Introduction

it is known that the proportions of different blood cell components are new inflammatory markers that have good predictive value in the outcome of chronic kidney disease, cardiovascular diseases, rheumatic diseases, among others, including the neutrophil/lymphocyte ratio, monocyte/lymphocyte ratio, and platelet/lymphocyte ratio.

Objective

to evaluate the inflammatory profile, through the neutrophil/lymphocyte, platelet/lymphocyte, and monocyte/lymphocyte parameters in patients with chronic kidney disease on hemodialysis.

Methods

analytical cross-sectional study. The analyses were conducted using R software (version 4.2.2). A total of 112 hemodialysis patients were evaluated, excluding cases with missing data per variable. Biomarkers such as neutrophil/lymphocyte, platelet/lymphocyte, and monocyte/lymphocyte ratios were analyzed by boxplot to verify symmetrical and outliers and compared between patients with and without inflammation. Student’s t-tests, preceded by assessments of normality (Shapiro-Wilk) and homogeneity of variance (Levene), compared the groups and the reference values of the biomarkers.

Results

the comparison between groups without inflammation and with inflammation, identified by the neutrophil/lymphocyte, platelet/lymphocyte and monocyte/lymphocyte ratio, showed a significant difference between the three parameters (p<0.05). To verify the consistency of the inflamed and non-inflamed groups, the parameters were compared to the reference values, in the three biomarkers, two groups differed statistically (p<0.05) from the reference value, with the exception of patients with inflammation, who in the platelet/lymphocyte ratio marker did not differ from the reference value, suggesting that this biomarker, alone, may not be sufficient to detect inflammation in this group.

Conclusion

the study highlights the relevance of hematological biomarkers in identifying inflammation in hemodialysis patients. Although isolated platelets/lymphocytes were not sufficient for this diagnosis, other markers stood out, indicating the need for an integrated analysis for greater diagnostic accuracy.

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