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Article

Markov State Modelling of Disease Courses and Mortality Risks of Patients with Community-Acquired Pneumonia

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Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Universität Leipzig, Härtelstr. 16-18, 04107 Leipzig, Germany
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German Center for Lung Research (DZL), Aulweg 130, 35392 Gießen, Germany
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Clinical Trial Centre Leipzig, Universität Leipzig, Härtelstr. 16-18, 04107 Leipzig, Germany
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Department of Anesthesiology and Intensive Care Medicine, Jena University Hospital, Am Klinikum 1, 07747 Jena, Germany
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Center for Sepsis Control & Care (CSCC), Jena University Hospital, Am Klinikum 1, 07747 Jena, Germany
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Center for Clinical Studies, Jena University Hospital, Salvador-Allende-Platz 27, 07747 Jena, Germany
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SepNet Critical Care Trials Group c/o Sepsis-Stiftung, Carl-Zeiß-Str. 12, 07743 Jena, Germany
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Department of Infectious Diseases and Respiratory Medicine, Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany
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Division of Pulmonary Inflammation, Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany
*
Author to whom correspondence should be addressed.
J. Clin. Med. 2020, 9(2), 393; https://doi.org/10.3390/jcm9020393
Received: 23 December 2019 / Revised: 23 January 2020 / Accepted: 30 January 2020 / Published: 5 February 2020
(This article belongs to the Special Issue Diagnosis and Treatment of Pneumonia)
Community-acquired pneumonia (CAP) is one of the most frequent infectious diseases worldwide, with high lethality. Risk evaluation is well established at hospital admission, and re-evaluation is advised for patients at higher risk. However, severe disease courses may develop from all levels of severity. We propose a stochastic continuous-time Markov model describing daily development of time courses of CAP severity. Disease states were defined based on the Sequential Organ Failure Assessment (SOFA) score. Model calibration was based on longitudinal data from 2838 patients with a primary diagnosis of CAP from four clinical studies (PROGRESS, MAXSEP, SISPCT, VISEP). We categorized CAP severity into five disease states and estimated transition probabilities for CAP progression between these states and corresponding sojourn times. Good agreement between model predictions and clinical data was observed. Time courses of mortality were correctly predicted for up to 28 days, including validation with patient data not used for model calibration. We conclude that CAP disease course follows a Markov process, suggesting the necessity of daily monitoring and re-evaluation of patient’s risk. Our model can be used for regular updates of risk assessments of patients and could improve the design of clinical trials by estimating transition rates for different risk groups. View Full-Text
Keywords: community-acquired pneumonia; prognosis; sepsis; SOFA score; stochastic model; continuous-time Markov model; medical decision making community-acquired pneumonia; prognosis; sepsis; SOFA score; stochastic model; continuous-time Markov model; medical decision making
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MDPI and ACS Style

Przybilla, J.; Ahnert, P.; Bogatsch, H.; Bloos, F.; Brunkhorst, F.M.; SepNet Critical Care Trials Group; PROGRESS study group; Bauer, M.; Loeffler, M.; Witzenrath, M.; Suttorp, N.; Scholz, M. Markov State Modelling of Disease Courses and Mortality Risks of Patients with Community-Acquired Pneumonia. J. Clin. Med. 2020, 9, 393. https://doi.org/10.3390/jcm9020393

AMA Style

Przybilla J, Ahnert P, Bogatsch H, Bloos F, Brunkhorst FM, SepNet Critical Care Trials Group, PROGRESS study group, Bauer M, Loeffler M, Witzenrath M, Suttorp N, Scholz M. Markov State Modelling of Disease Courses and Mortality Risks of Patients with Community-Acquired Pneumonia. Journal of Clinical Medicine. 2020; 9(2):393. https://doi.org/10.3390/jcm9020393

Chicago/Turabian Style

Przybilla, Jens, Peter Ahnert, Holger Bogatsch, Frank Bloos, Frank M. Brunkhorst, SepNet Critical Care Trials Group, PROGRESS study group, Michael Bauer, Markus Loeffler, Martin Witzenrath, Norbert Suttorp, and Markus Scholz. 2020. "Markov State Modelling of Disease Courses and Mortality Risks of Patients with Community-Acquired Pneumonia" Journal of Clinical Medicine 9, no. 2: 393. https://doi.org/10.3390/jcm9020393

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