Alumnus – obtained PhD degree June 2014
Phone: +31 53 489 1116
Welcome to my personal page on this website. My name is Benno Lansdorp. I was born in Amersfoort on September 1st, 1982. After high school, I came to the University of Twente (UT) to study mechanical engineering. By then, I already knew that my master specialization would be biomechanical engineering because from childhood, I was fascinated by the human body and its functioning. During my master program, a new educational program was born on the UT: Technical Medicine; a combination of the engineering approach from the fundamental sciences and the knowledge and application field of the health sciences. Because it was far too late for me to switch studies, I combined them and in November 2006 I obtained my master degree biomechanical engineering and my first year diploma of Technical Medicine.
Still fascinated by Technical Medicine I decided to stay and work in the experimental centre for Technical Medicine (ECTM) to help Remke Burie in developing and give content to the ECTM. In the meanwhile, I started my own PhD-research project and Prof. van Putten was so kind to adopt me in his group ‘Clinical Neurophysiology’ although my project was not exactly in the field of the neurosciences. The thing they do share: a great interest in the clinical application of physiological models. Curious? Read the part about my research!
Volume Responsiveness in Critically Ill Patients
Development and Implementation of a Decision Support System to predict fluid responsiveness in critically ill patients
Fluid administration is a daily intervention on the intensive care unit to improve cardiac output and stabilize circulation in critically ill patients. Simultaneously, the volume status of the patient is very difficult to assess. Too little volume leads to inadequate organ perfusion followed by ischemia and organ failure. Too much volume may worsen heart failure and cause pulmonary and peripheral edema and contribute to further tissue injury and organ dysfunction. Although dynamic indices (PPV, SVV, PEP) have been shown to be more accurate predictors of fluid responsiveness, this relevant and complex task is usually guided by static clinical variables and the specialist’s interpretation due to the fact that the interpretation of dynamic parameters is not fully developed and that they are not universally available. This lack of understanding is partially because of the complex interaction with mechanical ventilation. We hypothesize that knowing the exact physiology behind the dynamic indices will make it possible to improve their predictive value concerning the volume status of the patient.
The overall goal of the project is to design a decision support system (DSS, based on a mathematical model and validated by clinical data) that integrates relevant parameters (hemodynamic data and ventilatory parameters) to advise the specialist in his decision whether to administer fluid to a patient or not.