Author:
van de Ven N. L. M.,Bongers S. H.,Spijkerman R.,Koenderman L.,Leenen L. P. H.,Hietbrink F.,Nijdam Thomas M. P.,Bindels Bas J. J.,Jorritsma Nikita K. N.,Verhaegh Remi,Spanjaard Judith S.,Verboeket Benjamin W.,Laane Duco,van Wessem Karlijn,Buitenwerf Wiebe,van Spengler Daan E. J.,Mulder Eva,Vrisekoop Nienke,Heijerma Harry,van Goor Harriët M. R.,Daza Zabaleta Amely,van den Bos Frederiek,Stiphout Feikje,Kaasjager Karin A. H.,Rademaker Emma,Varkila Meri R. J.,de Mul Nikki,Cremer Olaf L.,Slooter Arjen,Limper Maarten,Leavis Helen,Delemarre Eveline M.,Pandit Aridaman,van Wijk Femke,Nierkens Stefan,Jukema Bernard N.,Clark Chantal C.,Barendrecht Arjan D.,Seinen Cor W.,Drost-Verhoef Sandra,Smits Simone,Parr Naomi M. J.,Sebastian Sylvie A. E.,Koekman Arnold C.,van Wesel Annet C.,van der Vries Erhard,Maas Coen,de Maat Steven,Haitjema Saskia,Hoefer Imo E.,Tinnevelt Gerjen H.,Jansen Jeroen J.,
Abstract
Abstract
Introduction
Bacterial infections are frequently seen in the emergency department (ED), but can be difficult to distinguish from viral infections and some non-infectious diseases. Common biomarkers such as c-reactive protein (CRP) and white blood cell (WBC) counts fail to aid in the differential diagnosis. Neutrophil CD64 (nCD64), an IgG receptor, is suggested to be more specific for bacterial infections. This study investigated if nCD64 can distinguish bacterial infections from other infectious and non-infectious diseases in the ED.
Methods
All COVID-19 suspected patients who visited the ED and for which a definitive diagnosis was made, were included. Blood was analyzed using an automated flow cytometer within 2 h after presentation. Patients were divided into a bacterial, viral, and non-infectious disease group. We determined the diagnostic value of nCD64 and compared this to those of CRP and WBC counts.
Results
Of the 291 patients presented at the ED, 182 patients were included with a definitive diagnosis (bacterial infection n = 78; viral infection n = 64; non-infectious disease n = 40). ROC-curves were plotted, with AUCs of 0.71 [95%CI: 0.64–0.79], 0.77 [0.69–0.84] and 0.64 [0.55–0.73] for nCD64, WBC counts and CRP, respectively. In the bacterial group, nCD64 MFI was significantly higher compared to the other groups (p < 0.01). A cut-off of 9.4 AU MFI for nCD64 corresponded with a positive predictive value of 1.00 (sensitivity of 0.27, a specificity of 1.00, and an NPV of 0.64). Furthermore, a diagnostic algorithm was constructed which can serve as an example of what a future biomarker prediction model could look like.
Conclusion
For patients in the ED presenting with a suspected infection, nCD64 measured with automatic flow cytometry, has a high specificity and positive predictive value for diagnosing a bacterial infection. However, a low nCD64 cannot rule out a bacterial infection. For future purposes, nCD64 should be combined with additional tests to form an algorithm that adequately diagnoses infectious diseases.
Publisher
Springer Science and Business Media LLC