M.P. Mulder MSc (Marijn)

I am an enthusiastic and driven technical physician; currently working as lecturer and
researcher at the University of Twente in the Cardiovascular and Respiratory Physiology (CRPH) group. I finished my master Technical Medicine in 2020, within the Medical Sensing and Stimulation track. During my PhD research I study human hemodynamics, since I find the analysis of complex problems and cardiovascular physiology fascinating. I can express my creativity and systematic way of thinking when programming, analysing and modelling. I find it important that my work is socially relevant, for example by directly improving patient care. With my passion for education and teaching I hope to also help, motivate and inspire others.

Medicine & Life Sciences

# Arterial Pressure
# Computer Simulation
# Hemodynamics
# Hypotension
# Intensive Care Units
# Machine Learning
# Observational Studies
# Randomized Controlled Trials

Faculty of Science and Technology (TNW), Cardiovascular and Respiratory Physiology (CRPH)

My research focuses on hemodynamic instability in critically ill patients, this a common and significant problem on the ICU. By the means of advanced signal analysis and computational modelling, we aim to unravel the underlying pathophysiology. In this way we can support clinicians in making the right treatment choice and therefore promote more personalized hemodynamic management.

Mulder, M. P. , Fresiello, L., Rumindo, K., Jalde, F., Hallbäck, M., Maksuti, E. , & Donker, D. W. (Accepted/In press). A computational platform for virtual patient trials of fluid responsiveness prediction in septic shock phenotypes. Abstract from ESICM LIVES Forum Conference 2023, Utrecht, Netherlands.

Mulder, M. P., Harmannij-Markusse, M. , Donker, D. W. , Fresiello, L., & Potters, J-W. (2023). Is Continuous Intraoperative Monitoring of Mean Arterial Pressure as Good as the Hypotension Prediction Index Algorithm? Research Letter. Anesthesiology, 138(6), 657-658. https://doi.org/10.1097/ALN.0000000000004541

Terwindt, L. E., Schuurmans, J., van der Ster, B. J. P., Wensing, C. A. G. C. L. , Mulder, M. P., Wijnberge, M., Cherpanath, T. G. V., Lagrand, W. K., Karlas, A. A., Verlinde, M. H., Hollmann, M. H., Geerts, B. F., Veelo, D. P., & Vlaar, A. P. J. (2022). Incidence, Severity and Clinical Factors Associated with Hypotension in Patients Admitted to an Intensive Care Unit: A Prospective Observational Study. Journal of Clinical Medicine, 11(22), 1-13. [6832]. https://doi.org/10.3390/jcm11226832

Mulder, M. P. , Fresiello, L. , & Donker, D. W. (2022). Computational models for hemodynamic management in critically ill patients: a systematic review. 10. Abstract from Virtual Physiological Human Conference, VPH 2022, Porto, Portugal.

Mulder, M. P., Broomé, M. , Donker, D. W. , & Westerhof, B. E. (2022). In silico arterial waveforms reveal hemodynamic deficiencies. Poster session presented at TechMed Research Day 2022, Enschede, Netherlands.

Mulder, M. P., Broomé, M. , Donker, D. W. , & Westerhof, B. E. (2022). Distinct morphologies of arterial waveforms reveal preload-, contractility-, and afterload-deficient hemodynamic instability: An in silico simulation study. Physiological Reports, 10(7), e15242. [e15242]. https://doi.org/10.14814/phy2.15242

Mulder, M. P., Broomé, M. , Donker, D. W. , & Westerhof, B. E. (2021). Simulated arterial blood pressure tracing reveal preload, contractility and afterload deficient hemodynamic instability. Poster session presented at ESICM 34th Annual Congress, LIVES 2021. https://doi.org/0.1186/1475-925X-12-69

Mulder, M., Broomé, M. , Donker, D. , & Westerhof, B. (2021). Distinct waveforms of peripheral arterial blood pressure tracings reveal preload‑, cardiac contractility‑ and afterload‑ defcient hemodynamic instability: an in‑silico simulation study. Intensive Care Medicine Experimental, 9(Supplement 1), 56-57. [000811]. https://doi.org/10.1186/s40635-021-00413-8

Wijnberge, M., Geerts, B. F., Hol, L., Lemmers, N. , Mulder, M. P., Berge, P., Schenk, J., Terwindt, L. E., Hollmann, M. W., Vlaar, A. P., & Veelo, D. P. (2020). Effect of a Machine Learning-Derived Early Warning System for Intraoperative Hypotension vs Standard Care on Depth and Duration of Intraoperative Hypotension during Elective Noncardiac Surgery: The HYPE Randomized Clinical Trial. JAMA - Journal of the American Medical Association, 323(11), 1052-1060. https://doi.org/10.1001/jama.2020.0592

Wijnberge, M., Schenk, J., Terwindt, L. E. , Mulder, M. P., Hollmann, M. W., Vlaar, A. P., Veelo, D. P., & Geerts, B. F. (2019). The use of a machine-learning algorithm that predicts hypotension during surgery in combination with personalized treatment guidance: Study protocol for a randomized clinical trial. Trials, 20(1), [582]. https://doi.org/10.1186/s13063-019-3637-4

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Half of my appointment at the UT I dedicate to teaching in both the bachelor and master program of Technical Medicine. I'm involved in the education and projects of Module 2 (Pathophysiology) and 6 (Cardiorespiratory system) in the bachelor, where I use models and simulations to explain basic (patho)physiological concepts of the cardiovascular system. In the master I teach the technical medical skills courses Injections, Punctures & Catheterisations and Emergency Reasoning, were students learn how to, for example, do a venepuncture and systematically approach a patient case. Next to that, I’m also involved in the master course Circulation & Ventilation, which covers ICU monitoring and management. As a technical supervisor, I supervise bachelor assignments (TGO) and master students during their clinical (specialisation) internships in projects connected to my research interests.

Bachelor

Technical Medicine

Master

Technical Medicine

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