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. 2024 Dec 26;17(1):1.
doi: 10.3390/pediatric17010001.

Biomarker Analysis in Upper Respiratory Tract Infections: Associations with Demographics and Clinical Outcomes

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Biomarker Analysis in Upper Respiratory Tract Infections: Associations with Demographics and Clinical Outcomes

Felicia Manole et al. Pediatr Rep. .

Abstract

Background/objectives: Upper respiratory tract infections (URTIs) are a significant global health burden, and understanding the immune response is crucial for developing effective diagnostic tools and treatment strategies.

Methods: This study investigated the levels of specific biomarkers in 188 patients with URTIs and their association with demographic factors, comorbidities, and clinical outcomes. Immunoglobulin A (IgA), immunoglobulin E (IgE), neutrophils, serum iron, C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR) were measured.

Results: The median age of the patients was 5 years, with 46% being female and 63% from urban areas. Adenoiditis (37%), otitis (25%), and rhinitis (20%) were the most common diagnoses. While most biomarkers did not vary significantly by gender, neutrophil levels were significantly higher in females (p = 0.020). IgE levels were significantly elevated in rural patients compared to urban counterparts (p = 0.034).

Conclusions: ESR was significantly associated with rhinitis diagnosis, and IgE and ESR were predictive of otitis in multivariate models. However, many biomarkers did not significantly correlate with other diagnoses, contradicting previous research focusing on individual biomarkers. This study highlights the complexity of immune responses in URTIs and the need for more effective diagnostic tools. The findings can inform the development of tailored treatment strategies based on gender, area of origin, and infection type.

Keywords: C-reactive protein; biomarkers; immunoglobulin A; immunoglobulin E; neutrophils; upper respiratory tract infections.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Frequency of diagnosis for the sample size.
Figure 2
Figure 2
Distribution of diagnoses by patient origin.
Figure 3
Figure 3
Graphical representations (violin plots) of key relationships between the studied characteristics.
Figure 3
Figure 3
Graphical representations (violin plots) of key relationships between the studied characteristics.

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