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The objective of this study was to investigate the efficacy and safety of intradialytic parenteral nutrition (IDPN) using ENEFLUID® (310 kcal, 550 mL) in mild-moderate malnutrition patients receiving maintenance hemodialysis. A total of 40 adult patients with a Nutritional Risk Index-Japanese Hemodialysis (NRI-JH) score of 5-10 were enrolled in this multicenter, randomized, open-label study. Patients in the intervention group received IDPN using ENEFLUID® via the dialysis circuit 3 times a week for 12 weeks; those in the control group did not. The primary endpoint was change in serum transthyretin (TTR). The secondary endpoints were changes in nutritional laboratory tests, nutritional parameters, food intake, plasma amino acids, and blood glucose. For both groups, mean age (72.1±11.4 years) and BMI (20.3±3.0), and median NRI-JH score [7.0 (interquartile range, 6-8)], did not differ. One patient withdrew before intervention, leaving 20 intervention and 19 control patients. Mean (95% confidence interval) change in serum TTR (mg/dL) at 12 weeks did not differ between groups: Intervention, 1.0 (-1.1-3.2); Control, -0.3 (-2.4-1.9); Intragroup difference, 1.3 (-1.7-4.3); P = 0.41. The values reflecting protein intake at 12 weeks compared to those on the study initiation day increased in the intervention group [the changes of blood urea nitrogen, 9.4 (2.6-16.2) mg/dL; P = 0.007, and normalized protein catabolic rate, 0.10 (0.02-0.18) g/kg/day; P = 0.02]. Mean food protein intake (g/kg/day) at 12 weeks increased in the intervention group and decreased in the control group, and differed between groups: Intervention, 0.12 (-0.03-0.28); Control, -0.18 (-0.43-0.08); Inter-group difference, 0.30 (0.00-0.60); P = 0.050. No adverse events occurred. In patients with mild to moderate malnutrition receiving ENEFLUID® for 12 weeks as IDPN, serum TTR was not improved, decreases in protein intake was mitigated, no adverse events occurred. Trial registration Name of the registry: Japan Registry of Clinical Trials Registration number: jRCTs031220296.

There are cases in which CKD progression is difficult to evaluate, because the changes in estimated glomerular filtration rate (eGFR) and proteinuria sometimes show opposite directions as CKD progresses. Indices and models that enable the easy and accurate risk prediction of end-stage-kidney disease (ESKD) are indispensable to CKD therapy. In this study, we investigated whether a CKD stage coordinate transformed into a vector field (CKD potential model) accurately predicts ESKD risk. Meta-analysis of large-scale cohort studies of CKD patients in PubMed was conducted to develop the model. The distance from CKD stage G2 A1 to a patient's data on eGFR and proteinuria was defined as r. We developed the CKD potential model on the basis of the data from the meta-analysis of three previous cohort studies: ESKD risk = exp(r). Then, the model was validated using data from a cohort study of CKD patients in Japan followed up for three years (n = 1,564). Moreover, the directional derivative of the model was developed as an index of CKD progression velocity. For ESKD prediction in three years, areas under the receiver operating characteristic curves (AUCs) were adjusted for baseline characteristics. Cox proportional hazards models with spline terms showed the exponential association between r and ESKD risk (p

BackgroundInformation of short-term prognosis after hemodialysis (HD) introduction is important for elderly patients with chronic kidney disease (CKD) and their families choosing a modality of renal replacement therapy. Therefore, we developed a risk score to predict early mortality in incident elderly Japanese hemodialysis patients.Materials and methodsWe analyzed data of incident elderly HD patients from a nationwide cohort study of the Japanese Society for Dialysis Therapy Renal Data Registry (JRDR) to develop a prognostic risk score. Candidate risk factors for early death within 1 year was evaluated using multivariate logistic regression analysis. The risk score was developed by summing up points derived from parameter estimate values of independent risk factors. The association between risk score and early death was tested using Cox proportional hazards models. This risk score was validated twice by using an internal validation cohort derived from the JRDR and an external validation cohort collected for this study.ResultsUsing the development cohort (n = 2,000), nine risk factors were retained in the risk score: older age (>85), yes = 2, no = 0; sex, male = 2, female = 0; lower body mass index (2.0 mg/dL), yes = 2, no = 0. In the internal and external validation cohorts (n = 739, 140, respectively), the medium- and high-risk groups (total score, 6 to 10 and 11 or more, respectively) showed significantly higher risk of early death than the low-risk group (total score, 0 to 5) (pConclusionWe developed a prognostic risk score predicting early death within 1 year in incident elderly Japanese HD patients, which may help detect elderly patients with a high-risk of early death after HD introduction.

Although the economic burden of multimorbidity is a growing global challenge, the contribution of multimorbidity in patients with high medical expenses remains unclear. We aimed to clarify multimorbidity patterns that have a large impact on medical costs in the Japanese population. We conducted a cross-sectional study using health insurance claims data provided by the Japan Health Insurance Association. Latent class analysis (LCA) was used to identify multimorbidity patterns in 1,698,902 patients who had the top 10% of total medical costs in 2015. The present parameters of the LCA model included 68 disease labels that were frequent among this population. Moreover, subgroup analysis was performed using a generalized linear model (GLM) to assess the factors influencing annual medical cost and 5-year mortality. As a result of obtaining 30 latent classes, the kidney disease class required the most expensive cost per capita, while the highest portion (28.6%) of the total medical cost was spent on metabolic syndrome (MetS) classes, which were characterized by hypertension, dyslipidemia, and type 2 diabetes. GLM applied to patients with MetS classes showed that cardiovascular diseases or complex conditions, including malignancies, were powerful determinants of medical cost and mortality. MetS was classified into 7 classes based on real-world data and accounts for a large portion of the total medical costs. MetS classes with cardiovascular diseases or complex conditions, including malignancies, have a significant impact on medical costs and mortality.

Chronic kidney disease (CKD) patients have high risks of end-stage kidney disease (ESKD) and pre-ESKD death. Therefore, accurately predicting these outcomes is useful among CKD patients, especially in those who are at high risk. Thus, we evaluated whether a machine-learning system can predict accurately these risks in CKD patients and attempted its application by developing a Web-based risk-prediction system. We developed 16 risk-prediction machine-learning models using Random Forest (RF), Gradient Boosting Decision Tree, and eXtreme Gradient Boosting with 22 variables or selected variables for the prediction of the primary outcome (ESKD or death) on the basis of repeatedly measured data of CKD patients (n = 3,714; repeatedly measured data, n = 66,981) in their electronic-medical records. The performances of the models were evaluated using data from a cohort study of CKD patients carried out over 3 years (n = 26,906). One RF model with 22 variables and another RF model with 8 variables of time-series data showed high accuracies of the prediction of the outcomes and were selected for use in a risk-prediction system. In the validation, the 22- and 8-variable RF models showed high C-statistics for the prediction of the outcomes: 0.932 (95% CI 0.916, 0.948) and 0.93 (0.915, 0.945), respectively. Cox proportional hazards models using splines showed a highly significant relationship between the high probability and high risk of an outcome (p

BackgroundAppropriate maxillofacial growth and development evaluation is important for effective orthodontic treatment. Growth evaluation is based on physiological age determined by individual development, but not chronological age. One strategy for determining physiological age is using the cervical vertebral bone age.ObjectivesThis study aimed to clarify the standard size of the upper and lower jawbones in Japanese patients using the cervical vertebral maturation stages (CVMS) as an index and clarify the growth pattern. And to use the cervical spine age as a diagnostic aid in orthodontic treatment.Material and methodsRandom sampling was performed from the outpatients who visited the Orthodontics department, Tokyo Medical and Dental University Dental Hospital, and 400 patients were enrolled before treatment. Lateral cephalometric radiographs were obtained to measure the height and length of the mandible and the maxilla length with cephalometric analysis. Standard values were calculated for each cervical-spine-age group to analyze changes during mandibular and maxillary growth. Furthermore, we compared the differences between males and females. The Kruskal-Wallis test was used to compare cervical-spine-age groups, and the Steel-Dwass test was used for multiple comparisons. The reliability of CVMS was confirmed by calculating the weighted kappa coefficient (κ).Resultsκ for the degree of intra-evaluator agreement and the degree of the inter-evaluator agreement were calculated, and both indicated almost perfect agreement. We found that the distance between the anterior nasal spine (ANS) and posterior nasal spine (PNS) (i.e., ANS-PNS) increased significantly between CVMS II and CVMS III in males. The distance between Articulare (Ar) and Gonion (Go) (i.e., Ar-Go) and the distance between Go and Pogonion (Pog) (i.e., Go-Pog) increased significantly between CVMS III and CVMS IV in males.ConclusionThe findings suggested that CVMS is a reliable indicator of the growth stage of the maxilla and mandible.

Serum zinc (Zn) levels tend to be low in chronic kidney disease (CKD) patients. This cohort study was conducted to investigate the relationship between zinc deficiency and CKD progression. Patients were classified into two groups based on Zn levels < 60 μg/dl (low-Zn group, n = 160) and ≥ 60 μg/dl (high-Zn group, n = 152). The primary outcome was defined as end-stage kidney disease (ESKD) or death and was examined over a 1-year observation period. Overall, the mean Zn level was 59.6 μg/dl and the median eGFR was 20.3 ml/min/1.73 m2. The incidence of the primary outcome was higher in the low-Zn group (p

BACKGROUND:Although dialysis patients are at a high risk of death, it is difficult for medical practitioners to simultaneously evaluate many inter-related risk factors. In this study, we evaluated the characteristics of hemodialysis patients using machine learning model, and its usefulness for screening hemodialysis patients at a high risk of one-year death using the nation-wide database of the Japanese Society for Dialysis Therapy. MATERIALS AND METHODS:The patients were separated into two datasets (n = 39,930, 39,930, respectively). We categorized hemodialysis patients in Japan into new clusters generated by the K-means clustering method using the development dataset. The association between a cluster and the risk of death was evaluated using multivariate Cox proportional hazards models. Then, we developed an ensemble model composed of the clusters and support vector machine models in the model development phase, and compared the accuracy of the prediction of mortality between the machine learning models in the model validation phase. RESULTS:Average age of the subjects was 65.7±12.2 years; 32.7% had diabetes mellitus. The five clusters clearly distinguished the groups on the basis of their characteristics: Cluster 1, young male, and chronic glomerulonephritis; Cluster 2, female, and chronic glomerulonephritis; Cluster 3, diabetes mellitus; Cluster 4, elderly and nephrosclerosis; Cluster 5, elderly and protein energy wasting. These clusters were associated with the risk of death; Cluster 5 compared with Cluster 1, hazard ratio 8.86 (95% CI 7.68, 10.21). The accuracy of the ensemble model for the prediction of 1-year death was 0.948 and higher than those of logistic regression model (0.938), support vector machine model (0.937), and deep learning model (0.936). CONCLUSIONS:The clusters clearly categorized patient on their characteristics, and reflected their prognosis. Our real-world-data-based machine learning system is applicable to identifying high-risk hemodialysis patients in clinical settings, and has a strong potential to guide treatments and improve their prognosis.

BackgroundThe Japan Chronic Kidney Disease Database (J-CKD-DB) is a nationwide clinical database of patients with chronic kidney disease (CKD) based on electronic health records. The objective of this study was to assess the prevalences of hyperuricemia and electrolyte abnormalities in Japanese patients with CKD.MethodsIn total, 35,508 adult outpatients with estimated glomerular filtration rates of 5-60 ml/min/1.73 m2 in seven university hospitals were included this analysis. The proportions of patients with CKD stages G3b, G4, and G5 were 23.5%, 7.6%, and 3.1%, respectively.ResultsLogistic regression analysis showed that prevalence of hyperuricemia was associated with CKD stages G3b (adjusted odds ratio [95% confidence interval]: 2.12 [1.90-2.37]), G4 (4.57 [3.92-5.32]), and G5 (2.25 [1.80-2.80]). The respective prevalences of hyponatremia, hypercalcemia, hyperphosphatemia, and narrower difference between serum sodium and chloride concentrations were elevated in patients with CKD stages G3b, G4, and G5, compared with those prevalences in patients with CKD stage G3a. The prevalences of hyperkalemia were 8.3% and 11.6% in patients with CKD stages G4 and G5, respectively. In patients with CKD stage G5, the proportions of patients with optimal ranges of serum uric acid, potassium, corrected calcium, and phosphate were 49.6%, 73.5%, 81.9%, and 56.1%, respectively.ConclusionsWe determined the prevalences of hyperuricemia and electrolyte abnormalities in Japanese patients with CKD using data from a nationwide cohort study.

BackgroundThe Japan Chronic Kidney Disease Database (J-CKD-DB) is a nationwide clinical database of patients with chronic kidney disease (CKD) based on electronic health records. The objective of this study was to assess the prevalence of anemia and the utilization rate of erythropoiesis-stimulating agents (ESAs) in Japanese patients with CKD.MethodsIn total, 31,082 adult outpatients with estimated glomerular filtration rates of 5-60 ml/min/1.73 m2 in seven university hospitals were included this analysis. The proportions of patients with CKD stages G3b, G4, and G5 were 23.5%, 7.6%, and 3.1%, respectively.ResultsThe mean (standard deviation) hemoglobin level of male patients was 13.6 (1.9) g/dl, which was significantly higher than the mean hemoglobin level of female patients (12.4 (1.6) g/dl). The mean (standard deviation) hemoglobin levels were 11.4 (2.1) g/dl in patients with CKD stage G4 and 11.2 (1.8) g/dl in patients with CKD stage G5. The prevalences of anemia were 40.1% in patients with CKD stage G4 and 60.3% in patients with CKD stage G5. Logistic regression analysis showed that diagnoses of CKD stage G3b (adjusted odds ratio [95% confidence interval]: 2.32 [2.09-2.58]), G4 (5.50 [4.80-6.31]), and G5 (9.75 [8.13-11.7]) were associated with increased prevalence of anemia. The utilization rates of ESAs were 7.9% in patients with CKD stage G4 and 22.4% in patients with CKD stage G5.ConclusionsWe determined the prevalence of anemia and utilization rate of ESAs in Japanese patients with CKD using data from a nationwide cohort study.

BACKGROUND:Protein energy wasting (PEW) is a risk factor for death. However, the cutoff vales for PEW are not optimized for early identification of hemodialysis patients with malnutrition. We evaluated the prognosis of Japanese maintenance hemodialysis patients using nutritional indices optimized for them. MATERIALS AND METHODS:We analyzed data from a nation-wide prospective cohort study of the Japanese Society for Dialysis Therapy Renal Data Registry to develop and validate a nutritional risk index (n = 48349, 48349, respectively). The association of nutritional factors with one-year death was tested using Cox proportional hazards models. Their cutoff levels were determined from the hazard ratios or receiver operating characteristic curves. Then, risk index was developed using scoring models. RESULTS:Male was 61.4%; average age, 65.7±12.2 years; and diabetes mellitus, 32.8%. Four clinical factors were retained in the final model: low BMI (

In patients with chronic kidney disease (CKD), low body mass index (BMI) is associated with high mortality. This relationship in emergently hospitalized CKD patients is unknown. We investigated the association between obesity and short-term mortality in emergently admitted patients with dialysis-independent CKD (DI-CKD) with and without infection. This retrospective cohort study examined Diagnosis Procedure Combination data of 26103 emergently hospitalized DI-CKD patients. Patients were divided into 8 groups according to their BMI and the presence of infectious diseases. The primary outcome was in-hospital death within 100 days. Cox proportional hazards models adjusted for baseline characteristics showed that low BMI was associated with the outcome both in infected and in non-infected patients (reference group as non-infected and medium BMI [24-26 kg/m2] group): infected and the lowest BMI (≤20 kg/m2) group, hazard ratio (HR) 1.82 (95% confidence interval 1.51, 2.19); non-infected and the lowest BMI group, 1.39 (1.16, 1.67). When patients were stratified according to presence of diabetes mellitus (DM), patients with DM showed that low BMI was associated with the outcome both in infected and in non-infected patients, whereas in non-DM patients, this relationship was attenuated in the non-infected group. For emergently hospitalized CKD patients with infection, high BMI was associated with lower mortality irrespective of the DM status. For non-infected patients, the effects of obesity for in-hospital mortality were modified by the DM status.

Atherosclerosis is often a complication of chronic kidney disease (CKD) because of dyslipidemia and CKD-mineral and bone disorder. High-density lipoproteins (HDLs) are grouped into various subclasses composed of multiple proteins and lipids, and their transformation is altered in CKD. We investigated the roles of lipoprotein subclasses in CKD progression, and atherosclerosis, and the relationships with Klotho and fibroblast growth factor (FGF) 23.Seventy-one CKD patients were enrolled in this prospective cohort study in Japan. The proportions of cholesterol level to total cholesterol level (cholesterol proportion) and lipoprotein particle numbers in 20 lipoprotein fractions were measured by a newly developed high-performance gel permeation chromatography.Diabetic nephropathy was observed in 23.9% of the patients. The mean age was 75.0 years and estimated glomerular filtration rate (eGFR) was 17.2 ml/min./1.73m2. The lipoprotein particle numbers in small HDLs were higher in Stage 4 group than in Stage 5 group (p = 0.002). Multivariate regression analysis adjusted for baseline characteristics showed that the cholesterol proportions in very small HDLs were associated with eGFR change rate [F19 β = -17.63, p = 0.036] and ABI [F19 β = 0.047, p = 0.047] in Stage 4 group, and that serum soluble α-Klotho level was associated with the lipoprotein particle numbers in very small HDLs [F19 β = 0.00026, p = 0.012; F20 β = 0.00041, p = 0.036] in Stage 5 group.This study showed that HDL subclasses are associated with CKD progression, ABI, and Klotho level in CKD-stage-specific manner.

For hemodialysis (HD) patients, many risk factors for death are associated with each other intricately. However, they are often considered separately in clinical settings. We evaluated the maintenance HD patients' risk of death within one year from multiple risk factors simultaneously considering their interrelationships using a novel index (survival index, SI) for HD patients in the United States developed using data from the Dialysis Outcomes and Practice Patterns Study (DOPPS).We analyzed data from 3899 and 3765 patients to develop and validate SI, respectively. To predict death within one year, candidate models were developed using logistic regression models. The final model was determined by comparing the accuracy among the models for the prediction of deaths.The model included age; body mass index; serum creatinine, albumin, total cholesterol and phosphorus levels; history of cardiovascular diseases; and arteriovenous fistula use. SI showed a higher accuracy in predicting death (c-statistic, 0.739) than geriatric nutritional risk index (0.647) and serum albumin level (0.637). The probability of death predicted on the basis of SI matched the observed number of deaths. Cox proportional hazard models for time-dependent SI showed that patients with low SI had a higher risk of death than patients with high SI [reference, Group 4 (26.1≤SI)]; Group 1 (SI

BACKGROUND:The relationship between hyperuricemia and chronic kidney disease (CKD) has been found in various observational studies. Although hypouricemia is associated with cardiovascular events, it has not been established as a risk factor for CKD. We investigated the relationship between serum uric acid level and the loss of kidney function and incident CKD in healthy people. MATERIALS AND METHODS:Healthy people were enrolled in this community-based prospective cohort study, the Saitama Cardiometabolic Disease and Organ Impairment Study, Japan. The analysis was conducted on 4188 subjects followed up for at least 3 years, 3102 for 6 years and 1052 for 9 years. Their data including glomerular filtration rate (eGFR) decline were examined every three years. The outcome event was incident CKD or the decrease in eGFR by more than 25% in three years. Multivariate statistical models were adjusted for the baseline characteristics. RESULTS:The following data was obtained: mean ± SD age, male, 39.6 ± 10.4 years, female 38.4 ± 10.8 years; eGFR, male, 81.9 ± 16.4 ml/min/1.73 m2, female, 82.1 ± 17.5 ml/min/1.73 m2; serum uric acid level, male, 5.8 ± 1.2 mg/dl, female, 4.1 ± 0.9 mg/dl. Both low and high serum uric acid levels were associated with the outcome and eGFR decline in males (multivariate logistic additional additive models, linear p = 0.0001, spline p = 0.043; generalized additive models, linear p = 0.0001, spline p = 0.012). In subjects with low serum uric acid levels (male,

Obesity is associated with diabetes mellitus and cardiovascular diseases. However, it has been reported that weight loss is associated with incident chronic kidney disease (CKD) in healthy males. The purpose of this prospective cohort study is to investigate the effects of weight loss on kidney function in healthy people in terms of body mass index (BMI) and gender.A total of 8447 nondiabetic healthy people were enrolled in the Saitama Cardiometabolic Disease and Organ Impairment Study, Japan. Relationships between estimated glomerular filtration rate (eGFR) change, BMI, and BMI change were evaluated using 3D-scatter plots with spline and generalized additive models (GAMs) adjusted for baseline characteristics.The subjects were stratified into four groups according to BMI. The mean±standard deviations for males and females were, respectively, 40.11±9.49, and 40.3±9.71 years for age and 76.39±17.72 and 71.49±18.4 ml/min/1.73m2 for eGFR. GAMs showed that a decreasing BMI change (

Although lifestyle is associated with metabolic syndrome and cardiovascular diseases, there has been no sufficient evidence of lifestyles on incident chronic kidney disease (CKD). The purpose of this prospective cohort study is to investigate the effects of lifestyles on kidney function in healthy people.A total of 7473 healthy people were enrolled in this Saitama Cardiometabolic Disease and Organ Impairment Study, Japan. Data on alcohol consumption, exercise frequency, and sleep duration were collected. The outcome event was incident CKD or decrease in estimated glomerular filtration rate (eGFR) by >25% in 3 years.Subjects were classified into four groups according to body mass index and gender. Mean ± standard deviation of age was 38.8±10.5 years; eGFR, 78.1±15.2 ml/min/1.73 m2. In the male groups, multivariate logistic regression models showed that the outcome events were associated with a small amount of alcohol consumed (20 to 140 g of alcohol/week) (ref. more than 140 g of alcohol/week); non-obese male, adjusted odds ratio 1.366 (95% confidence interval, 1.086, 1.718); obese male (body mass index ≥25), 1.634 (1.160, 2.302); and with frequent exercise (twice a week or more) (ref. no exercise); non-obese male, 1.417 (1.144, 1.754); obese male, 1.842 (1.317, 2.577). Sleep duration was not associated with the outcome events.These findings suggest that, regardless of obesity, a small amount of alcohol consumed and high exercise frequency were associated with the increased risk of loss of kidney function in the male groups.