• Alessandro Pincherle, Frederic Rossi, Jane Jöhr, Vincent Dunet, Philippe Ryvlin, Mauro Oddo, Nicolas Schiff, and Karin Diserens.
• Acute Neuro-rehabilitation Unit, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Bâtiment Champ de l'Air, Rue du Bugnon 21, 1011, Lausanne, Switzerland. apincherle@gmail.com.
• J. Neurol. 2021 Jan 1; 268 (1): 178-188.

AbstractBedside assessment of consciousness and awareness after a severe brain injury might be hampered by confounding clinical factors (i.e., pitfalls) interfering with the production of behavioral or motor responses to external stimuli. Despite the use of validated clinical scales, a high misdiagnosis rate is indeed observed. We retrospectively analyzed a cohort of 49 patients with severe brain injury admitted to an acute neuro-rehabilitation program. Patients' behavior was assessed using the Motor Behavior Tool and Coma Recovery Scale Revised. All patients underwent systematic assessment for pitfalls including polyneuropathy and/or myopathy and/or myelopathy, major cranial nerve palsies, non-convulsive status epilepticus, aphasia (expressive or comprehensive), cortical blindness, thalamic involvement and frontal akinetic syndrome. A high prevalence (75%) of pitfalls potentially interfering with sensory afference (polyneuropathy, myopathy, myelopathy, and sensory aphasia), motor efference (polyneuropathy, myopathy, motor aphasia, and frontal akinetic syndrome), and intrinsic brain activity (thalamic involvement and epilepsy) was found. Nonetheless, the motor behavior tool identified residual cognition (i.e. a cognitive motor dissociation condition) regardless of the presence of these pitfalls in 70% of the patients diagnosed as unresponsive using the Coma Recovery Scale Revised. On one hand, pitfalls might contribute to misdiagnosis. On the other, it could be argued that they are clues for diagnosing cognitive motor dissociation rather than true disorders of consciousness given their prominent effect on the sensory-motor input-output balance.

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