Rhabdomyolysis and COVID-19 Infection: Is It Due to Statin Use or Anti-TIF1-y Antibodies?

Coronavirus disease 2019 (COVID-19), now a global pandemic, has infected millions of people and caused hundreds of thousands of deaths.  Neurological presentation of the novel coronavirus includes headaches, seizures, myalgias, hyposmia, ageusia, etc. Guillain-Barre Syndrome (GBS) and its variant, Miller Fisher Syndrome, have been reported in COVID-19 patients presenting with lower limb weakness, paresthesia, facial diplegia, and ataxia. Most recently, large vessel occlusion strokes were seen in infected younger patients without vascular risk factors. We present a novel case of rhabdomyolysis associated with COVID-19 infection in a patient on atorvastatin, in whom we detected positive anti-transcriptional intermediary factor 1 gamma antibodies (anti-TIF1-y Ab). Bilateral upper and lower extremity weakness improved with aggressive fluid administration and intravenous immunoglobulin (IVIg) at 0.4mg/kg for a total of 5 days. Interrupting a strong cytokine response with IVIg early on during the disease may have led to rapid improvement

Methotrexate Polyglutamation in a Myasthenia Gravis Clinical Trial

Introduction. Methotrexate (MTX) is an immunosuppressive and anti-inflammatory drug used to treat rheumatoid arthritis (RA) and other autoimmune conditions. MTX is transported into cells, where glutamate moieties are added and is retained as methotrexate polyglutamates (MTXPGs). In the RA literature, it has been reported that the degree of polyglutamation correlates with the anti-inflammatory effect of MTX in RA. There are no prior studies evaluating the relationship between MTXPGs and myasthenia gravis (MG) outcome measures. The objective of this study was to assess the correlation between methotrexate (MTX) polyglutamates (MTXPGs) with Myasthenia Gravis (MG) outcome measures. Methods.xAn analysis was done of blood drawn from patients enrolled in the 12-month randomized, placebo-controlled study of MTX in MG study. Red blood cell MTXPGs were measured via ultraperformance liquid chromatography and tandem mass spectrometry. MTXPG was correlated to MG outcome measures using Spearman Correlation Coefficient. A two-group t-test was used to determine the difference in MTXPG based on clinical outcome responder definitions. Results. Twenty-one polyglutamate samples were analyzed of subjects on MTX while eight samples were analyzed from subjects on placebo. Pentaglutamate had the strongest correlation with the MG-ADL (0.99), while tetraglutamate had the strongest correlation with the QMG (0.54). Triglutamate had the strongest correlation with MGC (0.76). Conclusion. There were variable correlations between MTXPG1-5 and MG outcomes (rho range: 0.08 to 0.99). There are strong correlations between MTXPG and the MG-ADL, QMG, and MGC. Long chain methotrexate polyglutamates correlate better with MG outcomes

CIDP Diagnostic Criteria and Response to Treatment

AbstractIntroduction: Diagnostic criteria for CIDP have been proven useful for clinical trials. However, use of these criteria in clinics has been limited by time constraints and unknown usefulness in predicting outcomes. Methods: A retrospective chart review of CIDP patients at the University of Kansas seen between 2008 and 2014 was performed. We determined the diagnostic criteria fulfilled by each patient and assessed treatment responses. A positive response was defined by improvement sensory or motor examination as determined by a neuromuscular physician.Results: There were 38 total patients included in the study. The response rate to IVIG in patients who fulfilled EFNS/PNS criteria was 20/22 (90.1%). Among patients who fulfilled AAN criteria, 8/9 (88.9%) responded positively to IVIG. Slightly lower response rates were seen in patients fulfilling INCAT criteria and Saperstein criteria at 10/15 (66.7%) and 12/17 (70.6%), respectively.Discussion: EFNS/PNS and AAN criteria can similarly predict IVIG treatment response

Timing of Decremental Response During Repetitive Nerve Stimulation in Myasthenia Gravis

Background: A decrement >10% detected during repetitive nerve stimulation (RNS) is supportive of considering a diagnosis of myasthenia gravis (MG). Several studies have found that most of this decrement is seen between 4 to 6 min post-exercise. However, there are not available studies analyzing if shorter timing would be sufficient.   Objective: The objective of this study was to evaluate if RNS up to 2 min post-exercise is sufficient to detect a decrement response >10%. Methods: We performed a retrospective chart review study of patients referred to our neuromuscular clinic at The University of Kansas Medical Center with symptoms suggestive of MG from 2013 to 2017. Results: A total of 76 patients with MG and 100 controls were identified.  A significant decrement was detected in 95% of MG patients with abnormal RNS within 2 minutes post-exercise. Conclusion: RNS up to 2 min post-exercise might be sufficient to detect a significant decrement in MG patients.&nbsp

Amyloid Myopathy as an Inclusion Body Myositis Mimic

Introduction: Amyloid myopathy is a rare presentation of systemic amyloidosis. Amyloid myopathy can be initially misdiagnosed as sporadic inclusion body myositis (IBM). Methods: We report 4 cases of amyloid myopathy clinically mimicking inclusion body myositis and initially thought to be phenotypically IBM by neuromuscular experts. Results: Case 1 is an 81-year-old woman who presented with distal arm and proximal leg asymmetric weakness (myopathy pattern 4). Case 2 is a 76-year-old man with primary systemic amyloidosis who presented with myopathy pattern 4 and progressive dysphagia for four years. Case 3 is an 82-year-old man with progressive myopathy pattern 4 weakness and swallowing difficulty. Case 4 is a 62-year-old man with progressive bilateral finger flexor weakness. Muscle biopsies in all 4 cases showed perivascular amyloid deposits Discussion: Amyloid myopathy may be clinically indistinguishable from IBM. Muscle biopsy is of critical importance in the evaluation of patients suspected to have IBM

A Bayesian comparative effectiveness trial in action: developing a platform for multisite study adaptive randomization

A grant from the One-University Open Access Fund at the University of Kansas was used to defray the author's publication fees in this Open Access journal. The Open Access Fund, administered by librarians from the KU, KU Law, and KUMC libraries, is made possible by contributions from the offices of KU Provost, KU Vice Chancellor for Research & Graduate Studies, and KUMC Vice Chancellor for Research. For more information about the Open Access Fund, please see http://library.kumc.edu/authors-fund.xml.Background In the last few decades, the number of trials using Bayesian methods has grown rapidly. Publications prior to 1990 included only three clinical trials that used Bayesian methods, but that number quickly jumped to 19 in the 1990s and to 99 from 2000 to 2012. While this literature provides many examples of Bayesian Adaptive Designs (BAD), none of the papers that are available walks the reader through the detailed process of conducting a BAD. This paper fills that gap by describing the BAD process used for one comparative effectiveness trial (Patient Assisted Intervention for Neuropathy: Comparison of Treatment in Real Life Situations) that can be generalized for use by others. A BAD was chosen with efficiency in mind. Response-adaptive randomization allows the potential for substantially smaller sample sizes, and can provide faster conclusions about which treatment or treatments are most effective. An Internet-based electronic data capture tool, which features a randomization module, facilitated data capture across study sites and an in-house computation software program was developed to implement the response-adaptive randomization. Results A process for adapting randomization with minimal interruption to study sites was developed. A new randomization table can be generated quickly and can be seamlessly integrated in the data capture tool with minimal interruption to study sites. Conclusion This manuscript is the first to detail the technical process used to evaluate a multisite comparative effectiveness trial using adaptive randomization. An important opportunity for the application of Bayesian trials is in comparative effectiveness trials. The specific case study presented in this paper can be used as a model for conducting future clinical trials using a combination of statistical software and a web-based application. Trial registration ClinicalTrials.gov Identifier: NCT02260388, registered on 6 October 201

Database Evaluation for Muscle and Nerve Diseases - DEMAND: An academic neuromuscular coding system

Background: A database which documents the diagnosis of neuromuscular patients is useful for determining the types of patients referred to academic centers and for identifying participants for clinical trials and other studies. The ICD-9 or ICD-10 numeric systems are insufficiently detailed for this purpose. Objective: To develop a database for neuromuscular diagnoses Methods: We developed a detailed diagnostic coding system for neuromuscular diseases called DEMAND: Database Evaluation for Muscle and Nerve Diseases that has been adopted by neuromuscular clinics at University of Texas Health Science Center San Antonio (UTHSCSA), Ohio State University (OSU), University of Kansas Medical Center (KUMC), and University of Texas Southwestern (UTSW). At the initial visit, patients are assigned a diagnostic code which can be revised later if appropriate. Fields include patient’s name, date of birth, and diagnostic code. The neuromuscular database consisted of 457 codes. Each code has a prefix (MUS or PNS) followed by a three-digit number. Depending on whether muscle or nerve is primarily involved, there are eight broad groups: motor neuron disease (MUS codes 100-139); neuromuscular junction disorders (MUS 200-217); acquired and hereditary myopathies (MUS 300-600s); acquired and hereditary polyneuropathies (PNS 100-400); mononeuropathies (PNS 500s); plexopathies (PNS 600s); radiculopathies (PNS 700s); and mononeuritis multiplex (PNS 800s). Results: During a period of 10 years, 17,163 of patients were entered (1,752 at UTHSCSA, 1,840 at OSU, 3,699 at KUMC, 9,872 at UTSW). The number of patients in several broad categories are: 3,080 motor neuron disease; 1,575 neuromuscular junction disease; 1,851 muscular dystrophies; 633 inflammatory myopathies; 1,090 hereditary neuropathies; 1,001 immune-mediated polyneuropathies; 620 metabolic/toxic polyneuropathies; 535 mononeuropathies; 296 plexopathies; and 769 radiculopathies. Conclusion: A detailed diagnostic neuromuscular database can be utilized at multiple academic centers. The database should be simple without too many fields to complete, to ensure compliance during busy clinic operations. This database has been very useful in identifying groups of patients for retrospective, observational studies and for prospective treatment studies including trials for Amyotrophic Lateral Sclerosis (ALS), Muscular Dystrophies (MD), Myasthenia Gravis (MG), and retrospective studies of Primary Lateral Sclerosis (PLS), chronic inflammatory demyelinating neuropathy (CIDP), etc