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Multimodal Neuroprognostication in Disorders of Consciousness

Multimodal Neuroprognostication in Disorders of Consciousness

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT04534777
Acronym
M-Neuro-DoC
Enrollment
500
Registered
2020-09-01
Start date
2020-09-09
Completion date
2027-05-31
Last updated
2024-02-05

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Consciousness Disorder

Keywords

electroencephalography, evoked potentials, functional magnetic resonance imaging, minimally conscious state, positron emission tomography, resting state fMRI (functional magnetic resonance imaging ), transcranial magnetic stimulation, traumatic brain injury, unresponsive wakefulness syndrome, vegetative state, polysomnography

Brief summary

Disorders of consciousness frequently occur at the acute phase of brain injuries. For the most severe cases, consciousness impairment can be prolonged. To optimize the medical plan and the goal of care, it is fundamental to have precise tools to predict chances of recovery of consciousness and potential disability. Currently, multimodal assessment including behavioral, neurophysiological and neuroimaging technics is recommended. However, the respective predictive values of these markers are poorly understood and decision making is challenging when results are contradictory

Detailed description

Improved treatment of critically ill patients has resulted in increased patients' survival rates in Intensive Care Units (ICU). This is particularly true for brain injury such as traumatic brain injuries, cerebral hemorrhages or cardiac arrest. While some of these patients regain consciousness after a transient state known as coma, other will develop a prolonged disorder of consciousness (DoC) such as chronic unresponsive wakefulness syndrome (also known as vegetative state) or minimally conscious state, or will remain severely disabled. Consciousness diagnosis and prediction of recovery in DoC currently relies on standardized behavioral assessment and disease-specific markers. However, this strategy may fail to detect covert consciousness due to major sensory and motor deficits. Moreover, the DoC etiology and pathophysiology are heterogenous and most likely result from the combination of factors whose interplay still needs to be clarified. Consciousness detection in DoC is of great importance in term of medical management (e.g., pain management, communication), prognosis (e.g., orientation to adapted rehabilitation center to maximize chance of recovery) and end-of-life discussions (e.g., withholding and/or withdrawing of life support discussion). Furthermore, taking care of these patients can be very stressful due to the high levels of uncertainty associated to their potential of recovery. For all these reasons it is critical to develop personalized diagnosis and prognosis assessment tools that can allow better decisions. The M-NeuroDoC study will take advantage from the state-of-the-art multimodal assessment ongoing at our institution for both acute and chronic patients in order to improve recovery prediction. Indeed, our multimodal assessment practice constitutes a great and unique opportunity to better understand the respective diagnostic and prognostic accuracy performances of markers such as behavioral, electrophysiological and neuroimaging that are routinely performed at our institution. The overall outcome of this project will allow to draw better single-patient predictions of state, prognosis, and rehabilitation strategies and furthermore, a better understanding the pathophysiological mechanisms behind DoC that could result in groundbreaking new personalized therapeutic approaches. Based on the collected data, we will evaluate the respective diagnostic accuracy of all the markers acquired in clinical practice regarding the clinical outcome at 2 years. Data of interest will be: * repeated neurological assessments * repeated behavioural assessments suing validated tools: * neurophysiological explorations * conventional brain imagery (CT, IRM) * quantitative brain imagery * functional brain imagery , mental imagery

Interventions

OTHERrepeated neurological, behavioral assessments and conventional, quantitative and functional brain imagery

Based on the collected data, we will evaluate the respective diagnostic accuracy of all the markers acquired in clinical practice regarding the clinical outcome at 2 years.

Sponsors

Assistance Publique - Hôpitaux de Paris
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
OTHER

Eligibility

Sex/Gender
ALL
Age
18 Years to 80 Years
Healthy volunteers
No

Inclusion criteria

1. Consciousness disorder (acute sub-acute or chronic for which our expertise is requested to better characterize the diagnostic and prognosis of recovery) 2. Brain injuries on CT or MRI (e.g. TBI) (traumatic brain-injured ), anoxia or stroke related lesions, etc…) 3. Age between 18 and 80 years

Exclusion criteria

1. Deep sedation (e.g. elevated ICP(intracranial pressure ), refractory status epilepticus) 2. Sever known neurodegenerative disease (e.g. Alzheimer disease) 3. Pregnancy

Design outcomes

Primary

MeasureTime frameDescription
prognosis accuracy of respective predictive markers of consciousness recovery24 MONTHSCalculation of the value (Chi2 tests, specificity, sensitivity, positive and negative predictive values of each tests and of their combinations to distinguish patients states and outcome (24-month GOS-E ≥ 4 or \< 4).

Secondary

MeasureTime frameDescription
GOS-E Glasgow outcome scale - Extended6, 12 and 18 monthsEvolution of GOS-E (Glasgow outcome scale - Extended) scale from category 1 ==\> Death to category 8: good recovery upper ==\>no current problems related to the brain injury that affect daily life

Countries

France

Contacts

Primary ContactBenjamin ROHAUT, MD
benjamin.rohaut@aphp.fr184827888
Backup ContactLionel NACCACHE, PUPH
lionel.naccache@aphp.fr157274314

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 7, 2026