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Giuse pp e Penno Dipartimento di Medicina Clinica e Sperimentale Università di Pisa La nefropatia diabetica Inquadramento diagnostico della nefropatia diabetica

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  • Giuseppe PennoDipartimento di Medicina Clinica e SperimentaleUniversit di Pisa

    La nefropatia diabetica

    Inquadramento diagnostico della nefropatia diabetica

  • Dichiarazione esplicita di trasparenza delle fonti di finanziamentoe dei rapporti con soggetti portatori di interessi commerciali

    Il sottoscritto Dr. Giuseppe Penno

    in qualit diModeratore Relatore

    ai sensi dellart. 3.3 sul Conflitto di Interessi, pag. 17 del Reg. Applicativo dellAccordo Stato-Regione del 5 novembre 2009,

    dichiarache negli ultimi due anni ha avuto i seguenti rapporti anche di finanziamento con

    soggetti portatori di interessi commerciali in campo sanitario:

    AstraZeneca, Boerhinger Ingelheim, Eli-Lilly, Janssen, Merck Sharp & Dohme,

    Novo Nordisk, Takeda

    2 ottobre 2015

    NAPOLI, 9 GIUGNO 2018

  • Diagnostic parameters: albuminuria, eGFR and the clinical course of DKD

    Key points

  • Albuminuria is a key marker ofkidney damage

    Albuminuria indicates increased glomerular permeability Albuminuria can be categorised according to urine albumin-to-creatinine ratio or to

    24-hour urine albumin excretion, as follows:

    *Note that KDIGO 2012 guidelines recommend avoiding the terms microalbuminuria and macroalbuminuriaUACR, urine albumin-to-creatinine ratio

    UACR (mg/g)24-hour UAE (mg/24 h)

    Macroalbuminuria/severely increased*

    >300>300A3

    Microalbuminuria/moderately increased*

    3030030300

    A2

    Normal to mildly increased

  • Estimated glomerular filtration rate is the most commonly used index of renal function

    eGFR is generally reduced after widespread structural damage to the kidney It is categorised as follows:

    Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. Kidney Int Suppl 2013;3:1

    Kidney failure

  • KDIGO, Kidney Int Suppl 3: 1-150, 2013

    Low riskModerate riskHigh riskVery high risk

    Referral decision making by GFR and albuminuria. *Referring clinicians may wish to discuss with their nephrology service depending on local arrangements regarding monitoring or referring.

    Kidney Disease: Improving Global Outcomes (KDIGO) classification

  • KDIGO, Kidney Int Suppl 3: 1-150, 2013

    Kidney Disease: Improving Global Outcomes (KDIGO) classification

    GFR and albuminuria grid to reflect the risk of progression by intensity of coloring (green, yellow, orange, red, deep red). The numbers in the boxes are a guide to the frequency of monitoring (number of times per year).

    Low riskModerate riskHigh riskVery high risk

  • l Diagnostic parameters: albuminuria, eGFR and the clinical course of DKD

    l Albuminuria and eGFR: clinicalcourse (and epidemiology) of DKD

    Key points

  • Schematic presentation of the different clinical courses of diabetic kidney disease (DKD)

    Boger CA et al., PLOS Genetics, 8: e1002989, 2012 (modified)

    Normoalbuminuria

    Normal GFR

    Normoalbuminuria

    Normal GFR

    0 5 10 15 20Duration of diabetes (years)

    Increased GFR (hyperfiltration)

    Reduced GFR ESRD

    crosstalk between the two channels

    Normoalbuminuria

    Microalbuminuria

    Macroalbuminuria

    Normal GFR

  • 30-59 ml/min/1.73 m217.1%Normo 73.1%

    Micro22.2%

    Macro4.7%

    60-89 ml/min/1.73 m251.7%

    90 ml/min/1.73 m229.6%

  • 62.5%12.0%

    6.7%

    17.1%

    1.7%

    No CKD

    CKD stage 1

    CKD stage 2

    CKD stage 3

    CKD stages 4/5

    Approximately 40% of patientswith T2DM show signs of CKD (stages 1-5)

    Approximately 20% of patientswith T2DM show signs of renalfailure (eGFR

  • Severe(A3)

    Mild(A2)

    Normal(A1)

    15-29

    30-44

    45-59

    60-89

    >90

    Albuminuria

    Stage 2

    Stage 1Stage 0(no CKD)

    62.5%

    Stage 3

    Stage 4

    Stage 5

    Stage 1-2albuminuric phenotype

    18.7%

    Penno G et al. J Hypertens 29: 1802-1809, 2011

    Renal dysfunction is common in patients with T2DMThe RIACE Study: 15,773 patients with T2DM

    eGFRml/min/1.73 m2

  • Distribution of markers of CKD in RIACE and in NHANES participants with DM, hypertension, self-reported cardiovascular disease, & obesity, 20112014

    Data Source: National Health and Nutrition Examination Survey (NHANES), 20112014 participants age 20 & older. Single-sample estimates of eGFR & ACR; eGFR calculated using the CKD-EPI equation. Abbreviations: ACR, urine albumin/creatinine ratio; BMI, body mass index; CKD, chronic kidney disease; SR CVD, self-reported cardiovascular disease; eGFR, estimated glomerular filtration rate; HTN, hypertension.

    USRDS - 2016 Annual Data Report, Vol 1, CKD, Ch 1

    10.6%

    8.2%

    18.7%

    RIACE, Italy

  • De Cosmo S, et al., The AMD-Annals Study Group. Nephrol Dial Transplant, 29: 657-662, 2014

    Kidney dysfunction and related cardiovascular risk factorsamong patients with type 2 diabetes

    Clinical features of 120,903 patients with type 2 diabetes: whole sample and divided according to the presence/absence of albuminuria or low eGFR

    10.6% 18.7% 8.2%62.5%

  • Diabetic Kidney Disease (DKD)

    Thomas MC et al., Nature Reviews / Disease Primers, 1: 1-19, 2015

    The prevalence of CKD in different populations with type 2 diabetes

  • *Adjusted for age, sex, and race/ethnicity. p-values are for trendUACR, urine albumin-to-creatinine ratio

    Prevalent cases of diabetic kidney disease in the United States accounting for persistence

    Clinical manifestations of Kidney Disease among US Adults with Diabetes, 1988-2014

    p=0.39 p

  • p=0.001 p=0.15p

  • l Diagnostic parameters: albuminuria, eGFR and the clinical course of DKD

    l Albuminuria and eGFR: clinicalcourse (and epidemiology) of DKD

    l Albuminuria and eGFR in the KDIGO guidelines

    Key points

  • KDIGO, Kidney Int Suppl 3: 1-150, 2013

    Kidney Disease: Improving Global Outcomes (KDIGO) classification

  • KDIGO, Kidney Int Suppl 3: 1-150, 2013

    Kidney Disease: Improving Global Outcomes (KDIGO) classification

  • Matsushita K et al, JAMA 307: 1941-1951, 2012

    Distribution of estimated GFRData from 1.1 million adults from 25 general population cohorts,

    7 high-risk cohorts (of vascular disease), and 13 CKD cohorts

    Comparison of risk prediction using the CKD-EPI Equation and the MDRD Study Equation for Estimated Glomerular FiltrationRate

  • Matsushita K et al, JAMA 307: 1941-1951, 2012

    Reclassification across estimated GFR categories

    Comparison of risk prediction using the CKD-EPI Equation and the MDRD Study Equation for Estimated Glomerular FiltrationRate

  • Matsushita K et al, JAMA 307: 1941-1951, 2012

    Net reclassification improvements for all-cause mortality, cardiovascular mortality, and ESRD

    Comparison of risk prediction using the CKD-EPI Equation and the MDRD Study Equation for Estimated Glomerular FiltrationRate

  • KDIGO, Kidney Int Suppl 3: 1-150, 2013

    Kidney Disease: Improving Global Outcomes (KDIGO) classification

  • l Diagnostic parameters: albuminuria, eGFR and the clinical course of DKD

    l Albuminuria and eGFR: clinicalcourse (and epidemiology) of DKD

    l Albuminuria and eGFR in the KDIGO guidelines

    l Albuminuria and eGFR for DKD monitoring

    Key points

  • Normal AERn. 2,729 (75%)

    Micro-albuminurian. 438 (12%)

    Macro-albuminurian. 475 (13%)

    Regressedn. 102

    Persistentn. 336

    Persistentn. 364

    Regressedn. 111

    23.3% 23.4%

    The Finnish Diabetic Nephropathy Study

    Study subjects (n. 3,642)

    Men: 50.7%; Age: 37.4 11.9; BMI: 25.1 3.5

    6.9 years follow-up

    Jansson F et al., EASD, September 2016

  • The Finnish Diabetic Nephropathy Study

    Jansson F et al., EASD, September 2016

    0%

    10%

    20%

    30%

    40%

    50%

    0 5 10 15

    Incidence of first ever CVD event by albuminuria status (n=3,449)

    Time (years)

    NORMO

    MICRO

    MACRO

    HR = 1 (reference)

    HR = 2.28 (1.68-3.10)

    HR = 4.46 (3.46-5.77)

  • The Finnish Diabetic Nephropathy Study

    Jansson F et al., EASD, September 2016

    0%

    10%

    20%

    30%

    40%

    50%

    0 5 10 15

    MACRO -> MICRO/NORMO

    MICRO -> NORMO

    HR = 1 (reference)

    HR = 1.15 (0.61-2.19)

    HR = 2.28 (1.68-3.10)

    HR = 2.70 (1.73-4.24)

    HR = 4.46 (3.46-5.77)

    Time (years)

    Incidence of first ever CVD event by albuminuria status (n=3,449)

    NORMO

    MICRO

    MACRO

  • The Finnish Diabetic Nephropathy Study

    Jansson F et al., EASD, September 2016

    MACRO -> MICRO/NORMO

    MICRO -> NORMO

    HR = 1 (reference)NORMO

    MICRO

    MACRO

    0%

    10%

    20%

    30%

    40%

    0 5 10 15

    Total mortality

    Time (years)

    HR = 1.19 (0.58-2.43)

    HR = 2.65 (1.94-3.63)

    HR = 3.54 (2.33-5.36)

    HR = 6.32 (4.91-8.13)

  • l Diagnostic parameters: albuminuria, eGFR and the clinical course of DKD

    l Albuminuria and eGFR: clinicalcourse (and epidemiology) of DKD

    l Albuminuria and eGFR in the KDIGO guidelines

    l Albuminuria and eGFR and DKD monitoring

    l What the diagnosis of DKD implies

    Key points

  • Thomas MC et al., Nature Reviews / Disease Primers, 1: 1-19, 2015

    The strong association between DKD and increased incidence and prevalence of other diabetic complications

  • Impact of DKD on EASD/ADA Treatment Algorithm (Two-Drug Combibnations)

  • Glycemic control of type 2 diabetes mellitus across stages of renal impairment: information for primary care providers

    Tong L and Adker S. Postgraduate Medicine Published online: 18 Apr 2018.

  • Glycemic control of type 2 diabetes mellitus across stages of renal impairment: information for primary care providers

    Tong L and Adker S. Postgraduate Medicine Published online: 18 Apr 2018.

  • Role of lipids, glucose and BP on CVD and DKD. Solid blue lines = strong clinical evidence linking the treatment to end-organ benefit Blue

    dotted lines = inadequate evidence to support a clear benefit on CV or DKD

    Maqbool M et al., Seminars in Nephrology 38: 217-232, 2018

  • In type 2 diabetes with CVD and kidney disease, empagliflozin reduced mortality and hospitalization

    Wanner C et al., Circulation 137: 119-129, 2018

  • Diagnostic parameters: albuminuria, eGFR and the clinical course of DKD

    Albuminuria and eGFR: clinical course (and epidemiology) of DKD

    Albuminuria and eGFR in the KDIGO guidelines

    Albuminuria and eGFR and DKD monitoring

    What the diagnosis of DKD implies

    What the stratification by DKD phenotypes implies

    Key points

  • 0

    10

    20

    30

    40

    50

    CKD stages 1-2

    n. 2,949

    No CKD

    n. 9,865

    Maj

    or C

    VD e

    vent

    s, %

    794(26.9%)

    1,756(17.8%)

    Any CVD event by CKD phenotype

    Chi square, p

  • Kidney Disease and Increased Mortality in Type 2 Diabetes

  • Distribuzione dellEURODIAB PCS risk score in base ai fenotipi di CKD

    64.9

    28.3

    11.8

    0

    26.0

    37.7

    23.5

    8.39.1

    34.0

    64.7

    91.7

    0

    20

    40

    60

    80

    100

    No CKD CKD stadi1-2

    n. 53

    CKD stadi 3Alb-n. 17

    CKD stadi 3Alb+n. 12

    Rischio basso Rischio alto

    1-2n. 692

    p

  • Sopr

    avvi

    venz

    a cu

    mul

    ativ

    a

    Follow-up, anni

    K-M: Log Rank test p

  • HR 4.58(1.69-12.42)

    p=0.003

    HR 2.77(0.97-7.94)

    p=0.058

    Sopr

    avvi

    venz

    a cu

    mul

    ativ

    a

    Follow-up, anni

    Ref

    HR 2.57(1.11-5.94)

    p=0.027

    HR 95%CI p

    Sesso (M) 1.52 0.77-3.01 0.225

    EURODIAB risk scoreRischio bassoRischio intermedioRischio alto

    13.35

    11.74

    ---1.20-9.32

    4.44-31.04

  • Diagnostic parameters: albuminuria, eGFR and the clinical course of DKD

    Albuminuria and eGFR: clinical course (and epidemiology) of DKD

    Albuminuria and eGFR in the KDIGO guidelines

    Albuminuria and eGFR and DKD monitoring

    What the diagnosis of DKD implies

    What the stratification by DKD phenotypes implies

    The kidney biopsy and the biomarkers

    Key points

  • Thomas MC et al., Nature Reviews / Disease Primers, 1: 1-19, 2015

    Glomerulopathy in diabetes

    Morphological and functional alterations to renal glomeruli are one of the hallmarks of diabetic kidney disease

  • Indicazioni alla biopsia renale

    Indicata in pazienti con diabete nei quali esiste il sospetto della presenza di DKD differenti dalla nefropatia diabetica

    Permette di classificare la DKD in tre categorie associate a diverse prospettive prognostiche:

    1. nefropatia diabetica (ND)2. malattia renale non diabetica (NDRD, non-diabetic renal

    disease)3. condizione mista caratterizzata da NDRD sovrapposta a

    ND.

  • Indicazioni alla biopsia renale

    Le indicazioni legate alla presentazione atipica del danno renale sono le seguenti:

    SID. Position Statement sullAppropriatezza nella Prescrizione degli Esami Strumentali in Diabetologia; Esami strumentali per lo Screening della Nefropatia Diabetica

    - proteinuria in range nefrosico o riduzione del GFR in assenza di RD- proteinuria in range nefrosico o riduzione del GFR in soggetti con durata del

    diabete inferiore a 5 anni - ematuria (microscopica) isolata o presenza di sedimento urinario attivo;- insufficienza renale acuta (AKI)- sospetto di nefropatia associata ad altre malattie sistemiche (basso

    complemento, ANCA, ANA, dsDNA, anticorpi anticardiolipina, ASLO, HIV, M-Spike suggestivi di malattie monoclonali, crioglobuline, HCV)

    - mancanza della caratteristica cronologia della DKD (comparsa rapida di proteinuria senza progressione da micro- a macroalbuminuria, presentazione con sindrome nefrosica, progressivo rapido declino del GFR in pazienti con funzione renale precedentemente stabile)

    - significativa riduzione del GFR (>30%) dopo trattamento con bloccanti del RAS

  • CKD in diabetes: diabetic kidney disease versusnondiabetic kidney disease

    Anders HJ et al., Nature Review / Nephrology, 14: 361-377, 2018

    Causes of CKD in patients with diabetes mellitus and the pathophysiology of DKD

  • Presumed site of origin of commonly associated biomarkers predictive of DKD

    Colhoun HM and Marcovecchio L, Diabetologia, Online, 8 march 2018

  • Thank for your attention!

    Diapositiva numero 1Diapositiva numero 2Diapositiva numero 3Albuminuria is a key marker ofkidney damageEstimated glomerular filtration rate is the most commonly used index of renal function Diapositiva numero 6Diapositiva numero 7Diapositiva numero 8Diapositiva numero 9Diapositiva numero 10Diapositiva numero 11Diapositiva numero 12Diapositiva numero 13Diapositiva numero 14Diapositiva numero 15Diapositiva numero 16Diapositiva numero 17Diapositiva numero 18Diapositiva numero 19Diapositiva numero 20Diapositiva numero 21Diapositiva numero 22Diapositiva numero 23Diapositiva numero 24Diapositiva numero 25Diapositiva numero 26 Diapositiva numero 30Diapositiva numero 31Diapositiva numero 32Glycemic control of type 2 diabetes mellitus across stages of renal impairment: information for primary care providersGlycemic control of type 2 diabetes mellitus across stages of renal impairment: information for primary care providersDiapositiva numero 35Diapositiva numero 36Diapositiva numero 37Diapositiva numero 38Diapositiva numero 39Diapositiva numero 40Diapositiva numero 41Diapositiva numero 42Diapositiva numero 43Diapositiva numero 44Diapositiva numero 45Diapositiva numero 46Diapositiva numero 47Diapositiva numero 48Diapositiva numero 49