Pneumologie 2024; 78(S 01): S29-S30
DOI: 10.1055/s-0044-1778789
Abstracts
Infektiologie- und Tuberkulose

Blood eosinophil count predicts disease severity in hospitalised community-acquired pneumonia

B Weckler
1   Philipps-University Marburg; Department of Medicine, Pulmonary and Critical Care Medicine; Clinic for Airway Infections
,
H Pott
2   Department of Medicine, Pulmonary and Critical Care Medicine, Clinic for Airway Infections, University Medical Centre Marburg, Philipps-University Marburg
,
A Race
3   Philipps-University Marburg, Marburg, Germany; Institute for Medical Bioinformatics and Biostatistics
,
N Jugkaeo
4   Philipps-University Marburg; Department of Medicine; Data Integration Centre (Dic)
,
K Karki
4   Philipps-University Marburg; Department of Medicine; Data Integration Centre (Dic)
,
S Ringshandl
4   Philipps-University Marburg; Department of Medicine; Data Integration Centre (Dic)
,
C Seidemann
4   Philipps-University Marburg; Department of Medicine; Data Integration Centre (Dic)
,
I Schöndorf
5   Saperco GmbH
,
H Renz
6   Universitätsklinikum Gießen und Marburg; Abteilung für Klinische Chemie Und; Molekulare Diagnostik
,
S Fähndrich
7   Klinik für Klinik für Pneumologie des Universitätsklinikums Freiburg; Abteilung Pneumologie, Universitätsklinik Freiburg; Klinik für Pneumologie
,
A Jung
8   Institute for Lung Research, Universities of Giessen and Marburg Lung Center, German Center for Lung Research (Dzl), Philipps-University Marburg; Core Facility Flow Cytometry – Bacterial Vesicles, Philipps-University Marburg
,
W Bertrams
9   Philipps Universität Marburg; Ilung – Institute for Lung Research
,
A Makoudjou
10   University of Freiburg; Institute of Medical Biometry and Statistics; Faculty of Medicine and Medical Centre
,
D Zöller
11   University of Freiburg, Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Centre; University of Freiburg, Freiburg Centre for Data Analysis and Modelling
,
S Neurath-Finotto
12   Friedrich-Alexander-University (Fau) Erlangen-Nürnberg, University of Erlangen; Department of Molecular Pneumology
,
S Schild
13   Medical Centre for Information and Communication Technology, Erlangen, Germany
,
S Seuchter
14   Medical Centre for Information and Communication Technology; Erlangen, Germany
,
G Rohde
15   Universitätsklinikum Frankfurt; Medizinische Klinik 1; Schwerpunkt Pneumologie/Allergologie
,
F Trinkmann
16   Thoraxklinik Heidelberg gGmbH
,
T Greulich
17   Universitätsklinikum Marburg; Klinik für Innere Medizin, Schwerpunkt Pneumologie
,
C Vogelmeier
18   Department of Medicine, Pulmonary and Critical Care Medicine, Philipps University of Marburg; Deutsches Zentrum für Lungenforschung (Dzl); Klinik für Innere Medizin, Schwerpunkt Pneumologie
,
B Schmeck
19   Institut für Lungenforschung, Universities of Giessen and Marburg Lung Center, Philipps-Universität Marburg, Deutsches Zentrum für Lungenforschung (Dzl); Klinik für Innere Medizin M.S. Pneumologie, Philipps-Universität Marburg, Deutsches Zentrum für Lungenforschung (Dzl); Institute for Lung Research, Universities of Giessen and Marburg Lung Center, German Center for Lung Research (Dzl), Marburg, Germany
› Author Affiliations
 

Background and objective Mortality in patients with community-acquired pneumonia (CAP) continues to be high. Predictors of disease severity are required to improve patient management. This study investigated blood eosinophil levels at hospital admission as an independent biomarker for predicting severity of CAP.

Methods We retrospectively reviewed≥18-year-old patient cases hospitalised with CAP from 2009 to 2020 using data from electronic health records of five German university hospitals from the Medical Informatics in Research and Care in University Medicine consortium. Patients were divided into an eosinopenia group (eosinophils≤50/µL) and non-eosinopenia group (eosinophils>50/µL). Comorbidities between groups were compared. Risk of death and mechanical ventilation were analysed in a multivariate model. Risk of sepsis, length of mechanical ventilation, length of stay in survivors, and time to in-hospital death were calculated in an univariate model.

Results Overall, 6,748 patient cases were included in the analysis. Of those, 4,060 cases had blood eosinophils≤50/µL, while 2,688 cases had eosinophils>50/µL. In the eosinopenia group, the prevalence of COPD (14.2%; p=0.004), myocardial infarction (1.6%; p=0.019), peripheral vascular disease (7.2%; p=0.008), and renal disease (21.7%; p < 0.0001) was lower compared with the non-eosinopenia group (16.8%, 2.5%, 9.0%, 25.9%, respectively). The prevalence of asthma, congestive heart failure, cerebrovascular disease, dementia, diabetes mellitus, and liver disease were not different between groups. In the eosinopenia group, in-hospital mortality (13.8%; p < 0.0001), risk of mechanical ventilation (19.2%; p < 0.0001), and risk of sepsis (7.5%; < 0.0001) were increased compared to the non-eosinopenia group (9.1%, 14.3%, and 5.0%, respectively). Length of stay in survivors was longer (8.41 days; p < 0.0001) in the eosinopenia group versus the non-eosinopenia group (7.64 days), while length of mechanical ventilation did not differ (p=0.152) between groups. Time to in-hospital death was shorter in the eosinopenia (6.73 days; p=0.001) versus non-eosinopenia group (8.92 days).

Conclusions Eosinopenia≤50/µL may be used as independent predictor of disease severity in CAP. Future prospective studies are required to confirm our results.



Publication History

Article published online:
01 March 2024

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