Elevated systemic immune inflammation level increases the risk of total and cause-specific mortality among patients with chronic kidney disease: a large multi-center longitudinal study

Cardiovascular health metrics and diabetic nephropathy: a nationally representative cross-sectional study

BACKGROUND

The pathogenesis of diabetic nephropathy is well-documented to be multifactorial. However, research available on the association between cardiovascular health and diabetic nephropathy is limited. Thus, this study aimed to investigate these potential associations and provide guidance for disease prevention.

METHODS

We applied Life's Essential 8 (LE8) identified by the American Heart Association, which integrates multiple health behaviors and health factors to measure cardiovascular health. This study covered 4207 adults with diabetes from the National Health and Nutrition Examination Survey spanning 2007-2018. Weighted regression models assessed the estimated effect of LE8 score on the prevalence of diabetic nephropathy as well as their corresponding clinical indicators. Weighted restricted cubic spline models discussed the possible nonlinear dose-response relationships further. Subgroup analyses clarified the effects of other covariates on correlations.

RESULTS

After adjusting for all covariates, participants with moderate or high cardiovascular health showed a decreased prevalence of diabetic nephropathy (odds ratio [OR]:0.52; 95% confidence interval [CI]:0.42-0.63), and also a decrease in the urinary albumin-to-creatinine ratio [UACR] (β: - 0.83; 95% CI:- 1.00 to - 0.65). The prevalence of diabetic nephropathy and the level of UACR tended to decrease linearly as the total LE8 score increased (P for nonlinear > 0.05). Subgroup analyses showed that the effects of increased overall LE8 score and the specific cardiovascular health construct varied across age and obesity strata.

CONCLUSION

Elevated overall LE8 score was significantly associated with a lower prevalence of diabetic nephropathy in U.S. adults, and the effects of the specific cardiovascular health construct on diabetic nephropathy and their corresponding clinical indicators varied. In all, maintaining good cardiovascular health by refining LE8 metrics may help reduce the adverse effects.

Blood cell indices and inflammation-related markers with kidney cancer risk: a large-population prospective analysis in UK Biobank

Background

Kidney cancer is a prevalent malignancy with an increasing incidence worldwide. Blood cell indices and inflammation-related markers have shown huge potential as biomarkers for predicting cancer incidences, but that is not clear in kidney cancer. Our study aims to investigate the correlations of blood cell indices and inflammation-related markers with kidney cancer risk.

Methods

We performed a population-based cohort prospective analysis using data from the UK Biobank. A total of 466,994 participants, free of kidney cancer at baseline, were included in the analysis. The hazard ratios (HRs) and 95% confidence intervals (CIs) for kidney cancer risk were calculated using Cox proportional hazards regression models. Restricted cubic spline models were used to investigate nonlinear longitudinal associations. Stratified analyses were used to identify high-risk populations. The results were validated through sensitivity analyses.

Results

During a mean follow-up of 12.4 years, 1,710 of 466,994 participants developed kidney cancer. The Cox regression models showed that 13 blood cell indices and four inflammation-related markers were associated with kidney cancer incidence. The restricted cubic spline models showed non-linear relationships with kidney cancer. Finally, combined with stratified and sensitivity analyses, we found that the mean corpuscular hemoglobin concentration (MCHC), red blood cell distribution width (RDW), platelet distribution width (PDW), systemic immune-inflammation index (SII), and product of platelet count and neutrophil count (PPN) were related to enhanced kidney cancer risk with stable results.

Conclusion

Our findings identified that three blood cell indices (MCHC, RDW, and PDW) and two inflammation-related markers (SII and PPN) were independent risk factors for the incidence of kidney cancer. These indexes may serve as potential predictors for kidney cancer and aid in the development of targeted screening strategies for at-risk individuals.

Association of systemic immune-inflammation-index with all-cause and cause-specific mortality among type 2 diabetes: a cohort study base on population

PURPOSE

There have been limited studies examining the prospective association between the Systemic Immune-Inflammation Index (SII), a novel inflammatory marker, and mortality among individuals with diabetes in the United States.

METHODS

We utilized data from the National Health and Nutrition Examination Survey (NHANES), a representative sample of US adults, linked with information from the National Death Index.

RESULTS

Our study included 8697 individuals from NHANES spanning the years 1999 to 2018. SII was calculated by dividing the platelet count by the neutrophil count and then dividing that result by the lymphocyte count. We employed multivariable Cox proportional hazards regression analysis to investigate the associations between SII levels and all-cause as well as cause-specific mortality, while adjusting for potential confounding factors. SII levels were categorized into quartiles based on the study population distribution. Over a median follow-up period of 94.8 months (with a maximum of 249 months), we observed a total of 2465 all-cause deaths, 853 deaths from cardiovascular causes, 424 deaths from cancer, and 88 deaths related to chronic kidney disease. After adjusting for multiple variables, higher SII levels were significantly and non-linearly associated with an increased risk of all-cause mortality in Quartile 4 (HR 1.74, 95% CI 1.15-2.63, P for trend = 0.043) when Quartile 1 was used as the reference group. Additionally, we identified a linear association between SII and cardiovascular mortality, with a 70% higher risk of cardiovascular mortality in Quartile 4 (HR 1.70, 95% CI 1.18-3.30, P for trend = 0.041) compared to Quartile 1.

CONCLUSION

Our findings indicate that SII is significantly associated with an elevated risk of all-cause and cardiovascular mortality in US adults with diabetes.

Systemic immune-inflammatory indicators and bone mineral density in chronic kidney disease patients: A cross-sectional research from NHANES 2011 to 2018

BACKGROUND

The purpose of this study was to look at the relationship between the Systemic Immune Inflammatory Index (SII) and bone mineral density (BMD) in the pelvis, left upper and lower limbs, lumbar spine, thoracic spine, and trunk in a chronic kidney disease (CKD) population in the United States.

METHODS

The National Health and Nutrition Examination Survey (2011-2016) yielded 2302 people with CKD aged >18 years. CKD was defined as eGFR less than 90 ml/min/1.73 m2 or eGFR greater than 90 ml/min/1.73 m2 with urine ACR greater than 30 mg/L.SII was calculated as PC * (NC / LC) from platelet count (PC), neutrophil count (NC), and lymphocyte count (LC). Multiple logistic regression was used to examine the relationship between BMD and SII at different sites in CKD patients, smoothed curve-fitting and generalized weighting models were used to investigate non-linear relationships, and a two-tailed linear regression model was used to find potential inflection points in the model.

RESULTS

We discovered a negative correlation between SII and pelvic BMD among 2302 participants after controlling for gender, age, and race [β = -0.008; 95% confidence value -0.008; 95% confidence interval (CI) -0.014, -0.002]. Lower PEBMD was related to increasing SII (trend p = 0.01125). After additional correction, only pelvic BMD remained adversely linked with SII [value -0.006; 95% CI -0.012, -0.000, p = 0.03368]. Smoothed curve fitting revealed a consistent inverse relationship between SII and pelvic BMD. Further stratified analyses revealed a substantial positive negative connection between SII and pelvic BMD in individuals who did not have hypertension, diabetes, a BMI of more than 30 kg/m2, or stage 2 CKD. The connection between SII and PEBMD in people without diabetes revealed a strong inverted U-shaped curve.

CONCLUSION

In individuals with CKD in the United States, there was a negative connection between the systemic immunoinflammatory index (SII) and pelvic BMD. The SII might be a low-cost and simple test for CKD-related BMD loss.

Association between systemic inflammatory indicators with the survival of chronic kidney disease: a prospective study based on NHANES

Background

systemic inflammation disorders were observed in chronic kidney disease (CKD). Whether the systemic inflammatory indicators could be optimal predictors for the survival of CKD remains less studied.

Methods

In this study, participants were selected from the datasets of the National Health and Nutrition Examination Survey (NHANES) between 1999 to 2018 years. Four systemic inflammatory indicators were evaluated by the peripheral blood tests including systemic immune-inflammation index (SII, platelet*neutrophil/lymphocyte), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR). Kaplan-Meier curves, restricted cubic spline (RCS), and Cox regression analysis were used to evaluate the association between the inflammatory index with the all-cause mortality of CKD. Receiver operating characteristic (ROC) and concordance index (C-index) were used to determine the predictive accuracy of varied systemic inflammatory indicators. Sensitive analyses were conducted to validate the robustness of the main findings.

Results

A total of 6,880 participants were included in this study. The mean age was 67.03 years old. Among the study population, the mean levels of systemic inflammatory indicators were 588.35 in SII, 2.45 in NLR, 133.85 in PLR, and 3.76 in LMR, respectively. The systemic inflammatory indicators of SII, NLR, and PLR were all significantly positively associated with the all-cause mortality of CKD patients, whereas the high value of LMR played a protectable role in CKD patients. NLR and LMR were the leading predictors in the survival of CKD patients [Hazard ratio (HR) =1.21, 95% confidence interval (CI): 1.07-1.36, p = 0.003 (3rd quartile), HR = 1.52, 95%CI: 1.35-1.72, p<0.001 (4th quartile) in NLR, and HR = 0.83, 95%CI: 0.75-0.92, p<0.001 (2nd quartile), HR = 0.73, 95%CI: 0.65-0.82, p<0.001 (3rd quartile), and = 0.74, 95%CI: 0.65-0.83, p<0.001 (4th quartile) in LMR], with a C-index of 0.612 and 0.624, respectively. The RCS curves showed non-linearity between systemic inflammatory indicators and all-cause mortality risk of the CKD population.

Conclusion

Our study highlights that systemic inflammatory indicators are important for predicting the survival of the U.S. population with CKD. The systemic inflammatory indicators would add additional clinical value to the health care of the CKD population.

Novel biomarkers related to oxidative stress and immunity in chronic kidney disease

Introduction

The incidence of chronic kidney disease (CKD) has been increasing in recent years, gradually becoming a global health crisis. Due to limited treatment options, novel molecular pathways are urgently required to advance the treatment and diagnosis of CKD.

Materials and methods

The characteristics of differentially expressed genes (DEGs) in CKD patients were analyzed using Gene Expression Omnibus (GEO) database, and genes related to oxidative stress were retrieved from the Genecard database. Subsequently, a comprehensive approach was applied, including immune infiltration analysis, weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis, to identify hub genes among differentially expressed immune-related oxidative stress genes (DEIOSGs). Validation of hub genes was performed using an external data set, and diagnostic potential capability was evaluated through receiver operating curve (ROC) analysis. In animal experiments, the expression of hub genes in CKD was confirmed by inducing a CKD model through a 5/6 nephrectomy procedure. Finally, the relationship between these hub genes and clinical characteristics were assessed using the Nephroseq v5 database.

Results

29 DEIOSGs were identified by comprehensive bioinformatics analysis. PPI analysis screened the hub genes NCF2, S100A9, and SELL. ROC analysis demonstrated excellent diagnostic efficacy. Further validation from other databases and animal experiments confirmed a substantial upregulation in the expression of hub genes in CKD. Additionally, clinical correlation analysis established a clear link between hub gene expression and renal function deterioration.

Conclusions

Our study confirms NCF2, S100A9, and SELL as diagnostic biomarkers associated with immune response and oxidative stress in CKD, suggesting their potential as novel targets for CKD diagnosis and treatment.

Association of systemic immune-inflammation index and systemic inflammation response index with chronic kidney disease: observational study of 40,937 adults

BACKGROUND

Chronic kidney disease (CKD) is linked to immunity and inflammation. Systemic immune-inflammation index (SII) and systemic inflammation response index (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 from the National Health and Nutrition Examination Survey (NHANES) 1999-2018. SII and SIRI were log2-transformed before conducting regression analysis, considering that these inflammatory markers were right skewed distributed. Weighted logistic regression models assessed the association of log2-SII and log2-SIRI levels with CKD prevalence. Weighted Cox regression models were utilized to estimate the risk of death. Subgroup analyses were performed to further clarify the effects of other covariates on the associations. Sensitivity analyses were performed to assess the robustness of our results.

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, the highest level of log2-SII increased the CKD incidence (odds ratio [OR]: 1.47, 95% confidence intervals [CI]: 1.32-1.65, P < 0.001), as well as log2-SIRI (OR: 1.79, 95% CI 1.60-2.01, P < 0.001) when compared with the lowest level reference group. The highest level of log2-SII significantly increased all-cause mortality (hazard risk [HR]: 1.29; 95% CI 1.13-1.48, P < 0.001), cardiovascular mortality (HR: 1.61, 95% CI 1.25-2.09, P < 0.001), and hypertension mortality (HR: 1.73, 95% CI 1.23-2.42, P = 0.001) in CKD patients. Additionally, the positive associations were also found between log2-SIRI and all cause (HR: 1.54, 95% CI 1.35-1.76, P < 0.001), cardiovascular (HR: 1.90, 95% CI 1.38-2.60, P < 0.001), and hypertension mortality (HR: 2.15, 95% CI 1.56-2.94, P < 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, as well as mortality in patients with CKD in the U.S.

POPULATION

Association between systemic inflammation response index and chronic kidney disease: a population-based study

Introduction

Our objective was to explore the potential link between systemic inflammation response index (SIRI) and chronic kidney disease (CKD).

Methods

The data used in this study came from the National Health and Nutrition Examination Survey (NHANES), which gathers data between 1999 and 2020. CKD was diagnosed based on the low estimated glomerular filtration rate (eGFR) of less than 60 mL/min/1.73 m2 or albuminuria (urinary albumin-to-creatinine ratio (ACR) of more than 30 mg/g). Using generalized additive models and weighted multivariable logistic regression, the independent relationships between SIRI and other inflammatory biomarkers (systemic immune-inflammation index (SII), monocyte/high-density lipoprotein ratio (MHR), neutrophil/high-density lipoprotein ratio (NHR), platelet/high-density lipoprotein ratio (PHR), and lymphocyte/high-density lipoprotein ratio (LHR)) with CKD, albuminuria, and low-eGFR were examined.

Results

Among the recruited 41,089 participants, males accounted for 49.77% of the total. Low-eGFR, albuminuria, and CKD were prevalent in 8.30%, 12.16%, and 17.68% of people, respectively. SIRI and CKD were shown to be positively correlated in the study (OR = 1.24; 95% CI: 1.19, 1.30). Furthermore, a nonlinear correlation was discovered between SIRI and CKD. SIRI and CKD are both positively correlated on the two sides of the breakpoint (SIRI = 2.04). Moreover, increased SIRI levels were associated with greater prevalences of low-eGFR and albuminuria (albuminuria: OR = 1.27; 95% CI: 1.21, 1.32; low-eGFR: OR = 1.11; 95% CI: 1.05, 1.18). ROC analysis demonstrated that, compared to other inflammatory indices (SII, NHR, LHR, MHR, and PHR), SIRI exhibited superior discriminative ability and accuracy in predicting CKD, albuminuria, and low-eGFR.

Discussion

When predicting CKD, albuminuria, and low-eGFR, SIRI may show up as a superior inflammatory biomarker when compared to other inflammatory biomarkers (SII, NHR, LHR, MHR, and PHR). American adults with elevated levels of SIRI, SII, NHR, MHR, and PHR should be attentive to the potential risks to their kidney health.

Systemic immune-inflammation Index is associated with chronic kidney disease in the U.S. population: insights from NHANES 2007-2018

Objectives

The systemic immune-inflammation index (SII), a novel and systematic inflammatory biomarker that is associated with chronic kidney disease (CKD), has not received much attention. This study aimed to investigate the relationship between SII and CKD in the United States (U.S.) population.

Methods

Our study ultimately included a nationally representative sample of 10,787 adults who participated in the 2007-2018 National Health and Nutrition Examination Survey. Weighted multivariate logistic regression was used to assess the correlation between SII and CKD, and a restricted cubic spline (RCS) model was subsequently used to explore the non-linear relationship between SII and CKD. Subgroup analyses were performed to further the effects of other covariates on the relationship between SII and CKD.

Results

Following confounder adjustment, a higher SII was related to the incidence of CKD (OR =1.36; 95% CI, 1.07-1.73; p =0.01), as validated by multivariable logistic regression. The RCS curve revealed a non-linear positive correlation between SII/1000 and CKD incidence (p for non-linear =0.0206). Additionally, subgroup analysis confirmed a stronger correlation for male participants (OR =2.628; 95% CI, 1.829-3.776) than for female participants (OR =1.733; 95% CI, 1.379-2.178) (p for interaction =0.046).

Conclusions

SII is positively associated with the incidence of CKD among U.S. adults, especially in males. However, further studies are needed to confirm our findings and explore the causal factors that can contribute to the prevention and treatment of CKD.

Association between systemic immune-inflammation index and chronic kidney disease: A population-based study

BACKGROUND

Systemic immune-inflammation index (SII) is a new indicator of inflammation, and chronic kidney disease (CKD) has a connection to inflammation. However, the relationship between SII and CKD is still unsure. The aim of this study was whether there is an association between SII and CKD in the adult US population.

METHODS

Data were from the National Health and Nutrition Examination Survey (NHANES) in 2003-2018, and multivariate logistic regression was used to explore the independent linear association between SII and CKD. Smoothing curves and threshold effect analyses were utilized to describe the nonlinear association between SII and CKD.

RESULTS

The analysis comprised 40,660 adults in total. After adjusting for a number of factors, we found a positive association between SII and CKD [1.06 (1.04, 1.07)]. In subgroup analysis and interaction tests, this positive correlation showed differences in the age, hypertension, and diabetes strata (p for interaction<0.05), but remained constant in the sex, BMI, abdominal obesity, smoking, and alcohol consumption strata. Smoothing curve fitting revealed a non-linear positive correlation between SII and CKD. Threshold analysis revealed a saturation effect of SII at the inflection point of 2100 (1,000 cells/μl). When SII < 2100 (1,000 cells/μl), SII was an independent risk element for CKD.

CONCLUSIONS

In the adult US population, our study found a positive association between SII and CKD (inflection point: 2100). The SII can be considered a positive indicator to identify CKD promptly and guide therapy.

Association between systemic immune-inflammatory index and diabetes mellitus: mediation analysis involving obesity indicators in the NHANES

Background

Inflammation and obesity have been widely recognized to play a key role in Diabetes mellitus (DM), and there exists a complex interplay between them. We aimed to clarify the relationship between inflammation and DM, as well as the mediating role of obesity in the relationship.

Methods

Based on the National Health and Nutrition Examination Survey (NHANES) 2005-2018. Univariate analyses of continuous and categorical variables were performed using t-test, linear regression, and χ2 test, respectively. Logistic regression was used to analyze the relationship between Systemic Immune-Inflammatory Index (SII) or natural logarithm (Ln)-SII and DM in three different models. Mediation analysis was used to determine whether four obesity indicators, including body mass index (BMI), waist circumference (WC), visceral adiposity index (VAI) and lipid accumulation product index (LAP), mediated the relationship between SII and DM.

Results

A total of 9,301 participants were included, and the levels of SII and obesity indicators (BMI, WC, LAP, and VAI) were higher in individuals with DM (p < 0.001). In all three models, SII and Ln-SII demonstrated a positive correlation with the risk of DM and a significant dose-response relationship was found (p-trend <0.05). Furthermore, BMI and WC were associated with SII and the risk of DM in all three models (p < 0.001). Mediation analysis showed that BMI and WC mediated the relationship between SII with DM, as well as Ln-SII and DM, with respective mediation proportions of 9.34% and 12.14% for SII and 10.23% and 13.67% for Ln-SII (p < 0.001).

Conclusion

Our findings suggest that increased SII levels were associated with a higher risk of DM, and BMI and WC played a critical mediating role in the relationship between SII and DM.

Systemic Immune Inflammation Index as a Key Predictor of Dialysis in Pediatric Chronic Kidney Disease with the Use of Random Forest Classifier

BACKGROUND

Low-grade inflammation is a significant component of chronic kidney disease (CKD). Systemic immune inflammation index (SII), a newly defined ratio combining neutrophil, lymphocyte, and platelet counts, has not yet been evaluated in the pediatric CKD population nor in the context of CKD progression or dialysis. Thus, this study aimed to analyze the complete blood cell count (CBC)-driven parameters, including SII, in children with CKD and to assess their potential usefulness in the prediction of the need for chronic dialysis.

METHODS

A single-center, retrospective study was conducted on 27 predialysis children with CKD stages 4-5 and 39 children on chronic dialysis. The data were analyzed with the artificial intelligence tools.

RESULTS

The Random Forest Classifier (RFC) model with the input variables of neutrophil count, mean platelet volume (MPV), and SII turned out to be the best predictor of the progression of pediatric CKD into end-stage kidney disease (ESKD) requiring dialysis. Out of these variables, SII showed the largest share in the prediction of the need for renal replacement therapy.

CONCLUSIONS

Chronic inflammation plays a pivotal role in the progression of CKD into ESKD. Among CBC-driven ratios, SII seems to be the most useful predictor of the need for chronic dialysis in CKD children.

Association Between Systemic Immune Inflammation Level and Poor Prognosis Across Different Glucose Metabolism Status in Coronary Artery Disease Patients

Background

Blood glucose levels significantly affect the clinical prognosis of patients with coronary artery disease (CAD), and systemic immune inflammation is a common risk factor for both CAD and diabetes. However, the relationship between immune inflammation levels and poor prognosis in patients with CAD with different glucose metabolic statuses remains unclear.

Methods

Between January 2007 and December 2020, we recruited 84,645 patients with CAD. The systemic immune inflammation index (SII) was used to comprehensively reflect the immune and inflammatory levels of patients and was calculated using the following formula: neutrophils × platelets/lymphocytes. The patients were classified into nine groups according to their glucose metabolism status (diabetes mellitus [DM], pre-diabetes mellitus [pre-DM], and normal glucose regulation [NGR]). Cox regression models and competing risk Fine and Gray models were used to investigate the association between SII and clinical outcomes.

Results

During the follow-up period, 12,578 patients died, including 5857 cardiovascular-related and 1251 cancer-related deaths. The risk of all-cause and cause-specific mortality increased with increasing SII tertiles in CAD patients with NGR, pre-DM, and DM. When considering glucose metabolism status, the multivariate cox regression revealed that CAD patients with DM and SII-H levels had the highest risk of all-cause mortality (1.69 [1.56-1.83]), cardiovascular mortality (2.29 [2.02-2.59]), and cancer mortality (1.29 [1.01-1.66]). Moreover, incorporating the SII into traditional risk factor models significantly improved the C-index for predicting all-cause and cardiovascular mortality.

Conclusion

Systemic immune inflammation levels on admission were correlated with a higher risk of all-cause and cause-specific mortality in patients with CAD, particularly in those with DM.

Systemic Immune-Inflammation Index Was Significantly Associated with All-Cause and Cardiovascular-Specific Mortalities in Patients Receiving Peritoneal Dialysis

Purpose

The prognosis of patients receiving peritoneal dialysis (PD) is associated with inflammation. Systemic immune-inflammation index (SII) is one of inflammatory markers, and the role in predicting clinical outcomes in PD patients is unclear. We aimed to investigate the relationship between the SII and all-cause and cardiovascular-specific mortalities in patients undergoing PD.

Patients and Methods

A total of 1419 PD patients from the First Affiliated Hospital of Sun Yat-sen University between January 1, 2007 and December 31, 2019 were retrospectively included at baseline, and the patients were followed up until November 31, 2021. SII was calculated as platelet count×neutrophil count/lymphocyte count. Kaplan-Meier curves and Cox proportional hazards regression models were used to determine the relationship between SII levels and all-cause and cardiovascular-specific mortalities.

Results

During follow-up (median period was 42 months), 321 patients died (171 died of cardiovascular disease). With adjustment for the potential confounding factors, each 1-SD increase in the SII was associated with 20.2% increase in all-cause mortality (hazard ratio [HR]: 1.202, 95% confidence interval [CI]: 1.088-1.327, P<0.001) and 28.0% increase in cardiovascular-specific mortality (HR: 1.280, 95% CI: 1.126-1.456, P<0.001). High SII (vs low SII) was significantly associated with increased risks of all-cause mortality (HR: 1.391, 95% CI: 1.066-1.815, P-value: 0.015) and cardiovascular-specific mortality (HR: 1.637, 95% CI: 1.185-2.261, P-value: 0.003). Subgroups analyses showed similar results for those younger than 65-year-old only.

Conclusion

Elevated SII level was independently associated with increased risks of all-cause and cardiovascular-specific mortalities in PD patients, especially for those younger than 65-year-old.

Evaluating the baseline hemoglobin, albumin, lymphocyte, and platelet (HALP) score in the United States adult population and comorbidities: an analysis of the NHANES

Introduction

As a composite immunonutritional biomarker, the Hemoglobin, Albumin, Lymphocyte, Platelet (HALP) score has shown promise in assessing a patient's overall health status by integrating several routinely collected laboratory indicators. This biomarker has been examined in many different populations of patients and disease states (i.e., cancer), but an integrated, universal rubric using standardized thresholds has not thus far been developed. Pre-existing large population-based databases represent an ideal source to examine the distribution of HALP and the influence of diverse health statuses on this score.

Methods

We conducted a cross-sectional study using data from the National Health and Nutrition Examination Survey (NHANES) between 2017-2020, evaluating 8,245 participants across numerous demographic, socioeconomic, and health-related variables. Univariate and multivariate linear regression analyses assessed the associations between HALP scores and these factors.

Results

Our findings revealed significant associations between HALP scores and various demographic, socioeconomic, and health conditions. The median HALP score among the representative population was 49.0, with varying median scores across different groups and normal reference ranges for males and females. Multivariate regression analysis showed that anemia treatment, age over 65 years, weak/failing kidneys, and cancer were independent risk factors associated with lower HALP scores. Male participants demonstrated higher HALP scores than female participants, and age was inversely related to HALP. Moreover, HALP scores were negatively associated with the number of comorbidities.

Conclusion/discussion

This study set out to explore the HALP score from a population-based perspective, uncovering notable associations that offer vital insights into the score's clinical relevance and future applications. By determining a median HALP score of 49.0 and normal reference ranges within our diverse, representative sample, we establish a robust foundation for researchers to refine optimal HALP applications and thresholds. Considering the growing focus on personalized medicine, HALP holds promise as a prognostic tool, enabling clinicians to comprehend their patients' immunonutritional status better and deliver customized care.