Content: With Kanav’s creative skills that involved bartering, he traded me blog on a medical meeting that I attended in San Diego for my absence on October 7th. As such, Mithra was kind enough to record Dr. Greenes’ lecture that I was able to listen to. First, I will comment on the lecture, given by one of top men in the field. Even though Decision Analysis has really only been applied to public health situations, it utility in clinical situations is clear to me. Why the decision analysis service only functions at Tufts and has not been disseminated is not clear. I have used the hypotheco-deductive approach for many years and the logic that can be attached to decision analysis is really going to be useful in the future for me. I do not have straightforward patients. I have very complex neurology patients with multiple problems and multiple courses of action that have to be weighed. To have this type of analysis available and to be able to apply it, is useful. Unfortunately, the way to derive the probabilities and the numerical values for outcomes is problematic. I will have more to say on this as this evolves. The mathematical models for TPR, TNR, PV plus, etc. are neat and will also change my formal thinking. Second, the meeting in San Diego, was for the American Association of Neuromuscular and Electrodiagnostic Medicine. This organization involves a unification of two disparate medical fields, Neurology and Physiatry or Physical and Rehabilitative Medicine, much like what we see with biomedical informatics. In this field, we look at disorders of nerve and muscle and motor function from an electrophysiological standpoint and also a neuro-rehabilitative standpoint. With regard to decision analysis, the most important presentation at the meeting used these principles. A disorder called Chronic Inflammatory Demyelinating Polyneuropathy (CIDP) is an immunological disorder with varied cause that leads to chronic muscle weakness due to nerve dysfunction throughout the body. The standard criteria for making the diagnosis involve clinical and electrophysiological indices and have been poorly validated. Gorson et al in a recent article in the New England Journal of Medicine and presented at this meeting used a decision analysis approach to develop the best diagnostic criteria for CIDP. An expert group was first put together to generate a set of candidate variables that distinguish CIDP from other neuropathies (disorders of the nerves). In the second step, detailed case descriptions were obtained internationally on patients with putative CIDP that included clinical examination, electrophysiological studies, spinal fluid and blood evaluation and testing, genetic tests, and nerve biopsy information on 267 patients. A gold standard was designated as a consensus diagnosis on these cases by 11/13 experts. The cases were then divided into a “derivation sample” used to define a classification rule and a “validation sample” to validate the classification rule. A decision tree was developed that involved all possible partitions of the cases to distinguish CIDP from non-CIDP. Regressions between variables was used. A validated set of rules was determined from this. Using the initial set of rules and testing these in the validation sample, the sensitivity for the diagnostic criteria was 83% and the specificity was 97%. This important study will now allow more accurate diagnosis and appropriate treatment of patients with this disorder. Importantly, this disorder and its acute variant, guillain barre syndrome, may result from vaccination. There is current concern about the risk of the swine flu vaccine in raising the risk of these disorders.




Third, another presentation at the meeting focused on the concept that when we injure the motor strip in the brain, that there is weakness on the opposite side of the body. The part of the opposite side of the body is represented in an organized fashion in the brain. In fact on the motor strip of the cortex, the face and body are represented upside down based on ablation and many other studies. However, neurophysiologically, if the neurons in this motor strip are looked at, electrophysiologically using recording and complex mathematical models, precise areas of the body may be less localized than previously thought. The nerve cells associated with movement, however may have very different functions for direction of movement. In a virtual reality paradigm with a monkey with an artificial opposite sided limb, the plasticity of these nerve cells and their directionality of primary electrophysiological function, can be altered by learning and by cortical electrical stimulation. The monkey controls movement from the brain and not with the arm. If presented with virtual set of targets for precision and reaching, the brain and the subsequent movement associated with the artificial limb go through a learning phase with more and more precision with time. This is similar to the sorts of things that Kanav does with his virtual reality paradigms. The utility of the presented work is that provides a means to think about how to rehabilitate stroke victims with hemiplegia or weakness of varying degrees on one side of the body. However, the mathematical conceptualization may be an oversimplification of the total system. Systems models of how the brain works are narrow and must be part of a broader approach.



Fourth, I went to a 2 hour practical session on the electrical evaluation and distinction of weakness and pain in the distribution of one nerve, the ulnar nerve that controls the movement of our fifth finger. Disorders of this nerve are exceedingly common due to compression of the nerve as it runs through the elbow. Our tools for electrophysiological diagnosis have evolved over time, but still have real issues with usability. To get results, there is certainly an art involved in addition to the science and engineering aspects of the machine that we use. For my machine, the software code is written in Japanese and the way that this machine and its software for recording and reporting are not necessarily always in synch with taking care of American patients. There is a broad number of these types of machines and all have various advantage and disadvantages from an HCI standpoint, not to mention control of noise and other issues.



I found the review session by Kanav to be exceptionally useful. I continue to appreciate his approach to biomedical informatic problems. As I have said before, the diversity of background in this class is great. I recently learned that Nate Sutton has significant programming background. His expertise is very helpful. Daily, in these areas, I learn from other individuals, including Prabal, Di Pan, and Eric.



Stuart