Diagnosis, Classification, and Evaluation of Chronic Kidney Disease
View More View Less
  • 1 Division of Nephrology, Johns Hopkins University School of Medicine, Baltimore, Maryland
  • | 2 Department of Medicine, New York University Langone School of Medicine, New York, New York
  • 1

    Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group: KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Available at: https://kdigo.org/wp-content/uploads/2017/02/KDIGO_2012_CKD_GL.pdf. Accessed July 7, 2021

    • Search Google Scholar
    • Export Citation
  • 2

    United States Renal Data System: 2020 USRDS Annual Data Report: Epidemiology of kidney disease in the United States, Bethesda, MD, National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, 2020

    • Search Google Scholar
    • Export Citation
  • 3

    Chen TK, Knicely DH, Grams ME: Chronic kidney disease diagnosis and management: A review. JAMA 322: 12941304, 2019 PubMed

  • 4

    Chu CD, McCulloch CE, Banerjee T, Pavkov ME, Burrows NR, Gillespie BW, et al.; Centers for Disease Control and Prevention Chronic Kidney Disease Surveillance Team: CKD awareness among US adults by future risk of kidney failure. Am J Kidney Dis 76: 174183, 2020 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 5

    Whelton PK, Carey RM, Aronow WS, Casey DE Jr, Collins KJ, Dennison Himmelfarb C, et al.: 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: A report of the American College of Cardiology/American Heart Association task force on clinical practice guidelines. Hypertension 71: e13e115, 2018 PubMed

    • Search Google Scholar
    • Export Citation
  • 6

    Shlipak MG, Tummalapalli SL, Boulware LE, Grams ME, Ix JH, Jha V, et al.; Conference Participants: The case for early identification and intervention of chronic kidney disease: Conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) controversies conference Available at: https://kdigo.org/wp-content/uploads/2019/01/KDIGO-Early-CKD-ID-and-intervention-conf-report-FINAL.pdf. Accessed April 12, 2021

    • Search Google Scholar
    • Export Citation
  • 7

    Peralta CA, Frigaard M, Rolon L, Seal K, Tuot D, Senyak J, et al.: Screening for CKD to improve processes of care among nondiabetic veterans with hypertension: A pragmatic cluster-randomized trial. Clin J Am Soc Nephrol 15: 174181, 2020 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 8

    Burrows NR, Vassalotti JA, Saydah SH, Stewart R, Gannon M, Chen SC, et al.: Identifying high-risk individuals for chronic kidney disease: Results of the CHERISH community demonstration project. Am J Nephrol 48: 447455, 2018 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 9

    Stempniewicz N, Vassalotti JA, Cuddeback JK, Ciemins E, Storfer-Isser A, Sang Y, et al.: Chronic kidney disease testing among primary care patients with type 2 diabetes across 24 U.S. health care organizations. Diabetes Care 44: 20002009, 2021 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 10

    Shin JI, Chang AR, Grams ME, Coresh J, Ballew SH, Surapaneni A, et al.; CKD Prognosis Consortium: Albuminuria testing in hypertension and diabetes: An individual-participant data meta-analysis in a global consortium. Hypertension 78: 10421052, 2021 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 11

    American Diabetes Association: 11. Microvascular complications and foot care: Standards of medical care in diabetes-2021. Diabetes Care 44[Suppl 1]: S151S167, 2021 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12

    Cosentino F, Grant PJ, Aboyans V, Bailey CJ, Ceriello A, Delgado V, et al.; ESC Scientific Document Group: 2019 ESC guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD. Eur Heart J 41: 255323, 2020 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 13

    Qiao Y, Shin JI, Chen TK, Sang Y, Coresh J, Vassalotti JA, et al.: Association of albuminuria levels with the prescription of renin-angiotensin system blockade. Hypertension 76: 17621768, 2020 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14

    Umeukeje EM, Wild MG, Maripuri S, Davidson T, Rutherford M, Abdel-Kader K, et al.: Black Americans’ perspectives of barriers and facilitators of community screening for kidney disease. Clin J Am Soc Nephrol 13: 551559, 2018 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15

    Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D; Modification of Diet in Renal Disease Study Group: A more accurate method to estimate glomerular filtration rate from serum creatinine: A new prediction equation. Ann Intern Med 130: 461470, 1999 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 16

    Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF 3rd, Feldman HI, et al.; CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration): A new equation to estimate glomerular filtration rate. Ann Intern Med 150: 604612, 2009 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 17

    Powe NR: Black kidney function matters: Use or misuse of race? JAMA 324: 737738, 2020 PubMed

  • 18

    Delgado C, Baweja M, Crews DC, Eneanya ND, Gadegbeku CA, Inker LA, et al.: A unifying approach for GFR estimation: Recommendations of the NKF-ASN task force on reassessing the inclusion of race in diagnosing kidney disease. J Am Soc Nephrol 32: 29943015, 2021 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 19

    Inker LA, Eneanya ND, Coresh J, Tighiouart H, Wang D, Sang Y, et al.; Chronic Kidney Disease Epidemiology Collaboration: New creatinine- and cystatin C-based equations to estimate GFR without race. N Engl J Med 385: 17371749, 2021 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 20

    Inker LA, Titan S: Measurement and estimation of GFR for use in clinical practice: Core curriculum 2021. Am J Kidney Dis 78: 736749, 2021 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 21

    Hsu CY, Yang W, Parikh RV, Anderson AH, Chen TK, Cohen DL, et al.; CRIC Study Investigators: Race, genetic ancestry, and estimating kidney function in CKD. N Engl J Med 385: 17501760, 2021 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 22

    Inker LA, Schmid CH, Tighiouart H, Eckfeldt JH, Feldman HI, Greene T, et al.; CKD-EPI Investigators: Estimating glomerular filtration rate from serum creatinine and cystatin C. N Engl J Med 367: 2029, 2012 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 23

    Inker LA, Couture SJ, Tighiouart H, Abraham AG, Beck GJ, Feldman HI, et al.; CKD-EPI GFR Collaborators: A new panel-estimated GFR, including β2-microglobulin and β-trace protein and not including race, developed in a diverse population. Am J Kidney Dis 77: 673683.e1, 2021 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 24

    Coresh J, Inker LA, Sang Y, Chen J, Shafi T, Post WS, et al.: Metabolomic profiling to improve glomerular filtration rate estimation: A proof-of-concept study. Nephrol Dial Transplant 34: 825833, 2019 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 25

    Sumida K, Nadkarni GN, Grams ME, Sang Y, Ballew SH, Coresh J, et al.; Chronic Kidney Disease Prognosis Consortium: Conversion of urine protein-creatinine ratio or urine dipstick protein to urine albumin-creatinine ratio for use in chronic kidney disease screening and prognosis : An individual participant-based meta-analysis. Ann Intern Med 173: 426435, 2020 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 26

    Weaver RG, James MT, Ravani P, Weaver CGW, Lamb EJ, Tonelli M, et al.: Estimating urine albumin-to-creatinine ratio from protein-to-creatinine ratio: Development of equations using same-day measurements. J Am Soc Nephrol 31: 591601, 2020 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 27

    Naranjo FSSY, Sang Y, Ballew SH, Stempniewicz N, Dunning SC, Levey AS, et al.: Estimating kidney failure risk using electronic medical records. Kidney360 2: 415424, 2021 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 28

    Levey AS, de Jong PE, Coresh J, El Nahas M, Astor BC, Matsushita K, et al.: The definition, classification, and prognosis of chronic kidney disease: A KDIGO controversies conference report. Kidney Int 80: 1728, 2011 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 29

    Koye DN, Magliano DJ, Reid CM, Jepson C, Feldman HI, Herman WH, et al.: Risk of progression of nonalbuminuric CKD to end-stage kidney disease in people with diabetes: The CRIC (Chronic Renal Insufficiency Cohort) study. Am J Kidney Dis 72: 653661, 2018 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 30

    Halbesma N, Kuiken DS, Brantsma AH, Bakker SJ, Wetzels JF, De Zeeuw D, et al.: Macroalbuminuria is a better risk marker than low estimated GFR to identify individuals at risk for accelerated GFR loss in population screening. J Am Soc Nephrol 17: 25822590, 2006 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 31

    Tangri N, Stevens LA, Griffith J, Tighiouart H, Djurdjev O, Naimark D, et al.: A predictive model for progression of chronic kidney disease to kidney failure. JAMA 305: 15531559, 2011 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 32

    Tangri N, Grams ME, Levey AS, Coresh J, Appel LJ, Astor BC, et al.; CKD Prognosis Consortium: Multinational assessment of accuracy of equations for predicting risk of kidney failure: A meta-analysis. JAMA 315: 164174, 2016 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 33

    Grams ME, Sang Y, Ballew SH, Carrero JJ, Djurdjev O, Heerspink HJL, et al.: Predicting timing of clinical outcomes in patients with chronic kidney disease and severely decreased glomerular filtration rate. Kidney Int 93: 14421451, 2018 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 34

    Nelson RG, Grams ME, Ballew SH, Sang Y, Azizi F, Chadban SJ, et al.; CKD Prognosis Consortium: Development of risk prediction equations for incident chronic kidney disease. JAMA 322: 21042114, 2019 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 35

    Ramspek CL, Evans M, Wanner C, Drechsler C, Chesnaye NC, Szymczak M, et al.; EQUAL Study Investigators: Kidney failure prediction models: A comprehensive external validation study in patients with advanced CKD. J Am Soc Nephrol 32: 11741186, 2021 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 36

    Srivastava A, Palsson R, Kaze AD, Chen ME, Palacios P, Sabbisetti V, et al.: The prognostic value of histopathologic lesions in native kidney biopsy specimens: Results from the Boston Kidney Biopsy Cohort study. J Am Soc Nephrol 29: 22132224, 2018 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 37

    Mariani LH, Martini S, Barisoni L, Canetta PA, Troost JP, Hodgin JB, et al.: Interstitial fibrosis scored on whole-slide digital imaging of kidney biopsies is a predictor of outcome in proteinuric glomerulopathies. Nephrol Dial Transplant 33: 310318, 2018 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 38

    Royal V, Zee J, Liu Q, Avila-Casado C, Smith AR, Liu G, et al.: Ultrastructural characterization of proteinuric patients predicts clinical outcomes. J Am Soc Nephrol 31: 841854, 2020 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 39

    Palmer MB, Abedini A, Jackson C, Blady S, Chatterjee S, Sullivan KM, et al.: The role of glomerular epithelial injury in kidney function decline in patients with diabetic kidney disease in the TRIDENT cohort. Kidney Int Rep 6: 10661080, 2021 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 40

    Charlton JR, Xu Y, Wu T, deRonde KA, Hughes JL, Dutta S, et al.: Magnetic resonance imaging accurately tracks kidney pathology and heterogeneity in the transition from acute kidney injury to chronic kidney disease. Kidney Int 99: 173185, 2021 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 41

    Srivastava A, Cai X, Lee J, Li W, Larive B, Kendrick C, et al.: Kidney functional magnetic resonance imaging and change in eGFR in individuals with CKD. Clin J Am Soc Nephrol 15: 776783, 2020 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 42

    Sun Q, Baues M, Klinkhammer BM, Ehling J, Djudjaj S, Drude NI, et al.: Elastin imaging enables noninvasive staging and treatment monitoring of kidney fibrosis. Sci Transl Med 11: eaat4865, 2019 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 43

    Koratala A, Bhattacharya D, Kazory A: Point of care renal ultrasonography for the busy nephrologist: A pictorial review. World J Nephrol 8: 4458, 2019 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 44

    Koratala A, Teodorescu V, Niyyar VD: The nephrologist as an ultrasonographer. Adv Chronic Kidney Dis 27: 243252, 2020 PubMed

  • 45

    Koratala A, Segal MS, Kazory A: Integrating point-of-care ultrasonography into nephrology fellowship training: A model curriculum. Am J Kidney Dis 74: 15, 2019 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 46

    Mullangi S, Sozio SM, Hellmann DB, Martire C, Lohani S, Segal P, et al.: Integrative point-of-care ultrasound curriculum to impart diagnostic skills relevant to nephrology. Am J Kidney Dis 73: 894896, 2019 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 47

    Cavanaugh C, Perazella MA: Urine sediment examination in the diagnosis and management of kidney disease: Core curriculum 2019. Am J Kidney Dis 73: 258272, 2019 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 48

    Gohda T, Niewczas MA, Ficociello LH, Walker WH, Skupien J, Rosetti F, et al.: Circulating TNF receptors 1 and 2 predict stage 3 CKD in type 1 diabetes. J Am Soc Nephrol 23: 516524, 2012 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 49

    Niewczas MA, Gohda T, Skupien J, Smiles AM, Walker WH, Rosetti F, et al.: Circulating TNF receptors 1 and 2 predict ESRD in type 2 diabetes. J Am Soc Nephrol 23: 507515, 2012 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 50

    Coca SG, Nadkarni GN, Huang Y, Moledina DG, Rao V, Zhang J, et al.: Plasma biomarkers and kidney function decline in early and established diabetic kidney disease. J Am Soc Nephrol 28: 27862793, 2017 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 51

    Schrauben SJ, Shou H, Zhang X, Anderson AH, Bonventre JV, Chen J, et al.; CKD Biomarkers Consortium and the Chronic Renal Insufficiency Cohort (CRIC) Study Investigators: Association of multiple plasma biomarker concentrations with progression of prevalent diabetic kidney disease: Findings from the Chronic Renal Insufficiency Cohort (CRIC) study. J Am Soc Nephrol 32: 115126, 2021 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 52

    Chen TK, Estrella MM, Appel LJ, Coresh J, Luo S, Reiser J, et al.: Biomarkers of immune activation and incident kidney failure with replacement therapy: Findings from the African American study of kidney disease and hypertension. Am J Kidney Dis 78: 7584.e1, 2021 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 53

    Chen TK, Coca SG, Estrella MM, Appel LJ, Coresh J, Thiessen Philbrook H, et al.; CKD Biomarkers Consortium (BioCon): Longitudinal TNFR1 and TNFR2 and kidney outcomes: Results from AASK and VA NEPHRON-D. J Am Soc Nephrol 33: 9961010, 2022 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 54

    Greenberg JH, Abraham AG, Xu Y, Schelling JR, Feldman HI, Sabbisetti VS, et al.; CKD Biomarkers Consortium: Plasma biomarkers of tubular injury and inflammation are associated with CKD progression in children. J Am Soc Nephrol 31: 10671077, 2020 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 55

    Gutiérrez OM, Shlipak MG, Katz R, Waikar SS, Greenberg JH, Schrauben SJ, et al.: Associations of plasma biomarkers of inflammation, fibrosis, and kidney tubular injury with progression of diabetic kidney disease: A cohort study. Am J Kidney Dis 79: 849857, 2022 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 56

    Bhatraju PK, Zelnick LR, Shlipak M, Katz R, Kestenbaum B: Association of soluble TNFR-1 concentrations with long-term decline in kidney function: The multi-ethnic study of atherosclerosis. J Am Soc Nephrol 29: 27132721, 2018 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 57

    Sen T, Li J, Neuen BL, Neal B, Arnott C, Parikh CR, et al.: Effects of the SGLT2 inhibitor canagliflozin on plasma biomarkers TNFR-1, TNFR-2 and KIM-1 in the CANVAS trial. Diabetologia 64: 21472158, 2021 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 58

    Hayek SS, Sever S, Ko YA, Trachtman H, Awad M, Wadhwani S, et al.: Soluble urokinase receptor and chronic kidney disease. N Engl J Med 373: 19161925, 2015 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 59

    Luo S, Coresh J, Tin A, Rebholz CM, Chen TK, Hayek SS, et al.: Soluble urokinase-type plasminogen activator receptor in Black Americans with CKD. Clin J Am Soc Nephrol 13: 10131021, 2018 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 60

    Beck LH Jr, Bonegio RG, Lambeau G, Beck DM, Powell DW, Cummins TD, et al.: M-type phospholipase A2 receptor as target antigen in idiopathic membranous nephropathy. N Engl J Med 361: 1121, 2009 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 61

    Sethi S: New “antigens” in membranous nephropathy. J Am Soc Nephrol 32: 268278, 2021 PubMed

  • 62

    Bobart SA, De Vriese AS, Pawar AS, Zand L, Sethi S, Giesen C, et al.: Noninvasive diagnosis of primary membranous nephropathy using phospholipase A2 receptor antibodies. Kidney Int 95: 429438, 2019 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 63

    Burbelo PD, Joshi M, Chaturvedi A, Little DJ, Thurlow JS, Waldman M, et al.: Detection of PLA2R autoantibodies before the diagnosis of membranous nephropathy. J Am Soc Nephrol 31: 208217, 2020 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 64

    Tomas NM, Beck LH Jr, Meyer-Schwesinger C, Seitz-Polski B, Ma H, Zahner G, et al.: Thrombospondin type-1 domain-containing 7A in idiopathic membranous nephropathy. N Engl J Med 371: 22772287, 2014 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 65

    Cavanaugh C, Okusa MD: The evolving role of novel biomarkers in glomerular disease: A review. Am J Kidney Dis 77: 122131, 2021 PubMed

  • 66

    Ren S, Wu C, Zhang Y, Wang AY, Li G, Wang L, et al.: An update on clinical significance of use of THSD7A in diagnosing idiopathic membranous nephropathy: A systematic review and meta-analysis of THSD7A in IMN. Ren Fail 40: 306313, 2018 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 67

    Tomas NM, Hoxha E, Reinicke AT, Fester L, Helmchen U, Gerth J, et al.: Autoantibodies against thrombospondin type 1 domain-containing 7A induce membranous nephropathy. J Clin Invest 126: 25192532, 2016 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 68

    Sethi S, Madden BJ, Debiec H, Charlesworth MC, Gross L, Ravindran A, et al.: Exostosin 1/exostosin 2-associated membranous nephropathy. J Am Soc Nephrol 30: 11231136, 2019 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 69

    Sethi S, Debiec H, Madden B, Charlesworth MC, Morelle J, Gross L, et al.: Neural epidermal growth factor-like 1 protein (NELL-1) associated membranous nephropathy. Kidney Int 97: 163174, 2020 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 70

    Sethi S, Debiec H, Madden B, Vivarelli M, Charlesworth MC, Ravindran A, et al.: Semaphorin 3B-associated membranous nephropathy is a distinct type of disease predominantly present in pediatric patients. Kidney Int 98: 12531264, 2020 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 71

    Sethi S, Madden B, Debiec H, Morelle J, Charlesworth MC, Gross L, et al.: Protocadherin 7-associated membranous nephropathy. J Am Soc Nephrol 32: 12491261, 2021 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 72

    Cocchi E, Nestor JG, Gharavi AG: Clinical genetic screening in adult patients with kidney disease. Clin J Am Soc Nephrol 15: 14971510, 2020 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 73

    Lata S, Marasa M, Li Y, Fasel DA, Groopman E, Jobanputra V, et al.: Whole-exome sequencing in adults with chronic kidney disease: A pilot study. Ann Intern Med 168: 100109, 2018 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 74

    Groopman EE, Marasa M, Cameron-Christie S, Petrovski S, Aggarwal VS, Milo-Rasouly H, et al.: Diagnostic utility of exome sequencing for kidney disease. N Engl J Med 380: 142151, 2019 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 75

    Ottlewski I, Münch J, Wagner T, Schönauer R, Bachmann A, Weimann A, et al.: Value of renal gene panel diagnostics in adults waiting for kidney transplantation due to undetermined end-stage renal disease. Kidney Int 96: 222230, 2019 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 76

    Mann N, Braun DA, Amann K, Tan W, Shril S, Connaughton DM, et al.: Whole-exome sequencing enables a precision medicine approach for kidney transplant recipients. J Am Soc Nephrol 30: 201215, 2019 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 77

    Connaughton DM, Kennedy C, Shril S, Mann N, Murray SL, Williams PA, et al.: Monogenic causes of chronic kidney disease in adults. Kidney Int 95: 914928, 2019 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 78

    Rao J, Liu X, Mao J, Tang X, Shen Q, Li G, et al.; for “Internet Plus” Nephrology Alliance of National Center for Children’s Care: Genetic spectrum of renal disease for 1001 Chinese children based on a multicenter registration system. Clin Genet 96: 402410, 2019 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 79

    Hays T, Groopman EE, Gharavi AG: Genetic testing for kidney disease of unknown etiology. Kidney Int 98: 590600, 2020 PubMed

  • 80

    Yao T, Udwan K, John R, Rana A, Haghighi A, Xu L, et al.: Integration of genetic testing and pathology for the diagnosis of adults with FSGS. Clin J Am Soc Nephrol 14: 213223, 2019 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 81

    Rasouly HM, Groopman EE, Heyman-Kantor R, Fasel DA, Mitrotti A, Westland R, et al.: The burden of candidate pathogenic variants for kidney and genitourinary disorders emerging from exome sequencing. Ann Intern Med 170: 1121, 2019 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 82

    Xie J, Liu L, Mladkova N, Li Y, Ren H, Wang W, et al.: The genetic architecture of membranous nephropathy and its potential to improve non-invasive diagnosis. Nat Commun 11: 1600, 2020 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 83

    Schönauer R, Baatz S, Nemitz-Kliemchen M, Frank V, Petzold F, Sewerin S, et al.: Matching clinical and genetic diagnoses in autosomal dominant polycystic kidney disease reveals novel phenocopies and potential candidate genes. Genet Med 22: 13741383, 2020 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 84

    Mason AE, Sen ES, Bierzynska A, Colby E, Afzal M, Dorval G, et al.; UK RaDaR/NephroS Study: Response to first course of intensified immunosuppression in genetically stratified steroid resistant nephrotic syndrome. Clin J Am Soc Nephrol 15: 983994, 2020 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 85

    Howles SA, Thakker RV: Genetics of kidney stone disease. Nat Rev Urol 17: 407421, 2020 PubMed

  • 86

    Garrelfs SF, Frishberg Y, Hulton SA, Koren MJ, O’Riordan WD, Cochat P, et al.; ILLUMINATE-A Collaborators: Lumasiran, an RNAi therapeutic for primary hyperoxaluria type 1. N Engl J Med 384: 12161226, 2021 PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation

Metrics

All Time Past Year Past 30 Days
Abstract Views 371 371 266
Full Text Views 336 336 184
PDF Downloads 430 430 241