Biomarkers troponin and procalcitonin in addition to CRB-65 enhance risk stratification in patients with community-acquired pneumonia
Background Community-acquired pneumonia (CAP) remains a leading cause of infectious disease mortality globally, necessitating intensive care unit (ICU) admission for ∼10% of hospitalised patients. Accurate prediction of disease severity facilitates timely therapeutic interventions. Methods Our study...
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| Format: | Article |
| Language: | English |
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European Respiratory Society
2024-12-01
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| Series: | ERJ Open Research |
| Online Access: | http://openres.ersjournals.com/content/10/6/00420-2024.full |
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| author | Imrana Farhat Maciej Rosolowski Katharina Ahrens Jasmin Lienau Peter Ahnert Mathias Pletz Gernot Rohde Jan Rupp Markus Scholz Martin Witzenrath the CAPNETZ Study Group |
| author_facet | Imrana Farhat Maciej Rosolowski Katharina Ahrens Jasmin Lienau Peter Ahnert Mathias Pletz Gernot Rohde Jan Rupp Markus Scholz Martin Witzenrath the CAPNETZ Study Group |
| author_sort | Imrana Farhat |
| collection | DOAJ |
| description | Background
Community-acquired pneumonia (CAP) remains a leading cause of infectious disease mortality globally, necessitating intensive care unit (ICU) admission for ∼10% of hospitalised patients. Accurate prediction of disease severity facilitates timely therapeutic interventions.
Methods
Our study aimed to enhance the predictive capacity of the clinical CRB-65 score by evaluating eight candidate biomarkers: troponin T high-sensitive (TnT-hs), procalcitonin (PCT), N-terminal pro-brain natriuretic peptide, angiopoietin-2, copeptin, endothelin-1, lipocalin-2 and mid-regional pro-adrenomedullin. We utilised a machine-learning approach on 800 samples from the German CAPNETZ network (competence network for CAP) to refine risk prediction models combining these biomarkers with the CRB-65 score regarding our defined end-point: death or ICU admission during the current CAP episode within 28 days after study inclusion.
Results
Elevated levels of biomarkers were associated with the end-point. TnT-hs exhibited the highest predictive performance among individual features (area under the receiver operating characteristic curve, AUC=0.74), followed closely by PCT (AUC=0.73). Combining biomarkers with the CRB-65 score significantly improved prediction accuracy. The combined model of CRB-65, TnT-hs and PCT demonstrated the best balance between high predictive value and parsimony, with an AUC of 0.77 (95% CI: 0.72–0.82), while CRB-65 alone achieved an AUC of 0.67 (95% CI: 0.64–0.73).
Conclusion
Our findings suggest that augmenting the CRB-65 score with TnT-hs and PCT enhances the prediction of death or ICU admission in hospitalised CAP patients. Validation of this improved risk score in additional CAP cohorts and prospective clinical studies is warranted to assess its broad clinical utility. |
| format | Article |
| id | doaj-art-c73f84a74a3e4974afd8fd09c9089f89 |
| institution | Kabale University |
| issn | 2312-0541 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | European Respiratory Society |
| record_format | Article |
| series | ERJ Open Research |
| spelling | doaj-art-c73f84a74a3e4974afd8fd09c9089f892025-01-14T09:50:22ZengEuropean Respiratory SocietyERJ Open Research2312-05412024-12-0110610.1183/23120541.00420-202400420-2024Biomarkers troponin and procalcitonin in addition to CRB-65 enhance risk stratification in patients with community-acquired pneumoniaImrana Farhat0Maciej Rosolowski1Katharina Ahrens2Jasmin Lienau3Peter Ahnert4Mathias Pletz5Gernot Rohde6Jan Rupp7Markus Scholz8Martin Witzenrath9the CAPNETZ Study Group10 University of Leipzig, Institute for Medical Informatics, Statistics and Epidemiology, Leipzig, Germany University of Leipzig, Institute for Medical Informatics, Statistics and Epidemiology, Leipzig, Germany Charité – Universitaetsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Infectious Diseases, Respiratory Medicine and Critical Care, Berlin, Germany Charité – Universitaetsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Infectious Diseases, Respiratory Medicine and Critical Care, Berlin, Germany University of Leipzig, Institute for Medical Informatics, Statistics and Epidemiology, Leipzig, Germany Jena University Hospital, Institute of Infectious Diseases and Infection Control, Jena, Germany CAPNETZ STIFTUNG, Hannover, Germany CAPNETZ STIFTUNG, Hannover, Germany University of Leipzig, Institute for Medical Informatics, Statistics and Epidemiology, Leipzig, Germany Charité – Universitaetsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Infectious Diseases, Respiratory Medicine and Critical Care, Berlin, Germany CAPNETZ STIFTUNG, Hannover, Germany Background Community-acquired pneumonia (CAP) remains a leading cause of infectious disease mortality globally, necessitating intensive care unit (ICU) admission for ∼10% of hospitalised patients. Accurate prediction of disease severity facilitates timely therapeutic interventions. Methods Our study aimed to enhance the predictive capacity of the clinical CRB-65 score by evaluating eight candidate biomarkers: troponin T high-sensitive (TnT-hs), procalcitonin (PCT), N-terminal pro-brain natriuretic peptide, angiopoietin-2, copeptin, endothelin-1, lipocalin-2 and mid-regional pro-adrenomedullin. We utilised a machine-learning approach on 800 samples from the German CAPNETZ network (competence network for CAP) to refine risk prediction models combining these biomarkers with the CRB-65 score regarding our defined end-point: death or ICU admission during the current CAP episode within 28 days after study inclusion. Results Elevated levels of biomarkers were associated with the end-point. TnT-hs exhibited the highest predictive performance among individual features (area under the receiver operating characteristic curve, AUC=0.74), followed closely by PCT (AUC=0.73). Combining biomarkers with the CRB-65 score significantly improved prediction accuracy. The combined model of CRB-65, TnT-hs and PCT demonstrated the best balance between high predictive value and parsimony, with an AUC of 0.77 (95% CI: 0.72–0.82), while CRB-65 alone achieved an AUC of 0.67 (95% CI: 0.64–0.73). Conclusion Our findings suggest that augmenting the CRB-65 score with TnT-hs and PCT enhances the prediction of death or ICU admission in hospitalised CAP patients. Validation of this improved risk score in additional CAP cohorts and prospective clinical studies is warranted to assess its broad clinical utility.http://openres.ersjournals.com/content/10/6/00420-2024.full |
| spellingShingle | Imrana Farhat Maciej Rosolowski Katharina Ahrens Jasmin Lienau Peter Ahnert Mathias Pletz Gernot Rohde Jan Rupp Markus Scholz Martin Witzenrath the CAPNETZ Study Group Biomarkers troponin and procalcitonin in addition to CRB-65 enhance risk stratification in patients with community-acquired pneumonia ERJ Open Research |
| title | Biomarkers troponin and procalcitonin in addition to CRB-65 enhance risk stratification in patients with community-acquired pneumonia |
| title_full | Biomarkers troponin and procalcitonin in addition to CRB-65 enhance risk stratification in patients with community-acquired pneumonia |
| title_fullStr | Biomarkers troponin and procalcitonin in addition to CRB-65 enhance risk stratification in patients with community-acquired pneumonia |
| title_full_unstemmed | Biomarkers troponin and procalcitonin in addition to CRB-65 enhance risk stratification in patients with community-acquired pneumonia |
| title_short | Biomarkers troponin and procalcitonin in addition to CRB-65 enhance risk stratification in patients with community-acquired pneumonia |
| title_sort | biomarkers troponin and procalcitonin in addition to crb 65 enhance risk stratification in patients with community acquired pneumonia |
| url | http://openres.ersjournals.com/content/10/6/00420-2024.full |
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