A model‐based protocol for the diagnosis of von Willebrand disease. (10th October 2017)

• Record Type: Journal Article
• Authors: Castaldello, Christopher; Galvanin, Federico; Casonato, Alessandra; Padrini, Roberto; Barolo, Massimiliano; Bezzo, Fabrizio
• Is Part Of: Canadian journal of chemical engineering. Volume 96:Number 3(2018)
• Page Start: 628
• Page End: 638
• Publication Date: 2017-10-10
• Subjects: von Willebrand disease -- model identification -- disease diagnosis -- discriminant analysis -- nearest neighbours; Chemical engineering -- Periodicals; Technology -- Periodicals; 660.05
• DOI: 10.1002/cjce.22964
• Languages: English
• ISSNs: 0008-4034

Abstract

Abstract: Von Willebrand disease (VWD) is one of the main inherited coagulation disorders. It is caused by a deficiency and/or a dysfunction of the von Willebrand factor (VWF), a fundamental multimeric glycoprotein involved in the hemostasis process. Correct detection of the disease is not an easy task because the disease manifests itself in many variants and a high intra‐subject variability is observed. For these reasons, the diagnostic clinical trials typically rely on a 24‐h sampling protocol, which makes the overall test long, stressful, and costly. Using a new pharmacokinetic model derived from Galvanin et al.'s 2014 study, this study aims at i) assessing the theoretical possibility to perform a shorter clinical test and ii) proposing a set of model‐based diagnostic methods as a support for the clinical team. A preliminary information analysis is performed in order to understand which sampling instants are more informative for model identification. This allowed us to propose a novel, 8‐h diagnostic protocol, which is still able to ensure model identifiability. Three alternative diagnostic methods are then proposed based on this short‐length clinical protocol. One of them directly uses the pharmacokinetic model, whereas the other two are based on the use of three indices (two pharmacokinetic indices, namely clearance, total VWF released, and as third index the basal multimer ratio) to formulate the diagnosis problem as a classification one. The classification problem is then solved using K ‐nearest neighbours and linear discriminant analysis. Results show the theoretical feasibility of a VWD diagnosis based on a shorter protocol.