Dianna Quan, MD, FAAN, FANA,President of AANEM, University of Colorado School of Medicine
My name is Dianna Quan. I am the president of AANEM, and I am currently a professor of neurology at the University of Colorado School of Medicine. I'm also the head of the neuromuscular section and director of the EMG laboratory there at the University of Colorado.
It was my privilege to choose the theme of this meeting, and that's one of the responsibilities of the president, which is really fun. So, my theme this year was the confluence of two pipelines, neuromuscular medicine in the 21st century. And the two pipelines that I wanted to talk about were particularly the revolutionary biomedical and technical pipeline that's kind of pouring out different innovations in our space and also the delivery and workforce pipeline, which I think is increasingly under stress to deliver those innovations to the patients who need them.
There were so many different scientific innovations and treatments and mechanisms that were explored during this meeting.
There was one that was put forth by Anza Memon, MD who looked at micro RNAs and plasma exosomes as a noninvasive way of diagnosing diabetic peripheral neuropathy.
Our traditional methods of looking for diabetic neuropathy are nerve conduction and electromyography, skin biopsies and other kind of clinical measures.
And so this was a study that looked at something unique, which is small non-coding RNA molecules which influence gene expression. And they found two types in diabetic neuropathy patients. They were miR-206 and miR-214, which were identified in patients who had diabetes and peripheral neuropathy. And that was different from the profile that was seen in people who didn't have diabetes.
There was another one and this was kind of interesting and tantalizing. I'm not sure exactly how it's going to play out in the future, but it had to do with an AI model that could accurately classify neurogenic versus biogenic changes on ultrasound.
And that was presented by Dr. Abdullah AlQahtani, who is an assistant professor at Johns Hopkins. And he looked at kind of an advanced algorithm and deep learning technology to identify complex and subtle patterns that could allow for recognition of neurogenic or monogenic changes on ultrasound.
The model had a pretty good overall accuracy in identifying control versus abnormal muscle specimens. So, I think that the role of AI in the future will be really important for us, not just in neuromuscular medicine, obviously, but in our entire society.
I'm pretty excited about A.I. and what that's going to do for us as far as pushing the science forward and being able to process large amounts of data, protein analysis, predictive models. And I think that that's going to be useful in helping us develop new treatments.
I think there are going to be new drugs that will be introduced, perhaps not immediately this year, but definitely in the very near future for diseases that we never really had treatments for in the past.
The Duke MG Patient Registry: III. The Comparative Effectiveness of Azathioprine and Mycophenolate Mofetil in Myasthenia Gravis, A Retrospective Single Center Review
I'm Donald Sanders. I'm a neuromuscular neurologist at Duke. That means that we specialize in the diagnosis and treatment of patients with nerve and muscle problems.
I'm Janice Massey. I'm also at Duke as a neuromuscular medicine specialist.
Donald Sanders, MD
Duke University School of Medicine
Our presentation was the result of 40 years experience using two immunosuppressive agents that are in common use in my treatment of myasthenia gravis. One of them is Azathioprine and the other is Mycophenolate.
We reviewed the response of patients who had received one or the other of these two agents. And we looked at how long it took for patients to reach the level of improvement that we consider to be clinically desirable. We referred to that as our treatment goal. Basically, what it means is that the patient improved to the point that they have minimal dysfunction.
And we looked at how fast it took each of these two treatments to reach that stage of improvement and the percentage of patients who did, in fact, reach that level of improvement.
The results were very interesting, and to a certain extent, I think somewhat surprising. First of all, Mycophenolate gets better faster in the majority of patients and the level of improvement is greater. Not only is that true of Mycophenolate but it's true of men who take Mycophenolate.
And that was one of the surprising things. In case of the Azathioprine men also get better and get better faster than women being treated with Azathioprine. So, both of these two drugs reach benefit in men faster than they do in women.
Janice Massey, MD
Duke University School of Medicine
I think one of the take homes from this is that the older medications do quite well. There are a number of newer medications that have just sort of burst forth in the arena, so to speak, that give fairly rapid onset benefit. But it is not necessarily persistent and that that is sort of something that we're all looking at now that they're available for use.
But looking at the at the older drugs, it's very reassuring to see how well they work and the timeline and also these differences in gender it’s very interesting and maybe something for us to try to pursue.
Donald Sanders, MD
Duke University School of Medicine
We are continuing to look at these patients closely to see if there are other factors that we may have missed other than gender and age. The other major factor is the presence of a couple of antibodies in myasthenia. There are two major antibodies that are associated with the disease and then there are a fair number of patients who don't have any detectable antibody. And we're trying to tease out the differences in those patients that are related to these antibody differences because they are also clues to the best treatment modalities.
