Anemia in patients of diabetic kidney disease

What is the best predictor of mortality in patients with type 2 diabetes and chronic kidney disease: mean, variability of HbA1c or HbA1c-Hemoglobin ratio?

AIM

Limitations in the measurement of glycated hemoglobin (HbA1c) in patients with type 2 diabetes (T2D) and chronic kidney disease (CKD) result in uncertainty about the best predictor of mortality among these patients. Our study aimed to determine the association between the mean and average real variability (ARV) of HbA1c, as well as HbA1c-hemoglobin (HH) ratio with mortality among patients with T2D and CKD.

MATERIALS AND METHODS

We identified 16,868 T2D patients with stage 3 or above CKD from outpatient visits during 2003-2018. We ascertained all-cause and cardiovascular mortality through linkage to Taiwan's National Death Registry. Mortality rates were estimated using the Poisson distribution, and we conducted Cox proportional hazards regressions to assess relative risks of mortality corresponding to the mean HbA1c, ARV of HbA1c and HH ratio.

RESULTS

Compared to patients with a mean HbA1c of 7.0-7.9%, a mean HbA1c < 7.0% was persistently associated with highest risk of all-cause but not cardiovascular mortality after adjusting for confounders. On the contrary, patients with HbA1c-ARV in the second to fourth quartiles and HH ratios in the higher quartiles showed increased risk of all-cause and cardiovascular mortality compared to those in the first quartiles.

CONCLUSIONS

HbA1c-ARV was more effective than mean HbA1c or HH ratio in predicting mortality in T2D patients with CKD. Apart from optimal glucose control, multidisciplinary care focusing on glycemic variability is essential for reducing mortality in these patients.

Prognostic Value of Hemoglobin Concentration on Renal Outcomes with Diabetic Kidney Disease: A Retrospective Cohort Study

Objective

Diabetic kidney disease (DKD) patients with anemia face an elevated risk of glomerular filtration rate decline. However, the association between hemoglobin and estimated Glomerular Filtration Rate (eGFR) progression remains to be elucidated.

Methods

A retrospective cohort of 815 subjects with DKD was followed from January 2010 to January 2023. A Cox proportional hazard regression model was utilized to explore the predictive role of hemoglobin in renal outcomes. Renal outcomes were defined as a composite endpoint, including a 50% decline in eGFR from baseline or progression to End-Stage Renal Disease (ESRD). To unveil any nonlinear relationship between hemoglobin and renal outcomes, Cox proportional hazard regression with cubic spline functions and smooth curve fitting was conducted. Additionally, subgroup analyses were performed to identify specific patient populations that might derive greater benefits from higher hemoglobin.

Results

Among the 815 DKD subjects, the mean age was 56.482 ± 9.924 years old, and 533 (65.4%) were male. The mean hemoglobin was 121.521±22.960 g/L. The median follow-up time was 21.103±18.335 months. A total of 182 (22.33%) individuals reached the renal composite endpoint during the study period. After adjusting for covariates, hemoglobin was found to exert a negative impact on the renal composite endpoint in patients with DKD (HR 0.975, 95% CI [0.966, 0.984]). A nonlinear relationship between hemoglobin and the renal composite endpoint was identified with an inflection point at 109 g/L. Subgroup analysis unveiled a more pronounced association between hemoglobin and renal prognosis in males.

Conclusion

Hemoglobin emerges as a predictive indicator for the renal prognosis of diabetic kidney disease in China. This study reveals a negative and non-linear relationship between hemoglobin levels and the renal composite endpoint. A substantial association is noted when hemoglobin surpasses 109 g/L in relation to the renal composite endpoint.

A retrospective cohort study of clinical characteristics and outcomes of type 2 diabetic patients with kidney disease

Background

Type 2 diabetes mellitus (T2DM) with chronic kidney disease (CKD) poses a serious health threat and becomes a new challenge. T2DM patients with CKD fall into three categories, diabetic nephropathy (DN), non-diabetic kidney disease (NDKD), and diabetic nephropathy plus non-diabetic kidney disease (DN + NDKD), according to kidney biopsy. The purpose of our study was to compare the clinical characteristics and kidney outcomes of DN, NDKD, and DN + NDKD patients.

Methods

Data on clinical characteristics, pathological findings, and prognosis were collected from June 2016 to July 2022 in patients with previously diagnosed T2DM and confirmed DN and or NDKD by kidney biopsy at Tongji Hospital in Wuhan, China. The endpoint was defined as kidney transplantation, dialysis, or a twofold increase in serum creatinine.

Results

In our 6-year retrospective cohort research, a total of 268 diabetic patients were admitted and categorized into three groups by kidney biopsy. The 268 patients were assigned to DN (n = 74), NDKD (n = 109), and DN + NDKD (n = 85) groups. The most frequent NDKD was membranous nephropathy (MN) (n = 45,41.28%). Hypertensive nephropathy was the most common subtype in the DN+NDKD group (n = 34,40%). A total of 34 patients (12.7%) reached the endpoint. The difference between the Kaplan-Meier survival curves of the DN, NDKD, and DN + NDKD groups was significant (p < 0.05). Multifactorial analysis showed that increased SBP [HR (95% CI): 1.018(1.002-1.035), p = 0.025], lower Hb [HR(95% CI): 0.979(0.961-0.997), p = 0.023], higher glycosylated hemoglobin [HR(95% CI): 1.338(1.080-1.658), p = 0.008] and reduced serum ALB [HR(95% CI): 0.952(0.910-0.996), p = 0.032] were risk factors for outcomes in the T2DM patients with CKD.

Conclusions

This research based on a Chinese cohort demonstrated that the risk of endpoint events differed among DN, NDKD, and DN+NDKD patients. In T2DM patients with CKD, DN patients displayed worse kidney prognosis than those with NDKD or DN + NDKD. Increased SBP, higher glycosylated hemoglobin, lower Hb, and decreased serum ALB may be correlated with adverse kidney outcomes in T2DM patients.

FG-4592 relieves diabetic kidney disease severity by influencing metabolic profiles via gut microbiota reconstruction in both human and mouse models

Objective: Diabetic kidney disease (DKD) is one of the most prevalent complications of diabetes mellitus (DM) and is highly associated with devastating outcomes. Hypoxia-inducible factor (HIF), the main transcription factor that regulates cellular responses to hypoxia, plays an important role in regulating erythropoietin (EPO) synthesis. FG-4592 is the HIF stabilizer that is widely used in patients with renal anemia. We investigated the effect of FG-4592 on DKD phenotypes and the pharmacologic mechanism from the perspective of gut microbiota and systemic metabolism. Design: We collected the clinical data of 73 participants, including 40 DKD patients with combined renal anemia treated with FG-4592, and 33 clinical index-matched DKD patients without FG-4592 treatment from The First Affiliated Hospital of Zhengzhou University at the beginning and after a 3-6-month follow-up period. We established DKD mouse models treated by FG-4592 and performed fecal microbiota transplantation from FG-4592-treated DKD mice to investigate the effects of FG-4592 on DKD and to understand this mechanism from a microbial perspective. Untargeted metabolome-microbiome combined analysis was implemented to globally delineate the mechanism of FG-4592 from both microbial and metabolomic aspects. Result: DKD phenotypes significantly improved after 3-6 months of FG-4592 treatment in DKD patients combined with renal anemia, including a decreased level of systolic blood pressure, serum creatinine, and increased estimated glomerular infiltration rate. Such effects were also achieved in the DKD mouse model treated with FG-4592 and can be also induced by FG-4592-influenced gut microbiota. Untargeted plasma metabolomics-gut microbiota analysis showed that FG-4592 dramatically altered both the microbial and metabolic profiles of DKD mice and relieved DKD phenotypes via upregulating beneficial gut microbiota-associated metabolites. Conclusion: FG-4592 can globally relieve the symptoms of DKD patients combined with renal anemia. In the animal experiment, FG-4592 can reconstruct the intestinal microbial profiles of DKD to further upregulate the production of gut-associated beneficial metabolites, subsequently improving DKD phenotypes.

Establishment of a potent weighted risk model for determining the progression of diabetic kidney disease

BACKGROUND

Diabetic kidney disease (DKD) is a severe complication of diabetes. Currently, no effective measures are available to reduce the risk of DKD progression. This study aimed to establish a weighted risk model to determine DKD progression and provide effective treatment strategies.

METHODS

This was a hospital-based, cross-sectional study. A total of 1104 patients with DKD were included in this study. The random forest method was used to develop weighted risk models to assess DKD progression. Receiver operating characteristic curves were used to validate the models and calculate the optimal cutoff values for important risk factors.

RESULTS

We developed potent weighted risk models to evaluate DKD progression. The top six risk factors for DKD progression to chronic kidney disease were hemoglobin, hemoglobin A1c (HbA1c), serum uric acid (SUA), plasma fibrinogen, serum albumin, and neutrophil percentage. The top six risk factors for determining DKD progression to dialysis were hemoglobin, HbA1c, neutrophil percentage, serum albumin, duration of diabetes, and plasma fibrinogen level. Furthermore, the optimal cutoff values of hemoglobin and HbA1c for determining DKD progression were 112 g/L and 7.2%, respectively.

CONCLUSION

We developed potent weighted risk models for DKD progression that can be employed to formulate precise therapeutic strategies. Monitoring and controlling combined risk factors and prioritizing interventions for key risk factors may help reduce the risk of DKD progression.

One to one comparison of cell-free synthesized erythropoietin conjugates modified with linear polyglycerol and polyethylene glycol

With more than 20 Food and Drug Administration (FDA)-approved poly (ethylene glycol) (PEG) modified drugs on the market, PEG is the gold standard polymer in bioconjugation. The coupling improves stability, efficiency and can prolong blood circulation time of therapeutic proteins. Even though PEGylation is described as non-toxic and non-immunogenic, reports accumulate with data showing allergic reactions to PEG. Since PEG is not only applied in therapeutics, but can also be found in foods and cosmetics, anti-PEG-antibodies can occur even without a medical treatment. Hypersensitivity to PEG thereby can lead to a reduced drug efficiency, fast blood clearance and in rare cases anaphylactic reactions. Therefore, finding alternatives for PEG is crucial. In this study, we present linear polyglycerol (LPG) for bioconjugation as an alternative polymer to PEG. We report the conjugation of LPG and PEG by click-chemistry to the glycoprotein erythropoietin (EPO), synthesized in a eukaryotic cell-free protein synthesis system. Furthermore, the influence of the polymers on EPOs stability and activity on a growth hormone dependent cell-line was evaluated. The similar characteristics of both bioconjugates show that LPGylation can be a promising alternative to PEGylation.

Whether Renal Pathology Is an Independent Predictor for End-Stage Renal Disease in Diabetic Kidney Disease Patients with Nephrotic Range Proteinuria: A Biopsy-Based Study

Aims: To investigate whether renal pathology is an independent predictor for end-stage renal disease (ESRD) in diabetic kidney diseases (DKD) with nephrotic range proteinuria. Methods: A total of 199 DKD patients with nephrotic range proteinuria underwent renal biopsy and were divided into an ESRD group and a non-ESRD group. A Kaplan−Meier analysis was used to compare renal survival rate, and univariate and multivariate Cox proportional hazard analyses were used to determine the predictors of the ESRD. Results: The mean age of included patients was 51.49 ± 9.12 years and 113 patients (56.8%) progressed to ESRD. The median follow-up period was 16 (12−28) months. The glomerular pathology class III is the most common type (54.3%). In the Kaplan−Meier analysis, compared with patients without ESRD, patients with ESRD had a longer duration of diabetes (≥6 years), lower eGFR (<60 mL/min/1.73 m2), lower albumin (<30 g/L), lower hemoglobin (<120 g/L), and a higher grade of glomerular stage (class III + IV vs. class I + II) (p < 0.05). The hemoglobin and e-GFR, but not the histopathological damage, were significantly associated with a higher risk of ESRD in both the univariate and multivariate Cox analyses. Conclusions: In patients with diabetic kidney disease characterized by nephrotic range proteinuria, histopathological damage (glomerular alterations, interstitial fibrosis and tubular atrophy (IFTA), interstitial inflammation, and arteriolar hyalinosis) is not associated with poor renal outcomes, but hemoglobin and e-GFR could predict poor renal outcomes.

The Prevalence and Pattern of Anaemia in Type 2 Diabetics in Ogbomosho, An Urban Community in Southwestern Nigeria

Anaemia is a frequent finding in type 2 diabetes, but it is typically seen with established chronic kidney disease and renal insufficiency. Cases, where anaemia predates renal insufficiency, are associated with a worse prognosis for the type 2 diabetes patient and an increased susceptibility to complications. This study aims to determine the prevalence and type of anaemia in persons living with type 2 diabetes without established chronic kidney disease in our environment. The study was a hospital-based cross-sectional study that involved 141 people with known type 2 diabetes as the study group and 140 healthy persons as controls. The study population and the controls were selected using a multistage sampling technique. Data were collected using an interviewer-administered semistructured questionnaire at the Endocrinology clinic, Bowen University Teaching Hospital, Ogbomosho. The data obtained were analyzed using the IBM SPSS version 23.0 (p value ≤0.05 was considered significant). The biochemical (fasting lipids, HBA1C, FBG, serum albumin, creatinine, urea, uric acid, and insulin) and haematological (FBC and red cell indices; PVC, MCV, MCH, MCHC, and RCDW) parameters of the respondents were analyzed using standard methods. The study showed a statistically significant difference in the prevalence of anaemia among subjects, 69.2% as compared to 30.8% of the control group. Normochromic normocytic anaemia was predominant among the subjects, whereas microcytic hypochromic anaemia was the predominant type in the controls. There was no statistically significant difference between MCV and MCHC of both subjects and controls. There was a positive correlation between the incidence of anaemia and the duration of diabetes among the subjects. More people with type 2 diabetes are now living longer, and the addition of haematological parameters should be part of their baseline investigations to aid in the early detection of complications.

Development and internal validation of machine learning algorithms for end-stage renal disease risk prediction model of people with type 2 diabetes mellitus and diabetic kidney disease

Aims

Diabetic kidney disease (DKD) is the most common cause of end-stage renal disease (ESRD) and is associated with increased morbidity and mortality in patients with diabetes. Identification of risk factors involved in the progression of DKD to ESRD is expected to result in early detection and appropriate intervention and improve prognosis. Therefore, this study aimed to establish a risk prediction model for ESRD resulting from DKD in patients with type 2 diabetes mellitus (T2DM).

Methods

Between January 2008 and July 2019, a total of 390 Chinese patients with T2DM and DKD confirmed by percutaneous renal biopsy were enrolled and followed up for at least 1 year. Four machine learning algorithms (gradient boosting machine, support vector machine, logistic regression, and random forest (RF)) were used to identify the critical clinical and pathological features and to build a risk prediction model for ESRD.

Results

There were 158 renal outcome events (ESRD) (40.51%) during the 3-year median follow up. The RF algorithm showed the best performance at predicting progression to ESRD, showing the highest AUC (0.90) and ACC (82.65%). The RF algorithm identified five major factors: Cystatin-C, serum albumin (sAlb), hemoglobin (Hb), 24-hour urine urinary total protein, and estimated glomerular filtration rate. A nomogram according to the aforementioned five predictive factors was constructed to predict the incidence of ESRD.

Conclusion

Machine learning algorithms can efficiently predict the incident ESRD in DKD participants. Compared with the previous models, the importance of sAlb and Hb were highlighted in the current model.

Highlights

What is already known? Identification of risk factors for the progression of DKD to ESRD is expected to improve the prognosis by early detection and appropriate intervention.

What this study has found? Machine learning algorithms were used to construct a risk prediction model of ESRD in patients with T2DM and DKD. The major predictive factors were found to be CysC, sAlb, Hb, eGFR, and UTP.

What are the implications of the study? In contrast with the treatment of participants with early-phase T2DM with or without mild kidney damage, major emphasis should be placed on indicators of kidney function, nutrition, anemia, and proteinuria for participants with T2DM and advanced DKD to delay ESRD, rather than age, sex, and control of hypertension and glycemia.

Association of plasma fatty acid-binding protein 3 with estimated glomerular filtration rate in patients with type 2 diabetes mellitus

Background: Fatty acid-binding protein 3 (FABP3) located in renal mesangial and distal tubular cells, and had been shown to be a sensitive marker of renal injury, potentially be a mediator in pathogenesis of chronic kidney disease (CKD). Our previous study revealed that plasma FABP1 and FABP2 were independently associated with CKD, however, little is known about the relationship between plasma FABP3 level and CKD. The aim of this study was therefore to evaluate the plasma levels of FABP3 at different stages of estimated glomerular filtration rate (eGFR) in patients with type 2 diabetes mellitus (T2DM). Methods: A total of 334 subjects with T2DM who enrolled in a disease management program were included in this study and stratified according to eGFR. Plasma FABP3 concentrations were measured by an enzyme-linked immunosorbent assay. Results: FABP3 levels increased in parallel with the eGFR level. Increasing concentrations of FABP3 were independently and significantly associated with eGFR stage G2-G4. Age- and sex-adjusted FABP3 levels were positively associated with uric acid, urinary albumin-to-creatinine ratio, FABP1, FABP2, and fatty liver index, but negatively associated with eGFR and hemoglobin. Conclusion: Our results indicate that circulating FABP3 in patients with T2DM is associated with eGFR, which suggests that increased plasma FABP3 may be involved in the pathogenesis of CKD.

Biomarkers of Glyco-Metabolic Control in Hemodialysis Patients: Glycated Hemoglobin vs. Glycated Albumin

Background and Objectives: Glycated hemoglobin (HbA1c) dosage is considered the gold standard in glycol-metabolic monitoring, but it presents limits, which can underestimate the glycemia trend. In this regard, it was introduced the glycated albumin (GA). The aim of the study is to verify the predictivity of the GA compared to HbA1c in identifying glyco-metabolic alterations in non-diabetic and diabetic hemodialysis (HD) patients. Materials and Methods: For this purpose, we conducted a multicenter study involving one analysis laboratory and six dialysis centers in the Lazio region (Rome, Italy). Both diabetic and non-diabetic HD patients represent the study population, and the protocol included five time points. Results: The analyzed data highlighted the ability of GA to predict changes in glycemic metabolism in HD patients, and GA values are not significantly influenced, like HbA1c, by dialysis therapy itself and by comorbidities of the uremic state, such as normochromic and normocytic anemia. Thus, GA seems to reflect early glyco-metabolic alterations, both in patients with a previous diagnosis of diabetes and in subjects without diabetes mellitus. As part of this study, we analyzed two HD patients (one diabetic and one non-diabetic) in which GA was more predictive of glycol-metabolic alterations compared to HbA1c. Our study confirms the need to compare classical biomarkers used for the monitoring of glyco-metabolic alterations with new ones, likely more reliable and effective in specific subgroups of patients in which the classic biomarkers can be influenced by the preexisting pathological conditions. Conclusions: In conclusion, our evidence highlights that in uremic patients, GA shows a better ability to predict glyco-metabolic alterations allowing both an earlier diagnosis of DM and a prompt modulation of the hypoglycemic therapy, thus improving the clinical management of these patients.

Nephroprotective Effects of Tetramethylpyrazine Nitrone TBN in Diabetic Kidney Disease

Diabetic kidney disease (DKD) is the leading cause of end-stage renal failure, but therapeutic options for nephroprotection are limited. Oxidative stress plays a key role in the pathogenesis of DKD. Our previous studies demonstrated that tetramethylpyrazine nitrone (TBN), a novel nitrone derivative of tetramethylpyrazine with potent free radical-scavenging activity, exerted multifunctional neuroprotection in neurological diseases. However, the effect of TBN on DKD and its underlying mechanisms of action are not yet clear. Herein, we performed streptozotocin-induced rat models of DKD and found that TBN administrated orally twice daily for 6 weeks significantly lowered urinary albumin, N-acetyl-β-D-glycosaminidase, cystatin C, malonaldehyde, and 8-hydroxy-2′-deoxyguanosine levels. TBN also ameliorated renal histopathological changes. More importantly, in a nonhuman primate model of spontaneous stage III DKD, TBN increased the estimated glomerular filtration rate, decreased serum 3-nitrotyrosine, malonaldehyde and 8-hydroxy-2′-deoxyguanosine levels, and improved metabolic abnormalities. In HK-2 cells, TBN increased glycolytic and mitochondrial functions. The protective mechanism of TBN might involve the activation of AMPK/PGC-1α-mediated downstream signaling pathways, thereby improving mitochondrial function and reducing oxidative stress in the kidneys of DKD rodent models. These results support the clinical development of TBN for the treatment of DKD.

Evaluating the utilisation and expenditure patterns of erythropoietin stimulating agents and immunosuppressants in Australian chronic kidney disease patients

Objectives

This study aimed to characterise utilisation and expenditure patterns associated with erythropoietin stimulating agents (ESAs) (darbepoetin alfa, epoetin alfa, epoetin beta, epoetin lambda and methoxy polyethylene glycol-epoetin beta) and immunosuppressants (mycophenolate, tacrolimus, ciclosporine, sirolimus and everolimus) in the Australian chronic kidney disease (CKD) population from 2010–2018.

Methods

Utilisation and expenditure data for each drug were obtained from the Pharmaceutical Benefit Scheme and Highly Specialised Drugs program. Utilisation data were provided a number of dispensing per year, which was then converted to the daily defined dose per 1000 population per day for each year. Temporal trends were then analysed.

Key findings

Over the study period, utilisation of methoxy polyethylene glycol-epoetin beta and epoetin lambda rose by 13.7 and 81.4-fold, respectively. Contrastingly, the utilisation of darbepoetin alfa, epoetin alfa and epoetin beta declined by 6%, 42% and 70%, respectively. In 2018, tacrolimus, sirolimus, everolimus and mycophenolate utilisation was up 126%, 16.9%, 125% and 182% respectively; conversely, ciclosporine utilisation dropped 19%. Total Australian expenditure on all ESAs examined remained stable at around AUD 128 million over the study period, while total Australian expenditure across all immunosuppressants increased 1.1-fold reaching just over AUD 98 million.

Conclusions

It appears that immunosuppressant utilisation and expenditure are rising as transplantation rates in Australia continue to increase. Conversely, ESA utilisation and expenditure remained relatively unchanged over the study period. This may be due to increasing concerns around the safety of ESAs offsetting the increasing number of people with CKD.

NADH/NAD+ Redox Imbalance and Diabetic Kidney Disease

Diabetic kidney disease (DKD) is a common and severe complication of diabetes mellitus. If left untreated, DKD can advance to end stage renal disease that requires either dialysis or kidney replacement. While numerous mechanisms underlie the pathogenesis of DKD, oxidative stress driven by NADH/NAD⁺ redox imbalance and mitochondrial dysfunction have been thought to be the major pathophysiological mechanism of DKD. In this review, the pathways that increase NADH generation and those that decrease NAD⁺ levels are overviewed. This is followed by discussion of the consequences of NADH/NAD⁺ redox imbalance including disruption of mitochondrial homeostasis and function. Approaches that can be applied to counteract DKD are then discussed, which include mitochondria-targeted antioxidants and mimetics of superoxide dismutase, caloric restriction, plant/herbal extracts or their isolated compounds. Finally, the review ends by pointing out that future studies are needed to dissect the role of each pathway involved in NADH-NAD⁺ metabolism so that novel strategies to restore NADH/NAD⁺ redox balance in the diabetic kidney could be designed to combat DKD.

Real-world treatment patterns of renal anemia in hemodialysis patients: A multicenter cohort study performed using DialysisNet (RRAHD study)

A multicenter cohort study.The DialysisNet was previously developed for the management of hemodialysis (HD) patients based on the American Society for Testing and Materials Continuity of Care Records by metadata transformation. DialysisNet is a dialysis patient management program created by using the personal health record care platform to overcome the problems of registry studies, in real-time.Here, we aimed to investigate the pattern of treatment for renal anemia in HD patients using DialysisNet.We performed a multicenter cohort study among HD patients who were treated at one of the three Korean university-affiliated hospitals from January 2016 to December 2016. Subjects were divided into 4 hemoglobin variability groups by quartiles. The variable anemia treatment pattern was reviewed. To determine renal anemia treatment patterns, we automatically collected information on the practice of anemia treatment patterns such as erythropoietin stimulating agent (ESA) doses and administration frequencies, and targeted hemoglobin maintenance rate. Individual hemoglobin variabilities were expressed as (standard deviations)/(√(n/[n-1]).The records of 159 patients were analyzed (Hospital A: 35, Hospital B: 21, Hospital C: 103). Mean patients' age was 65.6 ± 12.8 years, and 61.6% were men. Overall, hemoglobin level was 10.5[7.43;13.93] g/dL. 158 (99.3%) patients were using ESA; and overall, the epoetin alfa dose was 33,000[4000;136,800] U per week. Hemoglobin levels (P = .206) and epoetin alfa doses were similar (P = .924) for patients with different hemoglobin variabilities. The hemoglobin target maintenance rate was lower in the highest hemoglobin variability group than in the lowest variability group (P = .045).In this study, detailed information on the actual anemia treatment patterns were obtained using the DialysisNet. We expect that DialysisNet will simplify and improve the renal anemia management for both dialysis patients and health care providers.