AI Summary & Key Takeaways
AI InsightConclusions: Tracking ECF with CBC subsets and indexes may be helpful in the early prediction of severity, diagnosis, and follow up of critical COVID-19 patients in the course of the disease.
📌 3 Key Takeaways
Abstract
Background/Aim: Differentiating COVID-19 positive patients from negative ones with similar symptoms and predicting the course of disease are major problems in COVID-19. For this purpose, we investigated the performance of Eosinophil Chemotactic Factor (CCL11) in COVID-19 and compared complete blood count parameters and indexes. Methods: In this retrospective case-control study, ECF/CCL11 values, as well as the clinical, laboratory and radiological data of thirty patients who were diagnosed with Covid-19 between 15 March-15 June 2020 were compared with those of thirty healthy controls. Results: Both patients and controls included 10 (33.30%) females and 20 (66.60%) males with a mean age of 57.2 (15.46) and 60.07 (20.59) years, respectively. Eosinophil counts of the patients on admission (EO1) were significantly lower than those of the controls and one-week later EO2 levels (P<0.001, P=0.004 respectively). EO1, NE1, NE2, PLT2/LYM2, LYM1/CRP1 and LYM2/CRP2 were the most predictive indexes. ECF values of the patients one week after admission (ECF2) were significantly lower than that of controls and admission levels (P=0.046, P=0.011 respectively). ECF2 values differentiated Covid19 negative individuals from patients with 46.70% sensitivity, 93.30% specificity at a cutoff value of ≤45.00 pg/mL. In ROC analysis of ECF2, AUC was 0.702 (P=0.045). Conclusions: Tracking ECF with CBC subsets and indexes may be helpful in the early prediction of severity, diagnosis, and follow up of critical COVID-19 patients in the course of the disease.