Summary: Researchers developed a multimodal approach combining PET scans, EEG, and fMRI to improve prognosis for patients with disorders of consciousness (DoC) after severe trauma or cardiac arrest.
This method enhances the accuracy of predicting cognitive recovery, aiding medical decision-making. The research, involving 349 patients over 12 years, shows that the more diagnostic modalities used, the better the prognosis accuracy. This approach aims to provide better care for DoC patients globally.
Key Facts:
- Multimodal Approach: Combines PET scans, EEG, fMRI, and cognitive evoked potentials.
- Study Findings: Higher accuracy in prognosis with more diagnostic tools.
- Global Impact: Aims to improve care for DoC patients worldwide.
Source: Paris Brain Institute
After a severe cranial trauma or cardiac arrest, some patients admitted to intensive care show little or no reaction to their environment—and are sometimes unable to communicate. This condition is called a disorder of consciousness (DoC), which includes comas, vegetative states and states of “minimal consciousness.”
This disorder sometimes persists for several days or weeks. In such cases, healthcare teams and relatives must obtain the most accurate information on the patient’s cognitive recovery capacities.
Usually, a neurological prognosis is established using several indicators—including standard measurements of brain anatomy (CT and MRI scans) and function (electroencephalogram).
“Despite having these data at our disposal, there remains a degree of uncertainty about the prognosis, which can significantly impact medical decision-making.
“These patients are often in a fragile state and prone to numerous complications, which raises questions about the appropriateness of the care they receive,” explains Benjamin Rohaut, neurologist, researcher and lead author of the study.
“Moreover, doctors sometimes observe a discrepancy between the patient’s behaviour and their brain activity: some patients in a vegetative state seem to understand what is being said to them but are unable to let their caregivers know.”
To improve the description of the state of consciousness of these patients, the “PICNIC team”, co-led by Lionel Naccache at the Paris Brain Institute, has been working for around fifteen years to define new brain measurements and clinical examination signs.
Their approach has gradually evolved towards “multi-modality”, combining PET scans, multivariate EEG analysis, functional MRI, cognitive evoked potentials (electrical responses to sensory stimulation) and other tools.
Consciousness markers under scrutiny
To assess the clinical value of this approach, the team worked with the “Neurologically Oriented Intensive Care Unit” at the Pitié-Salpêtrière Hospital in Paris. Led by Benjamin Rohaut and Charlotte Calligaris, the clinicians and researchers followed and assessed 349 intensive-care patients between 2009 and 2021.
At the end of each multimodal evaluation, they formulated a “good”, “uncertain”, or “unfavourable” prognostic opinion.
Their results indicate that patients with a “good prognosis” (22% of cases) showed a much more favourable evolution of their cognitive abilities than patients with a prognosis judged “uncertain” (45.5% of cases) or “unfavourable” (32.5% of cases); none of the patients assessed as “unfavourable” regained consciousness after one year.
Above all, this prognostic performance was correlated with the number of modalities: the greater the number of indicators used, the greater the accuracy of the prognosis, and the greater the team’s confidence in its assessments.
“This long-term study shows for the first time the benefit of the multimodal approach, which is essential information for intensive care units worldwide. It also provides empirical validation of the recent recommendations of the European and American Neurology Academies, ” explains Jacobo Sitt, who co-supervised this study.
Towards a standardised neuroprognostic approach
However, the multimodal approach is not a magic wand. It provides the best possible information to caregivers and families in situations of uncertainty—an ethical advance in patient care—but does not guarantee bias-free decision-making.
Finally, there is the question of access to assessment tools, which are expensive and require specific expertise. “We are aware that multimodal assessment is not accessible to all the intensive care units that receive these patients”, continues Lionel Naccache.
“We propose to build a network of collaborations at the national and European levels. Thanks to telemedicine tools and automated EEG or brain imaging analysis, all intensive care units could have a first level of access to multimodal assessment.
“Should this prove insufficient, recourse to a regional expert centre would provide a more in-depth assessment. Finally, in the most complex situations, it would be possible to call on all available experts, wherever they may be.
“We aim to ensure that all patients with a disorder of consciousness can benefit from the highest standards of neurological prognosis.”
About this neurology and consciousness research news
Author: Marie Simon
Source: Paris Brain Institute
Contact: Marie Simon – Paris Brain Institute
Image: The image is credited to Neuroscience News
Original Research: Open access.
“Multimodal assessment improves neuroprognosis performance in clinically unresponsive critical care patients with brain injury” by Benjamin Rohaut et al. Nature Medicine
Abstract
Multimodal assessment improves neuroprognosis performance in clinically unresponsive critical care patients with brain injury
Accurately predicting functional outcomes for unresponsive patients with acute brain injury is a medical, scientific and ethical challenge. This prospective study assesses how a multimodal approach combining various numbers of behavioral, neuroimaging and electrophysiological markers affects the performance of outcome predictions.
We analyzed data from 349 patients admitted to a tertiary neurointensive care unit between 2009 and 2021, categorizing prognoses as good, uncertain or poor, and compared these predictions with observed outcomes using the Glasgow Outcome Scale–Extended (GOS-E, levels ranging from 1 to 8, with higher levels indicating better outcomes).
After excluding cases with life-sustaining therapy withdrawal to mitigate the self-fulfilling prophecy bias, our findings reveal that a good prognosis, compared with a poor or uncertain one, is associated with better one-year functional outcomes (common odds ratio (95% CI) for higher GOS-E: OR = 14.57 (5.70–40.32), P < 0.001; and 2.9 (1.56–5.45), P < 0.001, respectively). Moreover, increasing the number of assessment modalities decreased uncertainty (OR = 0.35 (0.21–0.59), P < 0.001) and improved prognostic accuracy (OR = 2.72 (1.18–6.47), P = 0.011).
Our results underscore the value of multimodal assessment in refining neuroprognostic precision, thereby offering a robust foundation for clinical decision-making processes for acutely brain-injured patients.
ClinicalTrials.gov registration: NCT04534777.
