Association of Systemic Immune-inflammation Index and Systemic Inflammation Response Index with Chronic Kidney Disease: Observational Study of 40,937 Adults

doi:10.21203/rs.3.rs-3772588/v1

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Research Article

Association of Systemic Immune-inflammation Index and Systemic Inflammation Response Index with Chronic Kidney Disease: Observational Study of 40,937 Adults

https://doi.org/10.21203/rs.3.rs-3772588/v1

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published 15 Mar, 2024

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Background

Chronic kidney disease (CKD) is linked to immunity and inflammation. SII and SIRI are novel measures for gauging an individual's systemic inflammatory activity. We aim to investigate the potential associations between them.

Methods

This study encompassed a cohort of 40,937 adults. Logistic regression models assessed the association of SII and SIRI levels with CKD prevalence. Cox regression models were utilized to estimate the risk of death.

Results

6986 participants with CKD were recorded, and 2818 patients died during a mean follow-up time of 100 months. After adjusting for all covariates, higher levels of SII, SIRI increased the CKD incidence [ORQuartile4 (95% CI): 1.545 (1.422–1.679); 1.756 (1.610–1.916), respectively] compared with the low-level reference group (Ptrend < 0.05). The high levels of SII significantly increased all-cause, cardiovascular, and hypertension mortality in patients [HRQuartile4 (95% CI): 1.277 (1.145–1.426); 1.467 (1.197–1.798); 1.715 (1.320–2.228), respectively] (Ptrend < 0.001). Additionally, there existed noteworthy positive associations in SIRI [1.679 (1.480–1.906); 2.159 (1.706–2.732); 2.411 (1.802–3.227), respectively] (Ptrend < 0.001). Subgroup analyses unveiled variations in these effects among different populations.

Conclusion

There existed a substantial association of SII and SIRI levels with CKD prevalence in the general populace, as well as mortality in patients with CKD.

Systemic Immune-inflammation Index

Systemic Inflammation Response Index

CKD

Inflammation

NHANES

More than 10% of the world's population is affected by Chronic Kidney Disease (CKD), which is one of the leading causes of death worldwide[1]. It is anticipated that by 2040, it will be the fifth most significant contributor to the decrease in life expectancy around the world, creating a primary health concern on a global scale[2]. Consequently, it is critical to thoroughly comprehend the fundamental elements related to the development and outlook of CKD to devise successful treatment plans to stop the start and advancement of CKD.

The development of CKD is complicated, and several risk factors, including diabetes mellitus, hypertension, and excessive salt consumption, can affect its progression[3–5]. Recent research has demonstrated that immune and inflammatory elements are essential in the development of CKD, which could be linked to the stimulation of oxidative stress, changes in tissue metabolism, endothelial cell harm, and other processes[6]. The combination of inflammation and oxidative stress in CKD progression can increase reactive oxygen species (ROS) production, resulting in apoptosis of renal vascular endothelial cells and necrosis, which can cause renal damage by disrupting microcirculatory regulation and perfusion distribution within the kidney[7, 8]. Irrespective of the cause of CKD, inflammation can contribute to glomerular and tubulointerstitial lesions.

Systemic Immune-inflammation Index (SII) and Systemic Inflammation Response Index (SIRI) can measure an individual's systemic inflammatory activity, demonstrating the equilibrium between inflammation and immune response[9]. Previous research has shown that SII and SIRI can be employed to evaluate local inflammation and systemic immune response, and they have been extensively utilized in the prediction of numerous illnesses, thus enhancing the effectiveness of personalized treatment[10]. Despite this, there is a need for more research into the relationship between SII and SIRI and the occurrence of CKD in the general population, as well as mortality in patients with CKD.

2.1 Study design and study population

We conducted two observational studies. The associations of SII and SIRI with the occurrence of CKD in the general population were assessed by a cross-sectional study, and the correlations between SII and SIRI and the predicted risk of death in patients with CKD were investigated by a prospective cohort study, respectively.

This study incorporated National Health and Nutrition Examination Survey (NHANES) data from 1999 to 2018, with an initial enrollment of 101,316 participants. Simultaneously, we employed a set of exclusion criteria, and individuals who fulfilled any of the subsequent criteria were disqualified from participating in this study: (I) those with incomplete data in the SII and SIRI calculations; (II) those with incomplete data necessary for defining CKD; (III) pregnant[11];(IV) below the age of 20; (V) those with incomplete data on significant covariates. In the end, the study encompassed a total of 40,937 participants. The sample's screening process was shown in detail in Fig. 1.

2.2 Definition of CKD

As per the Kidney Disease Improving Global Outcomes (KDIGO) Guidelines[12], CKD was characterized by a diminished eGFR (< 60 mL/min per 1.73 m²) or an increased ACR (≥ 30 mg/g). The eGFR was determined using the Chronic Kidney Disease Epidemiology Collaborative (2021 CKD-EPI) equation[13], taking into account serum creatinine (S_Cr) (mg/dL) data obtained through the Jaffe rate method and adjusted for gender and age.

2.3 Exposure Variables

In this research, we chose hematological test indices from participants at the beginning of the study who were collected between 1999 and 2018 and computed SII and SIRI individually. SII was defined as (neutrophil count) *(platelet count)/ (lymphocyte count). SIRI was defined as (neutrophil count) *(monocyte count)/ (lymphocyte count).

2.4 Outcome ascertainment

The objective of the cross-sectional study was to determine the occurrence of CKD. The ultimate goal of the prospective cohort study was to assess patients’ CKD progress over time. The study involved participants with CKD connected to follow-up records in the National Death Index (NDI) until December 31, 2019, and matched by NHANES respondent serial number (SEQN) to ascertain their crucial condition and the length of their follow-up.

2.5 Covariates

In light of prior researches concerning the prevalence and outlook of CKD[14, 15], we ultimately examined for the incorporation of pertinent potential confounding factors. Covariates included demographic information: age (years), gender (male/female), race (Mexican American/other Hispanic/non-Hispanic white/non-Hispanic black/other race), marital status (married/living with a partner/widowed/divorced/separated), health insurance (presence/absence), body mass index (BMI) measured as body weight (kilograms) divided by height squared (square meters) determined, smoking (yes/no, defined as smokers smoking more than 100 cigarettes in their lifetime); laboratory test data: serum calcium (mmol/L), serum iron (µmol/L), serum phosphorus (mmol/L), serum sodium (mmol/L); health information: diabetes (yes/no, defined as a diagnosis of diabetes mellitus reported by a doctor/specialist), hypertension (yes/no, expressed as a diagnosis of hypertension reported by a doctor/specialist), Cardiovascular diseases (CVD, yes/no, defined as a physician/specialist, including coronary artery disease, congestive heart failure, stroke, angina, and heart attack), cancer (yes/no, defined as a physician/specialist-reported diagnosis of cancer or malignancy).

2.6 Statistical analyses

The participants were divided into four categories according to SII and SIRI quaternary groupings, with the lowest levels of SII and SIRI acting as the benchmark. We computed the odds ratios (ORs) and 95% confidence intervals (CIs) for the effects of SII and SIRI on CKD morbidity and the hazard ratios (HR) and 95% confidence intervals (CIs) for the impact of SII and SIRI on mortality in patients with CKD for each subgroup and calculated P values before and after adjustment. We utilized the outcomes of model 3, taking into account all covariates, as the primary model. The model examined the linear trend of each subgroup's median value as a continuous variable. We used Cox proportional hazard regression models to create Kaplan-Meyer survival curves for patients, taking into account the four SII and SIRI subgroups.

Furthermore, we conducted distinct subgroup analyses according to the participants' initial attributes. Age (< 60, ≥ 60) and BMI (< 25, 25 ~ 30, > 30)[16] were converted to categorical variables. The interaction tests were performed across the stratified factors. This study also employed sensitivity analyses to evaluate the reliability of the results. Introducing classification for model prediction based on quartiles, as SII and SIRI were continuous variables, could lead to a significant loss of information and potentially diminish the model's predictive capability. Therefore, we investigated the correlation between constant SII and SIRI and the mortality risk in patients with CKD by utilizing smoothed curve fitting. Logistic and Cox regression models were utilized to evaluate the correlations between SII and SIRI (both raw continuous data and continuous data after normalization) and the likelihood of CKD morbidity and mortality, respectively.

Statistical analyses were performed using the R software package (www.r-project.org, The R Foundation), the IBM SPSS Statistics statistical package (IBM SPSS Statistics for Windows, version 27.0 (IBM Corp., Armonk, N.Y., USA)) and Empower-Stats (www.empowerstats.com, X&Y Solutions, Inc., Boston, MA). Statistical significance was determined by a two-tailed test P < 0.05.

3.1 Participant Baseline Characteristics

The baseline characteristics of the 40,937 participants enrolled were shown in Table 1. It was discovered that individuals with elevated SII levels exhibited a higher likelihood of being older, female, non-Hispanic white, widowed/divorced, higher BMI levels, smokers, diabetes, hypertensive, cancer, higher UACR, and those with CVD. Additionally, elevated levels of SII were linked to decreased serum iron, sodium concentrations, and eGFR levels. Individuals with elevated SIRI levels exhibited a higher likelihood of being of advanced age, male, non-Hispanic white, widowed/divorced, possessing health insurance, higher BMI levels, smokers, diabetes, hypertensive, cancer, higher UACR, and those with CVD. Additionally, elevated levels of SIRI were linked to decreased levels of serum iron, sodium, and phosphorus concentrations, as well as eGFR.

3.2 Association of SII, SIRI, and CKD prevalence risk

Table 2 displayed the outcomes of the logistic regression analyses. After adjusting for all covariates, it was observed that the likelihood of CKD prevalence rose proportionally with the escalation of SII levels (HR = 1.545; 95% CI:0.422 ~ 1.679), and all subgroups with elevated concentrations displayed an elevated risk of CKD prevalence (P trend < 0.001). The likelihood of CKD prevalence rose as SIRI levels increased (HRQuartile4 = 1.756; 95% CI: 1.610 ~ 1.916), and all subgroups of higher concentrations exhibited a higher risk of CKD prevalence (P trend < 0.001).

3.3 Subgroup analyses and interaction tests

Table S1 displayed the outcomes of the stratified and interaction analyses based on age, gender, BMI, smoking status, diabetes, hypertension, cancer, and CVD. The interaction test revealed a noteworthy correlation between SIRI and CKD in the subgroups divided by gender (P for interaction = 0.036), and the impact of increased SIRI on the likelihood of developing CKD was more pronounced in females(Figure S1). No significant correlation was demonstrated in other strata (P for interaction tests were all > 0.05). The association between SIRI and CKD incidence was robust (all P values for interaction > 0.05).

3.4 Baseline characteristics of patients with CKD

The baseline characteristics of the 6986 patients with CKD were summarized in Table S2 and Table S3, which were based on the four subgroup levels of SII and SIRI. Individuals with elevated SII levels exhibited a higher likelihood of being older, female, non-Hispanic white, widowed, having lower serum iron and serum sodium concentrations, smoking, cancer, CVD, lower eGFR, and a higher UACR. Individuals with elevated SIRI levels exhibited a higher likelihood of being elderly, male, non-Hispanic white, widowed, possessing health insurance, having serum iron and serum sodium concentrations, and displaying elevated eGFR.

3.5 Association of SII, SIRI, and Mortality in Patients with CKD

The Kaplan-Meier survival curves for all-cause, CVD, and hypertension mortality in patients with CKD based on the 4 groupings of SII and SIRI were shown in Fig. 2. The curves all showed that participants in the Q4 group had a worse prognosis during the follow-up period (P-values for log-rank test < 0.05). Overall, these findings suggested that higher levels of SII and SIRI tended to have worse prognosis.

Cox regression models with stepwise adjustment for covariates were used to explore the effects of SII and SIRI levels in all cause mortality, cardiovascular mortality, hypertension mortality, respectively (Table 3). After adjusting for all confounders, high levels of SII significantly increased all cause mortality, cardiovascular mortality, hypertension mortality in patients with CKD [HR_Quartile4 (95% CI): 1.277(1.145–1.426); 1.467(1.197–1.798); 1.715(1.320–2.228), respectively] (P trend < 0.001). Similarly, high levels of SIRI significantly increased mortality in patients with CKD [HR_Quartile4(95% CI): 1.679(1.480–1.906); 2.159(1.706–2.732); 2.411(1.802–3.227), respectively] (P trend < 0.001).

3.6 Subgroup analyses and interaction tests

The results of stratified and interaction analyses were shown in Table 4. The results of the interaction test showed that elevated SII level was more significant for increasing the risk of all-cause mortality among those aged < 60 years, obese (BMI > 30), smoked, and those without hypertension. For CVD mortality, the effect of elevated SII levels was more pronounced among those aged < 60 years, men, obese (BMI > 30), smokers, diabetes, and those without CVD. For hypertension mortality, elevated SII level was more significant for increasing the risk of death in men, smokers, diabetes, and those without CVD. For all-cause mortality, elevated SIRI levels being more significant in increasing the risk of death in obese individuals, and those with CVD. For CVD and hypertension mortality, the effect of elevated SII levels was more significant among smokers and those with cardiovascular diseases(P for interaction < 0.05).(Figure S2)

3.7 Sensitivity analysis

Smooth curves were shown in Figure S3&S4. The results showed that SII and SIRI levels positively correlated with CKD incidence. Within a specific range, higher SII and SIRI levels tended to have higher all-cause mortality, CVD mortality, and hypertension mortality. Sensitivity analyses demonstrated the robustness of the findings, i.e., significant positive associations between SII and SIRI and the incidence of CKD in the general population, and all cause mortality, cardiovascular mortality, and hypertension mortality in patients with CKD (Table 2&3).

The present study provided comprehensive epidemiologic insights into the relationship between new metrics for assessing an individual's systemic inflammatory activity on the impact of CKD progression and prognostic outcomes. Our findings suggested that elevated levels of SII and SIRI were significantly associated with CKD morbidity in the general population, as well as mortality in patients with CKD.

As indicators for assessing an individual's systemic inflammatory activity, the higher the values of SII and SIRI, the more active the body's immune system and inflammatory state [9]. A study showed that high levels of SII increased all-cause and cardiovascular mortality in patients with CKD, with more than half of the deaths in patients attributed to cardiovascular diseases[17]. The authors suggest that a possible explanation is that inflammation accelerates the progression of atherosclerosis in patients with CKD, leading to coronary artery damage, which exacerbates myocardial ischemia and strikes a blow to patients' cardiac function, ultimately leading to death.

Despite the lack of systematic studies on the association of SII and SIRI with CKD, several previous studies have demonstrated that inflammation and inflammatory responses can contribute to the progression of CKD by altering or interfering with intrarenal microcirculatory regulation and perfusion distribution, causing renal damage[18–20]. Inflammatory cells such as monocytes, neutrophils, lymphocytes, and inflammatory cytokines such as interleukin-1 (IL-1) and tumor necrosis factor-a (TNF-a) are involved in the progression of CKD by a variety of mechanisms, including an increase in pro-inflammatory cytokines, activation of oxidative stress, chronic and recurrent infections, altered adipose tissue metabolism, and dysregulation of the gut microbiota and many other mechanisms[21]. Previous studies have shown that monocytes play an essential role in the progression of CKD and that NLRP3 inflammasomes associated with renal disease when stimulated by substances such as reactive oxygen species (ROS), promote the release of IL-1 from monocytes, which in turn activates the classical pro-inflammatory signaling pathways of the intrinsic immune system, NF-kB (nuclear factor-kB) and AP-1 (activator protein-1), destroying renal units and leading to intrarenal microcirculatory dysregulation[18, 22]. In addition, neutrophils contribute to the progression of CKD through migration, production of ROS, secretion of neutrophil serine proteases (NSPs), and release of neutrophil extracellular traps (NETs)[22, 23]. Patients with CKD also experience premature aging of their T lymphocytes, which express high levels of pro-inflammatory cytokines that interact with the chronic inflammatory milieu of the patients with CKD, exacerbating the progression of the CKD and increasing the patient's susceptibility to atherosclerosis and ischemic organ damage[24–26]. In addition, the decrease in lymphocyte count also reflects patients' impaired immune resistance, making them more prone to infections and deterioration of renal function^[21]. It has been demonstrated in animal studies that T lymphocytes infiltrating the kidneys increase free radicals to participate in the development of CKD and hypertension[27]. This finding is supported by observational studies showing that higher monocytes, neutrophils, and low lymphocytes are associated with a higher risk of CKD[28]. Meanwhile, platelets are involved in thrombus formation at the site of vascular injury, and changes in the PLT index reflect the severity of endothelial injury in renal vessels to some extent[29].

All cause mortality and CVD mortality in patients younger than 60 years were more susceptible to SII levels. It may result from more pronounced accelerated atherosclerosis triggered by chronic inflammation-induced vascular injury in younger individuals[26, 30]. In gender stratification, male patients were shown to have a higher risk of cardiovascular mortality and hypertension mortality. The protective, anti-inflammatory effects of estrogen on podocytes, as well as estrogen's ability to protect the renal endothelial barrier, may account for the gender differences[31, 32]. Notably, these differences were not found in the SIRI analysis. In addition, we found that high BMI increased all cause mortality and cardiovascular mortality in patients. This may be because abdominal fat deposition that may accompany obesity increases the level of inflammation and brings higher mortality in patients with CKD[33]. Our results showed that smoking interacted with SII and SIRI and increased risk of death. It may be because smoking-induced endothelial dysfunction may modulate immune and inflammatory cell responses, resulting in elevated levels of inflammation[34]. In addition, smoking negatively affects many processes closely related to the development of renal fibrosis [35].

In addition, we observed that SII and SIRI levels were associated with mortality in patients with different underlying diseases, including diabetes, hypertension, and CVD. The results of our analysis are consistent with previous studies: diabetes is a significant risk factor for cardiovascular death and death from hypertension[36, 37]. Previous studies have described several potential pathways of glycemic status that lead to effects on vascular outcomes associated with oxidative stress, late glycosylation processes, and epigenetic mechanisms, which in turn affect mortality in patients with CKD[38, 39]. In our analysis, the non-hypertensive population was more sensitive than patients with hypertension in the effect of SII on mortality, possibly because hypertension is usually accompanied by additional inflammation, and biomarkers of inflammation are elevated in patients with hypertension[40]. Thus, the altered mortality is more pronounced under a marginal inflammatory burden. The results of our subgroup analysis showed that cardiovascular diseases increased the risk of mortality in patients with CKD. As stated previously, most patients with CKD have cardiovascular disease. They are more likely to die from cardiovascular disease than from end-stage renal disease, which may be associated with impaired vascular reactivity, endothelial dysfunction, and increased arterial stiffness in patients with CKD[41]. However, the increase in SII was more significant for increasing the risk of death in patients without cardiovascular diseases. This may be due to the fact that SII is an index associated with platelet count, and platelet elevation leads to thrombosis and vascular endothelial changes. This effect is more pronounced in people who themselves have intact endothelial function^[42].

Our study has several strengths. First, this study is based on the large sample size and appropriate covariates adjustment, enhancing the reliability and representativeness of our findings. In addition, we performed sensitivity analyses to assess the robustness of our results. To the best of our knowledge, this is the first study to systematically report the association between these inflammatory indices and the incidence and prognosis of CKD.

We also note some limitations of this study. First, the blood cell-based test was performed once, and the concentrations of these blood cells may change during the follow-up period, not fully reflecting the long-term inflammatory index levels in the population. In addition, single measurements of blood cell counts may be affected by other factors, which may lead to residual confounding and require attention when interpreting results.

Data availability

The original data used in this study are nationally representative and publicly available, and can be directly obtained through application to NHANES, which is an ongoing periodic survey of a nationally representative sample of the U.S. noninstitutionalized civilian population using a complex multistage whole-population probability sampling strategy. More details about the survey can be found on the publicly available NHANES website.

Ethics Statement

The survey protocol for the NHANES was approved by CDC's National Center for Health Statistics Institutional Research Ethics Review Board.

Acknowledgments

We gratefully acknowledge that this study utilized data from NHANES, which is a vital biomedical database.

Author Contributions

All authors contributed to the study conception and design.

Peixian Huang: Conceptualization; Methodology; Formal analysis; Writing - Original Draft

Yanpei Mai: Methodology; Formal analysis; Writing - Original Draft; Writing - review & editing

Jun Zhao: Formal analysis; Writing - Original Draft

Yushan Yi: Formal analysis; Writing - Original Draft

Yaqing Wen: Data Curation; Writing - Original Draft

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Tables 1 to 4 are available in the Supplementary Files section.

No competing interests reported.

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You are reading this latest preprint version

Association of Systemic Immune-inflammation Index and Systemic Inflammation Response Index with Chronic Kidney Disease: Observational Study of 40,937 Adults

Status:

Journal Publication

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Abstract

Background

Methods

Results

Conclusion

Figures

1. Introduction

2. Materials and Methods

2.1 Study design and study population

2.2 Definition of CKD

2.3 Exposure Variables

2.4 Outcome ascertainment

2.5 Covariates

2.6 Statistical analyses

3. Results

3.1 Participant Baseline Characteristics

3.2 Association of SII, SIRI, and CKD prevalence risk

3.3 Subgroup analyses and interaction tests

3.4 Baseline characteristics of patients with CKD

3.5 Association of SII, SIRI, and Mortality in Patients with CKD

3.6 Subgroup analyses and interaction tests

3.7 Sensitivity analysis

4. Discussion

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1