Abstract

Abstract Background and Aims Maintenance haemodailaysis (HD) patients are at higher risk for severe coronavirus disease 2019 (COVID-19). Because of a limited number of facilities that can provide inpatient treatment for COVID-19 and HD, it is important to identify HD patients who are at high risk for severe COVID-19. For mild to moderate COVID-19 patients, chemokine CC-motif ligand 17 (CCL17) was reported to be a predictive marker for severe COVID-19; however, the validity of CCL17 among HD patients is unknown. Method This retrospective observational study enrolled 107 HD patients with mild or moderate COVID-19 at hospitalisation (mean age 70.1 ± 15.1 years; 71.0% male). Receiver operating characteristic and logistic regression analyses were used to examine the predictive validity of indices for severe COVID-19 which is defined as partial pressure of oxygen/fraction of inspired oxygen (P/F) ratio <300 or SpO2 <94%. Multi-variate logistic regression models were used to investigate the association of CCL17 level with the development of severe COVID-19. Furthermore, to evaluate the degree of improvement in predicting performance in the pre-existing model with the addition of CCL17 compared to the pre-existing model, we calculated net reclassification improvement (NRI) and the integrated discrimination improvement (IDI). Results During hospitalisation, 32 patients developed severe COVID-19. Serum CCL17 collected at admission exhibited a higher area under the curve value (0.818) compared with that of other indicators including LDH and C-reactive protein for the prediction of severe COVID-19. The optimal cut-off value for CCL17 was 150.5 pg/ml. A multi-variate logistic analysis revealed that CCL17 (above 150.5 pg/ml) was significantly associated with severe COVID-19 (Odds ratio, 0.063; 95% Confidence interval [CI], 0.017–0.227; P < 0.001) even after adjustment for covariates. The addition of the CCL17 to a model consisting of vaccination status, albumin, blood urea nitrogen, C-reacting protein and lactate dehydrogenase, that are variables incorporated in multivariate logistic model, significantly improved classification performance for severe COVID-19 using the NRI (1.16, 95% CI: 0.82–1.50, P < 0.001) and IDI (0.18, 95% CI: 0.09–0.26, P < 0.001). Conclusion CCL17 levels in HD patients with mild or moderate COVID-19 predict risk of developing severe COVID-19.

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