We retrospectively analyzed serum level of human epididymis protein 4 (HE4) as a pulmonary inflammatory biomarker in patients with COVID-19 pneumonia in association with disease severity and outcome.
Ninety-nine (40 critically ill, 40 severe and 19 mild) COVID-19 patients and as controls 25 age- and sex-matched non-COVID-19 bacterial sepsis subjects were included. Serum HE4 was measured by an immunoassay (Architect i1000SR, Abbott) in the baseline samples of all study participants obtained at intensive care unit (ICU) admission or during outpatient clinic visit and follow-up sera were available in case of 30 COVID-19 subjects with life-threating conditions. Associations were studied between serum HE4, routinely available laboratory parameters, clinical characteristics, and disease progression.
Baseline HE4 level was significantly higher (P < 0.0001) in critically ill (524.7 [300.1-1153.0] pmol/L) than severe COVID-19 subjects (157.4 [85.2-336.9] pmol/L) and in mild SARS-CoV-2 infection (46.7 [39.1-57.2] pmol/L). Similarly increased HE4 concentrations were found in bacterial sepsis (1118.0 [418.3-1953.0] pmol/L, P = 0.056) compared to critically ill COVID-19 individuals. Serum HE4 levels significantly correlated with age, SOFA-score, inflammation-dependent biomarkers, and the degree of lung manifestation evaluated by chest CT examination in ICU COVID-19 individuals. Based on ROC-AUC curve analysis, baseline HE4 independently indicated the severity of COVID-19 with an AUC value of 0.816 (95% CI [0.723-0.908]; P < 0.0001), while binary logistic regression test found HE4 as an independent prognostic parameter for death (OR: 10.618 [2.331-48.354]; P = 0.002). Furthermore, COVID-19 non-survivors showed much higher baseline HE4 levels without a substantial change under treatment vs. survivors (P < 0.0001). Finally, pre-treatment HE4 level of ≥ 331.7 pmol/L effectively predicted a larger risk for mortality (Log-Rank P < 0.0001) due to severe COVID-19 pneumonia.
Elevated serum HE4 level at ICU admission highly correlates with COVID-19 severity and predicts disease outcome.
© 2023. The Author(s).
