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Ann Thorac Surg 2003;75:1372-1376
© 2003 The Society of Thoracic Surgeons

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The statistician's page

Simulation models to predict outcome after aortic valve replacement

^a Department of Cardio-Thoracic Surgery, Erasmus University Medical Center, Rotterdam, The Netherlands
^b Providence Health System, Portland, Oregon, USA

^* Address reprint requests to Dr Takkenberg, Department of Cardio-Thoracic Surgery, Bd162, Erasmus University Medical Center Rotterdam, PO Box 2040, 3000CA Rotterdam, The Netherlands (Email: takkenberg@thch.azr.nl).

The first 300 words of the full text of this article appear below.

	Introduction

 
Which valve substitute would you prefer to implant in a 63-year-old male patient? And which valve substitute would in your opinion be best for a 36-year-old female patient? It can be quite complicated to predict prognosis after implantation of a certain aortic valve substitute in the individual patient who requires aortic valve replacement. Multiple interrelated factors (patient, physician, and prosthesis related) affect outcome after aortic valve replacement. Published clinical experiences provide information on outcome after aortic valve replacement on a group level. By applying standard parametric and semiparametric models for risk factor assessment, it is possible to identify factors that may influence long-term outcome in that particular patient group. One can translate this to the outcome in the individual patient by inserting his or her risk factors into the equation for the model. Although feasible, it is often not an easy task because it necessitates integration of information on many interrelated factors that simultaneously play a role. Simulation techniques may provide a useful adjunct to standard methods because they allow modeling of complex outcome paths resulting from many simultaneous risks.

Recently, several authors reported on the use of simulation techniques to predict outcome after aortic valve replacement and to support prosthetic valve choice [1–4]. These studies use a complex and mostly unknown methodology, and are therefore often difficult to interpret.

This report focuses on the microsimulation method that is used in the article in this issue [5] by Takkenberg and colleagues on outcome after aortic root replacement with cryopreserved allografts. The background and structure of the aortic valve replacement model will be described, the steps that are taken during one simulation cycle will be illustrated, and the advantages and disadvantages using this methodology will be highlighted.

	Background and structure of the microsimulation model

 
Simulation methodologies emerged from the field of operational research. The best known example . . . [Full Text of this Article]

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