Predictive value of neutrophil‐to‐lymphocyte ratio in terms of need for intensive care unit and mortality in maintenance hemodialysis patients with COVID‐19. Issue 3 (9th January 2022) - Oguz, Ebru Gok; Yeter, Haci Hasan; Akcay, Omer Faruk; Besli, Sevval; Selen, Tamer; Derici, Ulver; Sencan, Irfan; Ayli, Mehmet Deniz
Abstract: Introduction: The transmission risk of Severe Acute Respiratory Syndrome Coronavirus‐2 virus infection is increased in maintenance hemodialysis (MHD) patients, and also the disease causes much higher mortality than the normal population. The aim of this study is to define the predictive value of neutrophil‐to‐lymphocyte ratio (NLR) in terms of worse outcomes in MHD patients. Methods: A total of 123 MHD patients who had received inpatient care due to COVID‐19 infection were included in this multicentered retrospective study. Receiver operating curve analysis were plotted to illustrate C reactive protein (C‐rp), systemic inflammatory index (SII) and NLR best cut‐off values for estimation of need for intensive care unit (ICU) and mortality. Multivariate regression analysis and Cox proportional hazard models were constructed to determine the association between C‐rp, SII and NLR and mortality. Results: Twenty‐eight (23%) patients with MHD were dead due to COVID‐19. Nonsurvivor patients was significantly older than the survivors ( p < 0.001) and also had higher rates of diabetes mellitus ( p = 0.01) and coronary artery disease ( p = 0.02). Cox regression analysis revealed that NLR >5.17 significantly associated with mortality [HR: 6.508, p < 0.001]. Similarly, SII > 726 [HR: 3.124, p = 0.006] and C‐rp > 88 [HR: 4.590, p = 0.002] were significantly associated with mortality due to COVID‐19 in hospitalized MHD patients. Multivarite logistic regression analysis showed that age older than 60 years, higher ferritin, and NLR > 5.17 were independent factors associated with mortality. Conclusion: NLR had favorable predictive value than the C‐rp and SII in terms of need for ICU and mortality in MHD patients. Determining the poor prognosis with simple and easily applicable markers may reduce mortality in these patients with early supportive treatments.