There are some things that you never have to prepare for life – like the dreaded call that a loved one has in a coma, and you're responsible for making life choices, if they do not wake up.
These decisions are made even more difficult by the fact that there is no true test of consciousness. Unfortunately, it is difficult for doctors to predict who will wake up and who will not.
A research team from Columbia University's Irving Medical Center, however, has indicated that a tool available in nearly every hospital in the world has effectively revealed signs of "hidden consciousness" in comatose patients. These subtle patterns in brain activity are signals that the person is aware of but physically unable to show.
A study published in the New England Journal of Medicine found that an electroencephalogram (EEG) is a machine in one in seven people who can detect electrical activity in the brain just days after a serious brain injury Evidence of a hidden consciousness can be found. And at follow-up of patients a year later, researchers said that people who initially showed signs of hidden consciousness were more likely to recover.
The Gray Zone
If someone does not respond for days or weeks, doctors use a variety of tests to determine the likelihood of being pulled through. But these predictions are usually inaccurate, the researchers say – which is not surprising, considering that we are pretty much in the dark when it comes to understanding consciousness.
The consciousness and the way the brain makes it is far from fixed. Nonetheless, the researchers' interest in hidden consciousness is growing. At least one study found that a segment of patients who were outwardly vegetative had similar brain activity and connectivity as healthy, normal adults. But for some reason they can not wake up. Testing for these invisible signs of awareness could help doctors better manage their care in the future.
If one thing is clear, hidden forms of cognition are strong predictors of recovery. However, researchers have not come to the best possible way to recognize this gray area of consciousness in clinical settings.
Earlier this year, a research team noted that fMRI can detect brain patterns that signal consciousness. Not only is FMRI expensive, but it is also challenging to perform these tests on people with brain injury who may not be clinically stable. Patients must leave the safety of the intensive care unit and possibly the hospital as a whole to be transported to an fMRI machine.
EEG tests, however, are not associated with these limitations. Because the EEG measures brainwave patterns with small discs attached to the scalp with wires, the test can be performed at the patient's bedside. The availability and lower cost of the EEG offer an advantage over the fMRI when it comes to closely monitoring what happens in a coma's head.
Early signs of recovery
In the new study, researchers used machine learning to analyze EEG data from 104 unresponsive patients with brain injury due to hemorrhage, trauma or hypoxia. The algorithm looked for brain activity that suggested that the person could understand instructions for moving their hands. If the commands produced different patterns of brain activity, it indicated that the unresponsive person might be able to understand the command, but the movements failed to physically perform any injuries. Half of these patients improved and could follow verbal instructions before being discharged from the hospital. A year later, 44 percent were able to work independently for up to eight hours a day.
Some people who did not show early signs of hidden consciousness also improved, but their results were not as good. Around 26 percent of people who did not have such brain activity were eventually discharged from the hospital. In this group, only 14 percent could work for up to eight hours regardless of their one-year follow-up.
About one third of patients died in both groups after brain injury.
Although their initial results are encouraging, researchers are looking at more research to better understand how the EEG can be used to predict recovery in various causes of brain injury.