Today we had an excellent Clinical Problems in Consultation Psychiatry (CPCP) presentation on delirium detection using the EEG by our medical students. It was pretty thought-provoking. My contribution was to bring Turtles in keeping with our new Mascot, Hal. He’s a turtle.
As a psychiatric consultant in the general hospital, I’ve come to think of myself as a human Delirium Detector. That’s different from an expert who knows how to manage or prevent delirium although I know a thing or two about that also. There are many screening instruments for detecting delirium, the most well known being the Confusion Assessment Method (CAM) and it’s critical care variation, the CAM-ICU, both developed by non-psychiatric clinicians. I believe that other physicians could be better Delirium Detectors than I–which is saying a lot because I have a pretty big ego, in case you haven’t figured that out already.
On the other hand, researchers and clinicians are always trying to figure out ways to improve our ability to detect delirium. Using screening scales like the CAM is one method. We have about 20 of them. We often partner with nurses using them–or we try. What seems to happen is that nurses administer the screening tools and tell physicians the results, which may or may not lead to effective responses. This reminds me of a survey I ran a few years ago on my blog to find out (in a very informal way) how this worked out.
OK, sound good? To be fair, let me point out that, the other day, a surgery resident asked me how she could detect delirium herself. I don’t get questions like that very often…in fact, almost never. So I gave her the quick instructions on how to use the CAM and gave her a pocket card reminder:
One screener that didn’t make the cut because of sneaky copyright laws was the Sweet 16. There’s a similarity to the trademark on Turtles. It contained elements that were too similar to a 16 item version of the Mini Mental Status Exam. Don’t bother looking for any reference to it on the HELP website…it’s gone away. The other way to detect delirium is by using a box. We tried the Delbox several years ago (formerly called the Edinburgh Delirium Test Box) developed to test attention, the cognitive feature thought to be most affected. An early version looked like the picture below:
The newer version of the EDTB sounds very interesting. You can see one of my original posts about it here. As far as I know, we’re not using it here. I learned about the new and exciting box version of the Delirium Detector using an EEG device just lately. One of my colleagues, Dr. Gen Shinozaki and Dr. John Cromwell from the Surgery just received funding to study the issue the medical students talked about in the CPCP.
I wonder what the American Delirium Society would think about the idea. I submitted a question on their website at the link American Delirium Society Blog Clarifying the Confusion. It usually takes a while to get comments reviewed so check back frequently in the next month or so.
Another question I have is who would take ownership of the EEG machine if it were found to be a useful device. The nurses? The psychiatrists? The neurologists? The surgeons and intensivists?
In my opinion, focusing on using a validated Delirium Detector or even being a Delirium Detector is fine but the most important thing is what to do about delirium once you find it. I don’t find detection to be such a challenge usually although sometimes it can be. Preventing it in the first place is certainly possible and it can be done in about 30% of patients who are at moderate risk. I think my colleagues in Internal Medicine really are the go-to physicians in preventing and managing delirium because the safest course is to approach it not as a primary psychiatric disorder per se, but as a medical emergency.
van der Kooi, A. W., et al. (2015). “Delirium detection using eeg: What and how to measure.” Chest 147(1): 94-101.
BACKGROUND: Despite its frequency and impact, delirium is poorly recognized in postoperative and critically ill patients. EEG is highly sensitive to delirium but, as currently used, it is not diagnostic. To develop an EEG-based tool for delirium detection with a limited number of electrodes, we determined the optimal electrode derivation and EEG characteristic to discriminate delirium from nondelirium.METHODS: Standard EEGs were recorded in 28 patients with delirium and 28 age- and sex-matched patients who had undergone cardiothoracic surgery and were not delirious, as classified by experts using Diagnostic and Statistical Manual of Mental Disorders, 4th edition, criteria. The first minute of artifact-free EEG data with eyes closed as well as with eyes open was selected. For each derivation, six EEG parameters were evaluated. Using Mann-Whitney U tests, all combinations of derivations and parameters were compared between patients with delirium and those without. Corresponding P values, corrected for multiple testing, were ranked.RESULTS: The largest difference between patients with and without delirium and highest area under the receiver operating curve (0.99; 95% CI, 0.97-1.00) was found during the eyes-closed periods of the EEG, using electrode derivation F8-Pz (frontal-parietal) and relative δ power (median [interquartile range (IQR)] for delirium, 0.59 [IQR, 0.47-0.71] and for nondelirium, 0.20 [IQR, 0.17-0.26]; P = .0000000000018). With a cutoff value of 0.37, it resulted in a sensitivity of 100% (95% CI, 100%-100%) and specificity of 96% (95% CI, 88%-100%).CONCLUSIONS: In a homogenous population of nonsedated patients who had undergone cardiothoracic surgery, we observed that relative δ power from an eyes-closed EEG recording with only two electrodes in a frontal-parietal derivation can distinguish among patients who have delirium and those who do not.
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