Neutrophil:lymphocyte ratio predicts short-term outcome of COVID-19 in haemodialysis patients

Clin Kidney J. 2020 Nov 21;14(1):124-131. doi: 10.1093/ckj/sfaa194. eCollection 2021 Jan.

Abstract

Background: Information regarding coronavirus disease 2019 (COVID-19) in haemodialysis (HD) patients is limited and early studies suggest a poor outcome. We aimed to identify clinical and biological markers associated with severe forms of COVID-19 in HD patients.

Methods: We conducted a prospective, observational and multicentric study. Sixty-two consecutive adult HD patients with confirmed COVID-19 from four dialysis facilities in Paris, France, from 19 March to 19 May 2020 were included.Blood tests were performed before diagnosis and at Days 7 and 14 after diagnosis. Severe forms of COVID-19 were defined as requiring oxygen therapy, admission in an intensive care unit or death. Cox regression models were used to compute adjusted hazard ratios (aHRs). Kaplan-Meier curves and log-rank tests were used for survival analysis.

Results: Twenty-eight patients (45%) displayed severe forms of COVID-19. Compared with non-severe forms, these patients had more fever (93% versus 56%, P < 0.01), cough (71% versus 38%, P = 0.02) and dyspnoea (43% versus 6%, P < 0.01) at diagnosis. At Day 7 post-diagnosis, neutrophil counts, neutrophil:lymphocyte (N:L) ratio, C-reactive protein, ferritin, fibrinogen and lactate dehydrogenase levels were significantly higher in severe COVID-19 patients. Multivariate analysis revealed an N:L ratio >3.7 was the major marker associated with severe forms, with an aHR of 4.28 (95% confidence interval 1.52-12.0; P = 0.006). After a median follow-up time of 48 days (range 27-61), six patients with severe forms died (10%).

Conclusions: HD patients are at increased risk of severe forms of COVID-19. An elevated N:L ratio at Day 7 was highly associated with the severe forms. Assessing the N:L ratio could inform clinicians for early treatment decisions.

Keywords: biomarkers; dialysis; haemodialysis; prognosis; survival analysis.