Abstract
Monoclonal gammopathies (MGs) comprise a broad set of diseases involving the abnormal clonal proliferation of plasma cells. Treatments for MGs range for watchful monitoring to multidrug chemotherapeutic regimens and bone marrow transplant.
The clinical laboratory plays a central role in guiding these therapeutic decisions by performing a number of assays that detect monoclonal proteins within the patient’s blood or urine.
These assays are typically performed as a panel or as part of a reflexive algorithm to improve the accuracy and information yield. However, the complexity of these algorithms requires careful coordination between the medical technologists and the reviewing pathologist. This presentation will cover our institutional experience developing and adopting a computer-based workflow for coordinating and interpreting MG screening panels within the Phoresis (Sebia) computer application.
Speaker’s biography
Mark A. Zaydman, M.D, Ph.D., is a clinical pathologist and an Assistant Professor of Pathology and Immunology at Washington University School of Medicine in St. Louis and affiliated with Barnes-Jewish Hospital. His primary clinical focus is on clinical informatics and the application of data analytics to improve laboratory test utilization and to support clinical decisions. He also serves as medical director over monoclonal gammopathy diagnostics within the core laboratories of Barnes-Jewish Hospital. Dr. Zaydman received a BSE in Biomedical Engineering from Case Western Reserve University in Cleveland, Ohio before moving to Washington University in St. Louis to pursue his graduate training in Biomedical Engineering and in Medicine. Drawing on his expertise in engineering, medicine, computer science, and clinical pathology, his clinical research focuses on applications of data science to make the laboratory practice more efficient and reliable.
Un concentré de l’expertise de Sebia dans un instrument à haut débit.
La puissance de 36 capillaires dans un ilôt robotique grande capacité.
La technologie capillaire Sebia connectée à une chaine d’automatisation totale de laboratoire.
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