Can nCD64 and mCD169 biomarkers improve the diagnosis of viral and bacterial respiratory syndromes in the emergency department? A prospective cohort pilot study.

PURPOSE

Differentiating infectious from non-infectious respiratory syndromes is critical in emergency settings. This study aimed to assess whether nCD64 and mCD169 exhibit specific distributions in patients with respiratory infections (viral, bacterial, or co-infections) and to evaluate their diagnostic accuracy compared to non-infectious conditions.

METHODS

A prospective cohort study enrolled 443 consecutive emergency department patients with respiratory syndromes, categorized into four groups: no infection group (NOIG), bacterial infection group (BIG), viral infection group (VIG), and co-infection group (COING). Multinomial logistic regression was used to evaluate nCD64 and mCD169's association with diagnostic groups and estimate their predictive accuracy.

RESULTS

290 patients were included in VIG, 53 in BIG, 46 in COING, and 54 in NOIG. nCD64 was associated with bacterial infections and co-infections (p = 2.73 × 10 and p = 8.83 × 10, respectively), but not viral infections. mCD169 was associated with viral infections and co-infections (p = < 2 × 10 and p = 2.45 × 10, respectively), but not bacterial infections. The sensitivity and specificity of nCD64 for detecting bacterial infections were 0.75 and 0.84 (AUC = 0.83), respectively, while for mCD169 they were 0.87 and 0.91 (AUC = 0.92), respectively, for diagnosing viral infections. A diagnostic algorithm incorporating fever, nasopharyngeal swabs for the main respiratory virus, C-reactive protein, procalcitonin, and mCD169 reached an accuracy of 0.79 (95% CI 0.72-0.85) in distinguishing among the different groups.

CONCLUSIONS

nCD64 and MCD169 seem valuable for distinguishing between bacterial and viral respiratory infections. Integrating these biomarkers into diagnostic algorithms could enhance diagnostic accuracy aiding patient management in emergency settings.