ComaNCT03826407
Development of a Point of Care System for Automated Coma Prognosis
An observational study of Coma and Disorder of Consciousness, run by McMaster University at 1 site in Canada.
Trial summary
Electroencephalogram/event-related potentials (EEG/ERP) data will be collected from 50 participants in coma or other disorder of consciousness (DOC; i.e., Unresponsive Wakefulness Syndrome [UWS] or Minimally Conscious State [MCS]), clinically diagnosed using the Glasgow Coma Scale (GCS). Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Coma, Disorder of Consciousness, Minimally Conscious State
- How many people
- 33 participants
- Where
- 1 siteCanada
- Study dates
- 1 Oct 2019to Dec 2023
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: The Coma/DOC Group will include 50 patients from the Intensive Care Units, Neurological Step Down Unit, or Coronary Care Unit at Hamilton General Hospital (Ontario, Canada) who are in coma (GCS score =3-8), or who have other disorders of consciousness (MCS or UWS). The Control Group of 40 matched healthy controls will be recruited primarily from the Hamilton community (Ontario, Canada).
Who may be able to join
- Patients (≥ 18 years of age) primarily admitted to the Intensive Care Units, Neurological Step Down Unit, or Coronary Care Unit at Hamilton General Hospital who are in coma with Glasgow Coma Scale (GCS) score of 3-8, or;
- Patients (≥ 18 years of age) who have other disorders of consciousness, primarily Minimally Conscious State (MCS) or Unresponsive Wakefulness Syndrome (UWS; also known as vegetative state).
- ≥ 18 years of age
- no visual, language, learning, or hearing problems
- no history of neurological or psychiatric disorder
- not currently taking any medications that act on the central nervous system, such as antidepressants, anxiolytics, or anti-epileptics
Who cannot join
- Severe liver failure (i.e., Child-Pugh Class C)
- Severe renal failure (i.e., Urea ≥ 40)
- Previous open-head injury
- Known primary and secondary central nervous system malignancy
- Known hearing impairment
- Previous intracranial pathology requiring neurosurgical interventions in the past 72 hours
Show all 12Show fewer
- Anyone who is deemed medically unsuitable for this study by the attending intensivists
- Healthy Controls:
- (During the COVID-19 pandemic only)
- ≥ 60 years of age
- have a weakened immune system
- have one or more of the COVID-19 high risk medical conditions, according to the government of Canada website: https://www.canada.ca/en/public-health/services/publications/diseases-conditions/people-high-risk-for-severe-illness-covid-19.html.
Trial locations and contacts
1 site in 1 country.
Canada1 site
McMaster University Hamilton Health Sciences / Hamilton General Hospital
Hamilton, Ontario, L8L 2X2
About this study
Official title: Development of a Point of Care System for Automated Coma Prognosis - A Prospective Cohort Study
Electroencephalogram/event-related potentials (EEG/ERP) data will be collected from 50 participants in coma or other disorder of consciousness (DOC; i.e., Unresponsive Wakefulness Syndrome [UWS] or Minimally Conscious State [MCS]), clinically diagnosed using the Glasgow Coma Scale (GCS). For coma patients, EEG recordings will be conducted for up to 24 consecutive hours at a maximum of 5 timepoints, spanning 30 days from the date of recruitment, to track participants' clinical state. For DOC patients, there will be an initial EEG recording up to 24 hours, with possible subsequent weekly recordings up to 2 hours. An additional dataset from 40 healthy controls will be collected, each spanning up to a 12-hour recording period in order to formulate a baseline. Collected data are to form the basis for automatic analysis and detection of ERP components in DOC, using a machine learning paradigm. Salient features (i.e., biomarkers) extracted from the ERPs and resting-state EEG will be identified and combined in an optimal fashion to give an accurate indicator of prognosis.
Read the detailed description
The Problem: Coma is a state of unconsciousness with a variety of causes. Traditional tests for coma outcome prediction are mainly based on a set of clinical observations (e.g., pupillary constriction). Recently however, event-related potentials (ERPs; which are transient electroencephalogram [EEG] responses to auditory, visual, or tactile stimuli) have been introduced as useful predictors of a positive coma outcome (i.e., emergence). However, such tests require a skilled neurophysiologist, and such people are in short supply. Also, none of the current approaches has sufficient positive and negative predictive accuracies to provide definitive prognoses in the clinical setting.
Objective: The investigators will apply innovative machine learning methods to analyze patient EEGs (50 patients and 40 healthy controls) to develop a simple, objective, replicable, and inexpensive point of care system which can significantly improve the accuracy of coma prognosis relative to current methods. The physical requirements of the proposed system consist only of an EEG system (inexpensive in terms of medical equipment) and a conventional laptop computer.
Methodology: The investigators intend to extend the team's newest algorithms and develop machine learning tools for automatic analysis and detection of ERP components. Preliminary results by the team in this respect have been very promising. The most salient features (i.e., biomarkers) extracted from the ERP will be identified and combined in an optimal fashion to give an accurate indicator of prognosis. Features will be extracted from resting state brain networks and from network trajectories associated with the processing of ERP signals.
Significance: The proposed work will enable critical care physicians to assess coma prognosis with speed and accuracy. Thus, families and their health care team will be provided the most accurate information possible to guide discussions of goals of care and life-sustaining therapies in the context of dealing with the consequences of devastating neurological injury.
- Conditions
- Coma, Disorder of Consciousness, Minimally Conscious State, Vegetative State, Neuropathology
- Keywords
- Coma, Machine Learning, Prognosis, Electrophysiology, Event-related potentials, Electroencephalography, Mismatch Negativity, Auditory Brainstem Response, Disorders of Consciousness, EEG, ERP
- Medical subject headings
- Coma, Consciousness Disorders, Persistent Vegetative State
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| DOC patients | Patients in coma (GCS score of 3-8) or with other disorder of consciousness, primarily Minimally Conscious State (MCS) or Unresponsive Wakefulness Syndrome (UWS; also known as vegetative state) | |
| Healthy Control | Matched healthy controls without current neurological diagnoses |
What is being measured
The primary outcome is the main question the study is designed to answer.
Change in multiple electrophysiological measures across specified time points during coma
Event-related potentials (ERP) and resting state periods will be assessed at the specified intervals as a difference between successive timepoints. The ERP measures will include amplitude and latency values of N1, P2, MMN, P3a, P3b, and N400 to assess different levels of conscious processing and presence of signs of a conscious state predictive of subsequent emergence. Also, resting EEG measures will be obtained at regular intervals. EEG/ERP data will be recorded for up to 24 consecutive hours at a maximum of 5 timepoints spanning 30 days from the date of recruitment to track the participants' progression. The date of the initial assessment will be denoted as Day 0, and the subsequent assessments will take place ideally on Day 3, Day 10, Day 20 and Day 30, unless there is a ≥ 2 point of change in the patient's GCS score. Change in all specified measures will be assessed across the up to 24-hour recordings taken at 5 different timepoints.
Measured: up to 30 days from date of recruitment
Change in multiple electrophysiological measures across specified time points during MCS or UWS
Event-related potentials (ERP) and resting state periods will be assessed at the specified intervals as a difference between successive timepoints. The ERP measures will include amplitude and latency values of N1, P2, MMN, P3a, P3b, and N400 to assess different levels of conscious processing and presence of signs of a conscious state predictive of subsequent emergence. Also, resting EEG measures will be obtained at regular intervals. EEG/ERP data will be recorded for an initial period of up to 24 consecutive hours, followed by up to 2-hour long recordings that may be conducted approximately once a week until the patient either regains full consciousness, is no longer within the Hamilton Health Sciences system, or until 6 months from the date of their enrollment into the study, whichever occurs first. Change in all specified measures will be assessed across the recordings taken at each timepoint.
Measured: up to 6 months from date of recruitment
Correlation between behavioral and electrophysiological measures after coma/DOC emergence
Patient emergence will be monitored using the Glasgow Outcome Scale (GOS). In the case of patient emergence, the full electrophysiological test procedures are recorded to correlate with traditional behavioral measures. The electrophysiological measures obtained at this timepoint (emergence) will be compared to the same measures obtained at the different time points during coma/DOC (Outcome 1/2) to detect both clinically relevant change and possible prognostic markers that may have been obtained at an earlier test point.
Measured: Within a 30-day time period post recruitment
Sensitivity and specificity of prognostic capabilities of electrophysiological measures
Analyses will compare the electrophysiological measures as outcome predictors to traditional behaviorally-based tools.
Measured: Within a 30-day time period post recruitment
Feasibility of procedure
The team will also evaluate whether the repeated EEG sessions, lasting up to 24 hours, during the coma/DOC duration is a feasible approach to predict the emergence and outcome from coma.
Measured: up to 6 months from date of recruitment
Secondary outcomes (2)
Correlation between individual patient factors, EEG results, and outcome for coma
The study also collects demographic, medical history, injury information, and other physiological markers from the patient's health record and concurrent physiological assessment during the study period. Analyses will assess correlations between these factors and coma outcome and EEG findings.
Measured: up to 30 days from date of recruitment
Correlations between individual patient factors, EEG results, and outcome for DOC
The study also collects demographic, medical history, injury information, and other physiological markers from the patient's health record and concurrent physiological assessment during the study period. Analyses will assess correlations between these factors and DOC outcome and EEG findings.
Measured: up to 6 months from date of recruitment
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted1 Feb 2019
- Study start1 Oct 2019
- Primary completion12 Aug 2022
- Study completionDec 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (27)Papers the sponsor has linked to this study.
- Other trials for ComaStudies of the same condition, open and under way.
- More trials run by McMaster UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 33 participants (actual)
Sponsor and investigators
- Lead sponsor
- McMaster University
- Sponsor type
- University, hospital or other
- Collaborators
- Canadian Institutes of Health Research (CIHR), Natural Sciences and Engineering Research Council, Canada, Hamilton Health Sciences Corporation, Brain Vision Solutions Inc., McGill University
- Responsible party
- Sponsor
- Investigators
- John F Connolly, PhD, Principal investigator, McMaster UniversityAlison Fox-Robichaud, MD, Study chair, Hamilton Health Sciences - Hamilton General site
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03826407
- Sponsor's protocol ID
- ComaML2018
- Other IDs
- CPG158287, CHRP 523461-18
- Status last verified
- Feb 2023
- First submitted
- 18 Jan 2019
- Last updated
- 6 Feb 2023
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided: To be decided
Publications
Jones C. Glasgow coma scale. Am J Nurs. 1979 Sep;79(9):1551-3. No abstract available.
PubMed 258560Chiappa KH, Hill RA. Evaluation and prognostication in coma. Electroencephalogr Clin Neurophysiol. 1998 Feb;106(2):149-55. doi: 10.1016/s0013-4694(97)00118-1.
PubMed 9741776de Sousa LC, Colli BO, Piza MR, da Costa SS, Ferez M, Lavrador M. Auditory brainstem response: prognostic value in patients with a score of 3 on the Glasgow Coma Scale. Otol Neurotol. 2007 Apr;28(3):426-8. doi: 10.1097/MAO.0b013e3180326170.
PubMed 17303965Logi F, Fischer C, Murri L, Mauguiere F. The prognostic value of evoked responses from primary somatosensory and auditory cortex in comatose patients. Clin Neurophysiol. 2003 Sep;114(9):1615-27. doi: 10.1016/s1388-2457(03)00086-5.
PubMed 12948790Lew HL, Poole JH, Castaneda A, Salerno RM, Gray M. Prognostic value of evoked and event-related potentials in moderate to severe brain injury. J Head Trauma Rehabil. 2006 Jul-Aug;21(4):350-60. doi: 10.1097/00001199-200607000-00006.
PubMed 16915010Kane NM, Butler SR, Simpson T. Coma outcome prediction using event-related potentials: P(3) and mismatch negativity. Audiol Neurootol. 2000 May-Aug;5(3-4):186-91. doi: 10.1159/000013879.
PubMed 10859412Morlet D, Fischer C. MMN and novelty P3 in coma and other altered states of consciousness: a review. Brain Topogr. 2014 Jul;27(4):467-79. doi: 10.1007/s10548-013-0335-5. Epub 2013 Nov 27.
PubMed 24281786Fischer C, Morlet D, Bouchet P, Luaute J, Jourdan C, Salord F. Mismatch negativity and late auditory evoked potentials in comatose patients. Clin Neurophysiol. 1999 Sep;110(9):1601-10. doi: 10.1016/s1388-2457(99)00131-5.
PubMed 10479027Holeckova I, Fischer C, Giard MH, Delpuech C, Morlet D. Brain responses to a subject's own name uttered by a familiar voice. Brain Res. 2006 Apr 12;1082(1):142-52. doi: 10.1016/j.brainres.2006.01.089.
PubMed 16703673Garrido MI, Kilner JM, Stephan KE, Friston KJ. The mismatch negativity: a review of underlying mechanisms. Clin Neurophysiol. 2009 Mar;120(3):453-63. doi: 10.1016/j.clinph.2008.11.029. Epub 2009 Jan 31.
PubMed 19181570Sonnadara RR, Alain C, Trainor LJ. Occasional changes in sound location enhance middle latency evoked responses. Brain Res. 2006 Mar 3;1076(1):187-92. doi: 10.1016/j.brainres.2005.12.093. Epub 2006 Feb 17.
PubMed 16487494Duncan CC, Barry RJ, Connolly JF, Fischer C, Michie PT, Naatanen R, Polich J, Reinvang I, Van Petten C. Event-related potentials in clinical research: guidelines for eliciting, recording, and quantifying mismatch negativity, P300, and N400. Clin Neurophysiol. 2009 Nov;120(11):1883-1908. doi: 10.1016/j.clinph.2009.07.045. Epub 2009 Sep 30.
PubMed 19796989Schnakers C, Vanhaudenhuyse A, Giacino J, Ventura M, Boly M, Majerus S, Moonen G, Laureys S. Diagnostic accuracy of the vegetative and minimally conscious state: clinical consensus versus standardized neurobehavioral assessment. BMC Neurol. 2009 Jul 21;9:35. doi: 10.1186/1471-2377-9-35.
PubMed 19622138Guldenmund P, Stender J, Heine L, Laureys S. Mindsight: diagnostics in disorders of consciousness. Crit Care Res Pract. 2012;2012:624724. doi: 10.1155/2012/624724. Epub 2012 Nov 14.
PubMed 23213492Giacino JT, Fins JJ, Laureys S, Schiff ND. Disorders of consciousness after acquired brain injury: the state of the science. Nat Rev Neurol. 2014 Feb;10(2):99-114. doi: 10.1038/nrneurol.2013.279. Epub 2014 Jan 28.
PubMed 24468878
Study at a glance
From the registry record, last updated by the sponsor on 6 Feb 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development of a Point of Care System for Automated Coma Prognosis - A Prospective Cohort Study
- ClinicalTrials.gov ID
- NCT03826407
- Acronym / sponsor ID
- ComaML2018
- Conditions
- Coma, Disorder of Consciousness, Minimally Conscious State, Vegetative State, Neuropathology
- Keywords
- Coma, Machine Learning, Prognosis, Electrophysiology, Event-related potentials, Electroencephalography, Mismatch Negativity, Auditory Brainstem Response
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 33 participants (actual)
- Lead sponsor
- McMaster UniversityUniversity, hospital or other
- Collaborators
- Canadian Institutes of Health Research (CIHR), Natural Sciences and Engineering Research Council, Canada, Hamilton Health Sciences Corporation, Brain Vision Solutions Inc., McGill University
- Study start
- 1 Oct 2019 (actual)
- Primary completion
- 12 Aug 2022 (actual)
- Study completion
- Dec 2023 (estimated)
- First posted
- 1 Feb 2019 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Electroencephalogram/event-related potentials (EEG/ERP) data will be collected from 50 participants in coma or other disorder of consciousness (DOC; i.e., Unresponsive Wakefulness Syndrome [UWS] or Minimally Conscious State [MCS]), clinically diagnosed using the Glasgow Coma Scale (GCS). For coma patients, EEG recordings will be conducted for up to 24 consecutive hours at a maximum of 5 timepoints, spanning 30 days from the date of recruitment, to track participants' clinical state. For DOC patients, there will be an initial EEG recording up to 24 hours, with possible subsequent weekly recordings up to 2 hours. An additional dataset from 40 healthy controls will be collected, each spanning up to a 12-hour recording period in order to formulate a baseline. Collected data are to form the basis for automatic analysis and detection of ERP components in DOC, using a machine learning paradigm. Salient features (i.e., biomarkers) extracted from the ERPs and resting-state EEG will be identified and combined in an optimal fashion to give an accurate indicator of prognosis.
Detailed description
The Problem: Coma is a state of unconsciousness with a variety of causes. Traditional tests for coma outcome prediction are mainly based on a set of clinical observations (e.g., pupillary constriction). Recently however, event-related potentials (ERPs; which are transient electroencephalogram [EEG] responses to auditory, visual, or tactile stimuli) have been introduced as useful predictors of a positive coma outcome (i.e., emergence). However, such tests require a skilled neurophysiologist, and such people are in short supply. Also, none of the current approaches has sufficient positive and negative predictive accuracies to provide definitive prognoses in the clinical setting.
Objective: The investigators will apply innovative machine learning methods to analyze patient EEGs (50 patients and 40 healthy controls) to develop a simple, objective, replicable, and inexpensive point of care system which can significantly improve the accuracy of coma prognosis relative to current methods. The physical requirements of the proposed system consist only of an EEG system (inexpensive in terms of medical equipment) and a conventional laptop computer.
Methodology: The investigators intend to extend the team's newest algorithms and develop machine learning tools for automatic analysis and detection of ERP components. Preliminary results by the team in this respect have been very promising. The most salient features (i.e., biomarkers) extracted from the ERP will be identified and combined in an optimal fashion to give an accurate indicator of prognosis. Features will be extracted from resting state brain networks and from network trajectories associated with the processing of ERP signals.
Significance: The proposed work will enable critical care physicians to assess coma prognosis with speed and accuracy. Thus, families and their health care team will be provided the most accurate information possible to guide discussions of goals of care and life-sustaining therapies in the context of dealing with the consequences of devastating neurological injury.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| DOC patients | – | –Patients in coma (GCS score of 3-8) or with other disorder of consciousness, primarily Minimally Conscious State (MCS) or Unresponsive Wakefulness Syndrome (UWS; also known as vegetative state) |
| Healthy Control | – | –Matched healthy controls without current neurological diagnoses |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- The Coma/DOC Group will include 50 patients from the Intensive Care Units, Neurological Step Down Unit, or Coronary Care Unit at Hamilton General Hospital (Ontario, Canada) who are in coma (GCS score =3-8), or who have other disorders of consciousness (MCS or UWS). The Control Group of 40 matched healthy controls will be recruited primarily from the Hamilton community (Ontario, Canada).
Key inclusion criteria (6 listed)
- Patients (≥ 18 years of age) primarily admitted to the Intensive Care Units, Neurological Step Down Unit, or Coronary Care Unit at Hamilton General Hospital who are in coma with Glasgow Coma Scale (GCS) score of 3-8, or;
- Patients (≥ 18 years of age) who have other disorders of consciousness, primarily Minimally Conscious State (MCS) or Unresponsive Wakefulness Syndrome (UWS; also known as vegetative state).
- ≥ 18 years of age
- no visual, language, learning, or hearing problems
- no history of neurological or psychiatric disorder
Key exclusion criteria (12 listed)
- Severe liver failure (i.e., Child-Pugh Class C)
- Severe renal failure (i.e., Urea ≥ 40)
- Previous open-head injury
- Known primary and secondary central nervous system malignancy
- Known hearing impairment
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Change in multiple electrophysiological measures across specified time points during coma
Time frame: up to 30 days from date of recruitment
Event-related potentials (ERP) and resting state periods will be assessed at the specified intervals as a difference between successive timepoints. The ERP measures will include amplitude and latency values of N1, P2, MMN, P3a, P3b, and N400 to assess different levels of conscious processing and presence of signs of a conscious state predictive of subsequent emergence. Also, resting EEG measures will be obtained at regular intervals. EEG/ERP data will be recorded for up to 24 consecutive hours at a maximum of 5 timepoints spanning 30 days from the date of recruitment to track the participants' progression. The date of the initial assessment will be denoted as Day 0, and the subsequent assessments will take place ideally on Day 3, Day 10, Day 20 and Day 30, unless there is a ≥ 2 point of change in the patient's GCS score. Change in all specified measures will be assessed across the up to 24-hour recordings taken at 5 different timepoints.
Change in multiple electrophysiological measures across specified time points during MCS or UWS
Time frame: up to 6 months from date of recruitment
Event-related potentials (ERP) and resting state periods will be assessed at the specified intervals as a difference between successive timepoints. The ERP measures will include amplitude and latency values of N1, P2, MMN, P3a, P3b, and N400 to assess different levels of conscious processing and presence of signs of a conscious state predictive of subsequent emergence. Also, resting EEG measures will be obtained at regular intervals. EEG/ERP data will be recorded for an initial period of up to 24 consecutive hours, followed by up to 2-hour long recordings that may be conducted approximately once a week until the patient either regains full consciousness, is no longer within the Hamilton Health Sciences system, or until 6 months from the date of their enrollment into the study, whichever occurs first. Change in all specified measures will be assessed across the recordings taken at each timepoint.
Correlation between behavioral and electrophysiological measures after coma/DOC emergence
Time frame: Within a 30-day time period post recruitment
Patient emergence will be monitored using the Glasgow Outcome Scale (GOS). In the case of patient emergence, the full electrophysiological test procedures are recorded to correlate with traditional behavioral measures. The electrophysiological measures obtained at this timepoint (emergence) will be compared to the same measures obtained at the different time points during coma/DOC (Outcome 1/2) to detect both clinically relevant change and possible prognostic markers that may have been obtained at an earlier test point.
Sensitivity and specificity of prognostic capabilities of electrophysiological measures
Time frame: Within a 30-day time period post recruitment
Analyses will compare the electrophysiological measures as outcome predictors to traditional behaviorally-based tools.
Feasibility of procedure
Time frame: up to 6 months from date of recruitment
The team will also evaluate whether the repeated EEG sessions, lasting up to 24 hours, during the coma/DOC duration is a feasible approach to predict the emergence and outcome from coma.
2 secondary outcomes
Correlation between individual patient factors, EEG results, and outcome for coma
Time frame: up to 30 days from date of recruitment
Correlations between individual patient factors, EEG results, and outcome for DOC
Time frame: up to 6 months from date of recruitment
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 Feb 2023.
- Background: PubMed 258560Jones C. Glasgow coma scale. Am J Nurs. 1979 Sep;79(9):1551-3. No abstract available.
- Background: PubMed 9741776Chiappa KH, Hill RA. Evaluation and prognostication in coma. Electroencephalogr Clin Neurophysiol. 1998 Feb;106(2):149-55. doi: 10.1016/s0013-4694(97)00118-1.
- Background: PubMed 17303965de Sousa LC, Colli BO, Piza MR, da Costa SS, Ferez M, Lavrador M. Auditory brainstem response: prognostic value in patients with a score of 3 on the Glasgow Coma Scale. Otol Neurotol. 2007 Apr;28(3):426-8. doi: 10.1097/MAO.0b013e3180326170.
- Background: PubMed 12948790Logi F, Fischer C, Murri L, Mauguiere F. The prognostic value of evoked responses from primary somatosensory and auditory cortex in comatose patients. Clin Neurophysiol. 2003 Sep;114(9):1615-27. doi: 10.1016/s1388-2457(03)00086-5.
- Background: PubMed 16915010Lew HL, Poole JH, Castaneda A, Salerno RM, Gray M. Prognostic value of evoked and event-related potentials in moderate to severe brain injury. J Head Trauma Rehabil. 2006 Jul-Aug;21(4):350-60. doi: 10.1097/00001199-200607000-00006.
- Background: PubMed 10859412Kane NM, Butler SR, Simpson T. Coma outcome prediction using event-related potentials: P(3) and mismatch negativity. Audiol Neurootol. 2000 May-Aug;5(3-4):186-91. doi: 10.1159/000013879.
- Background: PubMed 24281786Morlet D, Fischer C. MMN and novelty P3 in coma and other altered states of consciousness: a review. Brain Topogr. 2014 Jul;27(4):467-79. doi: 10.1007/s10548-013-0335-5. Epub 2013 Nov 27.
- Background: PubMed 10479027Fischer C, Morlet D, Bouchet P, Luaute J, Jourdan C, Salord F. Mismatch negativity and late auditory evoked potentials in comatose patients. Clin Neurophysiol. 1999 Sep;110(9):1601-10. doi: 10.1016/s1388-2457(99)00131-5.
- Background: PubMed 16703673Holeckova I, Fischer C, Giard MH, Delpuech C, Morlet D. Brain responses to a subject's own name uttered by a familiar voice. Brain Res. 2006 Apr 12;1082(1):142-52. doi: 10.1016/j.brainres.2006.01.089.
- Background: PubMed 19181570Garrido MI, Kilner JM, Stephan KE, Friston KJ. The mismatch negativity: a review of underlying mechanisms. Clin Neurophysiol. 2009 Mar;120(3):453-63. doi: 10.1016/j.clinph.2008.11.029. Epub 2009 Jan 31.
- Background: PubMed 16487494Sonnadara RR, Alain C, Trainor LJ. Occasional changes in sound location enhance middle latency evoked responses. Brain Res. 2006 Mar 3;1076(1):187-92. doi: 10.1016/j.brainres.2005.12.093. Epub 2006 Feb 17.
- Background: PubMed 19796989Duncan CC, Barry RJ, Connolly JF, Fischer C, Michie PT, Naatanen R, Polich J, Reinvang I, Van Petten C. Event-related potentials in clinical research: guidelines for eliciting, recording, and quantifying mismatch negativity, P300, and N400. Clin Neurophysiol. 2009 Nov;120(11):1883-1908. doi: 10.1016/j.clinph.2009.07.045. Epub 2009 Sep 30.
- Individual participant dataSharing planned: Undecided. To be decided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
John F Connolly, PhD principal investigator
McMaster University
Alison Fox-Robichaud, MD study chair
Hamilton Health Sciences - Hamilton General site
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Coma and Disorder of Consciousness, run by McMaster University at 1 site in Canada.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 12 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 6 Feb 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Canada. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Change in multiple electrophysiological measures across specified time points during coma (time frame: up to 30 days from date of recruitment). The study lists 5 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03826407, which also lists 27 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 6 Feb 2023.