Point-of-care neutrophil CD64 as a rule in diagnostic test for bacterial infections in the emergency department.


Journal

BMC emergency medicine
ISSN: 1471-227X
Titre abrégé: BMC Emerg Med
Pays: England
ID NLM: 100968543

Informations de publication

Date de publication:
14 03 2023
Historique:
received: 31 05 2022
accepted: 28 02 2023
entrez: 14 3 2023
pubmed: 15 3 2023
medline: 16 3 2023
Statut: epublish

Résumé

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. 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. 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. 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.

Identifiants

pubmed: 36915043
doi: 10.1186/s12873-023-00800-2
pii: 10.1186/s12873-023-00800-2
pmc: PMC10010956
doi:

Substances chimiques

Biomarkers 0
C-Reactive Protein 9007-41-4

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

28

Investigateurs

Thomas M P Nijdam (TMP)
Bas J J Bindels (BJJ)
Nikita K N Jorritsma (NKN)
Remi Verhaegh (R)
Judith S Spanjaard (JS)
Benjamin W Verboeket (BW)
Duco Laane (D)
Karlijn van Wessem (K)
Wiebe Buitenwerf (W)
Daan E J van Spengler (DEJ)
Eva Mulder (E)
Nienke Vrisekoop (N)
Harry Heijerma (H)
Harriët M R van Goor (HMR)
Amely Daza Zabaleta (A)
Frederiek van den Bos (F)
Feikje Stiphout (F)
Karin A H Kaasjager (KAH)
Emma Rademaker (E)
Meri R J Varkila (MRJ)
Nikki de Mul (N)
Olaf L Cremer (OL)
Arjen Slooter (A)
Maarten Limper (M)
Helen Leavis (H)
Eveline M Delemarre (EM)
Aridaman Pandit (A)
Femke van Wijk (F)
Stefan Nierkens (S)
Bernard N Jukema (BN)
Chantal C Clark (CC)
Arjan D Barendrecht (AD)
Cor W Seinen (CW)
Sandra Drost-Verhoef (S)
Simone Smits (S)
Naomi M J Parr (NMJ)
Sylvie A E Sebastian (SAE)
Arnold C Koekman (AC)
Annet C van Wesel (AC)
Erhard van der Vries (E)
Coen Maas (C)
Steven de Maat (S)
Saskia Haitjema (S)
Imo E Hoefer (IE)
Gerjen H Tinnevelt (GH)
Jeroen J Jansen (JJ)

Informations de copyright

© 2023. The Author(s).

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Auteurs

N L M van de Ven (NLM)

Department of Trauma Surgery, University Medical Center Utrecht, Utrecht, The Netherlands.

S H Bongers (SH)

Department of Trauma Surgery, University Medical Center Utrecht, Utrecht, The Netherlands.
Center for Translational Immunology, University Medical Center Utrecht, Utrecht, The Netherlands.

R Spijkerman (R)

Center for Translational Immunology, University Medical Center Utrecht, Utrecht, The Netherlands.
Department of Respiratory Medicine, University Medical Center Utrecht, Utrecht, The Netherlands.

L Koenderman (L)

Center for Translational Immunology, University Medical Center Utrecht, Utrecht, The Netherlands.
Department of Respiratory Medicine, University Medical Center Utrecht, Utrecht, The Netherlands.

L P H Leenen (LPH)

Department of Trauma Surgery, University Medical Center Utrecht, Utrecht, The Netherlands.
Center for Translational Immunology, University Medical Center Utrecht, Utrecht, The Netherlands.

F Hietbrink (F)

Department of Trauma Surgery, University Medical Center Utrecht, Utrecht, The Netherlands. F.Hietbrink@umcutrecht.nl.
Center for Translational Immunology, University Medical Center Utrecht, Utrecht, The Netherlands. F.Hietbrink@umcutrecht.nl.

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