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Validation of a clinical prediction model for early admission to the intensive care unit of patients with pneumonia

Labarere, J. and Schuetz, P. and Renaud, B. and Claessens, Y. E. and Albrich, W. and Mueller, B.. (2012) Validation of a clinical prediction model for early admission to the intensive care unit of patients with pneumonia. Academic Emergency Medicine, 19 (9). pp. 993-1003.

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Official URL: http://edoc.unibas.ch/56817/

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Abstract

OBJECTIVES: The Risk of Early Admission to the Intensive Care Unit (REA-ICU) index is a clinical prediction model that was derived based on 4,593 patients with community-acquired pneumonia (CAP) for predicting early admission to the intensive care unit (ICU; i.e., within 3 days following emergency department [ED] presentation). This study aimed to validate the REA-ICU index in an independent sample. METHODS: The authors retrospectively stratified 850 CAP patients enrolled in a multicenter prospective randomized trial conducted in Switzerland, using the REA-ICU index, alternate clinical prediction models of severe pneumonia (SMART-COP, CURXO-80, and the 2007 IDSA/ATS minor severity criteria), and pneumonia severity assessment tools (the Pneumonia Severity Index [PSI] and CURB-65). Results: The rate of early ICU admission did not differ between the validation and derivation samples within each risk class of the REA-ICU index, ranging from 1.1% to 1.8% in risk class I to 27.1% to 27.6% in risk class IV. The areas under the receiver operating characteristic (ROC) curve were 0.76 (95% confidence interval [CI] = 0.70 to 0.83) and 0.80 (95% CI = 0.77 to 0.83) in the validation and derivation samples, respectively. In the validation sample, the REA-ICU index performed better than the pneumonia severity assessment tools, but failed to demonstrate an accuracy advantage over alternate prediction models in predicting ICU admission. CONCLUSIONS: The REA-ICU index reliably stratifies CAP patients into four categories of increased risk for early ICU admission within 3 days following ED presentation. Further research is warranted to determine whether inflammatory biomarkers may improve the performance of this clinical prediction model.
Faculties and Departments:03 Faculty of Medicine > Bereich Medizinische Fächer (Klinik) > Allgemeine innere Medizin AG > Argovia Professur für Medizin (Müller)
03 Faculty of Medicine > Departement Klinische Forschung > Bereich Medizinische Fächer (Klinik) > Allgemeine innere Medizin AG > Argovia Professur für Medizin (Müller)
UniBasel Contributors:Müller, Beat
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Wiley
ISSN:1069-6563
e-ISSN:1553-2712
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:30 Nov 2017 11:16
Deposited On:30 Nov 2017 11:16

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