The impact of Naples prognostic score on cognitive impairment in hemodialysis patients-A multicenter study

The impact of Naples prognostic score on cognitive impairment in hemodialysis patients-A multicenter study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The impact of Naples prognostic score on cognitive impairment in hemodialysis patients-A multicenter study Yan Ran, Yuqi Yang, Yanzhe Peng, Jingjing Da, Zuping Qian, Jing Yuan, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4773830/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract background Nutrition and inflammatory status is prevalent in hemodialysis(HD) patients, which is relates to the incident of cognitive impairment(CI). Naples prognostic score(NPS) is a comprehensive measure of patients’ inflammation and nutritional status. This study is to investigate the effect of Naples prognostic score on the risk of incident cognitive impairment in HD patients. Methods Two thousand seven hundred twenty-five HD patients were recruited and NPS score obtained based on albumin, total cholesterol(TC), lymphocytes, neutrophils, and monocytes. Cognitive function was assessed with Mini-Mental State Examination score (MMSE). Multiple Cox regression models, interactive analyses were conducted. Results Among 2725 HD patients (33.8%) experienced incident CI, the mean MMSE score was 26.87 ± 3.9. After adjusting clinical confounders, the association remained statistically significant, higher NPS was independently associated with increased rate of CI both as a continuous variable (OR = 1.106, 95% CI 1.018–1.202, p = 0.019) and as a categorized variable(OR = 1.552, 95%CI: 1.146–2.110, p = 0.015). The analysis illustrates a negative correlation between NPS and MMSE scores. This relationship was observed both as a continuous variable ( β =-0.178, 95% CI -0.321 - -0.035, p = 0.015) and as a categorized variable, compared to those in the NPS 0–1 score group, those with 4 score group was associated with an additional 0.68 faster cognitive decline ( p = 0.008). Further explored the relationship between NPS and the incidence of dementia, finding that NPS had higher risk of dementia with multivariate-adjusted ORs of 1.153 (95% CI 1.035–1.286, p = 0.010). Subgroup analysis showed that the effect of NPS on CI was more pronounced in male, under 65 years, low educational levels, without diabetes and Cerebrovascular disease(CVD). Except male, low education level, and non CVD, in patients who HD frequency under 3 times per week the association between NPS and dementia was more significant. Conclusions NPS was independently associated with cognitive impairment in HD patients. Naples prognostic score(NPS) cognitive impairment(CI) hemodialysis dementia Figures Figure 1 Figure 2 Figure 3 Introduction Studies have show that cognitive impairment(CI) is a common and notable health issue among individuals undergoing hemodialysis (HD), with research suggesting that up to 60–90% of patients with end-stage kidney disease (ESKD) receiving hemodialysis experience cognitive impairment [ 1 ] . Patients undergoing hemodialysis who experience cognitive impairment encounter significant challenges related to their disease, including an increased risk of hospitalization, higher mortality rates, elevated healthcare costs, and a diminished quality of life [ 2 ] . Despite the progress in diagnostic and treatment technologies, a considerable number of individuals with hemodialysis continue to experience cognitive impairment. The causes of CI in hemodialysis patients are multifactorial, including factors related to uremia and the dialysis process, such as uremic toxins, anemia, rapid fluid shifts, and cerebral hypoperfusion. Individuals undergoing hemodialysis often experience systemic inflammation and concurrent protein-energy malnutrition [ 2 ] , which are known to play a significant role in the development of cognitive impairment. The inflammatory and malnutrition status of these patients can lead to complications related to hemodialysis, ultimately resulting in cognitive impairment and increased mortality. Currently, there are no effective pharmacological treatments specifically targeting cognitive impairment in hemodialysis patients. Therefore, identifying modifiable risk factors for cognitive impairment in this population is of great importance. The Naples Prognostic Score (NPS) is a novel scoring system that encompasses various inflammation and nutritional biomarkers, including total cholesterol, lymphocyte to monocyte ratio (LMR), neutrophil to lymphocyte ratio (NLR), and serum albumin. Research has demonstrated that NPS has the ability to predict acute renal failure post-myocardial infarction, malnutrition in hypertensive individuals, and postoperative complications in patients with diverticulitis [ 3 , 4 ] . A study examining kidney transplant patients revealed that those with a creatinine reduction ratio below 30% exhibited a notably elevated incidence of NPS 3–4, decreased LMR levels, and heightened neutrophil and NLR levels [ 5 ] . Additionally, an empirical investigation into resected Cholangiocarcinoma patients demonstrated a direct correlation between preoperative malnutrition and NPS, with NPS serving as an independent prognostic indicator [ 6 ] . Meanwhile, the NPS serves as a valuable tool designed to evaluate the prognostic outcomes of different types of cancers. However, there is a lack of research on the relationship between NPS and cognitive impairment in the general population, particularly in individuals with HD patients who have a high prevalence of cognitive impairment, and there is a dearth of relevant studies on this topic. Understanding the complex interrelationships between NPS and CI is critical because of the high prevalence of these conditions in HD populations. Several previous research has established a correlation between the common conditions of nutrition and inflammation and cognitive decline in the general population. These studies have indicated that individuals with HD, who are likely to experience high levels of inflammation and malnutrition, also have a heightened risk of developing cognitive impairment [ 7 ] . Actually, in HD patients, fluctuations in inflammation and nutritional status may lead to variability in prognostic indicators for cognitive impairment over time. Despite this potential relationship, few research has been conducted on the correlation between changes in common nutritional and inflammatory conditions and cognitive impairment. Considering the notable prevalence of inflammation and malnutrition in hemodialysis patients with cognitive impairment, there is reason to suspect a potential correlation between these two significant complications. Nevertheless, limited research has been conducted on this particular population. Therefore, the objective of this study was to examine the relationships between NPS and severity scores with cognitive impairment in hemodialysis patients. Methods and materials Study design and participants This study was a multicenter, observational cohort study that recruited patients undergoing maintenance hemodialysis at twenty-two dialysis centers in Guizhou Province, China from June 2021 to June 2022. Inclusion criteria encompassed patients with end-stage kidney disease (ESKD) who had received regular bicarbonate-based dialysis treatment (twice or thrice per week)for at least three months or longer and aged ≥ 18 years or older, and had completed biochemical, anthropometric measurements, and questionnaire records. Exclusion criteria included: (1)those with mental illness, severe aphasia, and critical illness who cannot cooperate with the questionnaire survey; (2) extreme weakness leading to a life expectancy of less than half a year; (3)patients with severe liver failure, lung disease, and other related diseases that seriously affect patients’ cognitive function;(4) psychotropic drug or alcohol dependence; (5) serious limb defects and deformities or metal stents in the body that cannot be examined by bioelectrical impedance analysis. The study followed the Declaration of Helsinki and received informed consent approval from the Institutional Review Board of Guizhou Provincial People’s Hospital (Approval Number: (2020)208). All participants provided written informed consent. Assessment of covariates Standard questionnaires were utilized to gather demographic information, such as age, sex, ethnicity, household income, educational level (low:<9th grade; high:≥9th grade), physical activity levels, smoking status (yes or no), alcohol status (yes or no), medical history, and presence of any diseases during interviews. Hypertension was defined as systolic blood pressure (SBP) ≥ 140mmHg and/or diastolic blood pressure (DBP) ≥ 90 mmHg, or self-reported, or a medical record of responding diagnosis or medication (yes or no). Diabetes mellitus was diagnosed as fasting plasma glucose ≥ 126 mg/dL (7 mmol/L) or random blood glucose ≥ 200 mg/dL (11.1mmol/L) or HbA1c ≥ 6.5%, or self-reported, or a medical record of responding diagnosis or medication (yes or no). The following information of HD therapy was also recorded: Prior to hemodialysis, anthropometric measurements including height, waist circumference, weight, systolic blood pressure, diastolic blood pressure, and hip circumference were obtained by two trained nephrologists. Additionally, data on dialysis frequencies (twice/thrice per week), hemodialysis vintages, dialysis modality, dialysis dehydration amount, and complications during dialysis such as hypotension and hypoglycemia were recorded. Biochemical measurements For laboratory variables, all participants provided venous blood samples, after fasting for 8-10h and were collected before the initiation of hemodialysis therapy. We evaluated the following: leukocyte, hemoglobin, platelet, Neutrophils, Lymphocyte, monocyte, parathyroid hormone, albumin, serum uric acid, Urea, total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and other biochemical indicators. Cognitive function evaluation Cognitive function was assessed using the Mini-Mental State Examination (MMSE) questionnaire by the trained personnel of the research group. The total score of the evaluation scale is 30 points (including 10 points for orientation force, 3 points for memory, 5 points for attention and calculation, 3 points for memory, and 9 points for language ability). Participants with an MMSE score of less than 27 were diagnosed as CI and MMSE score of 23 or less were diagnosed as dementia [ 2 , 8 ] . Every patient completed the MMSE scores at baseline and follow-up. Calculation of Naples prognostic score The NPS was calculated based on the serum albumin, TC, NLR, and LMR. According to the previous reports, if the serum albumin ≥ 40 g/L,TC > 180 mg/dL, NLR 4.44 was scored as 0,while serum albumin < 40 g/L, TC ≤ 180 mg/dL, NLR ≥ 2.96, or LMR ≤ 4.44 was scored as 1 [ 4 ] . NPS is the sum of the scores of each of the four factors. The calculation of the NPS involves adding up the scores assigned to the parameters mentioned earlier. Patients were divided into three groups based on the NPS: group 0 (score of 0 or 1); group 1(score of 2 or 3); and group 2(score of 4). Statistical analysis Categorical data were expressed as numbers and percentages. Normally distributed continuous data were represented by mean and standard deviation while with a skewed distribution were described as the medians and interquartile range. There is no unified grouping standard for NPS, we divided patients into 3 groups based on increasing Naples scores (groups 0–2): group 0 with a score of 0 or 1; group 1 with a score of 2 or 3; group 2 with a score of 4. Univariate and multivariate logistic regression analyses were undertaken to investigate the correlation between NPS and the incidence of CI. Additionally, univariate and multivariate linear regression analyses were conducted to examine the relationships between MMSE score and NPS. Utilizing odds ratios (ORs), unstandardized coefficients (β), and confidence intervals (CIs) summarized, respectively. In model 1, there was no adjustment. In model 2, we adjusted for age and sex, BMI, Hypertension, alcohol, diabetes mellitus, smoke, SBP1, DBP1,CVD; In model 3, we adjusted for model 2 and education, HD vintages, Dialysis frequency;In model 4, we adjusted for model 3 and uric acid, creatinine, potassium, phosphorus, high density lipoprotein(HDL).The subgroup analysis was conducted to explore the potential effect modification by sex(female or male), age(< 65 years or ≥ 65 years), education level (low or high),HD frequency(< 3times or ≥ 3 times), smoking history(yes or no), hypertension history (yes or no), diabetes mellitus history(yes or no) ,history of diabetes (yes or no) and CVD(yes or no). All statistical analyses were performed by IBM SPSS Statistics (version 27.0, Chicago, USA) the R open-source software(version 4.3.3.) A two-sided P value < 0.05 was considered statistically different. Results Characteristics of study participants As illustrated in Fig. 1 , a total of 3902 hemodialysis patients were enrolled, and after applying exclusion criteria, the final analytical cohort included 2725 HD patients, the mean age of 54.44 ± 14.8 years, 1668 (61.2%) were male. The median dialysis vintage was 54.0 (33.0, 87.0) months. The average number of NPS components was 2.8 ± 1.0. The mean MMSE score was 26.87 ± 3.9, and the prevalence of CI (MMSE < 27) was 33.8%, the prevalence of dementia (MMSE ≤ 23) was 16.8%. The patients were stratified into two groups based on cognitive status: Normal cognition group (n = 1803, 66.2%) or CI group (n = 922, 33.8%). As shown in Table 1 , the mean age of the overall population was 54.44 ± 14.8 years, 1668 (61.2%) were male. Compared to the patients with normal cognition, those with CI were older, more likely male, lower educational level, lower DBP levels, higher prevalence rates of hypertension, lower uric acid levels, and lower hemoglobin, albumin,urea nitrogen and creatinine levels. Table 1 Baseline characteristics of hemodialysis patients according to cognitive function Varibles All (n = 2725) Normal cognition (n = 1803) Cognitive impairment (n = 922) P Male sex (n,%) 1668(61.2%) 1166(64.7%) 502(54.4%) < 0.001 Age (years) 54.4 ± 14.8 52.1 ± 14.4 59.1 ± 14.5 < 0.001 High education level(n,%) 161(5.9%) 113(6.3%) 48(5.2%) 0.266 Dialysis frequency (< thrice/week) (n,%) 439(16.1%) 298(16.5%) 141(15.3%) 0.407 Dialysis vintage (months) 54.0 [33.0,87.0] 55.0 [35.0,90.0] 52.0 [31.0,84.0] 0.007 Alcohol history (n,%) 195(7.2%) 118(6.5%) 77(8.4%) 0.083 Smoking history(n,%) 1041(38.2%) 675(37.4%) 366(39.7%) 0.251 History of hypertension (n,%) 2228(81.8%) 1434(79.5%) 794(86.1%) < 0.001 Diabetes mellitus (n,%) 933(34.2%) 568(31.5%) 365(39.6%) < 0.001 Heart failure (n,%) 675(24.8%) 440(24.4%) 235(25.5%) 0.535 CVD (n,%) 238(8.7%) 145(8.0%) 93(10.1%) 0.074 Pre-dialysis SBP(mmHg) 136.6 ± 18.4 136.7 ± 18.5 136.3 ± 18.4 0.646 Pre-dialysis DBP(mmHg) 78.2 ± 14.0 78.8 ± 13.8 76.9 ± 14.3 0.001 BMI (kg/m 2 ) 22.9 ± 3.6 22.9 ± 3.6 23.0 ± 3.6 0.624 Leukocyte (x10 9 /L) 6.4 ± 2.1 6.5 ± 2.2 6.3 ± 2.1 0.046 Hemoglobin (g/L) 109.5 ± 21.0 110.1 ± 20.6 108.3 ± 21.7 0.034 Platelet (x10 9 /L) 177.8 ± 63.2 178.6 ± 63.7 176.3 ± 62.2 0.380 Neutrophils (x10 9 /L) 4.4 ± 1.8 4.5 ± 1.9 4.4 ± 1.8 0.153 Lymphocyte (x10 9 /L) 1.3 ± 0.7 1.3 ± 0.8 1.2 ± 0.6 0.013 Monocyte (x10 9 /L) 0.5 ± 0.3 0.5 ± 0.4 0.5 ± 0.3 0.410 Parathyroid hormone (pg/mL) 316.9 [169.8,573.5] 322.9 [171.6,593.7] 305.1 [165.5,531.5] 0.055 Albumin (g/L) 40.0 ± 4.4 40.3 ± 4.2 39.3 ± 4.6 < 0.001 Serum uric acid(mmol/L) 427.3 ± 173.0 436.0 ± 190.5 410.3 ± 130.8 < 0.001 Urea (mmol/L) 20.8 ± 14.3 21.3 ± 14.5 19.8 ± 13.9 0.009 Serum creatinine(µmol/l) 888.0 [683.0,1103.0] 932.0 [732.0,1135.2] 808.6 [584.0,1016.6] < 0.001 Potassium (mmol/L) 4.7 ± 0.8 4.8 ± 0.8 4.6 ± 0.8 < 0.001 Total protein(mmol/L) 68.8 ± 6.4 69.0 ± 6.3 68.3 ± 6.5 0.006 Sodium (mmol/L) 139.0 ± 3.7 138.9 ± 3.7 139.1 ± 3.6 0.177 Calcium (mmol/L) 2.2 ± 0.3 2.2 ± 0.3 2.2 ± 0.3 0.115 Total cholesterol (mmol/L) 4.0 ± 1.0 4.0 ± 1.0 4.0 ± 1.1 0.449 HDL(mmol/L) 1.2 ± 0.4 1.1 ± 0.4 1.2 ± 0.4 0.005 Phosphorus (mmol/L) 1.8 ± 0.6 1.8 ± 0.6 1.7 ± 0.6 < 0.001 Triglyceride (mmol/L) 1.9 ± 1.5 2.0 ± 1.5 1.9 ± 1.5 0.285 LDL(mmol/L) 2.2 ± 0.8 2.2 ± 0.8 2.2 ± 0.9 0.913 NPS 3.0 [2.0,4.0] 3.0 [2.0,3.0] 3.0 [2.0,4.0] 0.001 Association between NPS and Cognitive Impairment Patients with NPS = 4 exhibited a higher prevalence of cognitive impairment compared to those with NPS = 2–3 and NPS = 0–1 (39.4% vs. 32.3% and 29.4%, respectively) as shown in Fig. 2 . Multivariate adjusted ORs and 95% CIs for incident cognitive impairment based on the continuous NPS value and increasing Naples scores (groups 0–2), were presented in Table 2 . When regarded as a continuous variable, NPS (OR = 1.106, 95% CI 1.018–1.202, P = 0.019) was independently correlated with CI occurrence. Patients were divided into three groups based on increasing Naples scores (groups 0–2). After adjusting Model 4, compared with those NPS of 0–1 as a reference, HD patients with NPS of 4 (OR = 1.552, 95%CI: 1.146–2.110, p = 0.005) showed a higher risk of CI. While, no significant differences were found in the 2–3 group. Table 2 Cox regression analyses for incident cognitive impairment according to NPS Varible Model 1 Model 2 Mode 3 Model 4 OR (95%CI) P-value OR (95%CI) P-value OR (95%CI) P-value OR (95%CI) P-value Categorical varible 0–1 Reference Reference Reference Reference 2–3 1.147(0.884–1.498) 0.308 1.10(0.838–1.452) 0.497 1.109(0.845–1.466) 0.459 1.159(0.880–1.537) 0.298 4 1.564(1.178–2.088) 0.002 1.457(1.084–1.969) 0.013 1.472(1.094–1.990) 0.011 1.552(1.146–2.110) 0.005 Continuous variable NPS 1.129(1.042–1.224) 0.003 1.102(1.014–1.199) 0.022 1.106(1.018–1.202) 0.019 1.106(1.018–1.202) 0.019 Note: P < 0.05 was considered statistically significant. Abbreviations: OR: odds ratio; CI: confidence interval; Model 1, unadjusted; Model 2, model 1 + age, sex, BMI, Hypertension, alcohol, diabetes mellitus, smoke, SBP1, DBP1,CVD; Model 3, model 2 + education, HD vintages, Dialysis frequency; Model 4, model 3 + uric acid, creatinine, potassium, phosphorus, high density lipoprotein(HDL). Table 3 depicts the relationship between NPS and MMSE score. When regarded as a continuous variable, NPS ( β =-0.178, 95% CI -0.321 - -0.035, p = 0.015) were significantly associated with lower MMSE scores. After adjusting Model 4, patients were further grouped by the increasing Naples scores (groups 0–2), Compared to those in the NPS 0–1 score group, those with 4 score group was associated with an additional 0.68 faster cognitive decline ( p = 0.008). Table 3 Association of NPS with MMSE score, using linear regression analysis among hemodialysis patients Varible Model 1 Model 2 Mode 3 Model 4 β(95%CI) P-value β(95%CI) P-value β(95%CI) P-value OR (95%CI) P-value Categorical varible 0–1 Reference Reference Reference Reference 2月3日 -0.246(-0.718,-0.227) 0.308 -0.124(-0.578,-0.330) 0.592 -0.137(-0.590,-0.317) 0.555 -0.210(-0.663,-0.244) 0.365 4 -0.823(-1.344,-0.302) 0.002 -0.596(-1.098,-0.094) 0.02 -0.607(-1.110,-0.106) 0.018 -0.681(-1.186,-0.176) 0.008 Continuous variable NPS -0.226(-0.373,-0.080) 0.003 -0.154(-0.29,-0.013) 0.033 -0.159(-0.300,-0.018) 0.028 -0.178(-0.321,-0.035) 0.015 Note: P < 0.05 was considered statistically significant. Abbreviations: β Unstandardized coefficient;CI: confidence interval༛MMSE Mini-mental state examination. Model 1, unadjusted; Model 2, model 1 + age, sex, BMI, Hypertension, alcohol, diabetes mellitus, smoke, SBP1, DBP1,CVD; Model 3, model 2 + education, HD vintages, Dialysis frequency; Model 4, model 3 + uric acid, creatinine, potassium, phosphorus, high density lipoprotein(HDL). This study further explored the relationship between NPS and the incidence of dementia (Table 4 ). The finding indicated that NPS had higher risk of dementia with multivariate-adjusted ORs of 1.153 (95% CI 1.035–1.286, p = 0.010). Table 4 Cox regression analyses for incident dementia according to NPS Varible Model 1 Model 2 Mode 3 Model 4 OR (95%CI) P-value OR (95%CI) P-value OR (95%CI) P-value OR (95%CI) P-value Categorical varible 0–1 Reference Reference Reference Reference 2–3 1.098(0.787–1.562) 0.591 1.054(0.747–1.515) 0.770 1.066(0.754–1.533) 0.725 1.111(0.784–1.603) 0.563 4 1.568(1.098–2.277) 0.015 1.459(1.008–2.144) 0.049 1.477(1.019–2.173) 0.043 1.538(1.055–2.276) 0.028 Continuous variable NPS 1.140(1.026–1.270) 0.005 1.137(1.023–1.265) 0.018 1.140(1.026–1.270) 0.016 1.153(1.035–1.286) 0.010 Note: P < 0.05 was considered statistically significant. Abbreviations: OR: odds ratio; CI: confidence interval; Model 1, unadjusted; Model 2, model 1 + age, sex, BMI, Hypertension, alcohol, diabetes mellitus, smoke, SBP1, DBP1,CVD; Model 3, model 2 + education, HD vintages, Dialysis frequency; Model 4, model 3 + uric acid, creatinine, potassium, phosphorus, high density lipoprotein(HDL). Subgroup analyses of association between NPS and incident CI AS show in Fig. 3 (A). A stronger association between NPS and incident CI was found among patients aged < 65 years (OR 1.21, 1.10–1.35, P < 0.001), low educational level (OR 1.13, 1.03–1.23, P < 0.001), under 3 times HD frequency (OR 1.11, 1.01–1.22, P = 0.026), hypertension history (OR 1.16, 1.05–1.27, P < 0.001),no-diabetes mellitus history(OR 1.13, 1.01–1.25, P = 0.03), CVD history (OR 1.16, 1.06–1.27, P = P < 0.001). Significant interaction effect of sex, age, education, CVD on the NPS-CI was observed (all P for interaction < 0.001)respectively. Subgroup analyses of association between NPS and incident dementia Figure 3 (B) shows. A stronger association between NPS and incident dementia was found among patients male(OR 1.17, 1.01–1.37, p < 0.04), aged < 65 years (OR 1.25, 1.09–1.44, p < 0.002), low educational leve (OR 1.15, 1.03–1.28, p < 0.014), under 3 times HD frequency (OR 1.52, 1.11–2.22, p = 0.011), hypertension history (OR 1.20, 1.07–1.36, p < 0.003), diabetes mellitus history(OR 1.24, 1.03–1.50, p = 0.023), no-CVD history(OR 1.19,1.06–1.33, p < 0.004). Significant interaction effect of sex,education, HD prequency, CVD on the NPS-dementia was observed ( p for interaction 0.004, 0.007, 0.024, < 0.001 respectively). Discussion To our knowledge, the present study is the first study to evaluate the longitudinal associations between NPS and incident CI in hemodialysis patients. Our findings indicate that higher NPS scores were associated with lower MMSE scores, and an increased incidence of CI. Furthermore, NPS was found to be independently associated with incident CI in hemodialysis patients, even after adjusting for Model4. Sex, age, education, CVD had an interactive role in the association between NPS and incident of CI. Sex, education, HD frequency, CVD had an interactive role in the association between NPS and incident dementia. Similar with the previous studies, malnutrition and inflammation leads to cognitive decline in hemodialysis patients [ 2 ] . NPS as a comprehensive measure of inflammation and nutritional biomarkers, has been used as a prognostic factor in many cancers and acute kidney disease [ 4 ] . The inflammation and nutritional are closely linked with CI, with each component independently associated with CI. However, this inflammatory scoring system has not been explored in CI, we propose investigating the relationship between nutritional status and CI, particularly in hemodialysis patients. Malnutrition is highly prevalent in HD patients. The link between malnutrition with CI has been demonstrated in several study [ 9 ] . The causes of malnutrition are complex and can be attributed to non-iatrogenic and iatrogenic factors. Albumin level is a sensitive method for identifying patients at risk for malnutrition [ 10 ] . Albumin serves as a marker for malnutrition and also reflects various non-nutritional factors that frequently occur among HD patients, including inflammation, anemia, dialysate losses, and hydration status [ 11 ] . Serum albumin has the ability to withstand both exogenous and endogenous oxidants, and a reduction in its levels may lead to an imbalance in oxidation and antioxidation processes, potentially resulting in cognitive impairment [ 12 ] . However, albumin concentrations can be affected by age, liver function, comorbidities, inflammation and alterations in body fluid volume, particularly in HD patients [ 13 ] . Several authors have proposed adding plasma cholesterol levels as a means to enhance the assessment of nutritional status [ 14 ] . The levels of TC,LDL and HDL in patients with CI are notable lower compared to those with normal cognitive function [ 15 ] . Moreover, increasing evidences strongly suggests that a lack of cholesterol in brain cellular could contribute to AD-related pathology. Neuronal morphology, function, and synaptic transmission may rely on substantial amounts of cholesterol for maintenance, as it serves as a crucial component of cell membranes and a regulator of signaling molecules [ 16 ] . Chronic inflammation is common in patients undergoing HD. Numerous studies have demonstrated that the detrimental effect of elevated inflammatory status on the cognitive abilities [ 17 ] , particularly in CKD and HD patients. NLR has been identified as being in closely associated with cognitive ability and various mental states. In their study, Zi-Wei Yu et al. observed a higher neutrophil count and a lower lymphocyte count in the group with mild cognitive impairment compared to the group with normal cognitive function [ 18 ] . Another study conducted on elderly individuals in Northeast China, revealed a positive correlation between the NLR and the presence of Alzheimer's disease (AD) and MCI, and the NLR was helpful in distinguishing normal cognitive function from AD or MCI [ 19 ] .A study focus on elderly patients with esophageal cancer, initially discovered a significant correlation between postoperative levels of NLR and MMSE scores [ 20 ] . Fang et al. showed that a high NLR was associated with poor visual memory and visuospatial performance [ 21 ] . Recent evidence suggested that lower lymphocyte count could predict ApoE "4-related cognitive decline in Parkinson’s disease(PD) [ 22 ] and associated with an increased risk of subsequent PD diagnosis [ 23 ] . In the context of the innate immune response, monocytes are crucial in serving as the primary defense against pathogens.Research findings, increases in peripheral soluble CD163 and CD14 remain markers commonly associated with cognitive impairment [ 24 ] . In HIV-uninfected individuals, elevated levels of intermediate monocytes may serve as a potential biomarker for distinguishing between individuals presenting with depressive symptoms and those who do not exhibit such symptoms [ 25 ] . The precise pathophysiological mechanism linking the NLR and cognitive impairment remains uncertain.Neutrophils are known to combat pathogens through phagocytosis and the ingestion of cellular debris, releasing inflammatory factors from granules and vesicles upon activation [ 26 ] . In the pathophysiology of neurodegenerative diseases, inflammation is a key factor. Persistent inflammation can cause vascular dysfunction, leading to compromised cerebral blood flow and oxygenation. Prolonged inflammation may result in adverse outcomes such as neuronal dysfunction, synaptic degeneration, and ultimately neuronal death, which can impact cognitive functions [ 27 ] . However, activated neutrophils have been shown to not only activate microglia and release neurotoxic substances, but also disrupt the blood-brain barrier through the promotion of reactive oxygen species (ROS) release. Additionally, activated neutrophils have been found to stimulate T lymphocytes by enhancing antigen presentation, ultimately resulting in neuroinflammation and neuronal damage [ 16 , 28 ] . Studies have shown that lymphocyte infiltration into the ischemic brain persists for a minimum of 72 days following the onset of a stroke, indicating a substantial role of lymphocytes in post-stroke cognitive impairment (PSCI). This suggests that therapeutic strategies aimed at depleting CD4 + T cells may be a promising approach for treatment [ 29 ] . The Naples prognostic score, a composite index of inflammatory and nutritional markers, has been previously investigated for its prognostic value in cancer patients [ 6 ] . The NPS incorporates three leukocyte subtypes, as well as albumin and cholesterol, suggesting that the combined effects may be more advantageous than those of the individual components. Our results demonstrate NPS has a predictive effect on cognitive function, both as a continuous indicator and a categorical indicator. The elemental indicators of the NPS are frequently utilized in clinical settings and are relatively straightforward to compute. The early calculation of the score could theoretically assist in identifying individuals who may benefit from preventative interventions. Subgroup analysis indicates that the effect of NPS on CI was more pronounced in male, under 65 years, low educational levels,without diabetes and CVD in HD patients.These findings suggest potential associations with gender-specific physiological, psychological, or social factors that may contribute to suboptimal nutrition or inflammation in the absence of timely recognition and intervention. Individuals under 65 years may exhibit relatively better physical health and being more sensitive to physiological and psychological responses to nutrition or inflammation, the negative impact of NPS on cognitive function may be more significant. Patients with lower education may have limited cognitive reserves, information processing abilities, potentially exacerbating the negative effects of NPS. Additionally, the presence of diabetes and cerebrovascular diseases can further impair cognitive function, in patients without these comorbidities, NPS may play a more prominent role in affecting cognitive function. Our study revealed that except male, low education level, and non CVD, a significant association between NPS and dementia in patients who receive hemodialysis less than three times per week. These findings provide us with a new perspective on the relationship between NPS and CI in HD patients. This study contributes novel findings regarding the relationship between NPS and cognitive impairment in patients with HD. However, it is important to acknowledge several limitations. Firstly, the study had a small sample size and a relatively limited duration for longitudinal analysis. Secondly, the diagnosis of cognitive impairment was based solely on the Mini-Mental State Examination (MMSE), which may not provide as much diagnostic certainty as comprehensive neuropsychological test batteries. Thirdly, the study did not investigate other inflammatory markers such as C-reactive protein, interleukins, and erythrocyte sedimentation rate. Conclusion In summary, we used a prediction model based on NPS and evaluated the incident of CI.we found that in patients with HD, higher baseline NPS is associated with the occurrence of CI. This study provides a justification to include assessment of malnutrition and inflammation using NPS as part of cognitive function assessment. NPS gives a comprehensive evaluation of the nutritional and inflammatory status of HD patients,we are looking forward to conduct prospective studies to further validate our findings. Declarations Authors’ contributions Yan Ran：investigation, data curation, methodology, validation, writing– original-draft, writing–review & editing. Yuqi Yang：investigation, methodology, conceptualization. Yanzhe Peng, Jingjing Da, Zuping Qian, Jing Yuan: investigation, conceptualization. Yan Zha : project administration, conceptualization, supervision. All authors have read and approved the final version of the manuscript. Funding Science and Technology Cooperation Foundation of Guizhou Province (ZK [2021]381). Availability of data and materials All data used in this study are publicly available. To assess the data, please contact the corresponding author. Ethics approval and consent to participate The study followed the Declaration of Helsinki and received informed consent approval from the Institutional Review Board of Guizhou Provincial People’s Hospital (Approval Number: (2020)208). All participants provided written informed consent. Consent for publication Not applicable. Competing interests The authors declare no competing interests. References van Zwieten A, Wong G, Ruospo M, et al. Prevalence and patterns of cognitive impairment in adult hemodialysis patients: the COGNITIVE-HD study. Nephrol Dial Transplant. 2018. 33(7): 1197-1206. Yang Y, Da J, Li Q, Long Y, Yuan J, Zha Y. The Impact of Malnutrition, Inflammation on Cognitive Impairment in Hemodialysis Patients: A Multicenter Study. Kidney Blood Press Res. 2022. 47(12): 711-721. Russell B, Zager Y, Mullin G, et al. Naples Prognostic Score to Predict Postoperative Complications After Colectomy for Diverticulitis. Am Surg. 2023. 89(5): 1598-1604. Karakoyun S, Cagdas M, Celik AI, et al. Predictive Value of the Naples Prognostic Score for Acute Kidney Injury in ST-Elevation Myocardial Infarction Patients Undergoing Primary Percutaneous Coronary Intervention. Angiology. 2024. 75(6): 576-584. Aytaç İ, Güven Aytaç B, Kilci O, Ölçücüoğlu E. Naples Prognostic Score for Graft Functions After Renal Transplantation: A Retrospective Analysis. Ann Transplant. 2023. 28: e942007. Xu B, Zhu J, Wang R, et al. Clinical Implications of Naples Prognostic Score for Patients with Resected Cholangiocarcinoma: A Real-World Experience. J Inflamm Res. 2024. 17: 655-667. Zhong C, Bu X, Xu T, et al. Serum Matrix Metalloproteinase-9 and Cognitive Impairment After Acute Ischemic Stroke. J Am Heart Assoc. 2018. 7(1): e007776. Ng TP, Feng L, Nyunt MS, et al. Metabolic Syndrome and the Risk of Mild Cognitive Impairment and Progression to Dementia: Follow-up of the Singapore Longitudinal Ageing Study Cohort. JAMA Neurol. 2016. 73(4): 456-63. Rotondi S, Tartaglione L, Pasquali M, et al. Association between Cognitive Impairment and Malnutrition in Hemodialysis Patients: Two Sides of the Same Coin. Nutrients. 2023. 15(4): 813. Zhang K, Gao J, Chen J, et al. MICS, an easily ignored contributor to arterial calcification in CKD patients. Am J Physiol Renal Physiol. 2016. 311(4): F663-F670. Friedman AN, Fadem SZ. Reassessment of albumin as a nutritional marker in kidney disease. J Am Soc Nephrol. 2010. 21(2): 223-30. Wang L, Wang F, Liu J, Zhang Q, Lei P. Inverse Relationship between Baseline Serum Albumin Levels and Risk of Mild Cognitive Impairment in Elderly: A Seven-Year Retrospective Cohort Study. Tohoku J Exp Med. 2018. 246(1): 51-57. Tokunaga R, Sakamoto Y, Nakagawa S, et al. CONUT: a novel independent predictive score for colorectal cancer patients undergoing potentially curative resection. Int J Colorectal Dis. 2017. 32(1): 99-106. Toyokawa T, Kubo N, Tamura T, et al. The pretreatment Controlling Nutritional Status (CONUT) score is an independent prognostic factor in patients with resectable thoracic esophageal squamous cell carcinoma: results from a retrospective study. BMC Cancer. 2016. 16(1): 722. Dietschy JM, Turley SD. Thematic review series: brain Lipids. Cholesterol metabolism in the central nervous system during early development and in the mature animal. J Lipid Res. 2004. 45(8): 1375-97. Ozturk HM, Ogan N, Erdogan M, Akpinar EE, Ilgar C, Ozturk S. The association between total cholesterol and cognitive impairment in chronic obstructive pulmonary disease patients. Prostaglandins Other Lipid Mediat. 2023. 164: 106697. Bauer IE, Pascoe MC, Wollenhaupt-Aguiar B, Kapczinski F, Soares JC. Inflammatory mediators of cognitive impairment in bipolar disorder. J Psychiatr Res. 2014. 56: 18-27. Yu ZW, Wang Y, Li X, Tong XW, Zhang YT, Gao XY. Association between the neutrophil to lymphocyte ratio and mild cognitive impairment in patients with type 2 diabetes. Aging Clin Exp Res. 2023. 35(6): 1339-1345. Dong X, Nao J, Shi J, Zheng D. Predictive Value of Routine Peripheral Blood Biomarkers in Alzheimer's Disease. Front Aging Neurosci. 2019. 11: 332. Zhao J, Dai T, Ding L, et al. Correlation between neutrophil/lymphocyte ratio, platelet/lymphocyte ratio and postoperative cognitive dysfunction in elderly patients with esophageal cancer. Medicine (Baltimore). 2023. 102(10): e33233. Fang Y, Doyle MF, Alosco ML, et al. Cross-Sectional Association Between Blood Cell Phenotypes, Cognitive Function, and Brain Imaging Measures in the Community-Based Framingham Heart Study. J Alzheimers Dis. 2022. 87(3): 1291-1305. Tsukita K, Sakamaki-Tsukita H, Takahashi R. Lower Circulating Lymphocyte Count Predicts ApoE ε4-Related Cognitive Decline in Parkinson's Disease. Mov Disord. 2021. 36(12): 2969-2971. Jensen MP, Jacobs BM, Dobson R, et al. Lower Lymphocyte Count is Associated With Increased Risk of Parkinson's Disease. Ann Neurol. 2021. 89(4): 803-812. Pulliam L, Gascon R, Stubblebine M, McGuire D, McGrath MS. Unique monocyte subset in patients with AIDS dementia. Lancet. 1997. 349(9053): 692-5. Lynall ME, Turner L, Bhatti J, et al. Peripheral Blood Cell-Stratified Subgroups of Inflamed Depression. Biol Psychiatry. 2020. 88(2): 185-196. Satoh A, Imai SI, Guarente L. The brain, sirtuins, and ageing. Nat Rev Neurosci. 2017. 18(6): 362-374. Kure CE, Rosenfeldt FL, Scholey AB, et al. Relationships Among Cognitive Function and Cerebral Blood Flow, Oxidative Stress, and Inflammation in Older Heart Failure Patients. J Card Fail. 2016. 22(7): 548-59. Sayed A, Bahbah EI, Kamel S, Barreto GE, Ashraf GM, Elfil M. The neutrophil-to-lymphocyte ratio in Alzheimer's disease: Current understanding and potential applications. J Neuroimmunol. 2020. 349: 577398. Weitbrecht L, Berchtold D, Zhang T, et al. CD4(+) T cells promote delayed B cell responses in the ischemic brain after experimental stroke. Brain Behav Immun. 2021. 91: 601-614. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4773830","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":339430740,"identity":"cd441a77-4034-4805-bfc3-6cbd59176358","order_by":0,"name":"Yan Ran","email":"","orcid":"","institution":"Guizhou Provincial People′s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Ran","suffix":""},{"id":339430741,"identity":"d1a813d9-7634-4a2c-b96b-a6bd5427fefd","order_by":1,"name":"Yuqi Yang","email":"","orcid":"","institution":"Guizhou Provincial People′s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuqi","middleName":"","lastName":"Yang","suffix":""},{"id":339430742,"identity":"36817535-25a6-4caf-bf02-0b8ea1299648","order_by":2,"name":"Yanzhe Peng","email":"","orcid":"","institution":"Guizhou Provincial People′s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yanzhe","middleName":"","lastName":"Peng","suffix":""},{"id":339430743,"identity":"65c4be16-d986-41f6-b9b7-5168a85942e0","order_by":3,"name":"Jingjing Da","email":"","orcid":"","institution":"Guizhou Provincial People′s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jingjing","middleName":"","lastName":"Da","suffix":""},{"id":339430744,"identity":"f03d74c5-69d6-4a86-8e02-a21ce39e5c98","order_by":4,"name":"Zuping Qian","email":"","orcid":"","institution":"Guizhou Provincial People′s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Zuping","middleName":"","lastName":"Qian","suffix":""},{"id":339430745,"identity":"d598796a-aff8-472b-877d-aa429f3427b1","order_by":5,"name":"Jing Yuan","email":"","orcid":"","institution":"Guizhou Provincial People′s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Yuan","suffix":""},{"id":339430746,"identity":"6efe7917-f502-42f6-b170-17a0cf19a7da","order_by":6,"name":"Yan Zha","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYBAC+xlg6r8cPzPzwQdEaWGEaGE2lmxnSzYgSUvihvM8ZgJEaWGWbn4m8XMHG+PmwwxmDAw1NtEEtbDJHDOT7D3Dw2x2mCHtAcOxtNwGQlp4JBLMJHjbJNiAWo4bMDYcJqxFQiL9m+TfNgMe42bGNgmitBhI5JhJ87YlSBgwM7MRraXYWrbtgIHEYTZmgwRi/GI/I33jzbdtB+r7+89/fPChxoawFiBgkYAzE4hQDgLMH4hUOApGwSgYBSMVAAC1bjpwvsqj6wAAAABJRU5ErkJggg==","orcid":"","institution":"Guizhou Provincial People′s Hospital","correspondingAuthor":true,"prefix":"","firstName":"Yan","middleName":"","lastName":"Zha","suffix":""}],"badges":[],"createdAt":"2024-07-20 15:45:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4773830/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4773830/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62799874,"identity":"81e565c3-8c27-4e0e-9d0c-10ffcfda2851","added_by":"auto","created_at":"2024-08-19 15:46:36","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":70443,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of the study. HD: hemodialysis; NPS: Naples prognostic score; CI:cognitive impairment\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4773830/v1/1c2a5589fa7f711d8aa7f04c.jpg"},{"id":62799875,"identity":"7f4c41c4-e41f-4e77-9ae6-69f6a1aeefdf","added_by":"auto","created_at":"2024-08-19 15:46:36","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":50783,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of cognitive impairment in HD patients stratified by NPS\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4773830/v1/cbee12f908fb852884f9c49c.jpg"},{"id":62799876,"identity":"4a938e19-2d6c-4dc6-b852-c5fc1c763e4c","added_by":"auto","created_at":"2024-08-19 15:46:37","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":5232058,"visible":true,"origin":"","legend":"\u003cp\u003eSubgroup analyses of association between NPS and cognitive impairment (A), and subgroup analyses of association between NPS and dementia(B). Model was adjusted for age, sex, BMI, Hypertension, alcohol, diabetes mellitus, smoke, SBP1, DBP1,CVD,education, HD vintages, Dialysis frequency, uric acid ,creatinine, potassium, phosphorus, high density lipoprotein(HDL).OR Odds ratio, CI Confidence interval, HD Hemodialysis, CVD cerebral vascular disease.\u003c/p\u003e","description":"","filename":"3copy.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4773830/v1/9690ad83e4fff273cf5cf4e4.jpg"},{"id":72846179,"identity":"ff0652fb-d2d5-4016-8494-24e229a33316","added_by":"auto","created_at":"2025-01-02 20:46:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6169215,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4773830/v1/442baf8e-b772-4c1d-a260-ce571d078377.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The impact of Naples prognostic score on cognitive impairment in hemodialysis patients-A multicenter study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eStudies have show that cognitive impairment(CI) is a common and notable health issue among individuals undergoing hemodialysis (HD), with research suggesting that up to 60\u0026ndash;90% of patients with end-stage kidney disease (ESKD) receiving hemodialysis experience cognitive impairment\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Patients undergoing hemodialysis who experience cognitive impairment encounter significant challenges related to their disease, including an increased risk of hospitalization, higher mortality rates, elevated healthcare costs, and a diminished quality of life\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Despite the progress in diagnostic and treatment technologies, a considerable number of individuals with hemodialysis continue to experience cognitive impairment. The causes of CI in hemodialysis patients are multifactorial, including factors related to uremia and the dialysis process, such as uremic toxins, anemia, rapid fluid shifts, and cerebral hypoperfusion. Individuals undergoing hemodialysis often experience systemic inflammation and concurrent protein-energy malnutrition\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e, which are known to play a significant role in the development of cognitive impairment. The inflammatory and malnutrition status of these patients can lead to complications related to hemodialysis, ultimately resulting in cognitive impairment and increased mortality. Currently, there are no effective pharmacological treatments specifically targeting cognitive impairment in hemodialysis patients. Therefore, identifying modifiable risk factors for cognitive impairment in this population is of great importance.\u003c/p\u003e \u003cp\u003eThe Naples Prognostic Score (NPS) is a novel scoring system that encompasses various inflammation and nutritional biomarkers, including total cholesterol, lymphocyte to monocyte ratio (LMR), neutrophil to lymphocyte ratio (NLR), and serum albumin. Research has demonstrated that NPS has the ability to predict acute renal failure post-myocardial infarction, malnutrition in hypertensive individuals, and postoperative complications in patients with diverticulitis\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. A study examining kidney transplant patients revealed that those with a creatinine reduction ratio below 30% exhibited a notably elevated incidence of NPS 3\u0026ndash;4, decreased LMR levels, and heightened neutrophil and NLR levels\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Additionally, an empirical investigation into resected Cholangiocarcinoma patients demonstrated a direct correlation between preoperative malnutrition and NPS, with NPS serving as an independent prognostic indicator\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Meanwhile, the NPS serves as a valuable tool designed to evaluate the prognostic outcomes of different types of cancers. However, there is a lack of research on the relationship between NPS and cognitive impairment in the general population, particularly in individuals with HD patients who have a high prevalence of cognitive impairment, and there is a dearth of relevant studies on this topic. Understanding the complex interrelationships between NPS and CI is critical because of the high prevalence of these conditions in HD populations. Several previous research has established a correlation between the common conditions of nutrition and inflammation and cognitive decline in the general population. These studies have indicated that individuals with HD, who are likely to experience high levels of inflammation and malnutrition, also have a heightened risk of developing cognitive impairment\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Actually, in HD patients, fluctuations in inflammation and nutritional status may lead to variability in prognostic indicators for cognitive impairment over time. Despite this potential relationship, few research has been conducted on the correlation between changes in common nutritional and inflammatory conditions and cognitive impairment.\u003c/p\u003e \u003cp\u003eConsidering the notable prevalence of inflammation and malnutrition in hemodialysis patients with cognitive impairment, there is reason to suspect a potential correlation between these two significant complications. Nevertheless, limited research has been conducted on this particular population. Therefore, the objective of this study was to examine the relationships between NPS and severity scores with cognitive impairment in hemodialysis patients.\u003c/p\u003e"},{"header":"Methods and materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and participants\u003c/h2\u003e \u003cp\u003eThis study was a multicenter, observational cohort study that recruited patients undergoing maintenance hemodialysis at twenty-two dialysis centers in Guizhou Province, China from June 2021 to June 2022. Inclusion criteria encompassed patients with end-stage kidney disease (ESKD) who had received regular bicarbonate-based dialysis treatment (twice or thrice per week)for at least three months or longer and aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years or older, and had completed biochemical, anthropometric measurements, and questionnaire records.\u003c/p\u003e \u003cp\u003eExclusion criteria included: (1)those with mental illness, severe aphasia, and critical illness who cannot cooperate with the questionnaire survey; (2) extreme weakness leading to a life expectancy of less than half a year; (3)patients with severe liver failure, lung disease, and other related diseases that seriously affect patients\u0026rsquo; cognitive function;(4) psychotropic drug or alcohol dependence; (5) serious limb defects and deformities or metal stents in the body that cannot be examined by bioelectrical impedance analysis.\u003c/p\u003e \u003cp\u003e The study followed the Declaration of Helsinki and received informed consent approval from the Institutional Review Board of Guizhou Provincial People\u0026rsquo;s Hospital (Approval Number: (2020)208). All participants provided written informed consent.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of covariates\u003c/h2\u003e \u003cp\u003eStandard questionnaires were utilized to gather demographic information, such as age, sex, ethnicity, household income, educational level (low:\u0026lt;9th grade; high:\u0026ge;9th grade), physical activity levels, smoking status (yes or no), alcohol status (yes or no), medical history, and presence of any diseases during interviews. Hypertension was defined as systolic blood pressure (SBP)\u0026thinsp;\u0026ge;\u0026thinsp;140mmHg and/or diastolic blood pressure (DBP)\u0026thinsp;\u0026ge;\u0026thinsp;90 mmHg, or self-reported, or a medical record of responding diagnosis or medication (yes or no). Diabetes mellitus was diagnosed as fasting plasma glucose\u0026thinsp;\u0026ge;\u0026thinsp;126 mg/dL (7 mmol/L) or random blood glucose\u0026thinsp;\u0026ge;\u0026thinsp;200 mg/dL (11.1mmol/L) or HbA1c\u0026thinsp;\u0026ge;\u0026thinsp;6.5%, or self-reported, or a medical record of responding diagnosis or medication (yes or no). The following information of HD therapy was also recorded: Prior to hemodialysis, anthropometric measurements including height, waist circumference, weight, systolic blood pressure, diastolic blood pressure, and hip circumference were obtained by two trained nephrologists. Additionally, data on dialysis frequencies (twice/thrice per week), hemodialysis vintages, dialysis modality, dialysis dehydration amount, and complications during dialysis such as hypotension and hypoglycemia were recorded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eBiochemical measurements\u003c/h2\u003e \u003cp\u003eFor laboratory variables, all participants provided venous blood samples, after fasting for 8-10h and were collected before the initiation of hemodialysis therapy. We evaluated the following: leukocyte, hemoglobin, platelet, Neutrophils, Lymphocyte, monocyte, parathyroid hormone, albumin, serum uric acid, Urea, total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and other biochemical indicators.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eCognitive function evaluation\u003c/h2\u003e \u003cp\u003eCognitive function was assessed using the Mini-Mental State Examination (MMSE) questionnaire by the trained personnel of the research group. The total score of the evaluation scale is 30 points (including 10 points for orientation force, 3 points for memory, 5 points for attention and calculation, 3 points for memory, and 9 points for language ability). Participants with an MMSE score of less than 27 were diagnosed as CI and MMSE score of 23 or less were diagnosed as dementia\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Every patient completed the MMSE scores at baseline and follow-up.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eCalculation of Naples prognostic score\u003c/h2\u003e \u003cp\u003eThe NPS was calculated based on the serum albumin, TC, NLR, and LMR. According to the previous reports, if the serum albumin\u0026thinsp;\u0026ge;\u0026thinsp;40 g/L,TC\u0026thinsp;\u0026gt;\u0026thinsp;180 mg/dL, NLR\u0026thinsp;\u0026lt;\u0026thinsp;2.96, or LMR\u0026thinsp;\u0026gt;\u0026thinsp;4.44 was scored as 0,while serum albumin\u0026thinsp;\u0026lt;\u0026thinsp;40 g/L, TC\u0026thinsp;\u0026le;\u0026thinsp;180 mg/dL, NLR\u0026thinsp;\u0026ge;\u0026thinsp;2.96, or LMR\u0026thinsp;\u0026le;\u0026thinsp;4.44 was scored as 1\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. NPS is the sum of the scores of each of the four factors. The calculation of the NPS involves adding up the scores assigned to the parameters mentioned earlier. Patients were divided into three groups based on the NPS: group 0 (score of 0 or 1); group 1(score of 2 or 3); and group 2(score of 4).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eCategorical data were expressed as numbers and percentages. Normally distributed continuous data were represented by mean and standard deviation while with a skewed distribution were described as the medians and interquartile range. There is no unified grouping standard for NPS, we divided patients into 3 groups based on increasing Naples scores (groups 0\u0026ndash;2): group 0 with a score of 0 or 1; group 1 with a score of 2 or 3; group 2 with a score of 4.\u003c/p\u003e \u003cp\u003eUnivariate and multivariate logistic regression analyses were undertaken to investigate the correlation between NPS and the incidence of CI. Additionally, univariate and multivariate linear regression analyses were conducted to examine the relationships between MMSE score and NPS. Utilizing odds ratios (ORs), unstandardized coefficients (β), and confidence intervals (CIs) summarized, respectively. In model 1, there was no adjustment. In model 2, we adjusted for age and sex, BMI, Hypertension, alcohol, diabetes mellitus, smoke, SBP1, DBP1,CVD; In model 3, we adjusted for model 2 and education, HD vintages, Dialysis frequency;In model 4, we adjusted for model 3 and uric acid, creatinine, potassium, phosphorus, high density lipoprotein(HDL).The subgroup analysis was conducted to explore the potential effect modification by sex(female or male), age(\u0026lt;\u0026thinsp;65 years or \u0026ge;\u0026thinsp;65 years), education level (low or high),HD frequency(\u0026lt;\u0026thinsp;3times or \u0026ge;\u0026thinsp;3 times), smoking history(yes or no), hypertension history (yes or no), diabetes mellitus history(yes or no) ,history of diabetes (yes or no) and CVD(yes or no).\u003c/p\u003e \u003cp\u003eAll statistical analyses were performed by IBM SPSS Statistics (version 27.0, Chicago, USA) the R open-source software(version 4.3.3.) A two-sided P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically different.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics of study participants\u003c/h2\u003e \u003cp\u003eAs illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, a total of 3902 hemodialysis patients were enrolled, and after applying exclusion criteria, the final analytical cohort included 2725 HD patients, the mean age of 54.44\u0026thinsp;\u0026plusmn;\u0026thinsp;14.8 years, 1668 (61.2%) were male. The median dialysis vintage was 54.0 (33.0, 87.0) months. The average number of NPS components was 2.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0. The mean MMSE score was 26.87\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9, and the prevalence of CI (MMSE\u0026thinsp;\u0026lt;\u0026thinsp;27) was 33.8%, the prevalence of dementia (MMSE\u0026thinsp;\u0026le;\u0026thinsp;23) was 16.8%. The patients were stratified into two groups based on cognitive status: Normal cognition group (n\u0026thinsp;=\u0026thinsp;1803, 66.2%) or CI group (n\u0026thinsp;=\u0026thinsp;922, 33.8%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the mean age of the overall population was 54.44\u0026thinsp;\u0026plusmn;\u0026thinsp;14.8 years, 1668 (61.2%) were male. Compared to the patients with normal cognition, those with CI were older, more likely male, lower educational level, lower DBP levels, higher prevalence rates of hypertension, lower uric acid levels, and lower hemoglobin, albumin,urea nitrogen and creatinine levels.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of hemodialysis patients according to cognitive function\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaribles\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2725)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal cognition (n\u0026thinsp;=\u0026thinsp;1803)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCognitive impairment\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;922)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex (n,%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1668(61.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1166(64.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e502(54.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54.4\u0026thinsp;\u0026plusmn;\u0026thinsp;14.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52.1\u0026thinsp;\u0026plusmn;\u0026thinsp;14.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59.1\u0026thinsp;\u0026plusmn;\u0026thinsp;14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh education level(n,%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e161(5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e113(6.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48(5.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.266\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDialysis frequency\u003c/p\u003e \u003cp\u003e(\u0026lt;\u0026thinsp;thrice/week) (n,%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e439(16.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e298(16.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e141(15.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.407\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDialysis vintage (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54.0 [33.0,87.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55.0 [35.0,90.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.0 [31.0,84.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol history (n,%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e195(7.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e118(6.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e77(8.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking history(n,%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1041(38.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e675(37.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e366(39.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.251\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of hypertension (n,%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2228(81.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1434(79.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e794(86.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus (n,%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e933(34.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e568(31.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e365(39.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart failure (n,%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e675(24.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e440(24.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e235(25.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.535\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCVD (n,%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e238(8.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e145(8.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e93(10.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-dialysis SBP(mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e136.6\u0026thinsp;\u0026plusmn;\u0026thinsp;18.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e136.7\u0026thinsp;\u0026plusmn;\u0026thinsp;18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e136.3\u0026thinsp;\u0026plusmn;\u0026thinsp;18.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.646\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-dialysis DBP(mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e78.2\u0026thinsp;\u0026plusmn;\u0026thinsp;14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78.8\u0026thinsp;\u0026plusmn;\u0026thinsp;13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e76.9\u0026thinsp;\u0026plusmn;\u0026thinsp;14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.624\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeukocyte (x10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e109.5\u0026thinsp;\u0026plusmn;\u0026thinsp;21.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110.1\u0026thinsp;\u0026plusmn;\u0026thinsp;20.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e108.3\u0026thinsp;\u0026plusmn;\u0026thinsp;21.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet (x10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e177.8\u0026thinsp;\u0026plusmn;\u0026thinsp;63.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e178.6\u0026thinsp;\u0026plusmn;\u0026thinsp;63.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e176.3\u0026thinsp;\u0026plusmn;\u0026thinsp;62.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.380\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophils (x10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.153\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte (x10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonocyte (x10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.410\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParathyroid hormone (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e316.9 [169.8,573.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e322.9 [171.6,593.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e305.1 [165.5,531.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlbumin (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40.0\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum uric acid(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e427.3\u0026thinsp;\u0026plusmn;\u0026thinsp;173.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e436.0\u0026thinsp;\u0026plusmn;\u0026thinsp;190.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e410.3\u0026thinsp;\u0026plusmn;\u0026thinsp;130.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrea (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20.8\u0026thinsp;\u0026plusmn;\u0026thinsp;14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.3\u0026thinsp;\u0026plusmn;\u0026thinsp;14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.8\u0026thinsp;\u0026plusmn;\u0026thinsp;13.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum creatinine(\u0026micro;mol/l)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e888.0 [683.0,1103.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e932.0 [732.0,1135.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e808.6 [584.0,1016.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotassium (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal protein(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69.0\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e68.3\u0026thinsp;\u0026plusmn;\u0026thinsp;6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSodium (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e139.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e138.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e139.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalcium (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.115\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal cholesterol (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.449\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhosphorus (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTriglyceride (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.913\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNPS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.0 [2.0,4.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.0 [2.0,3.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.0 [2.0,4.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAssociation between NPS and Cognitive Impairment\u003c/h2\u003e \u003cp\u003ePatients with NPS\u0026thinsp;=\u0026thinsp;4 exhibited a higher prevalence of cognitive impairment compared to those with NPS\u0026thinsp;=\u0026thinsp;2\u0026ndash;3 and NPS\u0026thinsp;=\u0026thinsp;0\u0026ndash;1 (39.4% vs. 32.3% and 29.4%, respectively) as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Multivariate adjusted ORs and 95% CIs for incident cognitive impairment based on the continuous NPS value and increasing Naples scores (groups 0\u0026ndash;2), were presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. When regarded as a continuous variable, NPS (OR\u0026thinsp;=\u0026thinsp;1.106, 95% CI 1.018\u0026ndash;1.202, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.019) was independently correlated with CI occurrence. Patients were divided into three groups based on increasing Naples scores (groups 0\u0026ndash;2). After adjusting Model 4, compared with those NPS of 0\u0026ndash;1 as a reference, HD patients with NPS of 4 (OR\u0026thinsp;=\u0026thinsp;1.552, 95%CI: 1.146\u0026ndash;2.110, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005) showed a higher risk of CI. While, no significant differences were found in the 2\u0026ndash;3 group.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ensp;Cox regression analyses for incident cognitive impairment according to NPS\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVarible\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eMode 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003eModel 4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCategorical varible\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.147(0.884\u0026ndash;1.498)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.10(0.838\u0026ndash;1.452)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.497\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.109(0.845\u0026ndash;1.466)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.459\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.159(0.880\u0026ndash;1.537)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.298\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.564(1.178\u0026ndash;2.088)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.457(1.084\u0026ndash;1.969)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.472(1.094\u0026ndash;1.990)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.552(1.146\u0026ndash;2.110)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eContinuous variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNPS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.129(1.042\u0026ndash;1.224)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.102(1.014\u0026ndash;1.199)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.106(1.018\u0026ndash;1.202)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.106(1.018\u0026ndash;1.202)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003eNote: P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Abbreviations: OR: odds ratio; CI: confidence interval; Model 1, unadjusted; Model 2, model 1\u0026thinsp;+\u0026thinsp;age, sex, BMI, Hypertension, alcohol, diabetes mellitus, smoke, SBP1, DBP1,CVD; Model 3, model 2\u0026thinsp;+\u0026thinsp;education, HD vintages, Dialysis frequency; Model 4, model 3\u0026thinsp;+\u0026thinsp;uric acid, creatinine, potassium, phosphorus, high density lipoprotein(HDL).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e depicts the relationship between NPS and MMSE score. When regarded as a continuous variable, NPS (\u003cem\u003eβ\u003c/em\u003e=-0.178, 95% CI -0.321 - -0.035, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015) were significantly associated with lower MMSE scores. After adjusting Model 4, patients were further grouped by the increasing Naples scores (groups 0\u0026ndash;2), Compared to those in the NPS 0\u0026ndash;1 score group, those with 4 score group was associated with an additional 0.68 faster cognitive decline (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of NPS with MMSE score, using linear regression analysis among hemodialysis patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVarible\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eMode 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003eModel 4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eβ(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eβ(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCategorical varible\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2月3日\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.246(-0.718,-0.227)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.124(-0.578,-0.330)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.592\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.137(-0.590,-0.317)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-0.210(-0.663,-0.244)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.365\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.823(-1.344,-0.302)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.596(-1.098,-0.094)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.607(-1.110,-0.106)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-0.681(-1.186,-0.176)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eContinuous variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNPS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.226(-0.373,-0.080)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.154(-0.29,-0.013)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.159(-0.300,-0.018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-0.178(-0.321,-0.035)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003eNote: P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Abbreviations: β Unstandardized coefficient;CI: confidence interval༛MMSE Mini-mental state examination. Model 1, unadjusted; Model 2, model 1\u0026thinsp;+\u0026thinsp;age, sex, BMI, Hypertension, alcohol, diabetes mellitus, smoke, SBP1, DBP1,CVD; Model 3, model 2\u0026thinsp;+\u0026thinsp;education, HD vintages, Dialysis frequency; Model 4, model 3\u0026thinsp;+\u0026thinsp;uric acid, creatinine, potassium, phosphorus, high density lipoprotein(HDL).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThis study further explored the relationship between NPS and the incidence of dementia (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The finding indicated that NPS had higher risk of dementia with multivariate-adjusted ORs of 1.153 (95% CI 1.035\u0026ndash;1.286, p\u0026thinsp;=\u0026thinsp;0.010).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCox regression analyses for incident dementia according to NPS\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVarible\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eMode 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003eModel 4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCategorical varible\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.098(0.787\u0026ndash;1.562)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.591\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.054(0.747\u0026ndash;1.515)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.770\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.066(0.754\u0026ndash;1.533)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.111(0.784\u0026ndash;1.603)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.563\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.568(1.098\u0026ndash;2.277)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.459(1.008\u0026ndash;2.144)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.477(1.019\u0026ndash;2.173)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.538(1.055\u0026ndash;2.276)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eContinuous variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNPS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.140(1.026\u0026ndash;1.270)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.137(1.023\u0026ndash;1.265)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.140(1.026\u0026ndash;1.270)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.153(1.035\u0026ndash;1.286)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003eNote: P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Abbreviations: OR: odds ratio; CI: confidence interval; Model 1, unadjusted; Model 2, model 1\u0026thinsp;+\u0026thinsp;age, sex, BMI, Hypertension, alcohol, diabetes mellitus, smoke, SBP1, DBP1,CVD; Model 3, model 2\u0026thinsp;+\u0026thinsp;education, HD vintages, Dialysis frequency; Model 4, model 3\u0026thinsp;+\u0026thinsp;uric acid, creatinine, potassium, phosphorus, high density lipoprotein(HDL).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analyses of association between NPS and incident CI\u003c/h2\u003e \u003cp\u003eAS show in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e(A). A stronger association between NPS and incident CI was found among patients aged\u0026thinsp;\u0026lt;\u0026thinsp;65 years (OR 1.21, 1.10\u0026ndash;1.35, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), low educational level (OR 1.13, 1.03\u0026ndash;1.23, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), under 3 times HD frequency (OR 1.11, 1.01\u0026ndash;1.22, P\u0026thinsp;=\u0026thinsp;0.026), hypertension history (OR 1.16, 1.05\u0026ndash;1.27, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001),no-diabetes mellitus history(OR 1.13, 1.01\u0026ndash;1.25, P\u0026thinsp;=\u0026thinsp;0.03), CVD history (OR 1.16, 1.06\u0026ndash;1.27, P\u0026thinsp;=\u0026thinsp;P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Significant interaction effect of sex, age, education, CVD on the NPS-CI was observed (all P for interaction\u0026thinsp;\u0026lt;\u0026thinsp;0.001)respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analyses of association between NPS and incident dementia\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e(B) shows. A stronger association between NPS and incident dementia was found among patients male(OR 1.17, 1.01\u0026ndash;1.37, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.04), aged\u0026thinsp;\u0026lt;\u0026thinsp;65 years (OR 1.25, 1.09\u0026ndash;1.44, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.002), low educational leve (OR 1.15, 1.03\u0026ndash;1.28, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.014), under 3 times HD frequency (OR 1.52, 1.11\u0026ndash;2.22, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.011), hypertension history (OR 1.20, 1.07\u0026ndash;1.36, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.003), diabetes mellitus history(OR 1.24, 1.03\u0026ndash;1.50, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.023), no-CVD history(OR 1.19,1.06\u0026ndash;1.33, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.004). Significant interaction effect of sex,education, HD prequency, CVD on the NPS-dementia was observed (\u003cem\u003ep\u003c/em\u003e for interaction 0.004, 0.007, 0.024, \u0026lt;\u0026thinsp;0.001 respectively).\u003c/p\u003e \u003c/div\u003e "},{"header":"Discussion","content":"\u003cp\u003eTo our knowledge, the present study is the first study to evaluate the longitudinal associations between NPS and incident CI in hemodialysis patients. Our findings indicate that higher NPS scores were associated with lower MMSE scores, and an increased incidence of CI. Furthermore, NPS was found to be independently associated with incident CI in hemodialysis patients, even after adjusting for Model4. Sex, age, education, CVD had an interactive role in the association between NPS and incident of CI. Sex, education, HD frequency, CVD had an interactive role in the association between NPS and incident dementia. Similar with the previous studies, malnutrition and inflammation leads to cognitive decline in hemodialysis patients\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. NPS as a comprehensive measure of inflammation and nutritional biomarkers, has been used as a prognostic factor in many cancers and acute kidney disease\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. The inflammation and nutritional are closely linked with CI, with each component independently associated with CI. However, this inflammatory scoring system has not been explored in CI, we propose investigating the relationship between nutritional status and CI, particularly in hemodialysis patients.\u003c/p\u003e \u003cp\u003eMalnutrition is highly prevalent in HD patients. The link between malnutrition with CI has been demonstrated in several study\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. The causes of malnutrition are complex and can be attributed to non-iatrogenic and iatrogenic factors. Albumin level is a sensitive method for identifying patients at risk for malnutrition\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Albumin serves as a marker for malnutrition and also reflects various non-nutritional factors that frequently occur among HD patients, including inflammation, anemia, dialysate losses, and hydration status\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Serum albumin has the ability to withstand both exogenous and endogenous oxidants, and a reduction in its levels may lead to an imbalance in oxidation and antioxidation processes, potentially resulting in cognitive impairment\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. However, albumin concentrations can be affected by age, liver function, comorbidities, inflammation and alterations in body fluid volume, particularly in HD patients\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. Several authors have proposed adding plasma cholesterol levels as a means to enhance the assessment of nutritional status\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. The levels of TC,LDL and HDL in patients with CI are notable lower compared to those with normal cognitive function\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Moreover, increasing evidences strongly suggests that a lack of cholesterol in brain cellular could contribute to AD-related pathology. Neuronal morphology, function, and synaptic transmission may rely on substantial amounts of cholesterol for maintenance, as it serves as a crucial component of cell membranes and a regulator of signaling molecules\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eChronic inflammation is common in patients undergoing HD. Numerous studies have demonstrated that the detrimental effect of elevated inflammatory status on the cognitive abilities\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e, particularly in CKD and HD patients. NLR has been identified as being in closely associated with cognitive ability and various mental states. In their study, Zi-Wei Yu et al. observed a higher neutrophil count and a lower lymphocyte count in the group with mild cognitive impairment compared to the group with normal cognitive function\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Another study conducted on elderly individuals in Northeast China, revealed a positive correlation between the NLR and the presence of Alzheimer's disease (AD) and MCI, and the NLR was helpful in distinguishing normal cognitive function from AD or MCI\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e.A study focus on elderly patients with esophageal cancer, initially discovered a significant correlation between postoperative levels of NLR and MMSE scores\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Fang et al. showed that a high NLR was associated with poor visual memory and visuospatial performance\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. Recent evidence suggested that lower lymphocyte count could predict ApoE \"4-related cognitive decline in Parkinson\u0026rsquo;s disease(PD)\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e and associated with an increased risk of subsequent PD diagnosis\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. In the context of the innate immune response, monocytes are crucial in serving as the primary defense against pathogens.Research findings, increases in peripheral soluble CD163 and CD14 remain markers commonly associated with cognitive impairment\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. In HIV-uninfected individuals, elevated levels of intermediate monocytes may serve as a potential biomarker for distinguishing between individuals presenting with depressive symptoms and those who do not exhibit such symptoms\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe precise pathophysiological mechanism linking the NLR and cognitive impairment remains uncertain.Neutrophils are known to combat pathogens through phagocytosis and the ingestion of cellular debris, releasing inflammatory factors from granules and vesicles upon activation\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. In the pathophysiology of neurodegenerative diseases, inflammation is a key factor. Persistent inflammation can cause vascular dysfunction, leading to compromised cerebral blood flow and oxygenation. Prolonged inflammation may result in adverse outcomes such as neuronal dysfunction, synaptic degeneration, and ultimately neuronal death, which can impact cognitive functions\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. However, activated neutrophils have been shown to not only activate microglia and release neurotoxic substances, but also disrupt the blood-brain barrier through the promotion of reactive oxygen species (ROS) release. Additionally, activated neutrophils have been found to stimulate T lymphocytes by enhancing antigen presentation, ultimately resulting in neuroinflammation and neuronal damage\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. Studies have shown that lymphocyte infiltration into the ischemic brain persists for a minimum of 72 days following the onset of a stroke, indicating a substantial role of lymphocytes in post-stroke cognitive impairment (PSCI). This suggests that therapeutic strategies aimed at depleting CD4\u0026thinsp;+\u0026thinsp;T cells may be a promising approach for treatment\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe Naples prognostic score, a composite index of inflammatory and nutritional markers, has been previously investigated for its prognostic value in cancer patients\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. The NPS incorporates three leukocyte subtypes, as well as albumin and cholesterol, suggesting that the combined effects may be more advantageous than those of the individual components. Our results demonstrate NPS has a predictive effect on cognitive function, both as a continuous indicator and a categorical indicator. The elemental indicators of the NPS are frequently utilized in clinical settings and are relatively straightforward to compute. The early calculation of the score could theoretically assist in identifying individuals who may benefit from preventative interventions.\u003c/p\u003e \u003cp\u003eSubgroup analysis indicates that the effect of NPS on CI was more pronounced in male, under 65 years, low educational levels,without diabetes and CVD in HD patients.These findings suggest potential associations with gender-specific physiological, psychological, or social factors that may contribute to suboptimal nutrition or inflammation in the absence of timely recognition and intervention. Individuals under 65 years may exhibit relatively better physical health and being more sensitive to physiological and psychological responses to nutrition or inflammation, the negative impact of NPS on cognitive function may be more significant. Patients with lower education may have limited cognitive reserves, information processing abilities, potentially exacerbating the negative effects of NPS. Additionally, the presence of diabetes and cerebrovascular diseases can further impair cognitive function, in patients without these comorbidities, NPS may play a more prominent role in affecting cognitive function. Our study revealed that except male, low education level, and non CVD, a significant association between NPS and dementia in patients who receive hemodialysis less than three times per week. These findings provide us with a new perspective on the relationship between NPS and CI in HD patients.\u003c/p\u003e \u003cp\u003eThis study contributes novel findings regarding the relationship between NPS and cognitive impairment in patients with HD. However, it is important to acknowledge several limitations. Firstly, the study had a small sample size and a relatively limited duration for longitudinal analysis. Secondly, the diagnosis of cognitive impairment was based solely on the Mini-Mental State Examination (MMSE), which may not provide as much diagnostic certainty as comprehensive neuropsychological test batteries. Thirdly, the study did not investigate other inflammatory markers such as C-reactive protein, interleukins, and erythrocyte sedimentation rate.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, we used a prediction model based on NPS and evaluated the incident of CI.we found that in patients with HD, higher baseline NPS is associated with the occurrence of CI. This study provides a justification to include assessment of malnutrition and inflammation using NPS as part of cognitive function assessment. NPS gives a comprehensive evaluation of the nutritional and inflammatory status of HD patients,we are looking forward to conduct prospective studies to further validate our findings.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYan Ran：investigation, data curation, methodology, validation, writing\u0026ndash; original-draft, writing\u0026ndash;review \u0026amp; editing. Yuqi Yang：investigation, methodology, conceptualization. Yanzhe Peng, Jingjing Da, Zuping Qian, Jing Yuan: investigation, conceptualization. Yan Zha : project administration, conceptualization, supervision. All authors have read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eScience and Technology Cooperation Foundation of Guizhou Province (ZK [2021]381).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data used in this study are publicly available. To assess the data, please contact the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study followed the Declaration of Helsinki and received informed consent approval from the Institutional Review Board of Guizhou Provincial People\u0026rsquo;s Hospital (Approval Number: (2020)208). All participants provided written informed consent.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003evan Zwieten A, Wong G, Ruospo M, et al. Prevalence and patterns of cognitive impairment in adult hemodialysis patients: the COGNITIVE-HD study. Nephrol Dial Transplant. 2018. 33(7): 1197-1206.\u003c/li\u003e\n\u003cli\u003eYang Y, Da J, Li Q, Long Y, Yuan J, Zha Y. The Impact of Malnutrition, Inflammation on Cognitive Impairment in Hemodialysis Patients: A Multicenter Study. Kidney Blood Press Res. 2022. 47(12): 711-721.\u003c/li\u003e\n\u003cli\u003eRussell B, Zager Y, Mullin G, et al. Naples Prognostic Score to Predict Postoperative Complications After Colectomy for Diverticulitis. Am Surg. 2023. 89(5): 1598-1604.\u003c/li\u003e\n\u003cli\u003eKarakoyun S, Cagdas M, Celik AI, et al. Predictive Value of the Naples Prognostic Score for Acute Kidney Injury in ST-Elevation Myocardial Infarction Patients Undergoing Primary Percutaneous Coronary Intervention. Angiology. 2024. 75(6): 576-584.\u003c/li\u003e\n\u003cli\u003eAyta\u0026ccedil; İ, G\u0026uuml;ven Ayta\u0026ccedil; B, Kilci O, \u0026Ouml;l\u0026ccedil;\u0026uuml;c\u0026uuml;oğlu E. Naples Prognostic Score for Graft Functions After Renal Transplantation: A Retrospective Analysis. Ann Transplant. 2023. 28: e942007.\u003c/li\u003e\n\u003cli\u003eXu B, Zhu J, Wang R, et al. Clinical Implications of Naples Prognostic Score for Patients with Resected Cholangiocarcinoma: A Real-World Experience. J Inflamm Res. 2024. 17: 655-667.\u003c/li\u003e\n\u003cli\u003eZhong C, Bu X, Xu T, et al. Serum Matrix Metalloproteinase-9 and Cognitive Impairment After Acute Ischemic Stroke. J Am Heart Assoc. 2018. 7(1): e007776.\u003c/li\u003e\n\u003cli\u003eNg TP, Feng L, Nyunt MS, et al. Metabolic Syndrome and the Risk of Mild Cognitive Impairment and Progression to Dementia: Follow-up of the Singapore Longitudinal Ageing Study Cohort. JAMA Neurol. 2016. 73(4): 456-63.\u003c/li\u003e\n\u003cli\u003eRotondi S, Tartaglione L, Pasquali M, et al. Association between Cognitive Impairment and Malnutrition in Hemodialysis Patients: Two Sides of the Same Coin. Nutrients. 2023. 15(4): 813.\u003c/li\u003e\n\u003cli\u003eZhang K, Gao J, Chen J, et al. MICS, an easily ignored contributor to arterial calcification in CKD patients. Am J Physiol Renal Physiol. 2016. 311(4): F663-F670.\u003c/li\u003e\n\u003cli\u003eFriedman AN, Fadem SZ. Reassessment of albumin as a nutritional marker in kidney disease. J Am Soc Nephrol. 2010. 21(2): 223-30.\u003c/li\u003e\n\u003cli\u003eWang L, Wang F, Liu J, Zhang Q, Lei P. Inverse Relationship between Baseline Serum Albumin Levels and Risk of Mild Cognitive Impairment in Elderly: A Seven-Year Retrospective Cohort Study. Tohoku J Exp Med. 2018. 246(1): 51-57.\u003c/li\u003e\n\u003cli\u003eTokunaga R, Sakamoto Y, Nakagawa S, et al. CONUT: a novel independent predictive score for colorectal cancer patients undergoing potentially curative resection. Int J Colorectal Dis. 2017. 32(1): 99-106.\u003c/li\u003e\n\u003cli\u003eToyokawa T, Kubo N, Tamura T, et al. The pretreatment Controlling Nutritional Status (CONUT) score is an independent prognostic factor in patients with resectable thoracic esophageal squamous cell carcinoma: results from a retrospective study. BMC Cancer. 2016. 16(1): 722.\u003c/li\u003e\n\u003cli\u003eDietschy JM, Turley SD. Thematic review series: brain Lipids. Cholesterol metabolism in the central nervous system during early development and in the mature animal. J Lipid Res. 2004. 45(8): 1375-97.\u003c/li\u003e\n\u003cli\u003eOzturk HM, Ogan N, Erdogan M, Akpinar EE, Ilgar C, Ozturk S. The association between total cholesterol and cognitive impairment in chronic obstructive pulmonary disease patients. Prostaglandins Other Lipid Mediat. 2023. 164: 106697.\u003c/li\u003e\n\u003cli\u003eBauer IE, Pascoe MC, Wollenhaupt-Aguiar B, Kapczinski F, Soares JC. Inflammatory mediators of cognitive impairment in bipolar disorder. J Psychiatr Res. 2014. 56: 18-27.\u003c/li\u003e\n\u003cli\u003eYu ZW, Wang Y, Li X, Tong XW, Zhang YT, Gao XY. Association between the neutrophil to lymphocyte ratio and mild cognitive impairment in patients with type 2 diabetes. Aging Clin Exp Res. 2023. 35(6): 1339-1345.\u003c/li\u003e\n\u003cli\u003eDong X, Nao J, Shi J, Zheng D. Predictive Value of Routine Peripheral Blood Biomarkers in Alzheimer\u0026apos;s Disease. Front Aging Neurosci. 2019. 11: 332.\u003c/li\u003e\n\u003cli\u003eZhao J, Dai T, Ding L, et al. Correlation between neutrophil/lymphocyte ratio, platelet/lymphocyte ratio and postoperative cognitive dysfunction in elderly patients with esophageal cancer. Medicine (Baltimore). 2023. 102(10): e33233.\u003c/li\u003e\n\u003cli\u003eFang Y, Doyle MF, Alosco ML, et al. Cross-Sectional Association Between Blood Cell Phenotypes, Cognitive Function, and Brain Imaging Measures in the Community-Based Framingham Heart Study. J Alzheimers Dis. 2022. 87(3): 1291-1305.\u003c/li\u003e\n\u003cli\u003eTsukita K, Sakamaki-Tsukita H, Takahashi R. Lower Circulating Lymphocyte Count Predicts ApoE \u0026epsilon;4-Related Cognitive Decline in Parkinson\u0026apos;s Disease. Mov Disord. 2021. 36(12): 2969-2971.\u003c/li\u003e\n\u003cli\u003eJensen MP, Jacobs BM, Dobson R, et al. Lower Lymphocyte Count is Associated With Increased Risk of Parkinson\u0026apos;s Disease. Ann Neurol. 2021. 89(4): 803-812.\u003c/li\u003e\n\u003cli\u003ePulliam L, Gascon R, Stubblebine M, McGuire D, McGrath MS. Unique monocyte subset in patients with AIDS dementia. Lancet. 1997. 349(9053): 692-5.\u003c/li\u003e\n\u003cli\u003eLynall ME, Turner L, Bhatti J, et al. Peripheral Blood Cell-Stratified Subgroups of Inflamed Depression. Biol Psychiatry. 2020. 88(2): 185-196.\u003c/li\u003e\n\u003cli\u003eSatoh A, Imai SI, Guarente L. The brain, sirtuins, and ageing. Nat Rev Neurosci. 2017. 18(6): 362-374.\u003c/li\u003e\n\u003cli\u003eKure CE, Rosenfeldt FL, Scholey AB, et al. Relationships Among Cognitive Function and Cerebral Blood Flow, Oxidative Stress, and Inflammation in Older Heart Failure Patients. J Card Fail. 2016. 22(7): 548-59.\u003c/li\u003e\n\u003cli\u003eSayed A, Bahbah EI, Kamel S, Barreto GE, Ashraf GM, Elfil M. The neutrophil-to-lymphocyte ratio in Alzheimer\u0026apos;s disease: Current understanding and potential applications. J Neuroimmunol. 2020. 349: 577398.\u003c/li\u003e\n\u003cli\u003eWeitbrecht L, Berchtold D, Zhang T, et al. CD4(+) T cells promote delayed B cell responses in the ischemic brain after experimental stroke. Brain Behav Immun. 2021. 91: 601-614.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Naples prognostic score(NPS), cognitive impairment(CI), hemodialysis, dementia","lastPublishedDoi":"10.21203/rs.3.rs-4773830/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4773830/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ebackground\u003c/h2\u003e \u003cp\u003eNutrition and inflammatory status is prevalent in hemodialysis(HD) patients, which is relates to the incident of cognitive impairment(CI). Naples prognostic score(NPS) is a comprehensive measure of patients\u0026rsquo; inflammation and nutritional status. This study is to investigate the effect of Naples prognostic score on the risk of incident cognitive impairment in HD patients.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e Two thousand seven hundred twenty-five HD patients were recruited and NPS score obtained based on albumin, total cholesterol(TC), lymphocytes, neutrophils, and monocytes. Cognitive function was assessed with Mini-Mental State Examination score (MMSE). Multiple Cox regression models, interactive analyses were conducted.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong 2725 HD patients (33.8%) experienced incident CI, the mean MMSE score was 26.87\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9. After adjusting clinical confounders, the association remained statistically significant, higher NPS was independently associated with increased rate of CI both as a continuous variable (OR\u0026thinsp;=\u0026thinsp;1.106, 95% CI 1.018\u0026ndash;1.202, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.019) and as a categorized variable(OR\u0026thinsp;=\u0026thinsp;1.552, 95%CI: 1.146\u0026ndash;2.110, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015). The analysis illustrates a negative correlation between NPS and MMSE scores. This relationship was observed both as a continuous variable (\u003cem\u003eβ\u003c/em\u003e=-0.178, 95% CI -0.321 - -0.035, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015) and as a categorized variable, compared to those in the NPS 0\u0026ndash;1 score group, those with 4 score group was associated with an additional 0.68 faster cognitive decline (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008). Further explored the relationship between NPS and the incidence of dementia, finding that NPS had higher risk of dementia with multivariate-adjusted ORs of 1.153 (95% CI 1.035\u0026ndash;1.286, p\u0026thinsp;=\u0026thinsp;0.010). Subgroup analysis showed that the effect of NPS on CI was more pronounced in male, under 65 years, low educational levels, without diabetes and Cerebrovascular disease(CVD). Except male, low education level, and non CVD, in patients who HD frequency under 3 times per week the association between NPS and dementia was more significant.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eNPS was independently associated with cognitive impairment in HD patients.\u003c/p\u003e","manuscriptTitle":"The impact of Naples prognostic score on cognitive impairment in hemodialysis patients-A multicenter study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-19 15:46:32","doi":"10.21203/rs.3.rs-4773830/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9367717b-578a-482e-a4cd-db9edd318d78","owner":[],"postedDate":"August 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-02T20:38:18+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-19 15:46:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4773830","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4773830","identity":"rs-4773830","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}