Background: Sodium-glucose cotransporter 2 (SGLT2) inhibitors slow the progression of chronic kidney disease (CKD), though their potential to prevent the development of CKD in type 2 diabetes needs to be examined. Purpose: Evaluate SGLT2 inhibitors for the primary prevention of CKD in people with type 2 diabetes. Data Sources: PubMed and Cochrane CENTRAL were searched through October 2025. Data Synthesis: Randomized controlled trials (RCTs) of SGLT2 inhibitors compared to placebo or other glucose-lowering agents in people with type 2 diabetes without baseline CKD were included. Outcomes were eGFR decline and incident albuminuria (i.e., UACR ≥30 mg/g). Random-effects meta-analyses were performed, and heterogeneity was assessed with I2. Certainty of evidence was evaluated with GRADE. PROSPERO CRD420251130722. Results: Eight RCTs were included: 5 cardiovascular outcomes trials comparing SGLT2 inhibitors and placebo (24072 participants) and 3 trials comparing SGLT2 inhibitors and sulfonylureas (2889 participants). Compared to placebo, SGLT2 inhibitors reduced the risk of incident albuminuria (3 trials, hazard ratio [HR]: 0.82, 95% CI (0.77-0.88), I2=0%, high certainty) and slowed eGFR decline based on chronic eGFR slope (5 trials, mean difference [MD]: 0.95 (0.84-1.07) ml/min/1.73 m2/year, I2=19%, high certainty) and total eGFR slope (4 trials, MD: 0.76 (0.50-1.03) ml/min/1.73 m2/year, I2=88%, moderate certainty). Compared to sulfonylureas, SGLT2 inhibitors slowed eGFR decline based on chronic eGFR slope (3 trials, MD: 2.43 (1.72-3.13) ml/min/1.73 m2/year, I2=55%, moderate certainty). Conclusions: In people with type 2 diabetes without CKD, SGLT2 inhibitors slow eGFR decline compared to both placebo and sulfonylureas and prevent incident albuminuria compared to placebo. Article Highlights (111/130 words) · Why did we undertake this study? To evaluate the use of sodium-glucose cotransporter 2 (SGLT2) inhibitors for the primary prevention of chronic kidney disease (CKD) in people with type 2 diabetes. · What is the specific question(s) we wanted to answer? Can SGLT2 inhibitors prevent the onset of CKD in people with type 2 diabetes who do not have evidence of CKD at baseline? · What did we find? In people with type 2 diabetes without baseline CKD, SGLT2 inhibitors prevent incident albuminuria and slow eGFR decline. · What are the implications of our findings? Evidence supports the use of SGLT2 inhibitors for the primary prevention of CKD in people with type 2 diabetes.

BACKGROUND:An elevated level of lipoprotein(a) (Lp[a]) is a genetically-determined cardiovascular risk factor. A size polymorphism in its apolipoprotein(a) (apo[a]) component, expressed as kringle (K) 4 repeat numbers, is a major contributor to variability in levels. While chronic kidney disease (CKD) increases Lp(a) levels, less is known about its effect on Lp(a) molecular properties. OBJECTIVE:To assess and compare Lp(a) lipidomic properties in patients with CKD and controls. METHODS:We assessed and compared Lp(a)-lipidomic properties in 54 nondiabetic, nondialysis patients with CKD and 39 controls. CKD was defined by an estimated glomerular filtration rate of <60 mL/min/1.73 m2. RESULTS:The mean age of the cohort was 63 years, 48% were women, and 77% were of European descent. Lp(a)-bound oxidized phospholipids (Lp[a]-OxPL) concentrations were higher in patients with CKD vs controls (median [IQR] 2.7 [0.5; 7.4] vs 1.2 [0.5; 3.4] U/L, P = 0.031), in particular for the medium (23-27 K repeats) apo(a) size range (P = 0.002). Among Lp(a)-OxPL subspecies, 1-palmitoyl-2-(5'-oxo-valeroyl)-sn-glycero-3-phosphocholine relative abundance was significantly higher in patients with CKD compared to controls (21% vs 16%, P = 0.0004). Of the 437 individual lipid species in Lp(a), 146 species primarily representing diacylglycerols (P = 0.009), acylcarnitines (P = 0.003), and triacylglycerols (P = 0.005) showed significantly higher abundance in patients with CKD vs controls. This pattern remained unchanged after adjusting for differences in Lp(a) levels, indicating an impact of the CKD condition on Lp(a) lipidomic properties. CONCLUSION:Among individuals without diabetes, kidney impairment was characterized by higher Lp(a)-OxPL concentrations and proinflammatory Lp(a)-lipidomic properties. Mechanisms underlying these changes and relevance to cardiovascular risk warrant further investigations.

Background: Hemodialysis affects glycemia in a manner that remains incompletely defined. Methods: In a prospective cohort study, 342 participants on maintenance hemodialysis wore a Dexcom G6 Pro continuous glucose monitor (CGM) for 10 days while dialyzing with standardized 100 mg/dL glucose dialysate. We examined glycemia relative to dialysis timing and tested associations of glycemia patterns with clinical characteristics and markers of overall glycemic control. Glucoregulatory hormones were measured pre- and post-dialysis in a subset of 20 participants. Results: Overall, CGM captured 1,001 hemodialysis sessions. Among participants with treated diabetes (n=143), untreated diabetes (n=78), and without diabetes (n=121), pre-dialysis glucose averaged 212 ± 84 mg/dL, 167 ± 65 mg/dL, and 120 ± 28 mg/dL, respectively. During dialysis, glucose declined by 53 ± 79 mg/dL, 29 ± 55 mg/dL, and 7 ± 32 mg/dL, respectively. Post-dialysis, glucose rebounded by 115 ± 70 mg/dL (to mean peak 265 ± 84 mg/dL), 95 ± 60 mg/dL (227 ± 71 mg/dL) and 61 ± 35 mg/dL (168 ± 37 mg/dL), respectively, with mean time to peak occurring later in treated (172 minutes post-dialysis) and untreated (169 min) diabetes compared with no diabetes (140 min). Post-dialytic rebound glycemia correlated with hemoglobin A1c and mean CGM glucose over the full observation period. Hypoglycemic events <70 mg/dL were uncommon (N=259); hypoglycemic event rates were significantly higher in the post-dialysis period compared with time-matched periods on non-dialysis days. There were no significant differences in hypoglycemic event rates pre- versus post-dialysis on dialysis days. In the substudy, most glucoregulatory peptides declined significantly (p<0.001) during dialysis including insulin (median change: -38%), glucagon (-43%), and glucagon-like peptide-1 (-38%). Conclusions: Hemodialysis induces intradialytic glucose declines and post-dialytic rebound that link to overall glycemic control, highlighting dialysis as a physiologic stressor on glucose homeostasis.

Background Chronic kidney disease (CKD) is a global health problem which is associated with poor outcomes, and its prevalence is expected to increase. Identifying novel risk factors for CKD may lead to improved outcomes. Circulating saturated fatty acids (SFAs) have been posited as contributors to CKD risk. Objectives We aimed to evaluate associations between circulating SFAs (measured in phospholipids in 7 cohorts, serum or plasma total in 5 cohorts, and cholesterol esters in 1 cohort) and incident CKD in 13 cohorts, and to pool results by meta-analysis across the studies. Methods SFAs were measured in 13 cohorts in the Fatty Acids Outcomes Research Consortium, including 18,193 participants with estimated glomerular filtration rate >60 mL/min/1.73 m2 across 9 countries. Associations between each SFA [palmitic acid (16:0), stearic acid (18:0), arachidic acid (20:0), behenic acid (22:0), and lignoceric acid (24:0)] and incident CKD (defined as an estimated glomerular filtration rate <60 mL/min/1.73 m2 and ≥25% decrease from baseline) were assessed by Cox or Poisson regressions. Results were pooled using inverse variance weighted meta-analysis. Results In total, 2554 participants developed CKD over a weighted median follow-up of 7.6 y. After adjustment, higher concentrations of 18:0 were associated with a lower risk of CKD with minimal heterogeneity (relative risk per interquintile range: 0.87; 95% confidence interval: 0.80, 0.95, P = 0.003, I2 = 14.7%). These associations remained consistent in secondary and sensitivity analyses. We did not observe significant associations of other SFAs with CKD. Conclusions In a meta-analysis of 18,193 participants across 9 countries, we observed no indication that SFA increased CKD risk, whereas higher 18:0 concentrations were associated with a lower risk of CKD. Future research is needed to assess mechanisms by which SFA 18:0 may exert kidney-protective effects, and how circulating SFA 18:0 concentrations may be altered.

KEY POINTS:Previous research has identified polygenic risk scores that are associated with low eGFR and albuminuria in the general population. We observed that these eGFR and albuminuria polygenic risk scores were associated with eGFR and albuminuria, respectively, in type 1 diabetes. Associations were independent of glycemic control and suggest shared genetic kidney risk factors between type 1 diabetes and the general population. BACKGROUND:Genetic risk factors underlying kidney disease in type 1 diabetes (T1D) remain poorly understood. We examined whether previously established polygenic risk scores (PRS) for eGFR and albuminuria are associated with these measures in adults with T1D in the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications study. METHODS:We applied eGFR and albuminuria PRS derived in general population cohorts to 1304 DCCT/Epidemiology of Diabetes Interventions and Complications participants with genome-wide genotyping. We tested PRS associations with eGFR and urine albumin excretion rate (AER) as well as incident eGFR <60 ml/min per 1.73 m 2 , AER ≥30 mg/24 h, and AER ≥300 mg/24 h. For consistency, PRS values were linearly transformed so higher scores corresponded to higher eGFR and AER. We also examined associations of kidney outcomes with rs55703767 in COL4A3 , which has previously been associated with CKD in T1D. RESULTS:At DCCT baseline, participants had a mean age of 27 years; 53% were male. 49% of participants were randomized to intensive versus conventional glucose-lowering therapy. Participants were followed for median of (first-third quartiles) 35 (33-37) years. The eGFR PRS was significantly associated with continuous eGFR (per one SD higher PRS 2.72 ml/min per 1.73 m 2 higher [95% confidence interval (CI), 2.05 to 3.40]) and incident eGFR <60 ml/min per 1.73 m 2 (hazard ratio [HR]=0.82 [95% CI, 0.73 to 0.92]), but not consistently with albuminuria. There was no association with quantitative AER (2.42 mg/24 h [95% CI, -1.86 to 6.89]) or sustained AER ≥30 mg/24 h (HR=1.03; [95% CI, 0.94 to 1.14]). The albuminuria PRS was significantly associated with incident AER ≥30 mg/24 h (HR=1.12 [95% CI, 1.02 to 1.22]) but not continuous eGFR (0.49 ml/min per 1.73 m 2 higher [95% CI, -0.23 to 1.21]) or incident eGFR <60 ml/min per 1.73 m 2 (HR=0.96 [95% CI, 0.85 to 1.08]). Associations were similar in analyses stratified by DCCT treatment group assignment. rs55703767 was associated with lower incident macroalbuminuria in the overall cohort (HR=0.77 per minor allele [95% CI, 0.59 to 0.99]), and upon stratification by DCCT treatment group assignment, only within the conventional and not intensive glucose-lowering therapy group. CONCLUSIONS:PRS associated with eGFR and albuminuria in the general population were associated with corresponding measures in adults with T1D. The results suggest shared genetic risk factors for kidney disease between T1D and the general population but different genetic risk factors for albuminuria and eGFR in T1D. CLINICAL TRIALS REGISTRATION NUMBERS:NCT00360893 , NCT00360815 .

AIM:The "2026 AHA/ACC/ADA/ASN Guideline for the Prevention, Detection, Evaluation, and Management of Cardiovascular-Kidney-Metabolic Syndrome" retires, replaces, and expands upon the "2013 AHA/ACC/TOS Guideline for the Management of Overweight and Obesity in Adults." The primary intended audience for this guideline is clinicians who care for patients across the spectrum of cardiovascular-kidney-metabolic syndrome, an interrelated condition characterized by the interconnections among metabolic risk factors (including obesity and type 2 diabetes), chronic kidney disease, and cardiovascular disease. METHODS:A comprehensive literature search was conducted from October 29, 2024, to April 14, 2025, to identify clinical studies, systematic reviews and meta-analyses, and other evidence conducted on human subjects that were published since 2015 in English from MEDLINE (through PubMed), EMBASE, the Cochrane Library, the Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline. STRUCTURE:The focus of this clinical practice guideline is to create a living, working document that provides current knowledge in the field of cardiovascular-kidney-metabolic syndrome aimed at all practicing cardiologists, endocrinologists, nephrologists, and primary care and specialty clinicians who manage these patients.

Background: The Kidney Precision Medicine Project (KPMP) consortium aims to redefine chronic kidney disease (CKD) by integrating clinical, pathological, and molecular tissue data from kidney biopsies. Here, we demonstrate how biopsy data in CKD can clarify disease etiology and contribute to understandings of disease pathophysiology and clinical prognosis. Methods: The KPMP is obtaining research kidney biopsies from individuals with CKD (defined as an estimated glomerular filtration rate [eGFR] < 60 mL/min/1.73m2 and/or albuminuria >30 mg/g creatinine) and diabetes (enrolled as diabetes and CKD or DKD) or hypertension (enrolled as hypertension and CKD or HCKD). A team of kidney pathologists and nephrologists adjudicated the primary clinico-pathological diagnosis for 258 participants with CKD. We compared pathological features and kidney transcriptional signatures between participants with a primary adjudicated diagnosis of diabetic nephropathy and those with other causes of CKD. We developed a model using clinical and biomarker data that predicted the probability of diabetic nephropathy and tested associations of the signature with CKD progression among Chronic Renal Insufficiency Cohort (CRIC) participants with diabetes (n=229). Results: Among 183 participants enrolled as DKD, 102 (56%) had a primary adjudicated clinico-pathologic diagnosis of diabetic nephropathy. Among 75 participants enrolled as HCKD, 42 (56%) had a primary diagnosis of hypertension-associated kidney disease. Those with diabetic nephropathy, compared with other diagnoses, had more severe interstitial fibrosis, tubular atrophy, tubular injury, segmental sclerosis, and severe arteriolar hyalinosis, and single-nucleus and single-cell transcriptional analyses revealed upregulation of immune and inflammatory pathways and downregulation of oxidative phosphorylation. A combination of age, hemoglobin A1c, urine albumin-creatinine ratio, and serum KIM-1 and sTNFR1 predicted a clinico-pathologic diagnosis of diabetic nephropathy in the KPMP (AUC 0.82, 95% CI 0.75-0.89) and was associated with an increased risk of CKD progression among patients with diabetes enrolled in CRIC (HR 1.48 [95% CI 1.27-1.73] per 10% higher predicted probability of diabetic nephropathy). Conclusion: In common presentations of CKD, kidney biopsies may alter a priori impressions, reveal a diversity of diagnosis, structure, and function that is associated with clinical outcomes and can impact therapeutic decisions. ### Competing Interest Statement The authors have declared no competing interest. ### Clinical Protocols ### Funding Statement The Kidney Precision Medicine Project (KPMP) is supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) through the following grants: U01DK133081, U01DK133091, U01DK133092, U01DK133093, U01DK133095, U01DK133097, U01DK114866, U01DK114908, U01DK133090, U01DK133113, U01DK133766, U01DK133768, U01DK114907, U01DK114920, U01DK114923, U01DK114933, U24DK114886, UH3DK114926, UH3DK114861, UH3DK114915, and UH3DK114937. Funding for the CRIC Study was obtained under a cooperative agreement from National Institute of Diabetes and Digestive and Kidney Diseases (U01DK060990, U01DK060984, U01DK061022, U01DK061021, U01DK061028,U01DK060980, U01DK060963, U01DK060902 and U24DK060990). In addition, this work was supported in part by: the Perelman School of Medicine at the University of Pennsylvania Clinical and Translational Science Award NIH/NCATS UL1TR000003, Johns Hopkins University UL1 TR-000424, University of Maryland GCRC M01 RR-16500, Clinical and Translational Science Collaborative of Cleveland, UL1TR000439 from the National Center for Advancing Translational Sciences (NCATS) component of the National Institutes of Health and NIH roadmap for Medical Research, Michigan Institute for Clinical and Health Research (MICHR) UL1TR000433, University of Illinois at Chicago CTSA UL1RR029879, Tulane COBRE for Clinical and Translational Research in Cardiometabolic Diseases P20 GM109036, Kaiser Permanente NIH/NCRR UCSF-CTSI UL1 RR-024131, Department of Internal Medicine, University of New Mexico School of Medicine Albuquerque, NM R01DK119199. We gratefully acknowledge the essential contributions of our patient participants and the support of the American public through their tax dollars. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study was approved by the University of Washington Institutional Review Board (IRB 20190213). Written informed consent was received from all participants prior to study participation. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Clinical and histopathological data used in the study are available upon request to the KPMP via kpmp.org. Biomarker and molecular data used in the study are available online at kpmp.org.

Developing a path forward for sodium-glucose cotransporter (SGLT) inhibitor treatment for heart and kidney disease in people with type 1 diabetes (T1D) is essential. This article offers the perspective of experts from the fields of endocrinology, nephrology, and cardiology on available data for the efficacy and safety of SGLT inhibitors in T1D, how the far more extensive data from people with type 2 diabetes (T2D) and people without diabetes would be expected to translate to T1D, and what steps are required to advance toward regulatory approvals and clinical uptake of SGLT inhibitors in T1D for heart and kidney disease. Our conclusion is that the mechanisms driving efficacy of SGLT inhibitors for heart and kidney disease in T2D and nondiabetic disease are likely applicable to T1D and that in light of the data supporting efficacy in these populations, registrational trials in T1D might not require powering for traditional event-based outcomes and investigators may instead rely on suitable surrogate end points, allowing for more feasible trials. Investigators in these trials must also carefully collect data associated with diabetic ketoacidosis (DKA), the critical risk of SGLT inhibitor use in T1D. DKA risk mitigation is essential for SGLT inhibitor use in T1D; protocols to mitigate risk have been developed, but rigorous data on their effectiveness are lacking. We describe a roadmap to advance SGLT inhibitors for T1D heart and kidney disease, which includes the use of feasible trial designs based on surrogate end points and rigorous safety protocols to minimize DKA events.

KEY POINTS:Hemodialysis disrupts glucose homeostasis: Levels fall during treatment, then rebound sharply afterward, often exceeding baseline. Postdialysis glucose rebound was higher and longer in people with diabetes, especially with insulin, but also occurred in people without diabetes. Hemodialysis disrupts glucoregulatory hormonal balance, and these disruptions may impair postprandial glucose disposal. BACKGROUND:Hemodialysis affects glycemia in a manner that remains incompletely defined. METHODS:In a prospective cohort study, 342 participants on maintenance hemodialysis wore a Dexcom G6 Pro continuous glucose monitor (CGM) for 10 days while dialyzing with standardized 100 mg/dl glucose dialysate. We examined glycemia relative to dialysis timing and tested associations of glycemia patterns with clinical characteristics and markers of overall glycemic control. Glucoregulatory hormones were measured before and after dialysis in a subset of 20 participants. RESULTS:Overall, CGM captured 1001 hemodialysis sessions. Among participants with treated diabetes ( n =143), with untreated diabetes ( n =78), and without diabetes ( n =121), predialysis glucose averaged 212±84, 167±65, and 120±28 mg/dl, respectively. During dialysis, glucose declined by 53±79, 29±55, and 7±32 mg/dl, respectively. After dialysis, glucose rebounded by 115±70 mg/dl (to mean peak 265±84 mg/dl), 95±60 mg/dl (227±71 mg/dl), and 61±35 mg/dl (168±37 mg/dl), respectively, with mean time to peak occurring later in treated (172 minutes after dialysis) and untreated (169 minutes) diabetes compared with no diabetes (140 minutes). Postdialytic rebound glycemia correlated with hemoglobin A1c and mean CGM glucose over the full observation period. Hypoglycemic events <70 mg/dl were uncommon ( N =259); hypoglycemic event rates were significantly higher in the postdialysis period compared with time-matched periods on nondialysis days. There were no significant differences in hypoglycemic event rates before versus after dialysis on dialysis days. In the substudy, most glucoregulatory peptides declined significantly ( P < 0.001) during dialysis, including insulin (median change: -38%), glucagon (-43%), and glucagon-like peptide-1 (-38%). CONCLUSIONS:Hemodialysis induces intradialytic glucose declines and postdialytic rebound that link to overall glycemic control, highlighting dialysis as a physiologic stressor on glucose homeostasis.

Chronic kidney disease (CKD) is closely intertwined with obesity, diabetes, hypertension, dyslipidemia, and cardiovascular disease. In 2023, the American Heart Association formally recognized these interconnections as a unified entity, the cardiovascular-kidney-metabolic (CKM) syndrome. The CKM syndrome brings renewed attention to the importance of CKD in cardiovascular disease and reinforces the need for effective, evidence-based, interdisciplinary approaches to diagnose and prevent its intersecting components. The Kidney Disease: Improving Global Outcomes (KDIGO) organization has long led efforts to synthesize knowledge and translate evidence to practice in this area through the lens of the kidney. This review highlights KDIGO clinical practice guidelines and controversies conference publications that directly address the CKM syndrome. These include guidelines addressing CKD, blood pressure, diabetes, and lipids; an upcoming guideline addressing heart failure in CKD; and controversies conference reports addressing obesity and CKD prevention. Overarching themes include the importance of early detection and intervention; comprehensive, personalized management of kidney and cardiovascular risk; and multidisciplinary care. Through integrated, evidence-based, disease-specific guidelines and reports, KDIGO has established a robust framework for the management of people at risk for or with CKM syndrome as well as priorities for ongoing research.

BACKGROUND:The oral glucose tolerance test (OGTT) captures integrated physiological responses involving intestinal glucose absorption, incretin signaling, and endogenous insulin secretion, whereas the hyperinsulinemic-euglycemic clamp (clamp) isolates insulin-mediated glucose uptake. Comparing plasma metabolomic responses to these two challenges may identify processes specific to intestinal nutrient delivery and how they vary in CKD. METHODS:Targeted plasma metabolomics was performed in 59 adults without diabetes (39 with CKD [eGFR <60 mL/min/1.73 m2] and 20 controls) from the Study of Glucose and Insulin in Renal Disease (SUGAR). Each participant underwent a 75-g OGTT and clamp approximately one week apart. Eighty-eight plasma metabolites were quantified at fasting and during each challenge. Metabolite levels were log-transformed and normalized using Systematic Error Removal Using Random Forest (SERRF). Metabolites were classified using adjusted regression slopes relating OGTT and clamp responses. RESULTS:The mean (SD) age and eGFR were 64 (13) years and 54 (26) mL/min/1.73 m2, respectively, and 41% were female. In the overall cohort, OGTT and clamp induced broad plasma metabolic changes, with 63 (72%) and 76 (86%) metabolites significantly altered from fasting, respectively. Seventy-three metabolites (83%) demonstrated a significant relationship between OGTT and clamp responses. Of these, 22 (25%) exhibited true concordance and 51 (58%) demonstrated similar directional changes but differed in magnitude. A total of 15 (17%) metabolites were discordant or non-corresponding, of which only three were discordant. The non-corresponding metabolites were enriched in amino acid metabolism. Eleven metabolites (13%) demonstrated differential responses between OGTT and clamp by CKD status, involving amino acid and glucose metabolism pathways. CONCLUSIONS:Metabolomic responses to OGTT and clamp were largely directionally concordant but differed in magnitude, with attenuation during OGTT. Discordant metabolites were rare, while non-corresponding metabolites were confined to amino acid pathways. CKD modified OGTT-clamp correspondence for metabolites involved in amino acid and glycolytic metabolism.

OBJECTIVE:Accurate assessment of glycemia in patients treated with maintenance dialysis is imperative and hampered by known biases of glycated hemoglobin (HbA1c) in kidney failure (KF). This study evaluated the accuracy, variability, and covariate bias of three glycemic biomarkers compared with glycemia measured by continuous glucose monitor (CGM) among people with and without diabetes treated with maintenance dialysis. RESEARCH DESIGN AND METHODS:In a prospective community-based cohort study, 251 participants treated with maintenance dialysis wore a Dexcom G6 Pro CGM for 10 days. We compared correlations of HbA1c, glycated albumin (GA), and fructosamine with CGM-derived mean glycemia and examined sources of bias. RESULTS:Participants (43% women; 63% with diabetes) had a median of 9.3 (interquartile range 8.5-9.4) valid days of CGM data. Mean (SD) HbA1c, GA, fructosamine, and mean CGM glucose were 6.2% (1.4%), 19.6% (6.3%), 351 (99) µmol/L, and 170 (63) mg/dL, respectively. HbA1c, GA, and fructosamine all strongly correlated with mean CGM blood glucose, with HbA1c and GA more correlated than fructosamine (overall, r = 0.85, r = 0.87, and r = 0.70, respectively; in diabetes, r = 0.84, r = 0.84, and r = 0.64, respectively). Compared with mean CGM glucose, HbA1c was significantly biased by erythropoiesis-stimulating agent dose, BMI, hemoglobin, and serum albumin; GA and fructosamine were biased by dialysis modality and vintage, residual kidney function, and BMI. CONCLUSIONS:HbA1c and GA were strongly correlated with mean CGM blood glucose, but all biomarkers had substantial bias by relevant clinical characteristics. HbA1c and GA may be useful assessments of average glycemia in patients treated with maintenance dialysis, if bias can be adequately addressed.

BACKGROUND AND AIMS:Continuous glucose monitors (CGMs) can comprehensively assess glycemic patterns in patients treated with dialysis, in whom conventional biomarkers such as glycated hemoglobin are inaccurate. Nonetheless, adoption of recent versions of CGMs in this population has been complicated by concerns about interstitial volume expansion, interfering substances, and effects of dialysis treatment. This study aimed to examine the accuracy of the G6 Pro and G7 CGM systems (Dexcom, Inc.) compared with self-monitored blood glucose (SMBG) in a dialysis population. METHODS:Twelve participants treated with maintenance dialysis (11 hemodialysis, 1 peritoneal dialysis [PD]) with diabetes wore concurrent G6 Pro and G7 CGMs for a period of 10 days, during which they measured SMBG using a Contour Next glucometer. We summarized CGM-glucometer Pearson correlations, calculated the mean absolute relative difference (MARD) of G6 Pro/G7 and SMBG, created Diabetes Technology Society (DTS) error grids, and investigated the CGM lag time that most closely corresponded with SMBG. RESULTS:Mean (standard deviation [SD]) age of participants was 50 (12) years, 50% were female, mean (SD) diabetes duration was 24 (9) years, and 92% used insulin. Participants collected 245 SMBG measurements over a total of 178 days of CGM. The Pearson correlations of G6 Pro and SMBG, G7 and SMBG, and G6 Pro and G7 were 0.87, 0.88, and 0.95, respectively. The MARDs of G6 Pro versus SMBG and G7 versus SMBG were 21.2% and 16.7%, respectively; excluding one PD participant with highly variable glucose, MARDs were 18.3% and 13.5%. The DTS error grids showed that 96.7% of G6 Pro and 98.0% of G7 measurements were clinically acceptable (Zones A/B) when compared with SMBG. We observed evidence of greater lag times than previously seen in nondialysis populations and substantial between- and within-person variability in CGM performance. CONCLUSIONS:Among patients with diabetes treated with maintenance dialysis, CGM measurements of glucose had high correlation with SMBG, with better performance of the G7 compared with G6 Pro. MARD was higher than previously reported in nondialysis populations, but most values fell within clinically acceptable ranges. While issues around lag time, sensor placement, and interfering substances that may impact CGM performance warrant further investigation, our study findings support the use of CGM to evaluate glycemia in the dialysis population.

Background: The benefits of renin-angiotensin-aldosterone system (RAAS) inhibitors in people with diabetes and chronic kidney disease (CKD) are well-established, though their effects in people with diabetes without CKD have yet to be fully characterized. Purpose: Evaluate the effects of RAAS inhibitors on the development of CKD in people with diabetes without CKD. Data Sources: Searches were conducted in PubMed and Cochrane CENTRAL through October 2025. Study Selection: Eligible studies were randomized controlled trials (RCTs) of RAAS inhibitors versus placebo in people with type 1 or type 2 diabetes without baseline CKD. Outcomes were incident albuminuria (UACR ≥30 mg/g) and eGFR decline (eGFR<60 ml/min/1.73 m2, slopes, mean change). Data Synthesis: Random-effects meta-analyses were conducted separately for type 1 and type 2 diabetes and heterogeneity was assessed using I2. Certainty of evidence was assessed following the GRADE approach. PROSPERO CRD420251145019. Results: Fifteen RCTs were identified, 9 for type 2 diabetes (majority with hypertension) and 6 for type 1 diabetes (all with normotension). RAAS inhibitors reduced the risk of incident albuminuria in type 2 diabetes (18938 participants, risk ratio [RR] 0.83, 95% CI (0.76-0.91), I2 = 13%, high certainty) but not in type 1 diabetes (4047 participants, 0.98 (0.66-1.47), I2 = 50%, moderate certainty). Evidence on eGFR decline was limited, with no clear effects in type 1 or type 2 diabetes. Conclusions: RAAS inhibitors prevent incident albuminuria in people with type 2 diabetes and hypertension, though effects on eGFR are unclear. No benefits were observed in people with type 1 diabetes and normotension. Article Highlights (120/130 words) · Why did we undertake this study? To evaluate the effect of renin-angiotensin-aldosterone system (RAAS) inhibitors on the primary prevention of chronic kidney disease (CKD) in people with type 1 and type 2 diabetes. · What is the specific question(s) we wanted to answer? Can RAAS inhibitors be used for the primary prevention of CKD in people with diabetes? · What did we find? RAAS inhibitors can help prevent incident albuminuria in people with type 2 diabetes and hypertension, though their effect on eGFR is uncertain. No benefits were found for people with type 1 diabetes and normotension. · What are the implications of our findings? Evidence supports the use of RAAS inhibitors for primary prevention of albuminuria in type 2 diabetes and hypertension.

RATIONALE:In contemporary cohorts of adults with cystic fibrosis (CF), risk factors and rates of kidney function decline are unknown. With improved life expectancy, preserving kidney function is paramount to preventing early cardiovascular disease and CF-related bone disease and to maintaining eligibility for lung transplantation. OBJECTIVES:To determine long-term kidney function decline among CF participants following the Standardized Treatment of Pulmonary Exacerbations 2 (STOP2) clinical trial and to identify specific risk factors. METHODS:We linked participants in STOP2 with the CF Foundation Patient Registry and defined decline in kidney function as a composite of ≥40% decline in the estimated glomerular filtration rate (eGFR) or development of end-stage renal disease. We calculated the associations of risk factors such as age, diabetes status, and number of pulmonary exacerbations treated with intravenous antibiotics on decline in kidney function. RESULTS:Among 915 STOP2 participants, the mean ± SD baseline eGFR was 114 ± 20 mL/min/1.73 m2 and 53 (6.0%) reached the composite endpoint over a median follow-up time of 3.8 years. Each 10-year increase in age was associated with a 24% greater risk of the composite outcome (hazard ratio [HR], 1.29 [95% CI, 1.01-1.65]), and participants with insulin-dependent diabetes had a greater risk of the composite endpoint (HR, 2.34 [95% CI, 1.33-4.12]). A multivariable adjusted time-updated Cox regression model demonstrated that each additional pulmonary exacerbation was associated with a greater risk of the composite outcome (HR, 1.13 [95% CI, 1.07-1.20]; P <.0001). CONCLUSIONS:Risk factors associated with kidney function decline included age, insulin-dependent diabetes, and number of pulmonary exacerbations. These findings highlight key contributors to kidney function decline in a modern cohort of adults with CF.

OBJECTIVE:There is a need for improved glycemia monitoring tools for people with type 2 diabetes (T2D) and end-stage kidney failure (ESKF). RESEARCH DESIGN AND METHODS:This prospective, randomized, crossover trial compared the efficacy of real-time continuous glucose monitoring (rtCGM) with capillary blood glucose (CBG) testing in adults with T2D and ESKF undergoing hemodialysis. The primary outcome was percentage of time below range (%TBR) <70 mg/dL. RESULTS:The %TBR <70 mg/dL was not significantly different between groups (mean 1.17% ± 1.8 vs. 1.29% ± 2.7; P = 0.28). Compared with CBG testing, percentage time in range (%TIR) was higher (63.4% ± 24 vs. 54.5% ± 23) and mean glucose lower (173.6 ± 37 vs. 187.7 ± 38 mg/dL) after the rtCGM intervention, while percentage time above range (%TAR) >180 mg/dL (35.3% ± 25 vs. 44.3% ± 23) and >250 mg/dL decreased (12.3% ± 15 vs. 18.8% ± 19) (all P ≤ 0.01). CONCLUSIONS:In adults with T2D and ESKF undergoing hemodialysis, TBR was minimal and not influenced by rtCGM use. Compared with CBG testing, %TIR and %TAR improved during the rtCGM intervention. Future studies are needed to confirm the benefits of rtCGM in this population.

The cardiovascular-kidney-metabolic framework recognizes the interconnected biological, clinical, and societal drivers of cardiovascular disease, chronic kidney disease, diabetes, and obesity. To advance an integrated perspective, aligned with the kidney community focus, the International Society of Nephrology convened an International Expert Forum, bringing together a global and multidisciplinary team of leaders in this field. This meeting report synthesizes key discussions spanning cardiovascular-kidney-metabolic risk stratification, lifestyle interventions, guideline-directed medical therapies, emerging late-stage therapeutics, and models of care delivery. Participants emphasized the importance of early, integrated case finding; long-term, joint kidney-cardiovascular risk assessment; and timely use of evidence-informed therapies to reduce kidney disease progression, kidney failure, and cardiovascular events. Persistent gaps, including therapeutic inertia, fragmented care, and global inequities in access to care, were highlighted, alongside promising multidisciplinary and system-level care models. Emerging therapies targeting residual risk further underscore the need for adaptive implementation strategies. Aligned with the International Society of Nephrology's mission, this forum represents a foundational step toward connecting disciplines, bridging evidence-to-practice gaps, and building global capacity to improve equitable cardiovascular-kidney-metabolic outcomes.

BACKGROUND:Existing methods for estimating GFR in people with diabetes have shown inaccuracies when compared to mGFR measurements. We developed and validated an artificial neural network - RenoTrue to improve estimating GFR in people with diabetes. METHODS:5,619 individuals from five international cohorts with type 1 and type 2 diabetes was split into training (70%), validation (10%) and test (20%) datasets. RenoTrue was developed to estimate GFR using age, sex, and serum creatinine. The performance was evaluated in the test dataset by estimating agreement, bias (mean difference), and accuracy (p30), and compared to CKD-EPI estimates through a multi-level mixed effect regression model. FINDINGS:Median mGFR was 75 ml/ min per 1.73 m2 [IQR: 49, 100] and median age was 59 years [IQR: 38, 69]. RenoTrue demonstrated high agreement (ICC: 0.87 (95% CI: 0.78, 0.93)), low bias (-0.57 (95% CI: -1.59, 0.46) ml/min per 1.73 m2) and p30 of 81% (95% CI: 79%, 83%) compared to mGFR measurements. The 2009 CKD-EPI equation had an ICC of 0.86 (95% CI: 0.77, 0.92), bias of 4.17 (95% CI: 3.14, 5.20) ml/min per 1.73 m2 and p30 of 74% (95% CI: 72%, 77%). CONCLUSION:For people with diabetes, RenoTrue demonstrated better performance compared to the 2009 CKD-EPI equation in terms of estimating GFR across the full range of GFR.