Sepsis disease severity

Optimizing care for patients with sepsis

Patients with infections may develop sepsis. Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. This can occur at any time during a hospital stay, either in the emergency department, the wards or in the ICU. In order to optimize treatment, patients need to be identified as early as possible, before organ dysfunction occurs. We investigate diagnostic strategies and develop prediction models to improve early identification.

In this research project we focus on early identification of sepsis by developing prediction models using vital parameters, novel serum biomarkers, genetic biomarkers, and aim to discover new biomarkers using mass spectrometry analysis.

Accurate prediction models can be implemented in routine clinical practice as screening tools and decision-making tools.

In two prospective cohorts in the ED (FORESEEN study) and the ICU (CIUM study) data is collected of patients with suspected infections. These data are used to generate prediction models for sepsis. These prediction models are then prospectively validated. These models are then used to guide disposition and treatment of patients.

Setting specific sepsis severity scores, with clinical guidance based on score.

Collaborations within Erasmus MC

• Intensive care medicine.
• Internal medicine.
• Viroscience.
• Clinical chemistry.
• Neurology, mass spectrometry department.

Collaborations outside of Erasmus MC

• Universidade Federale de Minas Gerais, Belo Horizonte, Brazil.

The early identification of disease progression in patients with suspected infection presenting to the emergency department: a multi-centre derivation and validation study. Saeed K, Wilson DC, Bloos F, Schuetz P, van der Does Y, Melander O, Hausfater P, Legramante JM, Claessens YE, Amin D, Rosenqvist M, White G, Mueller B, Limper M, Callejo CC, Brandi A, Macchi MA, Cortes N, Kutz A, Patka P, Yañez MC, Bernardini S, Beau N, Dryden M, van Gorp ECM, Minieri M, Chan L, Rood PPM, Del Castillo J. Crit Care. 2019 Feb 8;23(1):40.

Identifying patients with bacterial infections using a combination of C-reactive protein, procalcitonin, TRAIL, and IP-10 in the emergency department: a prospective observational cohort study. Van der Does Y, Rood PPM, Ramakers C, Schuit SCE, Patka P, van Gorp ECM, Limper M. Clin Microbiol Infect. 2018 Dec;24(12):1297-1304.

TRAIL and IP-10 as biomarkers of viral infections in the emergency department. Van der Does Y, Tjikhoeri A, Ramakers C, Rood PPM, van Gorp ECM, Limper M. J Infect. 2016 Jun;72(6):761-763.

• Yuri van der Does
• Kirby Tong-Minh
• Diederik Gommers
• Eric van Gorp
• Stephanie Klein Nagelvoort-Schuit
• Chris Ramakers
• Theo Luider