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Objective: To compare dialysis transition patterns of chronic kidney disease (CKD) patients with heart failure (HF) and without HF, including inpatient "crash start" initiation of long-term ("maintenance") dialysis, early dialysis initiation as evaluated by estimated glomerular filtration rate (eGFR), and rate of central venous catheter (CVC) use for hemodialysis., Methods: A cross-sectional study was performed within Kaiser Permanente Southern California of patients (age ≥18 years) with observed incidence of CKD who initiated maintenance dialysis between January 1, 2007, and December 31, 2018. Heart failure was further categorized into HF with preserved ejection fraction (>40%) or HF with reduced ejection fraction (≤40%). Associations between HF and risk of inpatient initiation of maintenance dialysis or hemodialysis vascular access were assessed by rate ratio (RR) using Poisson regression with robust variance error., Results: Of 6812 patients with CKD initiating dialysis, 2498 (37%) had HF. Inpatient dialysis initiation occurred in 463 (18.5%) patients with HF vs 416 (9.6%) without HF. Mean (SD) eGFR at dialysis was 11.3 (6.2) mL/min per 1.73 m 2 with HF vs 9.4 (5.2) mL/min per 1.73 m 2 without HF (P<.001). Of 5499 patients who initiated hemodialysis, CVC use occurred in 1302 (58.5%) HF patients vs 1698 (51.9%) non-HF patients. Compared with non-HF patients, patients with HF had multivariate RRs (95% CI) of 1.46 (1.26 to 1.69) and 1.04 (0.99 to 1.10) for inpatient dialysis initiation and CVC use, respectively. Patients with HF with reduced ejection fraction had CVC placement RR of 1.23 (1.14 to 1.33)., Conclusion: Patients with CKD and HF had higher rates of suboptimal dialysis initiation: more frequent inpatient dialysis starts, more frequent CVC placement for hemodialysis access, and higher eGFR at dialysis initiation. Our findings suggest that CKD patients with HF may warrant different management strategies as they progress to dialysis., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Introduction: Niacin is a non-statin lipid-lowering therapy that has been shown to lower triglycerides and improve other risk factors for renal outcomes. Despite these favorable data, the effect of niacin on long-term kidney outcomes remains unclear. The aim of this study was to examine the associations of niacin therapies with incident chronic kidney disease (CKD), end-stage renal disease (ESRD), and death in patients with estimated glomerular filtration rate (eGFR) of at least 60 mL/min/1.73 m2., Methods: In a nationwide historic cohort of 1,139,630 United States (US) veterans with normal baseline eGFR, we examined the association of de novo prescription of niacin with incident CKD (defined as eGFR <60 mL/min/1.73 m2 on two occasions, separated by ≥90 days), ESRD (defined as the initiation of kidney replacement therapy), and death. Associations were examined in Cox proportional hazards models adjusted for demographics, major comorbidities, laboratory measurements, and medications. Prescription time-distribution matching was used to control for survival bias., Results: We identified 133,450 new users of niacin. Overall, patients (n = 1,139,630) had a mean (standard deviation) age of 60 (13) years, with 6% female, 78% white, 16% black, and 6% Hispanic. Niacin users were more likely to be male, white, current, or former smokers, with higher frequencies of comorbidities and statin use. Niacin use (vs. nonuse) was associated with a higher risk of CKD (HR: 1.08, 95% confidence interval:1.07-1.10) but a lower risk of ESRD (0.82, 0.76-0.88) and death (0.90, 0.89-0.91)., Conclusions: In a large national cohort of US veterans with normal kidney function, niacin use was associated with a lower risk of ESRD and death but with a higher risk of incident CKD, which is potentially explained by acute effects on eGFR. Further studies are needed to corroborate the potential benefits of niacin on kidney function and survival., (© 2025 S. Karger AG, Basel.)

Purpose of Review: Protein-energy wasting (PEW) is increasingly more prevalent as chronic kidney disease (CKD) progresses to more advanced stages. There is a global recognition of the importance of preventing and mitigating PEW in the CKD population not on dialysis given the goal of extending dialysis-free time and delaying dialysis initiation and growing evidence of the clinical consequences of PEW which include the risk of death, hospitalization and clinical conditions such as infections. We reviewed the association of PEW and the malnutrition characteristics indicative of PEW on CKD progression., Recent Findings: Studies show the association between low serum albumin levels, low BMI, and diets with inadequate dietary energy and protein intake and CKD progression. Limited studies suggest low muscle mass impacts CKD progression. Optimizing nutrition by dietary management, including a moderately low protein (0.6-0.8 g/kg/day) and plant-based (>50% of protein source, known as PLADO) diet and as needed with supplementation [e.g. during acute kidney injury (AKI) event] administrated orally, enterally, or parenterally are the basis for the prevention and treatment of PEW in CKD and delaying CKD progression. Furthermore, other therapeutic methods such as treating or avoiding comorbidities and AKI, ensuring appropriate exercise and incremental transition to dialysis treatment may help ameliorate and prevent PEW development in CKD patients., Summary: Using tailored precision nutrition approaches and nutritional supplementation with or without other beneficial strategies may help prevent and treat PEW and its consequent occurrence of CKD progression., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose of Review: Initiation of hemodialysis treatment with a thrice-weekly prescription is currently the standard of care irrespective of patients' residual kidney function (RKF), comorbidities, and preferences., Recent Findings: Each year ∼12 000 Veterans with advanced kidney disease progress to end-stage kidney disease (ESKD) requiring dialysis and comprise greater than 10% of the US incident ESKD population. Dialysis is costly and is associated with impaired health-related quality of life (HRQOL) and high mortality risk, especially in the first year of treatment. Evidence suggests an incremental dialysis transition using twice-weekly hemodialysis provides various benefits, including more dialysis-free time, longer RKF preservation, less vascular access damage, and lower patient burden. Pragmatic studies are needed to inform the efficacy and safety of incremental hemodialysis as a personalized dialysis regimen, and could inform its consideration as a conservation strategy during times of supply shortages. Broadly implementing twice-weekly hemodialysis could also potentially allow more Veterans to receive care within VA-based dialysis units. The VA IncHVets Trial is a pragmatic, multicenter, randomized controlled trial comparing the efficacy and safety of twice-weekly incremental vs. thrice-weekly hemodialysis among Veterans transitioning to ESKD., Summary: Further research is needed to determine whether incremental hemodialysis is well tolerated, effective, and facilitates a more favorable transition to dialysis., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

This report represents the conclusions of 15 experts in nephrology and endocrinology, based on their knowledge of key studies and evidence in the field, on the role of continuous glucose monitors (CGMs) in patients with diabetes and chronic kidney disease (CKD), including those receiving dialysis. The experts discussed issues related to CGM accuracy, indications, education, clinical outcomes, quality of life, research gaps, and barriers to dissemination. Three main goals of management for patients with CKD and diabetes were identified: (1) greater use of CGMs for better glycemic monitoring and management, (2) further research evaluating the accuracy, feasibility, outcomes, and potential value of CGMs in patients with end-stage kidney disease (ESKD) on hemodialysis, and (3) equitable access to CGM technology for patients with CKD. The experts also developed 15 conclusions regarding the use of CGMs in this population related to CGMs' unique delivery of both real-time information that can guide monitoring and management of glycemia and continuous and predictive data in this population, which is at higher risk for hypoglycemia and hyperglycemia. The group noted three major clinical gaps: (1) CGMs are not routinely prescribed for patients with diabetes and CKD; (2) CGMs are not approved by the United States Food and Drug Administration (FDA) for patients with diabetes who are on dialysis; and (3) CGMs are not routinely available to all of those who need them because of structural barriers in the health care system. These gaps can be improved with greater stakeholder collaboration, education, and awareness brought to the use of CGM technology in CKD., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: C.M.R. has received honoraria and/or grant support from AstraZeneca, Dexcom, Fresenius, and Vifor. R.Y.G. has nothing to disclose. D.K. has received research support from Abbott Diabetes Care and has been a Consultant to Sanofi, Better Therapeutics, Perfood, and Abbott Diagnostics. A.P.-T. provides consulting and research services to Novo Nordisk, Lilly, Bayer, Dexcom, and Medtronic on behalf of her employer but receives no direct or indirect reimbursement for the services. C.P.K. received consulting feels from Astra Zeneca, Bayer, Boehringer, Ingelheim, Cara Therapeutics, Pharmacosmos, ProKidney, Renibus, and Takeda. R.C.S. has nothing to disclose. A.T.D. has nothing to disclose. R.J.G. has received research support from Novo Nordisk, Dexcom, Boehringer, and Eli Lilly and consulting/advisory/honoraria fees from Abbott, Aztra Zeneca, Bayer, Boehringer, Dexcom, Eli Lilly, Novo Nordisk and Medtronic. R.J.G. is partially supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) of the National Institutes of Health (NIH) under Award Numbers P30DK111024 (R.J.G.), K23DK123384 (R.J.G.). and R03DK138255-01. K.K.-Z. has received funding from the NIH to examine CGM in patients with CKD. J.J.N. is partially supported by NIH research grant OT2OD032581 and reports personal fees and other support from Bayer AG, Sanofi, Novo Nordisk, Boehringer Ingelheim, Eli Lilly, Proteomics International, and Dexcom outside the submitted work. I.H.d.B. consults for Alnylam, Boehringer Ingelheim, Lilly, Miter, and Novo Nordisk. I.H.D.B. has also received equipment and supplies for research donated to his institution from Dexcom and Novo Nordisk Research, and funding to his institution from NIDDK and Breakthrough T1D. M.L. has been a consultant or received honoraria from Astra Zeneca, Boehringer Ingelheim, Eli Lilly, Nordic InfuCare, and Novo Nordisk, and has received research grants from Eli Lilly and Novo Nordisk, all outside of the submitted work. S.H.K. reports a relationship with Morphic Medical that includes consulting or advisory. S.H.K. is partially supported by P30DK116074. A.T.A. is a consultant for Liom. C.N.H. is a consultant for Liom. R.E.A. has nothing to disclose. T.T. has nothing to disclose. D.C.K. is a consultant for Afon, embecta, Glucotrack, Lifecare, Novo, Samsung, SynchNeuro, and Thirdwayv.

Iodine is a micronutrient that is required for thyroid hormone synthesis. The iodide cycle in thyroid hormone synthesis consists of a series of transport, oxidation, organification, and binding/coupling steps in thyroid follicular cells. Common sources of iodine include the consumption of an iodine-rich diet or iodine-fortified foods, the administration of amiodarone, iodine-containing supplements, or iodinated contrast media, and other miscellaneous sources. Methods to assess population iodine status include the measurement of urinary iodine concentrations, blood thyroglobulin levels, prevalence of elevated neonatal thyrotropin levels, and thyroid volume. Although excessive iodine intake or exposure is generally well tolerated, an acute iodine load may result in thyroid dysfunction (hypothyroidism or hyperthyroidism) in certain susceptible individuals due to the failure to escape from the Wolff-Chaikoff effect and to the Jod-Basedow phenomenon, respectively. In this review, we discuss the associations between excessive iodine intake or exposure, with particular focus on iodinated contrast media as a common source of excess iodine in health care settings, and risks of incident thyroid dysfunction. We also summarize the risks of iodine excess in vulnerable populations and review current guidelines regarding the screening and monitoring of iodinated contrast-induced thyroid dysfunction. Finally, we discuss the long-term potential nonthyroidal health risks associated with iodine excess and suggest the need for more data to define safe upper limits for iodine intake, particularly in high-risk populations., (Published by Oxford University Press on behalf of the Endocrine Society 2024.)

Introduction: An error grid compares measured versus reference glucose concentrations to assign clinical risk values to observed errors. Widely used error grids for blood glucose monitors (BGMs) have limited value because they do not also reflect clinical accuracy of continuous glucose monitors (CGMs)., Methods: Diabetes Technology Society (DTS) convened 89 international experts in glucose monitoring to (1) smooth the borders of the Surveillance Error Grid (SEG) zones and create a user-friendly tool-the DTS Error Grid; (2) define five risk zones of clinical point accuracy (A-E) to be identical for BGMs and CGMs; (3) determine a relationship between DTS Error Grid percent in Zone A and mean absolute relative difference (MARD) from analyzing 22 BGM and nine CGM accuracy studies; and (4) create trend risk categories (1-5) for CGM trend accuracy., Results: The DTS Error Grid for point accuracy contains five risk zones (A-E) with straight-line borders that can be applied to both BGM and CGM accuracy data. In a data set combining point accuracy data from 18 BGMs, 2.6% of total data pairs equally moved from Zones A to B and vice versa (SEG compared with DTS Error Grid). For every 1% increase in percent data in Zone A, the MARD decreased by approximately 0.33%. We also created a DTS Trend Accuracy Matrix with five trend risk categories (1-5) for CGM-reported trend indicators compared with reference trends calculated from reference glucose., Conclusion: The DTS Error Grid combines contemporary clinician input regarding clinical point accuracy for BGMs and CGMs. The DTS Trend Accuracy Matrix assesses accuracy of CGM trend indicators., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: D.C.K. is a consultant for Afon, Lifecare, Novo, Samsung, embecta, Glucotrack, SynchNeuro, and Thirdwayv. G.F. is CEO of IfDT. G.F./IfDT has/have received research support, speakers’ honoraria or consulting fees in the last three years from Abbott, Ascensia, Berlin Chemie, Boydsense, Dexcom, Glucoset, i-SENS, Lilly, Menarini, Novo Nordisk, Perfood, Pharmasens, Roche, Sinocare, Terumo, Ypsomed. S.P. is an employee of IfDT. B.P.K. declares patent royalties handled by UVA from: DexCom, J&J, Novo Nordisk, and Sanofi; and research support handled by UVA: Dexcom, Novo Nordisk, Tandem Diabetes Care. D.K. has received research support from Abbott Diabetes Care. M.S.D.A. is currently receiving in kind support (CGM devices) from Dexcom Inc for an investigator-initiated clinical study. K.D. receives research funding from Dexcom, Abbott, Sanofi, Viacyte, Insulet, consulting fees from Eli Lilly, Dexcom, Insulet, Oppenheimer, Elsevier, honoraria from Academy for Continued Healthcare Learning, Med Learning Group, Medscape, Impact Education, and royalties from UptoDate. S.M. is in receipt of an investigator-initiated grant from DexCom, has received speaker fees from Sanofi & Lilly, is funded by a Wellcome Trust (223024/Z/21/Z), and is supported by the NIHR Imperial Biomedical Research Centre. A.S. was supported by the NSF Engineering Research Center for Precise Advanced Technologies and Health Systems for Underserved Populations (PATHS-UP) (#1648451). V.N.S. reports receiving personal fees from Sanofi, Embecta, NovoNordisk, Dexcom, Insulet, Tandem Diabetes Care, Ascensia Diabetes Care, Genomelink and LumosFit for consulting, advising or speaking. N.K.T. is a consultant for Roche Diagnostics / Roche Molecular Systems / Radiometer. UC Davis is a Roche Diagnostics Center of Excellence. N.K.T. has received speaking honoraria for Roche Diagnostics, Nova Biomedical, Thermo Fisher, and Radiometer. N.K.T. is also Chair-Elect for the Association for Diagnostic and Laboratory Medicine (ADLM) Critical and Point-of-Care Testing Division, Co-Founder of the Machine Intelligene Learning Optimizer (MILO), Inc, and a member of the International Federation for Clinical Chemistry (IFCC) continuous glucose monitoring workgroup. T.T. is a consultant for Clinical ink. R.E.A. is a consultant for Clinical ink. D.T.A. has received speaker’s honoraria from Abbott, Ascensia Diabetes Care, Insulet, Lilly Diabetes, Mannkind, Novo Nordisk, and Xeris Pharmaceuticals. D.T.A. has received consulting fees from Ascensia Diabetes Care, Lilly Diabetes, and Senseonics. H.K.A. received research grants through University of Colorado from Dexcom, Tandem Diabetes, Medtronic, Mannkind, IM Therapeutics, IAFMS, and received honorarium through University of Colorado for consulting from Dexcom, Tandem Diabetes, and Medtronic. M.E.A.-S. has served on the advisory boards for Abbott, Medtronic, Insulet, VitalAire, Sanofi, Eli Lilly, and Dexcom; has received honoraria for speaking from Abbott, Eli Lilly, Medtronic, Novo Nordisk, Sanofi, VitalAire, and Eli Lilly; and received research support from Medtronic and Sanofi. T.S.B. has received research support from Abbott Rapid Diagnostics, Biolinq, Dexcom, Eli Lilly, Medtronic, Medtrum, Novo Nordisk, Sanofi, Senseonics, and vTv Therapeutics and consulting honoraria from Abbott Diabetes, Abbott Rapid Diagnostics, ACON, CeQur, HagarTech, Intuity Medical, Lifescan, Mannkind, Medtronic, Novo, Perspirion, Sanofi, Sequel Med Tech, and Ypsomed. M.B. currently participates on the Hospital Advisory board with Dexcom and has received research support from Dexcom. L.B. has received research/product support from Dexcom, Ypsomed, and Boehringer Ingelheim; speaker honoraria from Dexcom and Oviva; and participated in advisory boards of Dexcom, Novo Nordisk, Sanofi, Ypsomed, Oviva, and Roche Diabetes Care. Y.M.B. has received honoraria for lectures and scientific advisory from Roche and AstraZeneca in the past 12 months. J.E.B. is on the Speaker’s bureau for Insulet and on the Advisory Board for Cardinal Health and Lifescan. J.E.B. is a consultant for Embecta. J.E.B. receives research support from the Leona M. and Harry B. Helmsley Charitable Trust. E.C. is on the scientific advisory board for Novo Nordisk, Eli-Lilly, Adocia, Arecor, Proventionbio, Portal Insulin, and MannKind. D.C. was a Dexcom employee from August 2018 to May 2024. D.C. is a shareholder of Dexcom, Lilly, Abbott and Tandem. M.C. has received consulting fees from Glooko and research support from Dexcom and Abbott Diabetes Care. G.L.C. is a shareholder of BioTex, Inc., Basepair Biotechnologies Inc., Coordination Centric, Inc., and Shape Memory Medical, Inc. G.L.C. is supported by the NSF Engineering Research Center for Precise Advanced Technologies and Health Systems for Underserved Populations (PATHS-UP) (#1648451). K.K.D. has received honoraria, travel, or fees for advisory boards from AstraZeneca, Novo Nordisk, Boehringer Ingelheim, Eli Lilly, Abbott Diabetes, Menarini, and Sanofi in the last 12 months. J.E. receives federal funding from FDA, NIMHD, and NCATS and is a consultant for Sanofi. C.F. receives royalties from Dexcom and Novo Nordisk managed through her institution. G.A.F. is an advisor for 180 Life Sciences, 89bio, Adocia, Abbott, AdipoPharma, Aerami, Amolyt, Carthera, Catalyst, Cohen Global, CMC Magnetics, Diasome, Eleos, Entera Bio, Enterin, Glyscend, Hagar, Hogan Lovells, IM Therapeutics, Innoneo, Intarcia, Levicure, Lilly Asia Ventures, Lumos, Mars Symbioscience, Melior, metaLead Therapeutics, Microbiotix, MMD, Modular Medical, New Amsterdam, Northwestern, NuSirt, NuVox, Oramed, Pano, Pasithea, PhylloPharma, Pleiogenix, Recordati, Regor, Remodeless, Renaissance, RenovoRx, Rivus, RxMP, Sera Biopharma, Seraxis, Serpin, SFC Fluidics, Skinject, SROne, Stalicla, Surf Bio, TIXiMED, Veroscience, Verthermia, WaveBreak, Zealand Pharma, and Zucara. M.A.L.G. is a consultant for Abbott, Medtronic, Novonordisk, and Roche. R.J.G. received research support from Novo Nordisk, Dexcom and Eli Lilly and consulting fees/advisory fees from Abbott Diabetes Care, Aztra Zeneca, Bayer, Boehringer, Dexcom, Eli Lilly, Novo Nordisk, and Medtronic, outside of this work. R.J.G. is partially supported by the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health under Award Numbers P30DK111024, K23DK123384, R03DK138255, and U2CD137135. A.M.G.-M. reports speaker fees from Novo Nordisk, Sanofi, Elli Lilly, Boehringer Ingelheim, Abbott, and Medtronic. L.H. is a consultant for a number of companies that are developing innovative solutions for the treatment of people with diabetes. N.H. reports Advisory Board member fees from Abbott Diabetes Care and Insulet as well as honoraria for lectures from Berlin-Chemie AG, Becton Dickenson, Sanofi Germany, Roche Diabetes Care, and Dexcom Germany. T.H. serves on the advisory board for Acella and Horizons Therapeutics (no financial compensation). S.H. has served on the advisory board for Tandem, Dexcom, and Medtronic, and received honoraria for nonpromotional educational and/or consultancy work from Abbott, Insulet, Dexcom, Roche, and Sanofi. P.G.J. is a shareholder of Pacific Diabetes Technologies Inc. and serves on the advisory board for Eli Lilly. P.G.J. received grant support from SFC Fluidics and research support from Eli Lilly and Dexcom. J.J. has received fees from lectures and or advisory boards from Abbott, Astra Zeneca, Boeringer Ingelheim, Eli Lilly, Medtronic, Nordic Infucare, Novo Nordisk, and Sanofi. S.R.J is a consultant for USV, Marico, Glenmark, Franco Indian, Twin Health, Biocon, and Zydus Lifesciences. S.R.J. received speaking honoraria from Abbott, Novo Nordisk, MSD, Sanofi, Boehringer Ingelheim, AstraZeneca, Lupin, Bayer Zydus, USV, DRL, Meyer Organics, Servier, Natco. R.A.L. is a consultant for Abbott Diabetes Care, Biolinq, Capillary Biomedical, Deep Valley Labs, Gluroo, PhysioLogic Devices, Portal Insulin, Sanofi, and Tidepool. R.A.L. has served on advisory boards for. ProventionBio and Lilly. R.A.L. receives research support through his institution from Insulet, Medtronic, Tandem, and Sinocare. L.A.L. has received research funding from, has provided CME on behalf of, and/or has acted as an advisor to Abbott, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Lexicon, Merck, Novo Nordisk, Pfizer, and Sanofi. M.L. has been a consultant or received honoraria from Astra Zeneca, Boehringer Ingelheim, Eli Lilly, Nordic InfuCare, and Novo Nordisk, and has received research grants from Eli Lilly and Novo Nordisk, all outside of the submitted work. J.K.M. is a member of advisory boards of Abbott Diabetes Care, Becton-Dickinson, Biomea Fusion, Eli Lilly, Embecta, Medtronic, NovoNordisk A/S, Roche Diabetes Care, Sanofi-Aventis, and Viatris and received speaker honoraria from A. Menarini Diagnostics, Abbott Diabetes Care, AstraZeneca, Boehringer Ingelheim, Dexcom, Eli Lilly, Medtrust, MSD, NovoNordisk A/S, Roche Diabetes Care, Sanofi, Viatris, and Ypsomed. J.K.M. is a shareholder of decide Clinical Software GmbH and elyte Diagnostics. A.M. reports speaker fees from Novo Nordisk. M.M. has an existing research & development relationship with Scientific Bioprocessing, Inc and has been a consultant for Abbott. S.-J.M. is a consultant for Abbott, Curestream, Daewoong, EOFlow, G2e, Huons, iSense, Medtronic, Novo Nordisk, and Sanofi. D.N.O. has served on advisory boards for Abbott Laboratories, Medtronic, Merck Sharp & Dohme, Novo Nordisk, Roche, and Sanofi; received research support from Medtronic, Novo Nordisk, Roche, Eli Lilly and Company, and Sanofi; and received travel support from Novo Nordisk and Merck Sharp & Dohme. F.J.P. has received research support (to Emory University) from Dexcom, Insulet, Novo Nordisk, Tandem, and Ideal Medical Technologies, and has received consulting fees from Dexcom. A.L.P. is on the advisory board of Medscape, Vertex, and Lilly; receives research support from Insulin and Abbott; and has stock options in Omada Health. R.P.-B. receives grant support from Novo Nordisk, Lexicon Pharmaceuticals, and Medtronic and received consulting fees from Bayer, Lexicon Pharmaceuticals, Novo Nordisk, and Roche. C.M.R. has received honoraria and/or grant support from AstraZeneca, Dexcom, Fresenius, and Vifor. D.B.S. is supported by the Intramural Research Program of the National Institutes of Health. S.S. was a Novo Nordisk employee from 2022-2023. S.S. has served as advisor for Novo Nordisk and has received speaker fees from Novo Nordisk and Nordic Infucare within the past three years. G.D.S’s employer, nonprofit International Diabetes Center, HealthPartners Institute, has received educational grant funds from Abbott Diabetes Care, Medscape, and Sanofi-Aventis Groupe. G.D.S receives no personal income/honorarium from these activities. K.S. received grant supports from Arkray, Terumo, and Dexcom. E.K.S. is partly supported by the VA Merit Award (1I01CX001825) from the US Department of Veterans Affairs Clinical Sciences Research and has received unrestricted research support from Dexcom and Tandem Diabetes (to Baltimore VA Medical Center and to University of Maryland) for the conduction of clinical trials. N.L.S. received funding from Novo Nordisk for an investigator-initiated research grant unrelated to the current project. G.E.U. is partly supported by research grants from National Institutes of Health (NIH/NATS UL 3UL1TR002378-05S2) from the Clinical and Translational Science Award program, and from National Institutes of Health and National Center for Research Resources (NIH/NIDDK 2P30DK111024-06). G.E.U. has received research support (to Emory University) from Abbott, Bayer, and Dexcom; and has participated in advisory boards for Dexcom and GlyCare. E.W. has received consulting fees from Abbott Diabetes Care, Ascensia, Bayer, Boehringer, Ingelheim, Embecta, GlaxoSmithKline, Lilly, Medtronic, Renalytix, and Sanofi. E.W. has received honoraria from Abbott Diabetes Care, Bayer, Boehringer Ingelheim, GlaxoSmithKline, Lilly, Medtronic, Renalytix, and Sanofi. E.W. is on the Speakers’ Bureau from Abbott Diabetes Care, Bayer, Boehringer, Ingelheim, GlaxoSmithKline, Lilly, Renalytix, and Sanofi. M.Z. is a consultant for DexCom, Inc. M.A.K. is Chief Medical Officer of QuesGen, Inc. C.T., C.L., B.V.H., J.S.K., W.A.L., S.Y.R., J.J.S., K.W., C.W., K.R., C.N.H., A.T.A., A.A., R.R.B., E.M.B., J.G.C., K.Y.C., A.D., N.E., S.K.K., U.M., N.M., C.M., J.H.N., A.P., P.R., S.M.S., B.S., M.V., H.W.V., J.W., A.H.B.W., and S.Y. have nothing to disclose.

Objective: In the general population, continuous glucose monitoring (CGM) provides convenient and less-invasive glucose measurements than conventional self-monitored blood glucose and results in reduced hypoglycemia and hyperglycemia and increased time in target glucose range. However, accuracy of CGM versus blood glucose is not well established in hemodialysis patients., Research Design and Methods: Among 31 maintenance hemodialysis patients with diabetes hospitalized from October 2020 to May 2021, we conducted protocolized glucose measurements using Dexcom G6 CGM versus blood glucose, with the latter measured before each meal and at night, plus every 30-min during hemodialysis. We examined CGM-blood glucose correlations and agreement between CGM versus blood glucose using Bland-Altman plots, percentage of agreement, mean and median absolute relative differences (ARDs), and consensus error grids., Results: Pearson and Spearman correlations for averaged CGM versus blood glucose levels were 0.84 and 0.79, respectively; Bland-Altman showed the mean difference between CGM and blood glucose was ∼+15 mg/dL. Agreement rates using %20/20 criteria were 48.7%, 47.2%, and 50.2% during the overall, hemodialysis, and nonhemodialysis periods, respectively. Mean ARD (MARD) was ∼20% across all time periods; median ARD was 19.4% during the overall period and was slightly lower during nonhemodialysis (18.2%) versus hemodialysis periods (22.0%). Consensus error grids showed nearly all CGM values were in clinically acceptable zones A (no harm) and B (unlikely to cause significant harm)., Conclusions: In hemodialysis patients with diabetes, although MARD values were higher than traditional optimal analytic performance thresholds, error grids showed nearly all CGM values were in clinically acceptable zones. Further studies are needed to determine whether CGM improves outcomes in hemodialysis patients., (© 2024 by the American Diabetes Association.)

Diabetes is the leading cause and a common comorbidity of advanced chronic kidney disease. Glycaemic management in this population is challenging and characterised by frequent excursions of hypoglycaemia and hyperglycaemia. Current glucose monitoring tools, such as HbA 1c , fructosamine and glycated albumin, have biases in this population and provide information only on mean glucose exposure. Revolutionary developments in glucose sensing and insulin delivery technology have occurred in the last decade. Newer factory-calibrated continuous glucose monitors provide real-time glucose data, with predictive alarms, allowing improved assessment of glucose excursions and preventive measures, particularly during and between dialysis sessions. Furthermore, integration of continuous glucose monitors and their predictive alerts with automated insulin delivery systems enables insulin administration to be decreased or stopped proactively, leading to improved glycaemic management and diminishing glycaemic fluctuations. While awaiting regulatory approval, emerging studies, expert real-world experience and clinical guidelines support the use of diabetes technology devices in people with diabetes and advanced chronic kidney disease., (© 2024. The Author(s).)

Individuals with end-stage kidney disease (ESKD) on dialysis experience high mortality and excessive burden of hospitalizations over time relative to comparable Medicare patient cohorts without kidney failure. A key interest in this population is to understand the time-dynamic effects of multilevel risk factors that contribute to the correlated outcomes of longitudinal hospitalization and mortality. For this we utilize multilevel data from the United States Renal Data System (USRDS), a national database that includes nearly all patients with ESKD, where repeated measurements/hospitalizations over time are nested in patients and patients are nested within (health service) regions across the contiguous U.S. We develop a novel spatiotemporal multilevel joint model (STM-JM) that accounts for the aforementioned hierarchical structure of the data while considering the spatiotemporal variations in both outcomes across regions. The proposed STM-JM includes time-varying effects of multilevel (patient- and region-level) risk factors on hospitalization trajectories and mortality and incorporates spatial correlations across the spatial regions via a multivariate conditional autoregressive correlation structure. Efficient estimation and inference are performed via a Bayesian framework, where multilevel varying coefficient functions are targeted via thin-plate splines. The finite sample performance of the proposed method is assessed through simulation studies. An application of the proposed method to the USRDS data highlights significant time-varying effects of patient- and region-level risk factors on hospitalization and mortality and identifies specific time periods on dialysis and spatial locations across the U.S. with elevated hospitalization and mortality risks., (© 2024. The Author(s).)

Background: Iodinated contrast is commonly used for radiological procedures, with one dose delivering several hundred-fold the daily requirements needed for normal thyroid hormone production. Risks of excess iodine include incident thyroid dysfunction, which is associated with adverse cardiac outcomes, yet there are no prospective studies investigating the changes in cardiac physiology following iodine contrast administration. This study was conducted to investigate the longitudinal relationships between the amount of iodinated contrast administration and changes in cardiac electrophysiology and structure. Methods: A longitudinal cohort study was conducted with prospectively enrolled participants who received iodine contrast for elective computed tomography or coronary angiography. Serum thyroid function tests, electrocardiograms (EKG), and transthoracic echocardiograms were obtained serially until 36 months. Trends of electrical and structural cardiac changes following iodine contrast administration were assessed using mixed effect models. Results: The cohort was composed of 129 patients (median age, 70 [interquartile range: 63, 75] years; 98% male). Larger amounts of iodine exposure were associated with increases in QRS and QTc durations and decreased ejection fraction (EF), and these associations were still observed for follow-up EF after additionally adjusting for baseline values (the high-iodine contrast group vs. the low-iodine contrast group, -4.23% [confidence interval, -7.66% to -0.79%]). Dose-response analyses also showed lower EF with larger amounts of iodine received; these trends were not significant for the EKG parameters studied. Conclusions: Over a period of up to 36 months, a larger amount of administered iodine contrast was associated with lower EF among participants. Further investigation is needed to elucidate the long-term trends of electrical and structural cardiac function after iodine contrast administration.

Dialysis has been the dominant treatment regimen in end-stage kidney disease as a means to remove uremic waste products and to maintain electrolyte, acid base, and fluid balance. However, given that dialysis may not always provide a survival benefit nor improved quality of life in certain subpopulations, there is growing recognition of the need for conservative and preservative management as an alternative treatment strategy for advanced chronic kidney disease (CKD). Personalized nutritional management tailored to patient's sociodemographics, social needs, psychological status, health literacy level, and preferences is a key component of conservative and preservative care, as well as in the management of patients transitioning from non-dialysis dependent CKD to dialysis. In this review, we discuss the nutritional and metabolic alterations that ensue in CKD; the rationale for low-protein diets in the conservative and preservative management of advanced CKD; the role of plant-based diets in kidney health; emerging data on dietary potassium and sodium intake on CKD outcomes; and the practical implementation of dietary interventions in advanced kidney disease.

Dialysis patients experience frequent hospitalizations and a higher mortality rate compared to other Medicare populations, in whom hospitalizations are a major contributor to morbidity, mortality, and healthcare costs. Patients also typically remain on dialysis for the duration of their lives or until kidney transplantation. Hence, there is growing interest in studying the spatiotemporal trends in the correlated outcomes of hospitalization and mortality among dialysis patients as a function of time starting from transition to dialysis across the United States Utilizing national data from the United States Renal Data System (USRDS), we propose a novel multivariate spatiotemporal functional principal component analysis model to study the joint spatiotemporal patterns of hospitalization and mortality rates among dialysis patients. The proposal is based on a multivariate Karhunen-Loéve expansion that describes leading directions of variation across time and induces spatial correlations among region-specific scores. An efficient estimation procedure is proposed using only univariate principal components decompositions and a Markov Chain Monte Carlo framework for targeting the spatial correlations. The finite sample performance of the proposed method is studied through simulations. Novel applications to the USRDS data highlight hot spots across the United States with higher hospitalization and/or mortality rates and time periods of elevated risk., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. [br]For permissions, please e-mail: journals.permissions@oup.com.)

Background: We examined the real-world comparative safety of sodium-glucose cotransporter-2 inhibitors (SGLT2i) vs. other newer anti-glycemic medications (dipeptidyl peptidase-4 inhibitors [DPP4i], glucagon-like peptide-1 receptor agonists [GLP1a]) in patients with and without chronic kidney disease (CKD)., Methods: Among US Veterans with diabetes receiving care from the Veterans Affairs (VA) healthcare system over 2004-19, we identified incident users of SGLT2i vs. DPP4i vs. GLP1a monotherapy. In analyses stratified by CKD status, defined by estimated glomerular filtration rate and albuminuria, we examined associations of SGLT2i vs. DPP4i vs. GLP1a use with risk of infection-related (primary outcome) and genitourinary infection hospitalizations (secondary outcome) using multivariable Cox models., Findings: Among 92,269 patients who met eligibility criteria, 52% did not have CKD, whereas 48% had CKD. In the overall and non-CKD cohorts, compared to DPP4i use, SGLT2i use was associated with lower infection-related hospitalization risk (HRs [95% CIs] 0.74 [0.67-0.81] and 0.77 [0.67, 0.88], respectively), whereas GLP1a use demonstrated comparable risk. However, in the CKD cohort SGLT2i and GLP1a use were each associated with lower risk (HRs [95% CIs] 0.70 [0.61, 0.81] and 0.91 [0.84, 0.99], respectively). Propensity score-matched analyses showed similar findings in the non-CKD and CKD cohorts. In the overall, non-CKD, and CKD cohorts, SGLT2i use was associated with lower genitourinary infection hospitalization risk whereas GLP1a use showed comparable risk vs. DPP4i use., Interpretation: In a national cohort of Veterans with diabetes, compared with DPP4i use, SGLT2i use was associated with lower infection-related and genitourinary infection hospitalization risk., Funding: VA Health Services Research and Development, USA., Competing Interests: CPK is supported by grant No. I01HX002680 from the VA Health Services Research and Development Service and has received royalties for two chapters from UpToDate and co-editing textbook on renal nutrition from Springer; consulting fees from Abbot, Akebia, AstraZeneca, Bayer, Boehringer Ingelheim, Cara Therapeutics, CSL Vifor, Eli Lilly, GSK, Pharmacosmos, ProKidney, CSL Behring, Renibus, and Rockwell; payment from Takeda for expert testimony; travel support from AstraZeneca, Bayer, and Boehringer Ingelheim; participation on a Data Safety Monitoring Board or Advisory Board of AstraZeneca (DIALIZE-O trial executive committee, GRAZE trial scientific committee) and Bayer (CardioRenal council member, FOUNTAIN Program Executive Advisory Committee Co-chair); and is President-Elect of the International Society of Renal Nutrition and Metabolism, which are unrelated to this study and manuscript. SS is funded by the NIH/NIMHD and CDC, which are unrelated to this study and manuscript. FT is supported by grant No. 1I01HX002680-01A1 from the VA the VA Health Services Research and Development Service through IPA (5 U.S.C. 3371–3376) with University of Tennessee Health Science Center. AA has served as primary or co-investigator of clinical trials sponsored by NIH/NIAID, NeuroRx Pharma, Pulmotect, Blade Therapeutics, Novartis, Takeda, Humanigen, Eli Lilly, PTC Therapeutics, Octapharma, Fulcrum Therapeutics, and Alexion; and as a speaker and/or consultant for Pfizer, Salix, Alexion, AstraZeneca, Bayer, Ferring, Seres, Spero, Eli Lilly, Nova Nordisk, Gilead, Renibus, GSK, Dexcom, Reprieve, HeartRite, Aseptiscope, which are unrelated to this study and manuscript. KKZ is supported by National Institute of Health and Veterans Administration; received honoraria and/or support from Ardelyx, American Society of Nephrology, DaVita, Fresenius, GSK, Haymarket Media, International Society of Renal Nutrition & Metabolism, Kabi, National Institutes of Health, National Kidney Foundations, VA, Vifor/CSL, and UpToDate, which are unrelated to this study and manuscript. None of the other authors declare competing interests.

Context: Iodinated contrast media (ICM) is a common source of excess iodine in medical settings, given the common use of iodinated radiologic procedures., Objective: To determine the long-term risks of thyroid dysfunction following iodinated contrast administration in a prospective study., Design, Setting, Participants: A longitudinal cohort study was conducted of patients in the U.S. Veterans Affairs medical system who received ICM., Main Outcome Measures: Serum thyroid function, thyroid antibody, and inflammatory markers were measured at baseline. Thyroid function tests were repeated at 1 month, 3 months, and every 6 months thereafter until 36 months. Risk of thyroid dysfunction and longitudinal changes in thyroid hormone levels were assessed using mixed effect models., Results: There were 122 participants (median age, 70.0 [IQR 62.2-74.0] years; 98.4% male). At baseline, six subjects had subclinical thyroid dysfunction prior to ICM receipt. During median follow-up of 18 months, iodine-induced thyroid dysfunction was observed in 11.5% (14/122); six (4.9%) developed hyperthyroidism (including one with overt hyperthyroidism) and eight (6.6%) subclinical hypothyroidism. At last follow-up, ten of 20 subjects with thyroid dysfunction (14 new-onset cases and six with preexisting thyroid dysfunction) had persistent subclinical hyperthyroidism or hypothyroidism. There were also subtle changes in thyroid hormones observed longitudinally within the reference ranges in the overall cohort., Conclusions: There is a rare long-term risk of an excess iodine load on thyroid dysfunction even among individuals from an overall iodine-sufficient region, supporting the need for targeted monitoring following iodinated contrast administration., (Published by Oxford University Press on behalf of the Endocrine Society 2024.)

Objective: Hypoglycemia is a frequent occurrence in chronic kidney disease patients due to alterations in glucose and insulin metabolism. However, there are sparse data examining the predictors and clinical implications of hypoglycemia including mortality risk among incident hemodialysis patients., Design and Methods: Among 58,304 incident hemodialysis patients receiving care from a large national dialysis organization over 2007-2011, we examined clinical characteristics associated with risk of hypoglycemia, defined as a blood glucose concentration <70 mg/dL, in the first year of dialysis using expanded case-mix + laboratory logistic regression models. We then examined the association between hypoglycemia during the first year of dialysis with all-cause mortality using expanded case-mix + laboratory Cox models., Results: In the first year of dialysis, hypoglycemia was observed among 16.8% of diabetic and 6.9% of nondiabetic incident hemodialysis patients. In adjusted logistic regression models, clinical characteristics associated with hypoglycemia included younger age, female sex, African-American race, presence of a central venous catheter, lower residual renal function, and longer dialysis session length. In the overall cohort, patients who experienced hypoglycemia had a higher risk of all-cause mortality risk (reference: absence of hypoglycemia): adjusted hazard ratio (95% confidence interval) 1.08 (1.04, 1.13). In stratified analyses, hypoglycemia was also associated with higher mortality risk in the diabetic and nondiabetic subgroups: adjusted hazard ratios (95% confidence interval's) 1.08 (1.04-1.13), and 1.17 (0.94-1.45), respectively., Conclusions: Hypoglycemia was a frequent occurrence among both diabetic and nondiabetic hemodialysis patients and was associated with a higher mortality risk. Further studies are needed to identify approaches that reduce hypoglycemia risk in the hemodialysis population., (Copyright © 2023 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.)

More than one-third of people with diabetes develop diabetic kidney disease (DKD), which substantially increases risks of kidney failure, cardiovascular disease (CVD), hypoglycemia, death, and other adverse health outcomes. A multifaceted approach incorporating self-management education, lifestyle optimization, pharmacological intervention, CVD prevention, and psychosocial support is crucial to mitigate the onset and progression of DKD. The American Diabetes Association convened an expert panel to develop the DKD Prevention Model presented herein. This model addresses prevention and treatment, including screening guidelines, diagnostic tools, and management approaches; comprehensive, holistic interventions; well-defined roles for interdisciplinary health care professionals; community engagement; and future directions for research and policy., Competing Interests: No potential conflicts of interest relevant to this article were reported., (©2024 by the American Diabetes Association.)

Objective: To examine the relationship between thyroid status and incident kidney dysfunction/chronic kidney disease (CKD) progression., Patients and Methods: We examined incident thyroid status, ascertained by serum thyrotropin (TSH) levels measured from January 1, 2007, through December 31, 2018, among 4,152,830 patients from the Optum Labs Data Warehouse, containing deidentified retrospective administrative claims data from a large national health insurance plan and electronic health record data from a nationwide network of provider groups. Associations of thyroid status, categorized as hypothyroidism, euthyroidism, or hyperthyroidism (TSH levels >5.0, 0.5-5.0, and <0.5 mIU/L, respectively), with the composite end point of incident kidney dysfunction in patients without baseline kidney dysfunction and CKD progression in those with baseline CKD were examined using Cox models., Results: Patients with hypothyroidism and hyperthyroidism had higher risk of incident kidney dysfunction/CKD progression in expanded case-mix analyses (reference: euthyroidism): adjusted hazard ratios (aHRs) (95% CIs) were 1.37 (1.34 to 1.40) and 1.42 (1.39 to 1.45), respectively. Incrementally higher TSH levels in the upper reference range and TSH ranges for subclinical, mild overt, and overt hypothyroidism (≥3.0-5.0, >5.0-10.0, >10.0-20.0, and >20.0 mIU/L, respectively) were associated with increasingly higher risk of the composite end point (reference: TSH level, 0.5 to <3.0 mIU/L): aHRs (95% CIs) were 1.10 (1.09 to 1.11), 1.37 (1.34 to 1.40), 1.70 (1.59 to 1.83), and 1.70 (1.50 to 1.93), respectively. Incrementally lower TSH levels in the subclinical (<0.5 mIU/L) and overt (<0.1 mIU/L) hyperthyroid ranges were also associated with the composite end point: aHRs (95% CIs) were 1.44 (1.41 to 1.47) and 1.48 (1.39 to 1.59), respectively., Conclusion: In a national cohort, TSH levels in the upper reference range or higher (≥3.0 mIU/L) and below the reference range (<0.5 mIU/L) were associated with incident kidney dysfunction/CKD progression., (Copyright © 2023 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.)

Introduction: While Asian and Native Hawaiian and other Pacific Islander (NHOPI) patients have a high prevalence of kidney disease risk factors, there are sparse data examining their end-stage kidney disease (ESKD) outcomes. As Hawaii has high representation of Asian and NHOPI individuals, we compared their ESKD outcomes based on residence in the mainland USA versus Hawaii/Pacific Islands (PIs)., Materials and Methods: Using United States Renal Data System data, we examined the impact of geographic residence in the mainland versus Hawaii/PIs on race-mortality associations among incident ESKD patients transitioning to dialysis over January 1, 2000-December 31, 2016 using Cox regression. We examined likelihood of post-dialysis kidney transplantation using Cox models and cumulative incidence curves., Results: Compared with White patients in the mainland, Asian and NHOPI patients in the mainland had lower mortality: adjusted HRs (95% CIs) 0.67 (0.66-0.67) and 0.72 (0.70-0.73), respectively. When examining Asian and NHOPI patients in Hawaii/PIs, survival benefit was attenuated in Asian and diminished to the null in NHOPI patients (ref: mainland White patients). Cumulative incidence curves comparing Asian, NHOPI, and White patients showed Asian and NHOPI patients in the mainland had the highest likelihood of transplantation, whereas NHOPI and Asian patients in Hawaii/PIs had the lowest likelihood., Conclusion: In the mainland, Asian and NHOPI patients had lower mortality versus White patients, whereas in Hawaii/PIs, this survival benefit was diminished in Asian and mitigated in NHOPI patients. NHOPI and Asian patients in Hawaii/PIs had less transplantation versus those in the mainland. Further research is needed to uncover factors contributing to differential ESKD outcomes among Asian and NHOPI patients across geographic residence., (© 2023 S. Karger AG, Basel.)

There is rising interest globally with respect to the health implications of vegetarian or plant-based diets. A growing body of evidence has demonstrated that higher consumption of plant-based foods and the nutrients found in vegetarian and plant-based diets are associated with numerous health benefits, including improved blood pressure, glycemic control, lipid levels, body mass index, and acid-base parameters. Furthermore, there has been increasing recognition that vegetarian and plant-based diets may have potential salutary benefits in preventing the development and progression of chronic kidney disease (CKD). While increasing evidence shows that vegetarian and plant-based diets have nephroprotective effects, there remains some degree of uncertainty about their nutritional adequacy and safety in CKD (with respect to protein-energy wasting, hyperkalemia, etc.). In this review, we focus on the potential roles of and existing data on the efficacy/effectiveness and safety of various vegetarian and plant-based diets in CKD, as well as their practical application in CKD management.

Objective: We investigated the association of oral iron replacement with the incidence of chronic kidney disease (CKD) in a population with normal kidney function to study the effects of iron replacement on the development of new onset CKD., Methods: In a national cohort of US Veterans with no pre-existing CKD, we identified 33 894 incident new users of oral iron replacement and a comparable group of 112 780 patients who did not receive any iron replacement during 2004-2018. We examined the association of oral iron replacement versus no iron replacement with the incidence of eGFR <60 mL/min/1.73 m 2 and the incidence of urine albumin creatinine ratio (UACR) ≥30 mg/g in competing risk regressions and in Cox models. We used propensity score weighing to account for differences in key baseline characteristics associated with the use of oral iron replacement., Results: In the cohort of 146 674 patients, a total of 18 547 (13%) patients experienced incident eGFR <60 mL/min/1.73 m 2 , and 16 117 patients (11%) experienced new onset UACR ≥30 mg/g. Oral iron replacement was associated with significantly higher risk of incident eGFR <60 mL/min/1.73 m 2 (subhazard ratio, 95% confidence interval [CI]: 1.3 [1.22-1.38], p < .001) and incident albuminuria (subhazard ratio, 95% CI: 1.14 [1.07-1.22], p < .001)., Conclusion: Oral iron replacement is associated with higher risk of new onset CKD. The long-term kidney safety of oral iron replacement should be tested in clinical trials., (© 2023 John Wiley & Sons Ltd. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

While dialysis has been the prevailing treatment paradigm for patients with advanced chronic kidney disease (CKD), emphasis on conservative and preservative management in which dietary interventions are a major cornerstone have emerged. Based on high-quality evidence, international guidelines support the utilization of low-protein diets as an intervention to reduce CKD progression and mortality risk, although the precise thresholds (if any) for dietary protein intake vary across recommendations. There is also increasing evidence demonstrating that plant-dominant low-protein diets reduce the risk of developing incident CKD, CKD progression, and its related complications including cardiometabolic disease, metabolic acidosis, mineral and bone disorders, and uremic toxin generation. In this review, we discuss the premise for conservative and preservative dietary interventions, specific dietary approaches used in conservative and preservative care, potential benefits of a plant-dominant low-protein diet, and practical implementation of these nutritional strategies without dialysis., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Context: Hypothyroidism is a common yet under-recognized condition in patients with chronic kidney disease (CKD), which may lead to end-organ complications if left untreated., Objective: We developed a prediction tool to identify CKD patients at risk for incident hypothyroidism., Methods: Among 15 642 patients with stages 4 to 5 CKD without evidence of pre-existing thyroid disease, we developed and validated a risk prediction tool for the development of incident hypothyroidism (defined as thyrotropin [TSH] > 5.0 mIU/L) using the Optum Labs Data Warehouse, which contains de-identified administrative claims, including medical and pharmacy claims and enrollment records for commercial and Medicare Advantage enrollees as well as electronic health record data. Patients were divided into a two-thirds development set and a one-third validation set. Prediction models were developed using Cox models to estimate probability of incident hypothyroidism., Results: There were 1650 (11%) cases of incident hypothyroidism during a median follow-up of 3.4 years. Characteristics associated with hypothyroidism included older age, White race, higher body mass index, low serum albumin, higher baseline TSH, hypertension, congestive heart failure, exposure to iodinated contrast via angiogram or computed tomography scan, and amiodarone use. Model discrimination was good with similar C-statistics in the development and validation datasets: 0.77 (95% CI 0.75-0.78) and 0.76 (95% CI 0.74-0.78), respectively. Model goodness-of-fit tests showed adequate fit in the overall cohort (P = .47) as well as in a subcohort of patients with stage 5 CKD (P = .33)., Conclusion: In a national cohort of CKD patients, we developed a clinical prediction tool identifying those at risk for incident hypothyroidism to inform prioritized screening, monitoring, and treatment in this population., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Reference intervals of thyroid-stimulating hormone (TSH) and free thyroxine (FT 4 ) are statistically defined by the 2·5-97·5th percentiles, without accounting for potential risk of clinical outcomes. We aimed to define the optimal healthy ranges of TSH and FT 4 based on the risk of cardiovascular disease and mortality., Methods: This systematic review and individual participant data (IPD) meta-analysis identified eligible prospective cohorts through the Thyroid Studies Collaboration, supplemented with a systematic search via Embase, MEDLINE (Ovid), Web of science, the Cochrane Central Register of Controlled Trials, and Google Scholar from Jan 1, 2011, to Feb 12, 2017 with an updated search to Oct 13, 2022 (cohorts found in the second search were not included in the IPD). We included cohorts that collected TSH or FT 4 , and cardiovascular outcomes or mortality for adults (aged ≥18 years). We excluded cohorts that included solely pregnant women, individuals with overt thyroid diseases, and individuals with cardiovascular disease. We contacted the study investigators of eligible cohorts to provide IPD on demographics, TSH, FT 4 , thyroid peroxidase antibodies, history of cardiovascular disease and risk factors, medication use, cardiovascular disease events, cardiovascular disease mortality, and all-cause mortality. The primary outcome was a composite outcome including cardiovascular disease events (coronary heart disease, stroke, and heart failure) and all-cause mortality. Secondary outcomes were the separate assessment of cardiovascular disease events, all-cause mortality, and cardiovascular disease mortality. We performed one-step (cohort-stratified Cox models) and two-step (random-effects models) meta-analyses adjusting for age, sex, smoking, systolic blood pressure, diabetes, and total cholesterol. The study was registered with PROSPERO, CRD42017057576., Findings: We identified 3935 studies, of which 53 cohorts fulfilled the inclusion criteria and 26 cohorts agreed to participate. We included IPD on 134 346 participants with a median age of 59 years (range 18-106) at baseline. There was a J-shaped association of FT 4 with the composite outcome and secondary outcomes, with the 20th (median 13·5 pmol/L [IQR 11·2-13·9]) to 40th percentiles (median 14·8 pmol/L [12·3-15·0]) conveying the lowest risk. Compared with the 20-40th percentiles, the age-adjusted and sex-adjusted hazard ratio (HR) for FT 4 in the 80-100th percentiles was 1·20 (95% CI 1·11-1·31) for the composite outcome, 1·34 (1·20-1·49) for all-cause mortality, 1·57 (1·31-1·89) for cardiovascular disease mortality, and 1·22 (1·11-1·33) for cardiovascular disease events. In individuals aged 70 years and older, the 10-year absolute risk of composite outcome increased over 5% for women with FT 4 greater than the 85th percentile (median 17·6 pmol/L [IQR 15·0-18·3]), and men with FT 4 greater than the 75th percentile (16·7 pmol/L [14·0-17·4]). Non-linear associations were identified for TSH, with the 60th (median 1·90 mIU/L [IQR 1·68-2·25]) to 80th percentiles (2·90 mIU/L [2·41-3·32]) associated with the lowest risk of cardiovascular disease and mortality. Compared with the 60-80th percentiles, the age-adjusted and sex-adjusted HR of TSH in the 0-20th percentiles was 1·07 (95% CI 1·02-1·12) for the composite outcome, 1·09 (1·05-1·14) for all-cause mortality, and 1·07 (0·99-1·16) for cardiovascular disease mortality., Interpretation: There was a J-shaped association of FT 4 with cardiovascular disease and mortality. Low concentrations of TSH were associated with a higher risk of all-cause mortality and cardiovascular disease mortality. The 20-40th percentiles of FT 4 and the 60-80th percentiles of TSH could represent the optimal healthy ranges of thyroid function based on the risk of cardiovascular disease and mortality, with more than 5% increase of 10-year composite risk identified for FT 4 greater than the 85th percentile in women and men older than 70 years. We propose a feasible approach to establish the optimal healthy ranges of thyroid function, allowing for better identification of individuals with a higher risk of thyroid-related outcomes., Funding: None., Competing Interests: Declaration of interests TIMK reports personal fees from IBSA, Meck, Berlin-Chemie, and Quidel; is an unpaid co-chair of the American Thyroid Association guidelines on thyroid and pregnancy. BBY reports grants from National Health and Medical Research Council, Fremantle Hospital Medical Research Foundation, and Ada Bartholomew Medical Research Trust. NR reports a grant from the Swiss National Science Foundation. SR reports a grant for an investigator-initiated trial by Merck; manufacturer of levothyroxine and speaker fees from Merck, Abbott Pharmaceuticals, IBSA (makers of levothyroxine). JWJ reports research grants from or was a speaker (with or without lecture fees) at (Continuing Medical Education accredited) meetings sponsored or supported by Abbott, Amarin, Amgen, Athera, Biotronik, Boston Scientific, Dalcor, Daiichi Sankyo, Edwards Lifesciences, GE Healthcare, Johnson and Johnson, Lilly, Medtronic, Merck-Schering-Plough, Novartis, Novo Nordisk, Pfizer, Roche, Sanofi Aventis, the Netherlands Heart Foundation, CardioVascular Research the Netherlands, the Netherlands Heart Institute, and the European Community Framework KP7 Programme. DCB reports research grants from the National institutes of Health. DF reports a research grant from DFG SFB TR 296 LOCOTACT. RGJW reports a research grant from the Novo Nordisk Foundation Challenge Programme (NNF17OC0027812). All other authors declare no competing interests., (Copyright © 2023 Elsevier Ltd. All rights reserved.)