Predictive Role of Platelet and Inflammation Markers for Severe COVID-19 by Propensity Score Matching.

BACKGROUND: This study aims to ascertain the predictive value of platelet and inflammation markers in severe cases of COVID-19.

METHODS: A retrospective real-world cohort study was conducted using propensity score matching (PSM). Patients were classified into severe and non-severe COVID-19 groups based on the severity of the disease, and the correlation between severe COVID-19 and laboratory parameters at admission was analyzed.

RESULTS: The study included 397 adult patients, comprising 212 (53%) males and 185 (47%) females. Among these, 309 were non-severe and 88 were severe cases. The severe group had a higher median age than the non-severe group (60 vs. 42 years, p < 0.001). Independent risk factors for severe COVID-19 included age, diabetes comorbidity, fever, respiratory symptoms, platelet count, high-sensitivity C-reactive protein (hsCRP), interleukin-6 (IL-6), and the ratio of arterial oxygen partial pressure (PaO2) to the fraction of inspired oxygen (FiO2) (P/F ratio). After one-to-one PSM, adjusted for age, diabetes comorbidities, fever, and respiratory symptoms, significant differences in laboratory parameters at admission were observed. Compared to the non-severe group (n = 71), in the severe group (n = 71), elevated levels of hsCRP (median: 27.1 mg/L vs. 14.6 mg/L, p = 0.005) and IL-6 (median: 16.2 pg/mL vs. 15.3 pg/mL, p = 0.005) were observed, while platelet count (164 ± 36 × 109 vs. 180 ± 50 × 109, p = 0.02) and P/F ratio (median: 351 vs. 397, p = 0.001) were reduced.

CONCLUSIONS: Elevated levels of hsCRP and IL-6, along with reduced platelet count and P/F ratio at admission, were significantly associated with severe COVID-19 and may serve as predictive indicators.