An Integrative Approach to Diagnose Heparin-Induced Thrombocytopenia: Development, Validation, and Implementation of a Multivariable Prediction Model

Michael Nagler, M.D., Ph.D., M.Sc.
Inselspital University Hospital and University of Bern
Bern, Switzerland

High hopes are invested in machine-learning approaches for diagnostic applications. Michael Nagler presents a web-based tool integrating laboratory and clinical data to rapidly diagnose heparin-induced thrombocytopenia. It was developed and validated in a prospective multicenter cohort study including 1,393 patients. The final model showed reduced false negative and false positive patients. This model has the potential to reduce overtreatment and delayed diagnosis.

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