To evaluate the potential of the serum uric acid to serum creatinine ratio (SUA/SCr) as a diagnostic biomarker for normoalbuminuric diabetic kidney disease (NADKD).

We retrospectively analyzed demographic and biochemical data from 3,101 type 2 diabetes patients. Patients were stratified into non-diabetic kidney disease (non-DKD), albuminuric diabetic kidney disease (ADKD), and NADKD groups according to their estimated glomerular filtration rate (eGFR), urinary albumin creatinine ratio (UACR), and urinary albumin excretion rate (UAER). We employed multivariate logistic regression analyses using a stepwise forward-LR method to develop a nomogram. Both area under the curve (AUC) from receiver operating characteristic (ROC), and calibration curves were employed to assess the predictive accuracy of the nomogram. A decision curve analysis (DCA) was conducted to assess the clinical utility of the nomogram.

SUA/SCr, along with glycosylated hemoglobin A1c (HbA1C) and fasting plasma glucose (FPG), showed significant associations with NADKD, both pre- and post-propensity score matching (PSM). Seven variables were incorporated into the risk nomogram. The calibration plots indicated strong agreement between predicted and observed outcomes in both training and validation cohorts. The NADKD risk model demonstrated robust performance, as evidenced by the AUC from ROC analysis and DCA.

SUA/SCr is a significant and independent predictor of NADKD risk. The developed nomograms offer valuable tools for clinical decision-making, potentially enhancing diagnostic accuracy for NADKD in type 2 diabetes patients.

No tools are available for identifying patients with chronic kidney disease and Type 2 diabetes at high risk of hyperkalaemia. Using the FIDELITY pooled patient data set, a risk model for incident hyperkalaemia was developed and validated.

The primary outcome was new-onset hyperkalaemia (serum potassium >5.5 mmol/L). Data from the placebo arm were used for derivation and from the finerenone arm for validation. An integer risk score was built and divided into low-, intermediate-, and high-risk hyperkalaemia categories. Assessed efficacy outcomes included cardiovascular and kidney composites.

Seven baseline covariates (serum potassium >4.5 mmol/L, prior history of hyperkalaemia, no sodium-glucose co-transporter-2 inhibitor use, urine albumin-to-creatinine ratio >1000 mg/g, haemoglobin <12 g/dL, no thiazide-type diuretic use, and estimated glomerular filtration rate <45 mL/min/1.73 m2) were independently associated with new-onset hyperkalaemia and used for building the integer risk model. The risk scores for derivation and validation were accurate and well calibrated. The derived integer score ranged from 0 to 12 points. The risk of new-onset hyperkalaemia increased across hyperkalaemia risk categories with 2.7, 7.0, and 16.7% of patients reporting a hyperkalaemia event in the low-risk (0-3 points), intermediate-risk (4-6 points), and high-risk (7-12 points) groups with placebo, respectively. Irrespective of hyperkalaemia risk, finerenone reduced cardiovascular and kidney events vs placebo.

This integer risk score for new-onset hyperkalaemia in patients with chronic kidney disease and Type 2 diabetes could facilitate tailored treatment strategies and mitigate hyperkalaemia in high-risk patients.

Background/Objectives: Diabetic kidney disease (DKD) is a major cause of end-stage kidney disease and a leading contributor to morbidity and mortality in patients with type 2 diabetes mellitus (T2DM). However, predictive models for DKD onset in Korean patients with T2DM remain underexplored. This study aimed to develop and validate a machine learning (ML)-based DKD prediction model for this population. Methods: This retrospective study utilized electronic health records from six secondary or tertiary hospitals in Korea. The Jeonbuk National University Hospital cohort was used for model development (ratio training: test data, 8:2), whereas datasets from five other hospitals supported external validation. We employed multiple ML algorithms, including lasso, ridge, and elastic net regression; random forest; XGBoost; support vector machines; and neural networks. The model incorporated demographic variables, comorbidities, medications, and laboratory test results. Results: Among 5120 patients with T2DM, 1361 (26.6%) developed DKD. In the development cohort, XGBoost achieved the highest predictive performance (AUC: 0.8099), followed by random forest and logistic regression models (AUCs: 0.7977-0.8019). External validation confirmed the model's robustness with high AUCs (XGBoost: 0.8113, logistic regression models: 0.8228-0.8271). Key predictive factors included age; baseline estimated glomerular filtration rate; and creatinine, hemoglobin, and hemoglobin A1c levels. Conclusions: Our findings highlight the potential of ML-based approaches in predicting DKD in patients with T2DM. The superior performance of XGBoost and logistic regression models underscores their clinical utility. External validation supports the model's generalizability. This model is a valuable tool for the early DKD risk assessment of Korean patients with T2DM.

Diabetes mellitus is the most common cause of chronic kidney disease leading to kidney failure and premature death. Over the years, the nomenclature of kidney involvement in diabetes mellitus has evolved, driven both by the understanding that the phenotype may be more diverse than initially thought and by pragmatism. In clinical practice, most patients with diabetes mellitus do not undergo a comprehensive work-up (including kidney biopsy and genetic testing) to exclude the presence or coexistence of additional factors or other kidney diseases. Furthermore, the inclusion criteria for successful kidney protection clinical trials that are the basis of current guidelines covered a wide range of kidney phenotypes under the label of "diabetes and kidney disease," without requiring proactive efforts to exclude other nephropathies. The aim of this review is to provide a critical review of the most common chronic kidney disease phenotypes in the context of diabetes mellitus and discuss the evolving nomenclature. Various topics are discuss diabetic kidney disease, classic diabetic nephropathy, regression of albuminuria, rapid progression, non-albuminuric and non-proteinuric kidney disease, the connections between and the impact of aging on these phenotypes and a glimpse into future phenotypes resulting from proactive prevention rather than reactive treatment of kidney disease in diabetes.

Type 2 diabetes (T2D), as well as obesity, are risk factors for chronic kidney disease (CKD) and end-stage renal disease. The renal impacts of glucose-lowering and weight-lowering drugs and their potential benefits in preventing CKD often guide clinicians in choosing them appropriately. Only limited data based on randomized controlled trials (RCTs) is currently available on the renal effects and safety profile of tirzepatide.

To explore the renal benefits and safety of tirzepatide vs controls.

RCTs involving patients receiving tirzepatide for any indication in the intervention arm and placebo or active comparator in the control arm were searched through multiple electronic databases. The co-primary outcomes were percent change from baseline (CFB) in urine albumin-to-creatinine ratio (UACR) and absolute CFB in estimated glomerular filtration rate (eGFR; in mL/min/1.73 m2); the secondary outcome was tirzepatide's renal safety profile. RevMan web was used to conduct meta-analysis using random-effects models. Outcomes were presented as mean differences (MD) or risk ratios with 95% confidence intervals.

Fifteen RCTs (n = 14471) with mostly low risk of bias (RoB) were included. Over 26-72 weeks, tirzepatide 10 mg [MD -26.95% (-40.13, -13.76), P < 0.0001] and 15 mg [MD -18.03% (-28.58, -7.47), P = 0.0008] were superior to placebo in percent reductions of UACR. Tirzepatide, at all doses, outperformed insulin in percent reductions of UACR. Compared to the placebo, the percent UACR reduction was greater in subjects with T2D than those with obesity but without T2D (MD -33.25% vs -7.93%; P = 0.001). The CFB in eGFR with all doses of tirzepatide was comparable [5 mg: MD 0.36 (-1.41, 2.14); 10 mg: MD 1.17 (-0.22, 2.56); 15 mg: MD 1.42 (-0.04, 2.88)]; P > 0.05 for all] vs insulin. Tirzepatide (pooled and separate doses) did not increase the risks of adverse renal events, urinary tract infection, nephrolithiasis, acute kidney injury, and renal cancer compared to the placebo, insulin, and glucagon-like peptide-1 receptor agonists.

Short-term data from RCTs with low RoB suggests that tirzepatide positively impacts UACR without detrimental effects on eGFR in subjects with T2D and obesity without T2D, with a reassuring renal safety profile. Larger RCTs are warranted to prove the longer-term renal benefits of tirzepatide, which might also prevent eGFR decline and worsening of CKD.

Background/Objectives: Post-translationally modified peptide fragments of fetuin-A (FetA) were identified as a potential biomarker of diabetic kidney disease (DKD). An independent association between urinary FetA-derived peptide levels (uPTM3-FetA) and DKD progression in patients with type 2 diabetes (T2D) was evidenced. This study aimed to explore uPTM3-FetA excretion and its associations with insulin resistance, inflammatory and metabolic biomarkers in patients with type 1 diabetes (T1D), and the normal albuminuria and estimated glomerular filtration rate (eGFR) > 60 mL/min/1.73 m2. Methods: uPTM3-FetA levels in aliquots of 24 h urine specimens, routine laboratory renal, metabolic and inflammatory tests, adipokines (leptin, adiponectin, resistin), and insulin resistance, assessed as the estimated glucose disposal rate (eGDR), were measured in a cohort of 169 adult T1D patients. To evaluate the changes in early renal dysfunction, the cohort was divided according to the median eGFR. Above- and below-median-eGFR groups were considered as having normal and declining kidney function, respectively. Results: The median (IQR) uPTM3-FetA level was 11.7 (8.43-16.65 µg/24 h), with no significant difference between males and females, as well as normal and declining kidney function patients. However, a sex-specific analysis revealed a significantly higher uPTM3-FetA excretion in male T1D patients with lower eGFRs, when compared to those with higher eGFRs, whereas no such difference was observed in female patients. BMI, hs-CRP, resistin and HDL-cholesterol were identified as independent predictors of uPTM3-FetA excretion. Conclusions: Our results implicate the potential role of uPTM3-FetA in the detection of an early renal dysfunction in male patients with T1DM and pinpoint the importance of a sex-specific approach in diabetes diagnostics and research.

Diabetic kidney disease (DKD) is one of the typical complications of type 2 diabetes (T2D), with approximately 10 % of DKD patients experiencing a Rapid decline (RD) in kidney function. RD leads to an increased risk of poor outcomes such as the need for dialysis. Albuminuria is a known kidney damage biomarker for DKD, yet RD cases do not always show changes in albuminuria, and the exact mechanism of RD remains unclear. Previous studies focused on a limited number of laboratory tests, no comprehensive study targeting a wide range of laboratory tests has been done. We target to develop a model that predicts RD among T2D and points to key laboratory tests of interest in understanding RD from various laboratory tests.

Our machine learning model predicts whether RD, as represented via eGFR, will happen within 1 year. Additionally, the model uses Recursive feature elimination with cross-validation (RFECV) to eliminate the features that do not contribute to the prediction. We trained and assessed the model using 1202 types of laboratory tests from 3438 diabetes patients at the University of Tokyo Hospital.

The means (95 % confidence interval) of the receiver operating characteristic area under the curve (ROC-AUC), precision-recall area under the curve, accuracy rate, and F1-score of an 8-feature-model were 0.820 (0.811, 0.829), 0.430 (0.410, 0.451), 0.754 (0.747, 0.761), and 0.500 (0.485, 0.515), respectively. The RFECV revealed that 7 test types (MCH, γ-GTP, Cre, HbA1c, HDL-C, eGFR, and Hct) contributed to RD prediction. The model's ROC-AUC of 0.820 improves on the ROC-AUC of 0.775 seen in previous studies.

The proposed model accurately predicts RD among diabetes patients and helps physicians focus on inhibiting progression of kidney damage. The contributing laboratory tests may serve as alternative biomarkers for DKD.

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

The widely adopted Kidney Disease: Improving Global Outcomes (KDIGO) classification system has been underused in assessing the burden and risk of adverse outcomes in type 1 diabetes. This observational study aimed to clarify how each KDIGO category correlates with adverse outcomes in this patient group.

In a cohort of 40,199 individuals with type 1 diabetes from the Swedish National Diabetes Register, we aimed to investigate the 1) prevalence of different KDIGO categories at baseline; 2) incidence of adverse kidney and cardiovascular (CV) outcomes, including mortality, within each category; and 3) association of baseline category with excess risk of five outcomes: a 40% decline in estimated glomerular filtration rate (eGFR), kidney failure, major adverse kidney/CV events, and all-cause mortality. Cox regression analyses were conducted using three different reference categories: 1) the conventional low-risk "combined G1A1 + G2A1"; 2) "G1A1" alone to assess whether G2A1 had excess risk; and 3) "G1bA1" alone to evaluate whether eGFR ≥105 mL/min/1.73 m2 had increased risk.

Among 39,067 included patients, with a mean follow-up of 9.1 years, 18.5% presented with chronic kidney disease (CKD), defined as eGFR <60 mL/min/1.73 m2 and/or albuminuria. A progressive increase in the incidence and adjusted hazard ratio for all studied outcomes was found with advancing eGFR and albuminuria categories, including in G2A1 (non-CKD). An eGFR ≥105 mL/min/1.73 m2 without albuminuria was not associated with increased risk.

A progressively increasing burden of all studied adverse outcomes was observed with advancing KDIGO categories. Even individuals with preserved eGFR and normoalbuminuria (G2A1), conventionally perceived as non-CKD, had an excess risk for all outcomes.

Diabetic nephropathy, as a severe microvascular complication of diabetes, manifests in four clinical types: classic, albuminuria regression, a rapid decline in kidney function (RDKF), and non-proteinuric or non-albuminuric DKD. Rapidly progressive diabetic nephropathy advances to end-stage renal disease more swiftly than the typical form, posing significant risks. However, a comprehensive understanding of rapidly progressive diabetic nephropathy is currently lacking. This article reviewed latest developments in genetic and clinical risk factors associated with rapidly progressive diabetic nephropathy, aiming to broad perspectives concerning the diagnosis and interventions of this condition.

Individuals with type 1 diabetes (T1D) and diabetic nephropathy (DN) experience progressive kidney function decline and high risk of cardiovascular disease (CVD) and mortality. This study explored changes in kidney function decline in new-onset DN between 2000 and 2020 and provided an updated prognosis for risk of kidney failure, CVD, and mortality.

This is a register-based cohort study in T1D with new-onset DN (severely increased albuminuria) between 2000 and 2020 at Steno Diabetes Center Copenhagen, Denmark. Data were derived from electronic health records and national registers. Kidney function development was expressed as trajectories of estimated glomerular filtration rate (eGFR) and measured GFR (mGFR) using mixed-effects models. The prognosis was presented in probabilities of developing complications, stratified by sex, prior CVD, and risk factor control by using simulations based on Poisson regression analysis.

The cohort comprised 591 individuals with median (interquartile range [IQR]) age at DN onset of 53 (39-66) years and 57% were male. In 283 participants, mGFR were available. Plots of eGFR trajectories illustrated tendencies toward higher eGFR in more recent years; however, this was not confirmed in mGFR trajectories. Poor risk factor control, prior CVD, and male sex impacted mortality and morbidity rates negatively. For men and women with fair risk factor control and no prior CVD, the 10-year mortality rate from onset of DN was 28% and 26%, respectively. For men and women with poor risk factor control and CVD prior to DN onset, the 10-year-mortality rate was 62% for each sex.

The results do not support an improved prognosis for T1D and DN, emphasizing the urgent need for new therapeutic approaches.

The aim of this study was to assess the predictive capabilities of a radiomics signature obtained from arterial spin labeling (ASL) imaging in forecasting and detecting stages of kidney damage in patients with diabetes mellitus (DM), as well as to analyze the correlation between texture feature parameters and biological clinical indicators. Additionally, this study seeks to identify the imaging risk factors associated with early renal injury in diabetic patients, with the ultimate goal of offering novel insights for predicting and diagnosing early renal injury and its progression in patients with DM.

In total, 42 healthy volunteers (Group A); 68 individuals with diabetes (Group B) who exhibited microalbuminuria, defined by a urinary albumin-to-creatinine ratio (ACR)< 30 mg/g and an estimated glomerular filtration rate (eGFR) within the range of 60-120 mL/min/1.73m²; and 53 patients with diabetic nephropathy (Group C) were included in the study. ASL using magnetic resonance imaging (MRI) at 3.0T was conducted. The radiologist manually delineated regions of interest (ROIs) on the ASL maps of both the right and left kidney cortex. Texture features from the ROIs were extracted utilizing MaZda software. Feature selection was performed utilizing a range of methods, such as the Fisher coefficient, mutual information (MI), probability of classification error, and average correlation coefficient (POE + ACC). A radiomics model was developed to detect early diabetic renal injury, extract imaging risk factors associated with early diabetic renal injury, and examine the relationship between significant texture feature parameters and biological clinical indicators. Patients with DM and kidney injury were followed prospectively. The study utilized seven machine learning algorithms to develop a detective radiomics model and a comprehensive predictive model for assessing the progression of kidney damage in patients with DM. The diagnostic efficacy of the models in detecting variations in diabetic kidney damage over time was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Empower (R) was used to establish a correlation between clinical biological indicators and texture feature metrics. Statistical analysis was conducted using R, Python, MedCalc 15.8, and GraphPad Prism 8.

A total of 367 texture features were extracted from the ROIs in the kidneys and refined based on selection criteria using MaZda software across groups A, B, and C. The renal blood flow (RBF) values of the renal cortex in groups A, B, and C exhibited a decreasing trend, with values of 256.458 ± 54.256 mL/100g/min, 213.846 ± 52.109 mL/100g/min, and 170.204 ± 34.992 mL/100g/min, respectively. There was a positive correlation between kidney RBF and eGFR (r = 0.439, P<0.001). The negative correlation between RBF and various clinical parameters including urinary albumin-to-creatinine ratio (UACR), body mass index (BMI), diastolic blood pressure (DBP), blood urea nitrogen (BUN), and serum creatinine (SCr) was investigated. Through the use of a least absolute shrinkage and selection operator (LASSO) regression model, the study identified the eight most significant texture features and biological indicators, namely GeoY, GeoRf, GeoRff, GeoRh, GeoW8, GeoW12, S (0, 4) Entropy, and S (5, -5) Entropy. Spearman correlation analysis revealed associations between imaging markers in early diabetic patients with kidney damage and factors such as age, systolic blood pressure (SBP), Alanine Transaminase (ALT), Aspartate Amino Transferase (AST) albumin, uric acid (UA), microalbuminuria (UMA), UACR, 24h urinary protein, fasting blood glucose (FBG), two hours postprandial blood glucose (P2BG), and HbA1c. The study utilized ASL imaging as a detection model to identify renal injury in patients with DM across different stages, achieving a sensitivity of 85.1%, specificity of 65.5%, and an AUC of 0.865. Additionally, a comprehensive prediction model combining imaging labels and biological indicators, with the naive Bayes machine learning algorithm as the best model, demonstrated an AUC of 0.734, accuracy of 0.74, and precision of 0.43.

ASL imaging sequences demonstrated the ability to accurately detect alterations in kidney function and blood flow in patients with DM. Strong associations were observed between renal blood flow values in ASL imaging and established clinical biomarkers. These values show promise in detecting early microstructural changes in the kidneys of diabetic patients. Utilizing image markers in conjunction with clinical indicators was effective in identifying early renal dysfunction and its progression in individuals with DM. Furthermore, the integration of imaging texture feature parameters with clinical biomarkers holds significant potential for predicting early renal damage and its progression in patients with diabetes.

This study estimated to what extent the number of measurements of cardiometabolic risk factors (e.g., blood pressure, cholesterol, glycated haemoglobin) were impacted by the COVID-19 pandemic and whether these have recovered to expected levels.

A cohort of individuals aged ≥18 years in England with records in the primary care-COVID-19 General Practice Extraction Service Data for Pandemic Planning and Research (GDPPR) were identified. Their records of 12 risk factor measurements were extracted between November 2018 and March 2024. Number of measurements per 1,000 individuals were calculated by age group, sex, ethnicity, and area deprivation quintile. The observed number of measurements were compared to a composite expectation band, derived as the union of the 95% confidence intervals of 2 estimates: (1) a projected trend based on data prior to the COVID-19 pandemic; and (2) an assumed stable trend from before pandemic. Point estimates were calculated as the mid-point of the expectation band. A cohort of 49,303,410 individuals aged ≥18 years were included. There was sharp drop in all measurements in March 2020 to February 2022, but overall recovered to the expected levels during March 2022 to February 2023 except for blood pressure, which had prolonged recovery. In March 2023 to March 2024, blood pressure measurements were below expectation by 16% (-19 per 1,000) overall, in people aged 18 to 39 (-23%; -18 per 1,000), 60 to 79 (-17%; -27 per 1,000), and ≥80 (-31%; -57 per 1,000). There was suggestion that recovery in blood pressure measurements was socioeconomically patterned. The second most deprived quintile had the highest deviation (-20%; -23 per 1,000) from expectation compared to least deprived quintile (-13%; -15 per 1,000).

There was a substantial reduction in routine measurements of cardiometabolic risk factors following the COVID-19 pandemic, with variable recovery. The implications for missed diagnoses, worse prognosis, and health inequality are a concern.

To evaluate the clinical value of early renal changes in type 2 diabetes mellitus (T2DM) using multiparameter MRI.

The study included 41 diabetics (normoalbuminuria: n = 23; microalbuminuria: n = 18) and 30 healthy controls. All subjects underwent intravoxel incoherent motion diffusion-weighted imaging (IVIM), blood oxygen level dependent (BOLD) and arterial spin labeling (ASL) examinations. One-way analysis of variance was used to compare MRI parameters among the three groups. Pearson correlation analysis was used to evaluate the relationship between MRI parameters and estimated glomerular filtration rate (eGFR) and albumin-creatinine ratio (ACR). Receiver operating characteristic analysis was performed to assess the diagnostic performance.

There were statistical differences in cortical D, D*, f, renal blood flow (RBF) and medulla D, D*, f, R2* among the three groups (P < 0.05). The cortical or medullary D, cortical f, and RBF were significantly positively correlated with eGFR (all P < 0.01). The cortical or medullary D, D*, f, cortical RBF were negatively correlated with ACR (all P < 0.05).To evaluate early kidney changes and degree of diabetes, cortical combined D and RBF (AUC [area under the curve]  = 0.796 and 0.947, respectively) was better than single D or RBF (all P > 0.05); medullary combined D and R2* (AUC = 0.899 and 0.923, respectively) was better than single D or R2* (all P > 0.05), except single D (P = 0.005) in differentiating normoalbuminuria group from control group.

The early changes of renal diffusion and perfusion, oxygenation level, and blood flow in T2DM could be evaluated noninvasively and quantitatively using IVIM, BOLD and ASL. Renal medullary combined IVIM-derived D and BOLD-derived R2* and cortical combined IVIM-derived D and ASL-derived RBF were better for evaluating early renal changes in T2DM.

Diabetes mellitus is one of the leading causes of chronic kidney disease and its progression to end-stage kidney disease (ESKD). Diabetic kidney disease (DKD) is characterized by glomerular hypertrophy, hyperfiltration, inflammation, and the onset of albuminuria, together with a progressive reduction in glomerular filtration rate. This progression is further accompanied by tubulointerstitial inflammation and fibrosis. Factors such as genetic predisposition, epigenetic modifications, metabolic derangements, hemodynamic alterations, inflammation, and inappropriate renin-angiotensin-aldosterone system (RAAS) activity contribute to the onset and progression of DKD. In this context, decades of work have focused on glycemic and blood pressure reduction strategies, especially targeting the RAAS to slow disease progression. Although much of the work has focused on targeting angiotensin II, emerging data support that the mineralocorticoid receptor (MR) is integral in the development and progression of DKD. Molecular mechanisms linked to the underlying pathophysiological changes derived from MR activation include vascular endothelial and epithelial cell responses to oxidative stress and inflammation. These responses lead to alterations in the microcirculatory environment, the abnormal release of extracellular vesicles, gut dysbiosis, epithelial-mesenchymal transition, and kidney fibrosis. Herein, we present recent experimental and clinical evidence on the MR in DKD onset and progress along with new MR-based strategies for the treatment and prevention of DKD.

We examined the trajectory of estimated glomerular filtrate rate (eGFR), associated risk factors, and its relationship with end-stage kidney disease (ESKD) among a multiethnic patient population with type 2 diabetes in Singapore.

A follow-up study included 62 080 individuals with type 2 diabetes aged ≥18 years in a multi-institutional SingHealth Diabetes Registry between 2013 and 2019. eGFR trajectories were analyzed using latent class linear mixed models. Factors associated with eGFR trajectories were evaluated using multinomial logistic regression. The association of eGFR trajectories with ESKD was assessed via competing risk models.

Trajectory of kidney function, determined by eGFR, was nonlinear. The trajectory pattern was classified as stable initially then gradual decline (75%), progressive decline (21.9%), and rapid decline (3.1%). Younger age, female sex, Malay ethnicity, lower-income housing type, current smoking, higher glycated hemoglobin, lower low-density lipoprotein, higher triglyceride, uncontrolled blood pressure, albuminuria, cardiovascular disease, hypertension, and higher eGFR levels each were associated with progressive or rapid decline. Compared with the trajectory of stable initially then gradual eGFR decline, progressive decline increased the hazard of ESKD by 6.14-fold (95% confidence interval [CI]: 4.96-7.61)) and rapid decline by 82.55 folds (95% CI: 55.90-121.89).

Three nonlinear trajectory classes of kidney function were identified among multiethnic individuals with type 2 diabetes in Singapore. About one in four individuals had a progressive or rapid decline in eGFR. Our results suggest that eGFR trajectories are correlated with multiple social and modifiable risk factors and inform the risk of ESKD.

Diabetes leads to chronic kidney disease (CKD) and kidney failure, requiring dialysis or transplantation. Astragalus, a common herbal medicine and US pharmacopeia-registered food ingredient, is shown kidney protective by retrospective and preclinical data but with limited long-term prospective clinical evidence. This trial aimed to assess the effectiveness of astragalus on kidney function decline in macroalbuminuric diabetic CKD patients.

This randomized, assessor-blind, standard care-controlled, multi-center clinical trial randomly assigned 118 patients with estimated glomerular filtration rate (eGFR) of 30-90 ml/min/1.73m2 and urinary albumin-to-creatinine ratio (UACR) of 300-5000 mg/g from 7 public outpatient clinics and the community in Hong Kong between July 2018 and April 2022 to add-on oral astragalus granules (15 gs of raw herbs daily equivalent) or to continue standard care alone as control for 48 weeks. Primary outcomes were the slope of change of eGFR (used for sample size calculation) and UACR of the intention-to-treat population. Secondary outcomes included endpoint blood pressures, biochemistry, biomarkers, concomitant drug change and adverse events. (ClinicalTrials.gov: NCT03535935) RESULTS: During the 48-week period, the estimated difference in the slope of eGFR decline was 4.6 ml/min/1.73m2 per year (95 %CI: 1.5 to 7.6, p = 0.003) slower with astragalus. For UACR, the estimated inter-group proportional difference in the slope of change was insignificant (1.14, 95 %CI: 0.85 to 1.52, p = 0.392). 117 adverse events from 31 astragalus-treated patients and 41 standard care-controlled patients were documented. The 48-week endpoint systolic blood pressure was 7.9 mmHg lower (95 %CI: -12.9 to -2.8, p = 0.003) in the astragalus-treated patients. 113 (96 %) and 107 (91 %) patients had post-randomization and endpoint primary outcome measures, respectively.

In patients with type 2 diabetes, stage 2 to 3 CKD and macroalbuminuria, add-on astragalus for 48 weeks further stabilized kidney function on top of standard care.

the aim of the study was to analyze glomerular filtration ratio (GFR) changes in diabetic patients assisted by General Practitioners (GPs) evaluating the risk factors related to glomerular function.

patients with diabetes with at least three recorded values of creatinine were recruited in the study and GFR values were estimated. The quarterly percentage change in GFR for each patient was estimated. Nephrotoxic drugs were identified, and glucose-lowering drugs use was described. Linear regression analyses were performed to identify eGFR changes predictors.

a total of 545 patients with diabetes were selected. According to the last eGFR values 64 (11.7 %) patients were classified in G1 stage, 277 (50,8 %) in G2, 175 (32.1 %) in G3a, 25 (4.6 %) in G3b and only 4 (0.7 %) in G4. Patients treated with at least one glucose-lowering drugs were 479 (87.9 %), most of them with biguanides (67.0 %). At least one nephrotoxic drug prescription was recorded in 524 (96.1 %) patients; proton pump inhibitors (74.7 %) and NSAIDs (71.6 %) were the most prescription classes. Heart failure, diabetes duration and preserved GFR values were related to reduced eGFR values.

patients with diabetes should be more carefully observed regardless of kidney risk factors and GFR values in clinical practice.

Type 2 diabetes mellitus (T2DM) is recognized an independent risk factor for chronic kidney disease (CKD). The precise contribution and differential response to treatment strategies to reduce kidney dysfunction, depending on whether obesity is present alongside T2DM or not, remain to be fully clarified. Our objective was to improve our understanding of how obesity contributes to kidney function in patients with T2DM and coronary heart disease (CHD), who are highly predisposed to CKD, to assign the most effective dietary approach to preserve kidney function.

1002 patients with CHD and estimated glomerular filtration rate (eGFR)≥30 ml/min/1.73m2, were randomized to consume a Mediterranean diet (35% fat, 22% MUFA, < 50% carbohydrates) or a low-fat diet (28% fat, 12% MUFA, > 55% carbohydrates). Patients were classified into four groups according to the presence of T2DM and/or obesity at baseline: Non-Obesity/Non-T2DM, Obesity/Non-T2DM, Non-Obesity/T2DM and Obesity/T2DM. We evaluated kidney function using serum creatinine-based estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (uACR) before and after 5-years of dietary intervention.

Patients with Obesity/T2DM had the lowest baseline eGFR and the highest baseline uACR compared to non-diabetics (p < 0.05). After dietary intervention, the Mediterranean diet induced a lower eGFR decline in patients with Obesity/T2DM, compared to a low-fat diet but not in the other groups (p = 0.014). The Mediterranean diet, but not the low-fat diet, also reduced uACR only in patients with Obesity/T2DM (p = 0.024).

Obesity provided an additive effect to T2DM resulting in a more pronounced decline in kidney function compared to T2DM alone when compared to non-diabetics. In patients with concomitant presence of T2DM and obesity, with more metabolic complications, consumption of a Mediterranean diet seemed more beneficial than a low-fat diet in terms of preserving kidney function. These findings provide valuable insights for tailoring personalized lifestyle modifications in secondary prevention of cardiovascular disease.

URL, http://www.cordioprev.es/index.php/en .

gov number, NCT00924937.

Diabetic kidney disease (DKD) is a major microvascular complication of both type 1 and type 2 diabetes. DKD is characterised by injury to both glomerular and tubular compartments, leading to kidney dysfunction over time. It is one of the most common causes of chronic kidney disease (CKD) and end-stage renal disease (ESRD). Persistent high blood glucose levels can damage the small blood vessels in the kidneys, impairing their ability to filter waste and fluids from the blood effectively. Other factors like high blood pressure (hypertension), genetics, and lifestyle habits can also contribute to the development and progression of DKD. The key features of renal complications of diabetes include morphological and functional alterations to renal glomeruli and tubules leading to mesangial expansion, glomerulosclerosis, homogenous thickening of the glomerular basement membrane (GBM), albuminuria, tubulointerstitial fibrosis and progressive decline in renal function. In advanced stages, DKD may require treatments such as dialysis or kidney transplant to sustain life. Therefore, early detection and proactive management of diabetes and its complications are crucial in preventing DKD and preserving kidney function.

This article focuses on extracting a standard feature set for predicting the complications of diabetes mellitus by systematically reviewing the literature. It is conducted and reported by following the guidelines of PRISMA, a well-known systematic review and meta-analysis method. The research articles included in this study are extracted using the search engine "Web of Science" over eight years. The most common complications of diabetes, diabetic neuropathy, retinopathy, nephropathy, and cardiovascular diseases are considered in the study.

The features used to predict the complications are identified and categorised by scrutinising the standards of electronic health records.

Overall, 102 research articles have been reviewed, resulting in 59 frequent features being identified. Nineteen attributes are recognised as a standard in all four considered complications, which are age, gender, ethnicity, weight, height, BMI, smoking history, HbA1c, SBP, eGFR, DBP, HDL, LDL, total cholesterol, triglyceride, use of insulin, duration of diabetes, family history of CVD, and diabetes. The existence of a well-accepted and updated feature set for health analytics models to predict the complications of diabetes mellitus is a vital and contemporary requirement. A widely accepted feature set is beneficial for benchmarking the risk factors of complications of diabetes.

This study is a thorough literature review to provide a clear state of the art for academicians, clinicians, and other stakeholders regarding the risk factors and their importance.

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Advanced glycation end products (AGEs) play a role in kidney disease in type 2 diabetes mellitus (T2DM). However, there have been no prior controlled clinical trials examining the effects of specific diets on AGE metabolism and their impact on kidney function. Our aim was to assess whether modulating AGE metabolism resulting in reduced AGEs levels, after consumption of two healthy diets, could delay kidney function decline in patients with T2DM and coronary heart disease (CHD).

T2DM patients (540 out of 1002 patients from the CORDIOPREV study), with estimated glomerular filtration rate (eGFR) ≥ 30 ml/min/1.73 m2, were classified based on their baseline kidney function: normal eGFR (≥ 90 ml/min/1.73 m2), mildly decreased eGFR (60- < 90 ml/min/1.73 m2) and moderately decreased eGFR (<60 ml/min/1.73 m2). Serum AGE levels, methylglyoxal (MG) and N-carboximethyllysine (CML), and gene expression related to AGE metabolism (AGER1, RAGE, and GloxI mRNA) were measured before and after 5-years of dietary intervention (a Mediterranean diet or a low-fat diet).

Mediterranean diet produced a lower declined of eGFR compared to the low-fat diet only in patients with mildly decreased eGFR (P = 0.035). Moreover, Mediterranean diet was able to decrease MG levels and increase GloxI expression in normal and mildly decreased eGFR patients (all P < 0.05). One standard deviation increment of MG levels after dietary intervention resulted in a 6.8-fold (95 % CI 0.039;0.554) higher probability of eGFR decline.

Our study showed that lowering circulating AGE levels, specifically MG, after following a Mediterranean diet, might be linked to the preservation of kidney function, evidenced by a decreased decline of eGFR in T2DM patients with CHD. Patients with mildly decreased eGFR could potentially benefit more from AGE reduction in maintaining kidney function.

We aimed to identify patterns within the rate of kidney function decline, determinants of these patterns and their association with all-cause mortality risk in the general population.

Participants aged ≥ 45 years with at least one assessment of creatinine-based estimated glomerular filtration rate (eGFR) taken between 1997 and 2018 were selected from a population-based cohort study. Analyses were performed using several distinct latent class trajectory modelling methods. Cumulative incidences were calculated with 45 years of age as the starting point.

In 12 062 participants (85 922 eGFR assessments, mean age 67.0 years, 58.7% women, median follow-up 9.6 years), four trajectories of eGFR change with age were identified: slow eGFR decline [rate of change in mL/min/1.73 m2 per year (RC), -0.9; 95% CI, -0.9 to -0.9; reference group], intermediate eGFR decline (RC, -2.5; 95% CI, -2.7 to -2.5) and fast eGFR decline (RC, -4.3; 95% CI, -4.4 to -4.1), and an increase/stable eGFR (RC, 0.3; 95% CI, 0.3 to 0.4). Women were more likely to have an increase/stable eGFR [odds ratio (OR), 1.94; 95% CI, 1.53 to 2.46] whereas men were more likely to have a fast eGFR decline (OR, 1.86; 95% CI, 1.33 to 2.60). Participants with diabetes, cardiovascular disease (CVD) or hypertension were more likely to have an intermediate or fast eGFR decline. All-cause mortality risks (cumulative incidence at age of 70 years) were 32.3% (95% CI, 21.4 to 47.9, slow eGFR decline), 6.7% (95% CI, 3.5 to 12.4, intermediate eGFR decline), 68.8% (95% CI, 44.4 to 87.8, fast eGFR decline) and 9.5% (95% CI, 5.5 to 15.7, increase/stable eGFR).

Sex, hypertension, diabetes and CVD were identified as trajectory membership determinants. Having fast eGFR decline was associated with the highest risk of all-cause mortality, highlighting the need for extensive monitoring and prevention of kidney function decline in individuals at risk of having fast eGFR decline.

The association of estimated glomerular filtration rate (eGFR) slope with progression of complications in people with type 2 diabetes (T2D) and early-stage chronic kidney disease (CKD) is less clear.

We identified 115,139 T2D participants without decreased eGFR (>60 mL/min/1.73 m2) between 2008 and 2015 from the electronic database of the Hong Kong Hospital Authority. eGFR slope calculated by linear-mixed effects model using 3-year eGFR measurements was categorized into quintiles. With Quintile 3 of eGFR slope as the reference group, we used Cox proportional or cause-specific models to investigate the association between eGFR slope and all-cause mortality, macrovascular and microvascular complications, as appropriate.

Over a median follow-up of 7.8 years, fastest eGFR declines (Quintile 1 with median eGFR slope: -4.32 mL/min/1.73 m2/year) were associated with increased risk of all adverse outcomes (adjusted hazard ratio [aHR] 1.36 to 2.97, all P < 0.0001), compared with less steep eGFR declines (Quintile 3: -1.08 mL/min/1.73 m2/year). Substantial eGFR increases (Quintile 5: 1.34 mL/min/1.73 m2/year) were associated with decreased risk of CKD and ≥ 40 % decline in eGFR (aHR [95 % CI] 0.65 [0.63, 0.67] and 0.85 [0.82, 0.89], respectively) and higher risk of death, CVD, DR and DN (aHR [95 % CI] 1.48 [1.40, 1.56], 1.19 [1.14, 1.25], 1.07 [1.004, 1.15] and 1.62 [1.37, 1.91], respectively).

In a cohort of T2D people without decreased eGFR, accelerated declines and increases in eGFR were associated with all-cause mortality, macrovascular and microvascular complications, supporting the potential prognostic utility of eGFR slope in T2D people with early-stage CKD.

Diabetic nephropathy (DN) is one of the most prevalent complications of diabetes mellitus (DM). However, there is still a lack of effective methods for non-invasive diagnosis of DN in clinical practice. We aimed to explore biomarkers from plasma cell-free DNA as a surrogate of renal biopsy for the differentiation of DN patients from patients with DM.

The plasma cell-free DNA (cfDNA) was sequenced from 53 healthy individuals, 53 patients with DM but without DN, and 71 patients with both DM and DN. Multidimensional features of plasma DNA were analyzed to dissect the cfDNA profile in the DM and DN patients and identify DN-specific cfDNA features. Finally, a classification model was constructed by integrating all informative cfDNA features to demonstrate the clinical utility in DN detection.

In comparison with the DM patients, the DN individuals exhibited significantly increased cfDNA concentration in plasma. The cfDNA from the DN patients showed a distinct fragmentation pattern with an altered size profile and preferred motifs that start with "CC" in the cfDNA ending sites, which were associated with deoxyribonuclease 1 like 3 (DNASE1L3) expression in the kidney. Moreover, patients with DM or DN were found to carry more alterations in whole-genome cfDNA coverage when compared with healthy individuals. We integrated DN-specific cfDNA features (cfDNA concentration, size, and motif) into a classification model, which achieved an area under the receiver operating characteristic curve (AUC) of 0.928 for the differentiation of DN patients from DM patients.

Our findings showed plasma cfDNA as a reliable non-invasive biomarker for differentiating DN patients from DM patients. The utility of cfDNA in clinical practice in large prospective cohorts is warranted.

The progressive nature of Crohn's disease is highly variable and hard to predict. In addition, symptoms correlate poorly with mucosal inflammation. There is therefore an urgent need to better characterize the heterogeneity of disease trajectories in Crohn's disease by utilizing objective markers of inflammation. We aimed to better understand this heterogeneity by clustering Crohn's disease patients with similar longitudinal fecal calprotectin profiles.

We performed a retrospective cohort study at the Edinburgh IBD Unit, a tertiary referral center, and used latent class mixed models to cluster Crohn's disease subjects using fecal calprotectin observed within 5 years of diagnosis. Information criteria, alluvial plots, and cluster trajectories were used to decide the optimal number of clusters. Chi-square test, Fisher's exact test, and analysis of variance were used to test for associations with variables commonly assessed at diagnosis.

Our study cohort comprised 356 patients with newly diagnosed Crohn's disease and 2856 fecal calprotectin measurements taken within 5 years of diagnosis (median 7 per subject). Four distinct clusters were identified by characteristic calprotectin profiles: a cluster with consistently high fecal calprotectin and 3 clusters characterized by different downward longitudinal trends. Cluster membership was significantly associated with smoking (P = .015), upper gastrointestinal involvement (P < .001), and early biologic therapy (P < .001).

Our analysis demonstrates a novel approach to characterizing the heterogeneity of Crohn's disease by using fecal calprotectin. The group profiles do not simply reflect different treatment regimens and do not mirror classical disease progression endpoints.

To develop a risk assessment tool to identify patients with type 2 diabetes (T2D) at higher risk for kidney disease progression and who might benefit more from sodium-glucose cotransporter 2 (SGLT2) inhibition.

A total of 41,204 patients with T2D from four Thrombolysis In Myocardial Infarction (TIMI) clinical trials were divided into derivation (70%) and validation cohorts (30%). Candidate predictors of kidney disease progression (composite of sustained ≥40% decline in estimated glomerular filtration rate [eGFR], end-stage kidney disease, or kidney death) were selected with multivariable Cox regression. Efficacy of dapagliflozin was assessed by risk categories (low: <0.5%; intermediate: 0.5 to <2%; high: ≥2%) in Dapagliflozin Effect on Cardiovascular Events (DECLARE)-TIMI 58.

There were 695 events over a median follow-up of 2.4 years. The final model comprised eight independent predictors of kidney disease progression: atherosclerotic cardiovascular disease, heart failure, systolic blood pressure, T2D duration, glycated hemoglobin, eGFR, urine albumin-to-creatinine ratio, and hemoglobin. The c-indices were 0.798 (95% CI, 0.774-0.821) and 0.798 (95% CI, 0.765-0.831) in the derivation and validation cohort, respectively. The calibration plot slope (deciles of predicted vs. observed risk) was 0.98 (95% CI, 0.93-1.04) in the validation cohort. Whereas relative risk reductions with dapagliflozin did not differ across risk categories, there was greater absolute risk reduction in patients with higher baseline risk, with a 3.5% absolute risk reduction in kidney disease progression at 4 years in the highest risk group (≥1%/year). Results were similar with the 2022 Chronic Kidney Disease Prognosis Consortium risk prediction model.

Risk models for kidney disease progression can be applied in patients with T2D to stratify risk and identify those who experience a greater magnitude of benefit from SGLT2 inhibition.

Diabetes is the leading cause of CKD and kidney failure. We assessed the real-world effectiveness of Rehmannia-6-based Chinese medicine treatment, the most used Chinese medicine formulation, on the change in eGFR and albuminuria in patients with diabetes and CKD with severely increased albuminuria.

In this randomized, assessor-blind, standard care-controlled, parallel, multicenter trial, 148 adult patients from outpatient clinics with type 2 diabetes, an eGFR of 30-90 ml/min per 1.73 m 2 , and a urine albumin-to-creatinine ratio (UACR) of 300-5000 mg/g were randomized 1:1 to a 48-week add-on protocolized Chinese medicine treatment program (using Rehmannia-6-based formulations in the granule form taken orally) or standard care alone. Primary outcomes were the slope of change in eGFR and UACR between baseline and end point (48 weeks after randomization) in the intention-to-treat population. Secondary outcomes included safety and the change in biochemistry, biomarkers, and concomitant drug use.

The mean age, eGFR, and UACR were 65 years, 56.7 ml/min per 1.73 m 2 , and 753 mg/g, respectively. Ninety-five percent ( n =141) of end point primary outcome measures were retrievable. For eGFR, the estimated slope of change was -2.0 (95% confidence interval [CI], -0.1 to -3.9) and -4.7 (95% CI, -2.9 to -6.5) ml/min per 1.73 m 2 in participants treated with add-on Chinese medicine or standard care alone, resulting in a 2.7 ml/min per 1.73 m 2 per year (95% CI, 0.1 to 5.3; P = 0.04) less decline with Chinese medicine. For UACR, the estimated proportion in the slope of change was 0.88 (95% CI, 0.75 to 1.02) and 0.99 (95% CI, 0.85 to 1.14) in participants treated with add-on Chinese medicine or standard care alone, respectively. The intergroup proportional difference (0.89, 11% slower increment in add-on Chinese medicine, 95% CI, 0.72 to 1.10; P = 0.28) did not reach statistical significance. Eighty-five adverse events were recorded from 50 participants (add-on Chinese medicine versus control: 22 [31%] versus 28 [36%]).

Rehmannia-6-based Chinese medicine treatment stabilized eGFR on top of standard care alone after 48 weeks in patients with type 2 diabetes, stage 2-3 CKD, and severely increased albuminuria.

Semi-individualized Chinese Medicine Treatment as an Adjuvant Management for Diabetic Nephropathy (SCHEMATIC), NCT02488252 .

To compare clinical and pathological characteristics as well as prognosis between diabetic nephropathy (DN) and non-diabetic renal disease (NDRD) so as to explore potential diagnostic criteria of DN and provide some guidance for the treatment of type 2 diabetes mellitus (T2DM) patients with kidney involvement.

T2DM patients with renal impairment who underwent kidney biopsy were included in this study, who were classified into 3 groups (DN, NDRD, DN with NDRD) based on their renal pathological diagnosis. Baseline clinical characteristics as well as follow-up data were collected and analyzed among 3 groups. Logistic regression was performed to determine the best predictors for DN diagnosis. Additional 34 MN patients without diabetes were enrolled by propensity score matching method to compare serum PLA2R antibody titer and kidney outcomes between diabetic MN patients and MN alone.

Among 365 patients with type 2 diabetes who underwent kidney biopsy, 179 (49.0%) patients were diagnosed with NDRD alone and 37 (10.1%) patients with NDRD combined DN. Risk factors for DN development in T2DM patients were longer time since diabetes diagnosis, higher level of serum creatinine, absence of hematuria and presence of diabetic retinopathy by multivariate analysis. Lower rate of proteinuria remission and higher risk of renal progression were observed in DN group compared with NDRD group. Membranous nephropathy was the most common NDRD in diabetic patients. There was no difference in serum PLA2R antibody positiveness or titer between MN patients with or without T2DM. There was lower remission rate but similar renal progression in diabetic MN when age, gender, baseline eGFR, albuminuria and IFTA score were adjusted.

Non-diabetic renal disease is not uncommon in T2DM patients with renal impairment, which has better prognosis with proper treatment. Coexisting diabetic status does not exert negative impact on renal progression in MN patients, and immunosuppressive agents should be administered when necessary.

We analyzed the incidence of kidney disease in the Diabetes Prevention Program Outcomes Study (DPPOS) by originally randomized treatment group assignment: Intensive Lifestyle (ILS), Metformin (MET) or Placebo (PLB).

The current analyses used a time-to-event approach in which the primary outcome was kidney disease, ascertained as urine albumin-to-creatinine ratio (ACR) ≥ 3.39 mg/mmol (30 mg/g) or eGFR <45 mL/min/1.73m2, with confirmation required at the next visit, or adjudicated end-stage kidney disease (ESKD).

At a median of 21 years following randomization in DPP, diabetes development was reduced in both the ILS (HR 0.73 [95%CI = 0.62, 0.85]) and MET groups (HR 0.85 [0.73, 0.99]) compared to the PLB group. Although risk for developing the primary kidney disease outcome was higher among those with incident diabetes compared to those without (HR 1.81 [1.43, 2.30]), it did not differ by intervention groups (ILS vs. PLB 1.02 (0.81, 1.29); MET vs. PLB 1.08 (0.86, 1.35). There was a non-significant metformin by age interaction (p = 0.057), with metformin being beneficial for kidney disease in the younger but potentially harmful in the older participants.

Development of kidney disease was increased in participants who developed diabetes but did not differ by original treatment group assignment.

Diabetes Prevention Program (DPP) Clinical trial reg. no. NCT00004992 DPP Outcomes Study (DPPOS) Clinical trial reg. no. NCT0038727.

Quality of life in chronic kidney disease (CKD) is impaired by a large burden of symptoms including some that overlap with the symptoms of heart failure (HF). We studied a group of individuals with CKD to understand the patterns and trajectories of HF-type symptoms in this setting.

Prospective cohort study.

3,044 participants in the Chronic Renal Insufficiency Cohort (CRIC) without prior diagnosis of HF.

Sociodemographics, medical history, medications, vital signs, laboratory values, echocardiographic and electrocardiographic parameters.

Trajectory over 5.5 years of a HF-type symptom score (modified Kansas City Cardiomyopathy Questionnaire [KCCQ] Overall Summary Score with a range of 0-100 where<75 reflects clinically significant symptoms).

Latent class mixed models were used to model trajectories. Multinomial logistic regression was used to model relationships of predictors with trajectory group membership.

Five trajectories of KCCQ score were identified in the cohort of 3,044 adults, 45% of whom were female, and whose median age was 61 years. Group 1 (41.7%) had a stable high score (minimal symptoms, average score of 96); groups 2 (35.6%) and 3 (15.6%) had stable but lower scores (mild symptoms [average of 81] and clinically significant symptoms [average of 52], respectively). Group 4 (4.9%) had a substantial worsening in symptoms over time (mean 31-point decline), and group 5 (2.2%) had a substantial improvement (mean 33-point increase) in KCCQ score. A majority of group 1 was male, without diabetes or obesity, and this group had higher baseline kidney function. A majority of groups 2 and 3 had diabetes and obesity. A majority of group 4 was male and had substantial proteinuria. Group 5 had the highest proportion of baseline cardiovascular disease (CVD).

No validation cohort available, CKD management changes in recent years may alter trajectories, and latent class models depend on the missing at random assumption.

Distinct HF-type symptom burden trajectories were identified in the setting of CKD, corresponding to different baseline characteristics. These results highlight the diversity of HF-type symptom experiences in individuals with CKD.

Thrombospondin-2 (TSP2) is a matricellular protein with tissue expression induced by hyperglycaemia. TSP2 has been implicated in non-diabetic renal injury in preclinical studies and high circulating levels were associated with worse kidney function in cross-sectional clinical studies. Therefore, we investigated the prospective associations of circulating TSP2 level with kidney function decline and the trajectories of estimated glomerular filtration rate (eGFR) in type 2 diabetes.

Baseline serum TSP2 level was measured in 5471 patients with type 2 diabetes to evaluate its association with incident eGFR decline, defined as ≥ 40% sustained eGFR decline, using multivariable Cox regression analysis. Among participants with relatively preserved kidney function (Baseline eGFR ≥ 60 ml/min/1.73m2), joint latent class modelling was employed to identify three different eGFR trajectories. Their associations with baseline serum TSP2 was evaluated using multinomial logistic regression analysis. The predictive performance of serum TSP2 level was examined using time-dependent c-statistics and calibration statistics.

Over a median follow-up of 8.8 years, 1083 patients (19.8%) developed eGFR decline. Baseline serum TSP2 level was independently associated with incident eGFR decline (HR 1.21, 95%CI 1.07-1.37, P = 0.002). With internal validation, incorporating serum TSP2 to a model of clinical risk factors including albuminuria led to significant improvement in c-statistics from 83.9 to 84.4 (P < 0.001). Among patients with eGFR ≥ 60 ml/min/1.73m2, baseline serum TSP2 level was independently associated with a rapidly declining eGFR trajectory (HR 1.63, 95%CI 1.26-2.10, P < 0.001).

Serum TSP2 level was independently associated with incident eGFR decline, particularly a rapidly declining trajectory, in type 2 diabetes.

Plasma creatinine is a marker of interest in renal transplantation but data on its kinetics in the first days following transplantation are scarce. The aim of this study was to identify clinically relevant subgroups of creatinine trajectories following renal transplantation and to test their association with graft outcome. Among 496 patients with a first kidney transplant included in the French ASTRE cohort at the Poitiers University hospital, 435 patients from donation after brain death were considered in a latent class modeling. Four distinct classes of creatinine trajectories were identified: "poor recovery" (6% of patients), "intermediate recovery" (47%), "good recovery" (10%) and "optimal recovery" (37%). Cold ischemia time was significantly lower in the "optimal recovery" class. Delayed graft function was more frequent and the number of hemodialysis sessions was higher in the "poor recovery" class. Incidence of graft loss was significantly lower in "optimal recovery" patients with an adjusted risk of graft loss 2.42 and 4.06 times higher in "intermediate recovery" and "poor recovery" patients, respectively. Our study highlights substantial heterogeneity in creatinine trajectories following renal transplantation that may help to identify patients who are more likely to experience a graft loss.