Vegetative State: Can we measure the potential for change?
When we hear the term “vegetative state” we commonly think of a person who has experienced a brain injury of such magnitude where a return to consciousness is unlikely. A recent study conducted by Steven Laureys, MD, PhD and his colleagues of the University of Liege in Belgium shows that enhanced imaging methodology offers a better opportunity to predict outcomes than clinical exams. In Dr. Laureys’ group of 13 individuals identified as clinically vegetative who were assessed with one of two imaging methods, 9 eventually returned to full awareness. FDG-PET, short for positron emission tomography with flurodeoxyglucose tracer) was the more accurate method as reported in the online The Lancet. It correctly predicted outcomes in 75 of 102 patients or a rate of 74% accuracy. Active fMRI or functional Magnetic Resonance Imaging were less accurate at 36 of 65 patients scanned using that technique or 56%.
Dr. Laureys noted that “Cerebral FDG-PET scans could be used to complement bedside examinations and predict the long-term recovery of patients with unresponsive wakefulness syndrome” (a term synonymous with vegetative state). The study supports treating individuals with “unresponsive wakefulness syndrome” as being conscious and providing the appropriate treatment at bedside. The fMRI approach continues to offer promise as it is regarded as more sensitive for nonvolitional signs of consciousness. In a study of fMRI and FDG-PET consisting of126 individuals: 41 patients with unresponsive wakefulness syndrome, 81 considered minimally conscious and 4 with locked-in syndrome (fully conscious but unable to move or communicate), the 4 with locked-in syndrome were found to be fully conscious with FDG-PET and fMRI. In spite of problems with scanning some of the participants, both imaging methods had positive predictive values of 65% with the negative outcome predictive value of FDG-PET identified as superior at 92% vs. 52%.
The small study offers much promise in establishing greater reliability in identifying patients who are likely to regain consciousness and to rally greater resources around these individuals to promote recovery.