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Dynamic Monitoring of Seroconversion using a Multianalyte Immunobead Assay for Covid-19
Published on: February 16, 2022
Serum calprotectin can indicate current and future severity of COVID-19
Hajar Shokri-Afra1, Mona Moradi2, Hadis Musavi3
1Gut and Liver Research Center, Non-communicable Diseases Institute, Mazandaran University of Medical Sciences, Sari, Iran.
Background:
Predictive and prognostic biomarkers to guide 2019 novel coronavirus disease (COVID-19) are critically evolving. Dysregulated immune responses are the pivotal cause of severity mainly mediated by neutrophil activation. Thus, we evaluated the association of calprotectin, neutrophil secretory protein, and other mediators of inflammation with the severity and outcomes of COVID-19.
Methods:
This two-center prospective study focused on PCR-proven COVID-19 patients (n = 76) with different clinical presentations and SARS-CoV-2 negative control subjects (n = 24). Serum calprotectin (SC) was compared with IL-6 and other laboratory parameters.
Results:
Median levels of SC were significantly higher in COVID-19 patients in comparison to the control group (3760 vs. 2100 ng/ml, p < 0.0001). Elevated SC was significantly respective of disease severity (3760 ng/ml in mild up to 5700 ng/ml in severe cases, p < 0.0001). Moreover, the significant positive and negative correlations of SC with disease severity and oxygenation status indicated disease progression and respiratory worsening, respectively. It was found that SC was high in severe patients during hospitalization and significantly declined to normal after recovery. The logistic analysis identified the independent predictive power of SC for respiratory status or clinical severity. Indeed, SC behaved as a better discriminator for both outcomes, as it exhibited the largest area under the curve (receiver operating curve analysis), with the highest specificity and sensitivity when the predictive value of inflammatory biomarkers was compared.
Conclusion:
Calprotectin can be used as a reliable prognostic tool to predict the poor clinical outcomes of COVID-19 patients.
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