Sequential organ failure assessment score is an excellent operationalization of disease severity of adult patients with hospitalized community acquired pneumonia - results from the prospective observational PROGRESS study

Peter Ahnert, Petra Creutz, Katrin Horn, Fabian Schwarzenberger, Michael Kiehntopf, Hamid Hossain, Michael Bauer, Frank Martin Brunkhorst, Konrad Reinhart, Uwe Völker, Trinad Chakraborty, Martin Witzenrath, Markus Löffler, Norbert Suttorp, Markus Scholz, PROGRESS Study Group, Stefan Angermair, Christoph Arntzen, Lorenz Balke, Robert Bals, Michael Benzke, Ayhan Berber, Frank Bloos, Martin Buchenroth, Lea Deterding, Nicolas Dickgreber, Oleg Dmitriev, Hermann Druckmiller, Holger Flick, Ulrike Föllmer, Julia Freise, Carmen Garcia, Sven Gläser, Christian Grah, Simone Hamberger, Karsten Hartung, Barabara Hauptmeier, Matthias Held, Frederik Hempel, Iris Hering, Carola Hobler, Andreas Hocke, Ursula Hoffmann, Henning Kahnert, Oliver Kanwar, Lena Kappauf, Charlotte Keller, Nils Keller, Walter Knüppel, Eva Koch, Martin Kolditz, Christine Krollmann, Cornelia Kropf-Sanchen, Josefa Lehmke, Christian Lensch, Andreas Liebrich, Achim Lies, Katrin Ludewig, Lena-Maria Makowski, Phillippr Mayer, Brigitte Mayer, Agata Mikolajewska, Anne Moeser, Thomas Müller, Michaela Niebank, Markus Niesen, Tim Oqueka, Wulf Pankow, Judith Pannier, Claus Peckelsen, Mathias Plauth, Mathias Pletz, Jan Pluta, Kalina Popkirova, Jessicar Rademache, Mirja Ramke, Felix Rosenow, Stefan Rüdiger, Bernhard Ruf, Jan Rupp, Bernhard Schaaf, Tom Schaberg, Marianne Schelle, Patrick Schmidt-Schridde, Galina Schott, Barbara Schröder, Tetyana Shchetynska-Marinova, Michael Simpfendörfer, Thomas Spinner, Norbert Suttorp, Dorina Thiemig, Daniel Thomas-Rüddel, Markus Unnewehr, Barbara Wagener, Gudrun Wakonigg, Deborah Wehde, Hubert Wirtz, Charite Icu-Teams, Peter Ahnert, Petra Creutz, Katrin Horn, Fabian Schwarzenberger, Michael Kiehntopf, Hamid Hossain, Michael Bauer, Frank Martin Brunkhorst, Konrad Reinhart, Uwe Völker, Trinad Chakraborty, Martin Witzenrath, Markus Löffler, Norbert Suttorp, Markus Scholz, PROGRESS Study Group, Stefan Angermair, Christoph Arntzen, Lorenz Balke, Robert Bals, Michael Benzke, Ayhan Berber, Frank Bloos, Martin Buchenroth, Lea Deterding, Nicolas Dickgreber, Oleg Dmitriev, Hermann Druckmiller, Holger Flick, Ulrike Föllmer, Julia Freise, Carmen Garcia, Sven Gläser, Christian Grah, Simone Hamberger, Karsten Hartung, Barabara Hauptmeier, Matthias Held, Frederik Hempel, Iris Hering, Carola Hobler, Andreas Hocke, Ursula Hoffmann, Henning Kahnert, Oliver Kanwar, Lena Kappauf, Charlotte Keller, Nils Keller, Walter Knüppel, Eva Koch, Martin Kolditz, Christine Krollmann, Cornelia Kropf-Sanchen, Josefa Lehmke, Christian Lensch, Andreas Liebrich, Achim Lies, Katrin Ludewig, Lena-Maria Makowski, Phillippr Mayer, Brigitte Mayer, Agata Mikolajewska, Anne Moeser, Thomas Müller, Michaela Niebank, Markus Niesen, Tim Oqueka, Wulf Pankow, Judith Pannier, Claus Peckelsen, Mathias Plauth, Mathias Pletz, Jan Pluta, Kalina Popkirova, Jessicar Rademache, Mirja Ramke, Felix Rosenow, Stefan Rüdiger, Bernhard Ruf, Jan Rupp, Bernhard Schaaf, Tom Schaberg, Marianne Schelle, Patrick Schmidt-Schridde, Galina Schott, Barbara Schröder, Tetyana Shchetynska-Marinova, Michael Simpfendörfer, Thomas Spinner, Norbert Suttorp, Dorina Thiemig, Daniel Thomas-Rüddel, Markus Unnewehr, Barbara Wagener, Gudrun Wakonigg, Deborah Wehde, Hubert Wirtz, Charite Icu-Teams

Abstract

Background: CAP (Community acquired pneumonia) is frequent, with a high mortality rate and a high burden on health care systems. Development of predictive biomarkers, new therapeutic concepts, and epidemiologic research require a valid, reproducible, and quantitative measure describing CAP severity.

Methods: Using time series data of 1532 patients enrolled in the PROGRESS study, we compared putative measures of CAP severity for their utility as an operationalization. Comparison was based on ability to correctly identify patients with an objectively severe state of disease (death or need for intensive care with at least one of the following: substantial respiratory support, treatment with catecholamines, or dialysis). We considered IDSA/ATS minor criteria, CRB-65, CURB-65, Halm criteria, qSOFA, PSI, SCAP, SIRS-Score, SMART-COP, and SOFA.

Results: SOFA significantly outperformed other scores in correctly identifying a severe state of disease at the day of enrollment (AUC = 0.948), mainly caused by higher discriminative power at higher score values. Runners-up were the sum of IDSA/ATS minor criteria (AUC = 0.916) and SCAP (AUC = 0.868). SOFA performed similarly well on subsequent study days (all AUC > 0.9) and across age groups. In univariate and multivariate analysis, age, sex, and pack-years significantly contributed to higher SOFA values whereas antibiosis before hospitalization predicted lower SOFA.

Conclusions: SOFA score can serve as an excellent operationalization of CAP severity and is proposed as endpoint for biomarker and therapeutic studies.

Trial registration: clinicaltrials.gov NCT02782013 , May 25, 2016, retrospectively registered.

Keywords: Biomarker; Clinical epidemiology; Infectious disease; Lung disease; Prospective clinical study; Severity score.

Conflict of interest statement

Ethics approval and consent to participate

In this manuscript, data from the PROGRESS study (clinicaltrials.gov: NCT02782013) were used. PROGRESS was approved by the ethics committee of the University of Jena (2403–10/08) and by locally responsible ethics committees of each study center. All participants or their legal guardians gave written informed consent for participation in the study. Requirements of the Declaration of Helsinki [22] and the ICH-GCP guideline [23] were met.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Study sites, hospitals in Germany (N = 54) and Austria (N = 2) participating in the study (Size and color of circles indicate the number of patients collected by the corresponding site)
Fig. 2
Fig. 2
Flow chart of study procedures
Fig. 3
Fig. 3
Primary Endpoint (PE) in the PROGRESS study. a Distribution of observed PE states across study events (adm = admission to hospital, d0 = enrollment, d1 = study visit 1, d2 = study visit 2, d3 = study visit 3, d4 = study visit 4, d4+ = time between study visit 4 and 28d follow-up. b Frequencies of specific treatments qualifying for the PE
Fig. 4
Fig. 4
Performance of scores regarding PE prediction. a Receiver operating characteristics for severity scores at enrollment. b Percentage of patients with PE in dependence on severity scores: Severity scores were rescaled to the unit interval for this purpose. For SOFA we pooled scores > 10, for Halm > 5 and for SMART-COP > 8 in order to deal with sparsely filled score classes. For SCAP, quintiles were used
Fig. 5
Fig. 5
Time series data of SOFA. a ROC analysis of SOFA for different study time points: Diagnostic power is similar for all time points; b Contribution of SOFA sub-scores for day of enrollment and study visits. As expected, the pulmonary SOFA sub-score has the largest impact, which even increases during the course of therapy. Displayed numbers refer to the percentage of the pulmonary SOFA sub-score

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