S, Kopell NJ, Tavares-Stoeckel C, Habeeb K, Merhar R, Brown EN. Electroencephalogram signatures of loss and recovery of consciousness from propofol. Proc Natl Acad Sci U S A. 2013 Mar 19;110(12):E1142-51. doi: 10.1073/pnas.1221180110. Epub 2013 Mar 4.
Reference Type
BACKGROUND
Purdon PL, Sampson A, Pavone KJ, Brown EN. Clinical Electroencephalography for Anesthesiologists: Part I: Background and Basic Signatures. Anesthesiology. 2015 Oct;123(4):937-60. doi: 10.1097/ALN.0000000000000841.
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BACKGROUND
Radtke FM, Franck M, Lendner J, Kruger S, Wernecke KD, Spies CD. Monitoring depth of anaesthesia in a randomized trial decreases the rate of postoperative delirium but not postoperative cognitive dysfunction. Br J Anaesth. 2013 Jun;110 Suppl 1:i98-105. doi: 10.1093/bja/aet055. Epub 2013 Mar 28.
Reference Type
BACKGROUND
Rundshagen I. Postoperative cognitive dysfunction. Dtsch Arztebl Int. 2014 Feb 21;111(8):119-25. doi: 10.3238/arztebl.2014.0119.
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BACKGROUND
Schnider TW, Minto CF, Shafer SL, Gambus PL, Andresen C, Goodale DB, Youngs EJ. The influence of age on propofol pharmacodynamics. Anesthesiology. 1999 Jun;90(6):1502-16. doi: 10.1097/00000542-199906000-00003.
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BACKGROUND
Sebel PS, Bowdle TA, Ghoneim MM, Rampil IJ, Padilla RE, Gan TJ, Domino KB. The incidence of awareness during anesthesia: a multicenter United States study. Anesth Analg. 2004 Sep;99(3):833-839. doi: 10.1213/01.ANE.0000130261.90896.6C.
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Soehle M, Dittmann A, Ellerkmann RK, Baumgarten G, Putensen C, Guenther U. Intraoperative burst suppression is associated with postoperative delirium following cardiac surgery: a prospective, observational study. BMC Anesthesiol. 2015 Apr 28;15:61. doi: 10.1186/s12871-015-0051-7.
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Steinmetz J, Rasmussen LS. Peri-operative cognitive dysfunction and protection. Anaesthesia. 2016 Jan;71 Suppl 1:58-63. doi: 10.1111/anae.13308.
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Strom C, Rasmussen LS, Sieber FE. Should general anaesthesia be avoided in the elderly? Anaesthesia. 2014 Jan;69 Suppl 1(Suppl 1):35-44. doi: 10.1111/anae.12493.
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Vutskits L, Xie Z. Lasting impact of general anaesthesia on the brain: mechanisms and relevance. Nat Rev Neurosci. 2016 Oct 18;17(11):705-717. doi: 10.1038/nrn.2016.128.
Reference Type
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Other Identifiers
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2017P000413
Identifier Type: -
Identifier Source: org_study_id
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