Association between complete blood count-derived inflammatory biomarkers and renal failure: a cross-sectional study...

Renal failure is a serious public health concern, and its prevalence has been steadily increasing in recent years. This study aims to use data from a nationally representative sample of adults in the USA to investigate the association between inflammatory markers derived from complete blood counts and the prevalence of renal failure.

This study is a cross-sectional study.

The National Health and Nutrition Examination Survey 2007-2020.

A total of 13 193 participants aged 20-80 years (renal failure n=443, non-renal failure n=12 750) were included in this study.

The outcome variable in this study was based on the questionnaire responses in which participants reported having experienced kidney failure.

This study included a total of 13 193 participants, with 3.36% of the study population experiencing renal failure. After adjusting for confounding variables, the systemic inflammatory response index (SIRI) was positively correlated with the prevalence of renal failure (model III OR=1.21, 95% CI 1.12 to 1.30, p<0.0001). Smooth curve fitting and curve threshold effect analysis revealed a non-linear relationship between SIRI and the prevalence of kidney failure. Specifically, when SIRI was less than 2.67, a significant positive correlation was observed between SIRI and the prevalence of kidney failure (model III OR=1.67, 95% CI 1.43 to 1.94, p<0.0001). Subgroup analysis and interaction tests of the association between SIRI and kidney failure revealed that the positive correlation remained consistent across subgroup analyses. Gender, race and body mass index (BMI) interacted with this association (p for interaction<0.05). The monocyte-to-lymphocyte ratio (MLR) was positively associated with the prevalence of kidney failure (model III OR=5.60, 95% CI 3.25 to 9.63, p<0.0001). Smooth curve fitting and curve threshold effect analysis showed a non-linear relationship between MLR and the prevalence of kidney failure. Furthermore, when MLR<0.49, there was a significant positive correlation between MLR and the incidence of renal failure (model III OR=26.50, 95% CI 9.18 to 76.49, p<0.0001). The positive correlation between MLR and renal failure remained consistent in subgroup analyses. Furthermore, gender and diabetes interacted with this association (p for interaction<0.05). The neutrophil-lymphocyte ratio (NLR) was positively correlated with the incidence of kidney failure (model III OR=1.14, 95% CI 1.08 to 1.20, p<0.0001). Smooth curve fitting revealed a non-linear relationship between MLR and the prevalence of kidney failure. Curve threshold effect analysis showed that when NLR<4.12, there was a significant positive correlation between NLR and the prevalence of kidney failure (model III OR=1.40, 95% CI 1.25 to 1.56, p<0.0001). The positive correlation between NLR and kidney failure remained consistent in subgroup analyses. Gender, race and BMI interacted with this association (p for interaction<0.05).

Our research indicates that elevated levels of inflammation biomarkers, as measured by complete blood counts, in the adult population of the USA are associated with an increased risk of renal failure. However, this association needs to be further validated in other prospective studies, and the underlying mechanisms also require further investigation. These findings may help individuals reduce the risk of renal failure and better manage the disease by modulating inflammatory responses.