Patricia Stassen

Associate professor

I completed my medical school in Maastricht in 1995. Then I was trained in internal medicine and specialized in nephrology in UMCG, where I also completed my PhD thesis on Wegener’s disease. Since 2008, I have worked at MUMC+, where I also started/designed a new internal medicine specialization: acute medicine. Since 2010, I have worked as chief of acute internal medicine in addition to practicing as an all-round clinician and engaging in student, nurse and resident education within the faculty of medicine and health. I was appointed as an associate professor (mixed profile) in 2022.

My area of interest is acute internal medicine. I concentrate on all kinds of diseases ranging from sepsis to cardiovascular diseases, and include not only the emergency department (ED) but also the trajectory before (general practitioner, EMS, acute internal medicine, emergency medicine) and after the ED (MCU/ICU).

The aim of my research is to improve acute care and to achieve a short laboratory-to-bed-time. In addition, my aim is to involve students and to improve their skills in both science and acute medicine. Currently, I am working on the prediction of poor outcomes in ED patients using ML technology, on an exploration of the acute care trajectory and on the added value of simulation techniques for residents in the acute care.

I am member of the national research consortium in acute medicine that organizes short but original studies called “flash mobs” across the country. I also coordinate studies in Limburg in collaboration with acute internists and emergency physicians. My goal is to work with all kinds of professionals interested in acute medicine at MUMC/FHML, including intensivists, general practitioners, education/simulation experts, clinical chemistry specialists and cardiologists.

Until now, I have been a co-promotor of 7 PhD students, and I currently supervise 4 PhD students.

Dept of Internal Medicine
P. Debyelaan 25, 6229 HX Maastricht
PO Box 616, 6200 MD Maastricht
Room number: 5C2025
T: +31(0)43 387 50 05

2024
- Wynants, L., Broers, N., Platteel, T., Venekamp, R., Barten, D., Leers, M., Verheij, T., Stassen, P., Cals, J., & de Bont, E. (2024). Development and validation of a risk prediction model for hospital admission in COVID-19 patients presenting to primary care. European Journal of General Practice, 30(1), Article 2339488. https://doi.org/10.1080/13814788.2024.2339488
- Weijers, J., Prins, M. L. M., van Dam, D. G. H. A., van Nieuwkoop, C., Alsma, J., Haak, H. R., V Uffen, J. W., Kaasjager, K. A. H., Kremers, M. N. T., Nanayakkara, P. W. B., Stassen, P. M., Groeneveld, G. H., & AcuteCare@Home Study Group (2024). Patients' Perspectives and Feasibility of Home Monitoring in Acute Care: The AcuteCare@Home Flash Mob Study. Telemedicine and E-health. Advance online publication. https://doi.org/10.1089/tmj.2024.0166
- van Dam, P. M. E. L., Pena, R. E. L., Mommertz, J. A., Borggreve, H. F., van Loon, N. P. H., Zelis, N., Westerman, D., Henry, R. M. A., Posthouwer, D., Cals, J. W. L., & Stassen, P. M. (2024). Acute internal medicine physicians' clinical intuition based on acute care telephone referral: A prospective study. PLOS ONE, 19(6), Article e0305566. https://doi.org/10.1371/journal.pone.0305566
- Claassen, L., Ritter, L. M., Latten, G. H. P., Zelis, N., Cals, J. W. L., & Stassen, P. M. (2024). From symptom onset to ED departure: understanding the acute care chain for patients with undifferentiated complaints. International Journal of Emergency Medicine, 17(1), Article 55. https://doi.org/10.1186/s12245-024-00629-x
- van Doorn, W. P. T. M., Helmich, F., van Dam, P. M. E. L., Jacobs, L. H. J., Stassen, P. M., Bekers, O., & Meex, S. J. R. (2024). Explainable Machine Learning Models for Rapid Risk Stratification in the Emergency Department: A Multicenter Study. Journal of Applied Laboratory Medicine, 9(2), 212-222. Article jfad094. https://doi.org/10.1093/jalm/jfad094
- van Dam, P. M. E. L., van Doorn, W. P. T. M., van Gils, F., Sevenich, L., Lambriks, L., Meex, S. J. R., Cals, J. W. L., & Stassen, P. M. (2024). Machine learning for risk stratification in the emergency department (MARS-ED) study protocol for a randomized controlled pilot trial on the implementation of a prediction model based on machine learning technology predicting 31-day mortality in the emergency department. Scandinavian Journal of Trauma Resuscitation & Emergency Medicine, 32(1), Article 5. https://doi.org/10.1186/s13049-024-01177-2
2023
- van Dam, P. M. E. L., Lievens, S., Zelis, N., van Doorn, W. P. T. M., Meex, S. J. R., Cals, J. W. L., & Stassen, P. M. (2023). Head-to-head comparison of 19 prediction models for short-term outcome in medical patients in the emergency department: a retrospective study. Annals of Medicine, 55(2), Article 2290211. https://doi.org/10.1080/07853890.2023.2290211
- Wanrooij, V. H. M., Cobussen, M., Stoffers, J., Buijs, J., Bergmans, D. C. J. J., Zelis, N., & Stassen, P. M. (2023). Sex differences in clinical presentation and mortality in emergency department patients with sepsis. Annals of Medicine, 55(2), Article 2244873. https://doi.org/10.1080/07853890.2023.2244873
- van Bakel, S. I. J., Gietema, H. A., Stassen, P. M., Gosker, H. R., Gach, D., van den Bergh, J. P., van Osch, F. H. M., Schols, A. M. W. J., & Beijers, R. J. H. C. G. (2023). CT Scan-Derived Muscle, But Not Fat, Area Independently Predicts Mortality in COVID-19. Chest, 164(2), 314-322. https://doi.org/10.1016/j.chest.2023.02.048
- Cobussen, M., Verhave, J. C., Buijs, J., & Stassen, P. M. (2023). The incidence and outcome of AKI in patients with sepsis in the emergency department applying different definitions of AKI and sepsis. International Urology and Nephrology, 55(1), 183-190. https://doi.org/10.1007/s11255-022-03267-5

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Patricia Stassen

Associate professor