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Introduction: End-stage kidney disease (ESKD) is associated with increased morbidity and mortality. Identifying patients with stage 4 CKD (CKD4) at risk of rapid progression to ESKD remains challenging. Accurate prediction of CKD4 progression can improve patient outcomes by improving advanced care planning and optimizing healthcare resource allocation., Methods: We obtained electronic health record data from patients with CKD4 in a large health system between January 1, 2006, and December 31, 2016. We developed and validated four models, including Least Absolute Shrinkage and Selection Operator (LASSO) regression, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network (ANN), to predict ESKD at 3 years. We utilized area under the receiver operating characteristic curve (AUROC) to evaluate model performances and utilized Shapley additive explanation (SHAP) values and plots to define feature dependence of the best performance model., Results: We included 3,160 patients with CKD4. ESKD was observed in 538 patients (21%). All approaches had similar AUROCs; ANN yielded the highest AUROC (0.77; 95%CI 0.75 to 0.79) and LASSO regression (0.77; 95%CI 0.75 to 0.79), followed by random forest (0.76; 95% CI 0.74 to 0.79), and XGBoost (0.76; 95% CI 0.74 to 0.78)., Conclusions: We developed and validated several models for near-term prediction of kidney failure in CKD4. ANN, random forest, and XGBoost demonstrated similar predictive performances. Using this suite of models, interventions can be customized based on risk, and population health and resources appropriately allocated., (© 2023. The Author(s).)

Aims: Chronic kidney disease (CKD) increases risk of cardiovascular disease (CVD). Less is known about how CVD associates with future risk of kidney failure with replacement therapy (KFRT)., Methods and Results: The study included 25 903 761 individuals from the CKD Prognosis Consortium with known baseline estimated glomerular filtration rate (eGFR) and evaluated the impact of prevalent and incident coronary heart disease (CHD), stroke, heart failure (HF), and atrial fibrillation (AF) events as time-varying exposures on KFRT outcomes. Mean age was 53 (standard deviation 17) years and mean eGFR was 89 mL/min/1.73 m2, 15% had diabetes and 8.4% had urinary albumin-to-creatinine ratio (ACR) available (median 13 mg/g); 9.5% had prevalent CHD, 3.2% prior stroke, 3.3% HF, and 4.4% prior AF. During follow-up, there were 269 142 CHD, 311 021 stroke, 712 556 HF, and 605 596 AF incident events and 101 044 (0.4%) patients experienced KFRT. Both prevalent and incident CVD were associated with subsequent KFRT with adjusted hazard ratios (HRs) of 3.1 [95% confidence interval (CI): 2.9-3.3], 2.0 (1.9-2.1), 4.5 (4.2-4.9), 2.8 (2.7-3.1) after incident CHD, stroke, HF and AF, respectively. HRs were highest in first 3 months post-CVD incidence declining to baseline after 3 years. Incident HF hospitalizations showed the strongest association with KFRT [HR 46 (95% CI: 43-50) within 3 months] after adjustment for other CVD subtype incidence., Conclusion: Incident CVD events strongly and independently associate with future KFRT risk, most notably after HF, then CHD, stroke, and AF. Optimal strategies for addressing the dramatic risk of KFRT following CVD events are needed., Competing Interests: Conflict of interest: P.B.M. reports grants and personal fees from Boehringer Ingelheim; personal fees and non-financial support from Napp, Astrazeneca; personal fees from GSK, Pharmacosmos, and Astellas, outside the submitted work. J.J.C. is a Statistical Editor for the European Heart Journal. K.M. reports grants from NIDDK, during the conduct of the study; grants and personal fees from Kyowa Kirin, personal fees from Akebia, Kowa, and Fukuda Denshi, outside the submitted work. M.E.G. reports grants from National Kidney Foundation and from Kidney Disease Improving Global Outcomes outside the submitted work. J.C. reports grants from National Institute of Health and National Kidney Foundation during the conduct of the study; consulting at Healthy.io and scientific advisor to SomaLogic outside the submitted work. J.Ch. reports grants from National Health and Medical Research Council of Australia and grants and personal fees from Servier International outside the submitted work. L.C. reports consulting from CSL Vifor, honorarium for giving a talk from Fresenius Medical Care, and grants from NIH-NIDDK outside the submitted work. A.R.C. reports personal fees from Novartis, Amgen, Reata; grants from Novo Nordisk, Bayer, outside the submitted work. D.d.Z. reports personal fees from Merck during the conduct of the study, Bayer, Boehringer Ingelheim, and Travere outside the submitted work. M.E. reports institutional grants from Astellas pharma, AstraZeneca, and Vifor Pharma; honoraria form Astellas pharma, AstraZeneca, Baxter healthcare, and Fresenius Medical Care; support for attending meetings from Baxter healthcare, participation on a DSMB or Advisory Board for Astellas pharma, AstraZeneca, and Vifor pharma, and a leadership or fiduciary role on the Steering Committee of the Swedish Renal Registry, outside the submitted work. O.M.G. reports personal fees from Akebia, Amgen, AstraZeneca, Reata, Ardelyx, and QED, outside the submitted work. H.J.L.H. reports grants and honoraria for steering committee to his institution from Abbvie; grants and honoraria for steering committee and payments for advisory boards to his institution from AstraZeneca; honoraria for steering committee and payments for advisory boards from Bayer; grants and honoraria for steering committee and payments for advisory boards to his institution from Boehringer Ingelheim; honoraria for steering committee to his institution from CSL Behring, Chinook, Dimerix, Gilead; grants and honoraria for steering committee to his institution from Janssen, honoraria for steering committee to his institution from Eli Lilly, Merck, Mitsubishi Tanabe; grants and honoraria for steering committee to his institution from Novo Nordisk; and honoraria for steering committee to his institution from Travere Pharmaceuticals outside the submitted work. W.G.H. reports SHARP was funded by Merck & Co., Inc., Whitehouse Station, NJ USA, during the conduct of the study; he received grants from Boehringer Ingelheim and Eli Lilly; grants and fellowship from MRC UK, and fellowship from Kidney Research UK outside the submitted work. R.W.M. reports grants from NIHR and Kidney Research UK during the conduct of the study. G.N.N. reports personal fees, non-financial support, and other support (Scientific Cofounder, have equity/stock options, royalties and consulting) from Renalytix; personal fees and non-financial support from Pensieve Health; non-financial support and other support (Scientific Cofounder, have equity/stock options) from Nexus I Connect, Sole proprietor of Data2Wisdom LLC; personal fees from Variant Bio, Qiming Capital, Cambridge Consulting, Daiichi Sankyo, and Menarini Health, outside the submitted work. M.R. reports grants from NIH during the conduct of the study. N.S. reports being a current employee of GSK and employed at AMGA at the time of this study. B.S. reports grants from AstraZeneca, GlaxoSmithKline, and Fresenius Medical Care outside the submitted work. D.C.W. reports personal fees from AstraZeneca during the conduct of the study; personal fees from Amgen, Astellas, Bayer, Boehringer Ingelheim, Gilead, GlaxoSmithKline, Janssen, Mundipharma, Merck Sharp and Dohme, Tricida, Vifor and Zydus; and personal fees from AstraZeneca outside the submitted work. J.v.d.B. reports being an employee and stakeholder of Binnovate Digital Health BV outside the submitted work. All other co-authors have nothing to disclose. Some of the data reported here have been supplied by the United States Renal Data System. The interpretation and reporting of these data are the responsibility of the authors and in no way should be seen as an official policy or interpretation of the US Government., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Significance Statement: The kidney failure risk equation (KFRE) uses age, sex, GFR, and urine albumin-to-creatinine ratio (ACR) to predict 2- and 5-year risk of kidney failure in populations with eGFR <60 ml/min per 1.73 m 2 . However, the CKD-EPI 2021 creatinine equation for eGFR is now recommended for use but has not been fully tested in the context of KFRE. In 59 cohorts comprising 312,424 patients with CKD, the authors assessed the predictive performance and calibration associated with the use of the CKD-EPI 2021 equation and whether additional variables and accounting for the competing risk of death improves the KFRE's performance. The KFRE generally performed well using the CKD-EPI 2021 eGFR in populations with eGFR <45 ml/min per 1.73 m 2 and was not improved by adding the 2-year prior eGFR slope and cardiovascular comorbidities., Background: The kidney failure risk equation (KFRE) uses age, sex, GFR, and urine albumin-to-creatinine ratio (ACR) to predict kidney failure risk in people with GFR <60 ml/min per 1.73 m 2 ., Methods: Using 59 cohorts with 312,424 patients with CKD, we tested several modifications to the KFRE for their potential to improve the KFRE: using the CKD-EPI 2021 creatinine equation for eGFR, substituting 1-year average ACR for single-measure ACR and 1-year average eGFR in participants with high eGFR variability, and adding 2-year prior eGFR slope and cardiovascular comorbidities. We also assessed calibration of the KFRE in subgroups of eGFR and age before and after accounting for the competing risk of death., Results: The KFRE remained accurate and well calibrated overall using the CKD-EPI 2021 eGFR equation. The other modifications did not improve KFRE performance. In subgroups of eGFR 45-59 ml/min per 1.73 m 2 and in older adults using the 5-year time horizon, the KFRE demonstrated systematic underprediction and overprediction, respectively. We developed and tested a new model with a spline term in eGFR and incorporating the competing risk of mortality, resulting in more accurate calibration in those specific subgroups but not overall., Conclusions: The original KFRE is generally accurate for eGFR <45 ml/min per 1.73 m 2 when using the CKD-EPI 2021 equation. Incorporating competing risk methodology and splines for eGFR may improve calibration in low-risk settings with longer time horizons. Including historical averages, eGFR slopes, or a competing risk design did not meaningfully alter KFRE performance in most circumstances., (Copyright © 2023 by the American Society of Nephrology.)

Aims: The 2021 European Society of Cardiology (ESC) guideline on cardiovascular disease (CVD) prevention categorizes moderate and severe chronic kidney disease (CKD) as high and very-high CVD risk status regardless of other factors like age and does not include estimated glomerular filtration rate (eGFR) and albuminuria in its algorithms, systemic coronary risk estimation 2 (SCORE2) and systemic coronary risk estimation 2 in older persons (SCORE2-OP), to predict CVD risk. We developed and validated an 'Add-on' to incorporate CKD measures into these algorithms, using a validated approach., Methods: In 3,054 840 participants from 34 datasets, we developed three Add-ons [eGFR only, eGFR + urinary albumin-to-creatinine ratio (ACR) (the primary Add-on), and eGFR + dipstick proteinuria] for SCORE2 and SCORE2-OP. We validated C-statistics and net reclassification improvement (NRI), accounting for competing risk of non-CVD death, in 5,997 719 participants from 34 different datasets., Results: In the target population of SCORE2 and SCORE2-OP without diabetes, the CKD Add-on (eGFR only) and CKD Add-on (eGFR + ACR) improved C-statistic by 0.006 (95%CI 0.004-0.008) and 0.016 (0.010-0.023), respectively, for SCORE2 and 0.012 (0.009-0.015) and 0.024 (0.014-0.035), respectively, for SCORE2-OP. Similar results were seen when we included individuals with diabetes and tested the CKD Add-on (eGFR + dipstick). In 57 485 European participants with CKD, SCORE2 or SCORE2-OP with a CKD Add-on showed a significant NRI [e.g. 0.100 (0.062-0.138) for SCORE2] compared to the qualitative approach in the ESC guideline., Conclusion: Our Add-ons with CKD measures improved CVD risk prediction beyond SCORE2 and SCORE2-OP. This approach will help clinicians and patients with CKD refine risk prediction and further personalize preventive therapies for CVD., Competing Interests: Conflict of interest: Ku.M. reports grants from NIDDK; grants and personal fees from Kyowa Kirin, personal fees from Akebia outside the submitted work. M.G. reports grants from NIH and National Kidney Foundation outside the submitted work. J.A. reports personal fees from AstraZeneca, Novartis, and Boerhinger Ingelheim outside the submitted work. A.R.C. reports personal fees from Novartis, Reata, and Amgen; grants from Novo Nordisk outside the submitted work. N.E. reports personal fees from Bayer and AG Leverkusen outside the submitted work. K.E. reports grants from Amgen, Astra Zenceca, Bayer, Evotec, and Vifor; personal fees from Akebia, Astra Zeneca, Bayer, Otsuka, and Retrophin outside the submitted work. S.K.J reports salary support from US Government and Department of Veterans Affairs during the conduct of the study. C.K. reports personal fees from Bayer, Abbott, Astra-Zeneca, Takeda, Tricida, Akebia, Cara Therapeutics, Vifor, Rockwell, CSL Behring, Reata, Boehringer Ingelheim, and GSK outside the submitted work. A.S.L. reports grants and contracts from NIH and NKF for studies in CKD and a contract from AstraZeneca for DSMB for clinical trials of dapagliflozin. Ka.M. reports grants from Ministry of Health, Labor, and Welfare, Japan. G.N.N reports personal fees from Renalytix, Daiichi Sankyo, Menarini Medical, Qiming Capital, and Variant Bio; other fees from Pensieve Health, Nexus I Connect outside the submitted work; patent KidneyIntelX pending to Renalytix. M.G.S. reports grants from NIH- NIA/NIDDK/NHLBI during the conduct of the study; personal fees from Cricket Health, Intercept Pharmaceuticals, Bayer Pharmaceuticals, AztraZeneca, Boeringer Ingelheim; grants from Bayer Pharmaceuticals outside the submitted work. M.D.S reports a honoraria from AstraZeneca outside the submitted work. N.S. is a current employee of GSK and employed at AMGA. M.W. reports personal fees from Amgen and Freeline outside the submitted work. J.C. reports grants from National Institute of Health and National Kidney Foundation, during the conduct of the study; personal fees from Healthy.io and SomaLogic outside the submitted work. No other potential conflicts of interest relevant to this article were reported. All other authors report no potential conflicts., (© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Purpose of Review: Risk stratification for chronic kidney is becoming increasingly important as a clinical tool for both treatment and prevention measures. The goal of this review is to identify how machine learning tools contribute and facilitate risk stratification in the clinical setting., Recent Findings: The two key machine learning paradigms to predictively stratify kidney disease risk are genomics-based and electronic health record based approaches. These methods can provide both quantitative information such as relative risk and qualitative information such as characterizing risk by subphenotype., Summary: The four key methods to stratify chronic kidney disease risk are genomics, multiomics, supervised and unsupervised machine learning methods. Polygenic risk scores utilize whole genome sequencing data to generate an individual's relative risk compared with the population. Multiomic methods integrate information from multiple biomarkers to generate trajectories and prognostic different outcomes. Supervised machine learning methods can directly utilize the growing compendia of electronic health records such as laboratory results and notes to generate direct risk predictions, while unsupervised machine learning methods can cluster individuals with chronic kidney disease into subphenotypes with differing approaches to care., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Estimated glomerular filtration rate (eGFR) reflects kidney function. Progressive eGFR-decline can lead to kidney failure, necessitating dialysis or transplantation. Hundreds of loci from genome-wide association studies (GWAS) for eGFR help explain population cross section variability. Since the contribution of these or other loci to eGFR-decline remains largely unknown, we derived GWAS for annual eGFR-decline and meta-analyzed 62 longitudinal studies with eGFR assessed twice over time in all 343,339 individuals and in high-risk groups. We also explored different covariate adjustment. Twelve genome-wide significant independent variants for eGFR-decline unadjusted or adjusted for eGFR-baseline (11 novel, one known for this phenotype), including nine variants robustly associated across models were identified. All loci for eGFR-decline were known for cross-sectional eGFR and thus distinguished a subgroup of eGFR loci. Seven of the nine variants showed variant-by-age interaction on eGFR cross section (further about 350,000 individuals), which linked genetic associations for eGFR-decline with age-dependency of genetic cross-section associations. Clinically important were two to four-fold greater genetic effects on eGFR-decline in high-risk subgroups. Five variants associated also with chronic kidney disease progression mapped to genes with functional in-silico evidence (UMOD, SPATA7, GALNTL5, TPPP). An unfavorable versus favorable nine-variant genetic profile showed increased risk odds ratios of 1.35 for kidney failure (95% confidence intervals 1.03-1.77) and 1.27 for acute kidney injury (95% confidence intervals 1.08-1.50) in over 2000 cases each, with matched controls). Thus, we provide a large data resource, genetic loci, and prioritized genes for kidney function decline, which help inform drug development pipelines revealing important insights into the age-dependency of kidney function genetics., (Copyright © 2022 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.)

Objective: To predict adverse kidney outcomes for use in optimizing medical management and clinical trial design., Research Design and Methods: In this meta-analysis of individual participant data, 43 cohorts (N = 1,621,817) from research studies, electronic medical records, and clinical trials with global representation were separated into development and validation cohorts. Models were developed and validated within strata of diabetes mellitus (presence or absence) and estimated glomerular filtration rate (eGFR; ≥60 or <60 mL/min/1.73 m2) to predict a composite of ≥40% decline in eGFR or kidney failure (i.e., receipt of kidney replacement therapy) over 2-3 years., Results: There were 17,399 and 24,591 events in development and validation cohorts, respectively. Models predicting ≥40% eGFR decline or kidney failure incorporated age, sex, eGFR, albuminuria, systolic blood pressure, antihypertensive medication use, history of heart failure, coronary heart disease, atrial fibrillation, smoking status, and BMI, and, in those with diabetes, hemoglobin A1c, insulin use, and oral diabetes medication use. The median C-statistic was 0.774 (interquartile range [IQR] = 0.753, 0.782) in the diabetes and higher-eGFR validation cohorts; 0.769 (IQR = 0.758, 0.808) in the diabetes and lower-eGFR validation cohorts; 0.740 (IQR = 0.717, 0.763) in the no diabetes and higher-eGFR validation cohorts; and 0.750 (IQR = 0.731, 0.785) in the no diabetes and lower-eGFR validation cohorts. Incorporating the previous 2-year eGFR slope minimally improved model performance, and then only in the higher-eGFR cohorts., Conclusions: Novel prediction equations for a decline of ≥40% in eGFR can be applied successfully for use in the general population in persons with and without diabetes with higher or lower eGFR., (© 2022 by the American Diabetes Association.)

Rationale and Objective: APOL1 risk alleles are associated with increased cardiovascular and chronic kidney disease (CKD) risk. It is unknown whether knowledge of APOL1 risk status motivates patients and providers to attain recommended blood pressure (BP) targets to reduce cardiovascular disease., Study Design: Multicenter, pragmatic, randomized controlled clinical trial., Setting and Participants: 6650 individuals with African ancestry and hypertension from 13 health systems., Intervention: APOL1 genotyping with clinical decision support (CDS) results are returned to participants and providers immediately (intervention) or at 6 months (control). A subset of participants are re-randomized to pharmacogenomic testing for relevant antihypertensive medications (pharmacogenomic sub-study). CDS alerts encourage appropriate CKD screening and antihypertensive agent use., Outcomes: Blood pressure and surveys are assessed at baseline, 3 and 6 months. The primary outcome is change in systolic BP from enrollment to 3 months in individuals with two APOL1 risk alleles. Secondary outcomes include new diagnoses of CKD, systolic blood pressure at 6 months, diastolic BP, and survey results. The pharmacogenomic sub-study will evaluate the relationship of pharmacogenomic genotype and change in systolic BP between baseline and 3 months., Results: To date, the trial has enrolled 3423 participants., Conclusions: The effect of patient and provider knowledge of APOL1 genotype on systolic blood pressure has not been well-studied. GUARDD-US addresses whether blood pressure improves when patients and providers have this information. GUARDD-US provides a CDS framework for primary care and specialty clinics to incorporate APOL1 genetic risk and pharmacogenomic prescribing in the electronic health record., Trial Registration: ClinicalTrials.govNCT04191824., (Copyright © 2022. Published by Elsevier Inc.)

Importance: Risk variants in the apolipoprotein L1 (APOL1 [OMIM 603743]) gene on chromosome 22 are common in individuals of West African ancestry and confer increased risk of kidney failure for people with African ancestry and hypertension. Whether disclosing APOL1 genetic testing results to patients of African ancestry and their clinicians affects blood pressure, kidney disease screening, or patient behaviors is unknown., Objective: To determine the effects of testing and disclosing APOL1 genetic results to patients of African ancestry with hypertension and their clinicians., Design, Setting, and Participants: This pragmatic randomized clinical trial randomly assigned 2050 adults of African ancestry with hypertension and without existing chronic kidney disease in 2 US health care systems from November 1, 2014, through November 28, 2016; the final date of follow-up was January 16, 2018. Patients were randomly assigned to undergo immediate (intervention) or delayed (waiting list control group) APOL1 testing in a 7:1 ratio. Statistical analysis was performed from May 1, 2018, to July 31, 2020., Interventions: Patients randomly assigned to the intervention group received APOL1 genetic testing results from trained staff; their clinicians received results through clinical decision support in electronic health records. Waiting list control patients received the results after their 12-month follow-up visit., Main Outcomes and Measures: Coprimary outcomes were the change in 3-month systolic blood pressure and 12-month urine kidney disease screening comparing intervention patients with high-risk APOL1 genotypes and those with low-risk APOL1 genotypes. Secondary outcomes compared these outcomes between intervention group patients with high-risk APOL1 genotypes and controls. Exploratory analyses included psychobehavioral factors., Results: Among 2050 randomly assigned patients (1360 women [66%]; mean [SD] age, 53 [10] years), the baseline mean (SD) systolic blood pressure was significantly higher in patients with high-risk APOL1 genotypes vs those with low-risk APOL1 genotypes and controls (137 [21] vs 134 [19] vs 133 [19] mm Hg; P = .003 for high-risk vs low-risk APOL1 genotypes; P = .001 for high-risk APOL1 genotypes vs controls). At 3 months, the mean (SD) change in systolic blood pressure was significantly greater in patients with high-risk APOL1 genotypes vs those with low-risk APOL1 genotypes (6 [18] vs 3 [18] mm Hg; P = .004) and controls (6 [18] vs 3 [19] mm Hg; P = .01). At 12 months, there was a 12% increase in urine kidney disease testing among patients with high-risk APOL1 genotypes (from 39 of 234 [17%] to 68 of 234 [29%]) vs a 6% increase among those with low-risk APOL1 genotypes (from 278 of 1561 [18%] to 377 of 1561 [24%]; P = .10) and a 7% increase among controls (from 33 of 255 [13%] to 50 of 255 [20%]; P = .01). In response to testing, patients with high-risk APOL1 genotypes reported more changes in lifestyle (a subjective measure that included better dietary and exercise habits; 129 of 218 [59%] vs 547 of 1468 [37%]; P < .001) and increased blood pressure medication use (21 of 218 [10%] vs 68 of 1468 [5%]; P = .005) vs those with low-risk APOL1 genotypes; 1631 of 1686 (97%) declared they would get tested again., Conclusions and Relevance: In this randomized clinical trial, disclosing APOL1 genetic testing results to patients of African ancestry with hypertension and their clinicians was associated with a greater reduction in systolic blood pressure, increased kidney disease screening, and positive self-reported behavior changes in those with high-risk genotypes., Trial Registration: ClinicalTrials.gov Identifier: NCT02234063.

Background: Although measuring albuminuria is the preferred method for defining and staging chronic kidney disease (CKD), total urine protein or dipstick protein is often measured instead., Objective: To develop equations for converting urine protein-creatinine ratio (PCR) and dipstick protein to urine albumin-creatinine ratio (ACR) and to test their diagnostic accuracy in CKD screening and staging., Design: Individual participant-based meta-analysis., Setting: 12 research and 21 clinical cohorts., Participants: 919 383 adults with same-day measures of ACR and PCR or dipstick protein., Measurements: Equations to convert urine PCR and dipstick protein to ACR were developed and tested for purposes of CKD screening (ACR ≥30 mg/g) and staging (stage A2: ACR of 30 to 299 mg/g; stage A3: ACR ≥300 mg/g)., Results: Median ACR was 14 mg/g (25th to 75th percentile of cohorts, 5 to 25 mg/g). The association between PCR and ACR was inconsistent for PCR values less than 50 mg/g. For higher PCR values, the PCR conversion equations demonstrated moderate sensitivity (91%, 75%, and 87%) and specificity (87%, 89%, and 98%) for screening (ACR >30 mg/g) and classification into stages A2 and A3, respectively. Urine dipstick categories of trace or greater, trace to +, and ++ for screening for ACR values greater than 30 mg/g and classification into stages A2 and A3, respectively, had moderate sensitivity (62%, 36%, and 78%) and high specificity (88%, 88%, and 98%). For individual risk prediction, the estimated 2-year 4-variable kidney failure risk equation using predicted ACR from PCR had discrimination similar to that of using observed ACR., Limitation: Diverse methods of ACR and PCR quantification were used; measurements were not always performed in the same urine sample., Conclusion: Urine ACR is the preferred measure of albuminuria; however, if ACR is not available, predicted ACR from PCR or urine dipstick protein may help in CKD screening, staging, and prognosis., Primary Funding Source: National Institute of Diabetes and Digestive and Kidney Diseases and National Kidney Foundation.

Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through trans-ancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we identified 264 associated loci (166 new). Of these, 147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research.

Rationale & Objective: Chronic kidney disease (CKD) is complicated by abnormalities that reflect disruption in filtration, tubular, and endocrine functions of the kidney. Our aim was to explore the relationship of specific laboratory result abnormalities and hypertension with the estimated glomerular filtration rate (eGFR) and albuminuria CKD staging framework., Study Design: Cross-sectional individual participant-level analyses in a global consortium., Setting & Study Populations: 17 CKD and 38 general population and high-risk cohorts., Selection Criteria for Studies: Cohorts in the CKD Prognosis Consortium with data for eGFR and albuminuria, as well as a measurement of hemoglobin, bicarbonate, phosphorus, parathyroid hormone, potassium, or calcium, or hypertension., Data Extraction: Data were obtained and analyzed between July 2015 and January 2018., Analytical Approach: We modeled the association of eGFR and albuminuria with hemoglobin, bicarbonate, phosphorus, parathyroid hormone, potassium, and calcium values using linear regression and with hypertension and categorical definitions of each abnormality using logistic regression. Results were pooled using random-effects meta-analyses., Results: The CKD cohorts (n=254,666 participants) were 27% women and 10% black, with a mean age of 69 (SD, 12) years. The general population/high-risk cohorts (n=1,758,334) were 50% women and 2% black, with a mean age of 50 (16) years. There was a strong graded association between lower eGFR and all laboratory result abnormalities (ORs ranging from 3.27 [95% CI, 2.68-3.97] to 8.91 [95% CI, 7.22-10.99] comparing eGFRs of 15 to 29 with eGFRs of 45 to 59mL/min/1.73m 2 ), whereas albuminuria had equivocal or weak associations with abnormalities (ORs ranging from 0.77 [95% CI, 0.60-0.99] to 1.92 [95% CI, 1.65-2.24] comparing urinary albumin-creatinine ratio > 300 vs < 30mg/g)., Limitations: Variations in study era, health care delivery system, typical diet, and laboratory assays., Conclusions: Lower eGFR was strongly associated with higher odds of multiple laboratory result abnormalities. Knowledge of risk associations might help guide management in the heterogeneous group of patients with CKD., (Copyright © 2018 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.)

Chronic kidney disease (CKD) affects ~10% of the global population, with considerable ethnic differences in prevalence and aetiology. We assemble genome-wide association studies of estimated glomerular filtration rate (eGFR), a measure of kidney function that defines CKD, in 312,468 individuals of diverse ancestry. We identify 127 distinct association signals with homogeneous effects on eGFR across ancestries and enrichment in genomic annotations including kidney-specific histone modifications. Fine-mapping reveals 40 high-confidence variants driving eGFR associations and highlights putative causal genes with cell-type specific expression in glomerulus, and in proximal and distal nephron. Mendelian randomisation supports causal effects of eGFR on overall and cause-specific CKD, kidney stone formation, diastolic blood pressure and hypertension. These results define novel molecular mechanisms and putative causal genes for eGFR, offering insight into clinical outcomes and routes to CKD treatment development.

Rationale & Objective: Random assignment to intensive blood pressure (BP) lowering (systolic BP<120mmHg) compared to a less intensive BP target (systolic BP<140mmHg) in the Action to Control Cardiovascular Risk in Diabetes BP (ACCORD-BP) trial resulted in a more rapid decline in estimated glomerular filtration rate (eGFR). Whether this reflects hemodynamic effects or intrinsic kidney damage is unknown., Study Design: Longitudinal analysis of a subgroup of clinical trial participants., Settings & Participants: A subgroup of 529 participants in ACCORD-BP., Exposures: Urine biomarkers of tubular injury (kidney injury molecule 1, interleukin 18 [IL-18]), repair (human cartilage glycoprotein 39 [YKL-40]), and inflammation (monocyte chemoattractant protein 1) at baseline and year 2., Outcomes: Changes in eGFR from baseline to 2 years., Analytical Approach: We compared changes in biomarker levels and eGFRs across participants treated to an intensive versus less intensive BP goal using analysis of covariance., Results: Of 529 participants, 260 had been randomly assigned to the intensive and 269 to the standard BP arm. Mean age was 62±6.5 years and eGFR was 90mL/min/1.73m 2 . Baseline clinical characteristics, eGFRs, urinary albumin-creatinine ratios (ACRs), and urinary biomarker levels were similar across BP treatment groups. Compared to less intensive BP treatment, eGFR was 9.2mL/min/1.73m 2 lower in the intensive BP treatment group at year 2. Despite the eGFR reduction, within this treatment group, ACR was 30% lower and 4 urinary biomarker levels were unchanged or lower at year 2. Also within this group, participants with the largest declines in eGFRs had greater reductions in urinary IL-18 and YKL-40 levels. In a subgroup analysis of participants developing incident chronic kidney disease (sustained 30% decline and eGFR<60mL/min/1.73m 2 ; n=77), neither ACR nor 4 biomarker levels increased in the intensive treatment group, whereas the level of 1 biomarker, IL-18, increased in the less intensive treatment group., Limitations: Few participants with advanced baseline chronic kidney disease. Comparisons across treatment groups do not represent comparisons of treatment arms created solely through randomization., Conclusions: Among a subset of ACCORD-BP trial participants, intensive BP control was associated with reductions in eGFRs, but not with an increase in injury marker levels. These findings support that eGFR decline observed with intensive BP goals in ACCORD participants may predominantly reflect hemodynamic alterations., (Copyright © 2018 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.)

Background: Chronic kidney disease (CKD) patients who live far (>30 miles) from their nephrologist experience lower rates of clinic visit adherence, limited access to treatment, and higher rates of hospitalization and mortality than patients who live in close proximity to their nephrologist. Strategies to minimize disparities between urban and remotely located CKD patients are needed. The purpose of this study was to determine whether adherence to clinic visits and clinical outcomes in the remote management of CKD via telenephrology is comparable to in-person conventional care., Methods: Renal clinic adherence and composite outcomes of death, end-stage renal disease (ESRD), or doubling of serum creatinine (Cr) were measured in geographically remote Hudson Valley VA Medical Center (HVVAMC) CKD patients enrolled in telenephrology (n = 112) and CKD patients enrolled in the Bronx VAMC renal clinic (n = 116)., Results: Prior to implementing the telenephrology service, 53.1% of scheduled visits of rural HVVAMC patients to the Bronx VAMC renal clinic were either cancelled or were "no-shows." This was reduced by nearly half (28.5%) after instituting telenephrology (p < 0.001). Moreover, the frequency of attending appointments was greater in the telenephrology (71.9%) vs. in-person Bronx VA cohort (61.0%). The incidence of the composite outcome of death, ESRD, or doubling of Cr was similar between both groups (p = 0.96) over 2 years of follow-up., Conclusions: Remote CKD care delivered through telenephrology improves renal clinic visit adherence while delivering comparable renal outcomes. Application of this technology is a promising method to provide access to care to rural CKD patients and to minimize the disparity between urban/rural patients., (Published by S. Karger AG, Basel.)

Objective To examine rates of readmission after parathyroidectomy in patients with chronic kidney disease and determine primary etiologies, timing, and risk factors for these unplanned readmissions. Study Design Retrospective cohort study. Setting Nationwide Readmissions Database. Subjects and Methods The Nationwide Readmissions Database was queried for parathyroidectomy procedures performed in patients with chronic kidney disease between January 2013 and November 2013. Patient-, admission-, and hospital-level characteristics were compared for patients with and without at least 1 unplanned 30-day readmission. Outcomes of interest included rates, etiology, and timing of readmission. Multivariate logistic regression was used to identify predictors of 30-day readmission. Results There were 2756 parathyroidectomies performed in patients with chronic kidney disease with an unplanned readmission rate of 17.2%. Hypocalcemia/hungry bone syndrome accounted for 40% of readmissions. Readmissions occurred uniformly throughout the 30 days after discharge, but readmissions for hypocalcemia/hungry bone syndrome peaked in the first 10 days and decreased over time. Weight loss/malnutrition at time of parathyroidectomy and length of stay of 5 to 6 days conferred increased risk of readmission with adjusted odds ratios (aOR) of 3.31 (95% confidence interval [CI], 1.55-7.05; P = .002) and 1.87 (95% CI, 1.10-3.19; P = .02), respectively. Relative to primary hyperparathyroidism, parathyroidectomies performed for secondary hyperparathyroidism (aOR, 2.53; 95% CI, 1.07-5.95; P = .03) were associated with higher risk of readmission. Conclusion Postparathyroidectomy readmission rates for patients with chronic kidney disease are nearly 5 times that of the general population. Careful consideration of postoperative care and electrolyte management is crucial to minimize preventable readmissions in this vulnerable population.

Importance: Trials in patients with hypertension have demonstrated that intensive blood pressure (BP) lowering reduces the risk of cardiovascular disease and all-cause mortality but may increase the risk of chronic kidney disease (CKD) incidence and progression. Whether intensive BP lowering is associated with a mortality benefit in patients with prevalent CKD remains unknown., Objectives: To conduct a systematic review and meta-analysis of randomized clinical trials (RCTs) to investigate if more intensive compared with less intensive BP control is associated with reduced mortality risk in persons with CKD stages 3 to 5., Data Sources: Ovid MEDLINE, Cochrane Library, EMBASE, PubMed, Science Citation Index, Google Scholar, and clinicaltrials.gov electronic databases., Study Selection: All RCTs were included that compared 2 defined BP targets (either active BP treatment vs placebo or no treatment, or intensive vs less intensive BP control) and enrolled adults (≥18 years) with CKD stages 3 to 5 (estimated glomerular filtration rate <60 mL/min/1.73 m2) exclusively or that included a CKD subgroup between January 1, 1950, and June 1, 2016., Data Extraction and Synthesis: Two of us independently evaluated study quality and extracted characteristics and mortality events among persons with CKD within the intervention phase for each trial. When outcomes within the CKD group had not previously been published, trial investigators were contacted to request data within the CKD subset of their original trials., Main Outcome and Measure: All-cause mortality during the active treatment phase of each trial., Results: This study identified 30 RCTs that potentially met the inclusion criteria. The CKD subset mortality data were extracted in 18 trials, among which there were 1293 deaths in 15 924 participants with CKD. The mean (SD) baseline systolic BP (SBP) was 148 (16) mm Hg in both the more intensive and less intensive arms. The mean SBP dropped by 16 mm Hg to 132 mm Hg in the more intensive arm and by 8 mm Hg to 140 mm Hg in the less intensive arm. More intensive vs less intensive BP control resulted in 14.0% lower risk of all-cause mortality (odds ratio, 0.86; 95% CI, 0.76-0.97; P = .01), a finding that was without significant heterogeneity and appeared consistent across multiple subgroups., Conclusions and Relevance: Randomization to more intensive BP control is associated with lower mortality risk among trial participants with hypertension and CKD. Further studies are required to define absolute BP targets for maximal benefit and minimal harm.

Background/aims: Depression is common in patients with end-stage renal disease (ESRD) on hemodialysis (HD). Although, depression is associated with mortality, the effect of depression on in-hospital outcomes has not been studied as yet., Methods: We analyzed the National Inpatient Sample for trends and outcomes of hospitalizations with depression in patients with ESRD., Results: The proportion of ESRD hospitalizations with depression doubled from 2005 to 2013 (5.01-11.78%). Hospitalized patients on HD with depression were younger (60.47 vs. 62.70 years, p < 0.0001), female (56.93 vs. 47.81%, p < 0.0001), white (44.92 vs. 34.01%, p < 0.0001), and had higher proportion of comorbidities. However, there was a statistically significant lower risk of mortality in HD patients within the top 5 reasons for admissions., Conclusion: There were significant differences in demographics and comorbidities for hospitalized HD patients with depression. Depression was associated with an increased rate of adverse effects in discharged patients, and decreased in-hospital mortality., (© 2017 S. Karger AG, Basel.)

Purpose of Review: Current biomarkers for chronic kidney disease (CKD) are limited by lack of sensitivity and inability to prognosticate CKD progression. Significant recent research has better characterized novel biomarker candidates that are associated with CKD progression and cardiovascular mortality in CKD. This review discusses the most significant advances within the past year., Recent Findings: We discuss biomarkers for outcomes in CKD under two categories: emerging (defined as having been validated in an independent cohort), which include serum cystatin C, serum β-trace protein, β2-microglobulin, soluble urokinase-type plasminogen activator receptor, soluble tumor necrosis factor receptors 1/2, urinary monocyte chemotactic protein-1, neutrophil gelatin-associated lipocalin, kidney injury molecule-1, and fibroblast growth factor-23; and novel (which have shown associations in smaller observational studies but have not been validated yet), which include indoxyl sulfate, p-cresyl sulfate, trimethylamine-N-oxide, IL-18, Klotho, markers of endothelial dysfunction, vimentin, and procollagen type III N-terminal propeptide. Further, we also discuss future directions for biomarker research including unbiased -omics approaches., Summary: There are a number of promising biomarkers that can better prognosticate outcomes in and progression of CKD. Further research is warranted to examine whether these biomarkers validate independently as well, and if their incorporation improves clinical practice or trial enrollment.

Recent advances in genomics and sequencing technology have led to a better understanding of genetic risk in CKD. Genetics could account in part for racial differences in treatment response for medications including antihypertensives and immunosuppressive medications due to its correlation with ancestry. However, there is still a substantial lag between generation of this knowledge and its adoption in routine clinical care. This review summarizes the recent advances in genomics and CKD, discusses potential reasons for its underutilization, and highlights potential avenues for application of genomic information to improve clinical care and outcomes in this particularly vulnerable population., (Copyright © 2016 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.)

Importance: Identifying patients at risk of chronic kidney disease (CKD) progression may facilitate more optimal nephrology care. Kidney failure risk equations, including such factors as age, sex, estimated glomerular filtration rate, and calcium and phosphate concentrations, were previously developed and validated in 2 Canadian cohorts. Validation in other regions and in CKD populations not under the care of a nephrologist is needed., Objective: To evaluate the accuracy of the risk equations across different geographic regions and patient populations through individual participant data meta-analysis., Data Sources: Thirty-one cohorts, including 721,357 participants with CKD stages 3 to 5 in more than 30 countries spanning 4 continents, were studied. These cohorts collected data from 1982 through 2014., Study Selection: Cohorts participating in the CKD Prognosis Consortium with data on end-stage renal disease., Data Extraction and Synthesis: Data were obtained and statistical analyses were performed between July 2012 and June 2015. Using the risk factors from the original risk equations, cohort-specific hazard ratios were estimated and combined using random-effects meta-analysis to form new pooled kidney failure risk equations. Original and pooled kidney failure risk equation performance was compared, and the need for regional calibration factors was assessed., Main Outcomes and Measures: Kidney failure (treatment by dialysis or kidney transplant)., Results: During a median follow-up of 4 years of 721,357 participants with CKD, 23,829 cases kidney failure were observed. The original risk equations achieved excellent discrimination (ability to differentiate those who developed kidney failure from those who did not) across all cohorts (overall C statistic, 0.90; 95% CI, 0.89-0.92 at 2 years; C statistic at 5 years, 0.88; 95% CI, 0.86-0.90); discrimination in subgroups by age, race, and diabetes status was similar. There was no improvement with the pooled equations. Calibration (the difference between observed and predicted risk) was adequate in North American cohorts, but the original risk equations overestimated risk in some non-North American cohorts. Addition of a calibration factor that lowered the baseline risk by 32.9% at 2 years and 16.5% at 5 years improved the calibration in 12 of 15 and 10 of 13 non-North American cohorts at 2 and 5 years, respectively (P = .04 and P = .02)., Conclusions and Relevance: Kidney failure risk equations developed in a Canadian population showed high discrimination and adequate calibration when validated in 31 multinational cohorts. However, in some regions the addition of a calibration factor may be necessary.

Objectives: We sought to synthesize and analyze the available data from randomized controlled trials (RCTs) for trimetazidine (TMZ) in the prevention of contrast-induced nephropathy (CIN)., Background: Contrast-induced nephropathy after coronary angiography is associated with poor outcomes. Trimetazidine is an anti-ischemic drug that might reduce incidence of CIN, but current data are inconclusive., Methods: We searched MEDLINE/PubMed, EMBASE, Scopus, Cochrane Library, Web of Science, and ScienceDirect electronic databases for RCTs comparing intravenous hydration with normal saline (NS) and/or N-acetyl cysteine (NAC) versus TMZ plus NS ± NAC for prevention of CIN. We used RevMan 5.2 for statistical analysis with the fixed effects model., Results: Of the 808 studies, 3 RCTs met criteria with 290 patients in the TMZ plus NS ± NAC group and 292 patients in the NS ± NAC group. The mean age of patients was 59.5 years, and baseline serum creatinine ranged from 1.3 to 2 mg/dL. Trimetazidine significantly reduced the incidence of CIN by 11% (risk difference 0.11; 95% confidence interval, 0.16-0.06; P < .01). There was no significant heterogeneity between the studies (I(2) statistic = 0). The number needed to treat to prevent 1 episode of CIN was 9., Conclusions: The addition of TMZ to NS ± NAC significantly decreased the incidence of CIN in patients undergoing coronary angiography. In conclusion, TMZ could be considered as a potential tool for prevention of CIN in patients with renal dysfunction., (© The Author(s) 2015.)

Self-reported ancestry, genetically determined ancestry, and APOL1 polymorphisms are associated with variation in kidney function and related disease risk, but the relative importance of these factors remains unclear. We estimated the global proportion of African ancestry for 9048 individuals at Mount Sinai Medical Center in Manhattan (3189 African Americans, 1721 European Americans, and 4138 Hispanic/Latino Americans by self-report) using genome-wide genotype data. CKD-EPI eGFR and genotypes of three APOL1 coding variants were available. In admixed African Americans and Hispanic/Latino Americans, serum creatinine values increased as African ancestry increased (per 10% increase in African ancestry, creatinine values increased 1% in African Americans and 0.9% in Hispanic/Latino Americans; P≤1x10(-7)). eGFR was likewise significantly associated with African genetic ancestry in both populations. In contrast, APOL1 risk haplotypes were significantly associated with CKD, eGFR<45 ml/min per 1.73 m(2), and ESRD, with effects increasing with worsening disease states and the contribution of genetic African ancestry decreasing in parallel. Using genetic ancestry in the eGFR equation to reclassify patients as black on the basis of ≥50% African ancestry resulted in higher eGFR for 14.7% of Hispanic/Latino Americans and lower eGFR for 4.1% of African Americans, affecting CKD staging in 4.3% and 1% of participants, respectively. Reclassified individuals had electrolyte values consistent with their newly assigned CKD stage. In summary, proportion of African ancestry was significantly associated with normal-range creatinine and eGFR, whereas APOL1 risk haplotypes drove the associations with CKD. Recalculation of eGFR on the basis of genetic ancestry affected CKD staging and warrants additional investigation., (Copyright © 2015 by the American Society of Nephrology.)

Twenty-six million Americans are estimated to have chronic kidney disease (CKD) with increased risk for cardiovascular disease and end stage renal disease. CKD is frequently undiagnosed and patients are unaware, hampering intervention. A tool for accurate and timely identification of CKD from electronic medical records (EMR) could improve healthcare quality and identify patients for research. As members of eMERGE (electronic medical records and genomics) Network, we developed an automated phenotyping algorithm that can be deployed to identify rapidly diabetic and/or hypertensive CKD cases and controls in health systems with EMRs It uses diagnostic codes, laboratory results, medication and blood pressure records, and textual information culled from notes. Validation statistics demonstrated positive predictive values of 96% and negative predictive values of 93.3. Similar results were obtained on implementation by two independent eMERGE member institutions. The algorithm dramatically outperformed identification by ICD-9-CM codes with 63% positive and 54% negative predictive values, respectively.