Información de la revista
Vol. 41. Núm. 6.Noviembre - Diciembre 2021
Páginas 605-712
Compartir
Compartir
Descargar PDF
Más opciones de artículo
Visitas
...
Vol. 41. Núm. 6.Noviembre - Diciembre 2021
Páginas 605-712
Original article
Open Access
Epidemiology, clinical profile, management, and two-year risk complications among patients with chronic kidney disease in Spain
Epidemiología, perfil clínico, manejo y riesgo de complicaciones a 2 años en pacientes con enfermedad renal crónica en España
Visitas
...
Carlos Escobara,
Autor para correspondencia
, Unai Arandab, Beatriz Palaciosb, Margarita Capelb, Antoni Sicrasc, Aram Sicrasc, Antonio Hormigod, Roberto Alcázare, Nicolás Manitof, Manuel Botanag
a University hospital La Paz, Madrid, Spain
b AstraZeneca, Spain
c Health Economics and Outcomes Research, Atrys Health, Barcelona, Spain
d Primary care center Salud Puerta Blanca, Malaga, Spain
e University hospital Infanta Leonor, Madrid, Spain
f Hospital de Bellvitge, Hospitalet de Llobregat, Barcelona, Spain
g Hospital Universitario Lucus Augusti, Lugo, Spain
Información del artículo
Resumen
Texto completo
Bibliografía
Descargar PDF
Estadísticas
Figuras (1)
Tablas (5)
Table 1. Baseline clinical characteristics of the CKD population at index date (1st January 2018) and according to the presence of type 2 diabetes and CKD stage.
Table 2. Event rates after 2 years of follow-up in the overall population and according to the presence of type 2 diabetes and CKD stage.
Table 3. Hospitalization and mortality rates after 2 years of follow-up in the overall CKD population and according to the presence of type 2 diabetes.
Table 4. Baseline clinical characteristics of the DAPA-CKD population at index date (1st January 2018) and according to the presence of type 2 diabetes and CKD stage.
Table 5. Event rates after 2 years of follow-up in the DAPA-CKD population and according to the presence of type 2 diabetes and CKD stage.
Mostrar másMostrar menos
Material adicional (1)
Abstract
Objectives

To describe the epidemiology, clinical profile, treatments, and to determine cardiovascular and renal outcomes after two years of follow-up in a contemporary chronic kidneay disease (CKD) population in Spain. This was also analyzed among the DAPA-CKD-like population (patients who met most inclusion criteria of DAPA-CKD trial).

Methods

Observational, retrospective, population-based study using BIG-PAC database. The CKD population was defined as patients ≥18 years, with at least one diagnostic code of CKD prior to the index date (January 1st, 2018). CKD was defined as estimated glomerular filtration rate (eGFR) <60mL/min/1.73m2 (CKD-EPI), or albuminuria >30mg/g.

Results

We identified 56,435 CKD patients after exclusions (76.4 years, 52.2% men, urine albumin-to-creatinine ratio 390.8mg/g, eGFR 49.7mL/min/1.73m2). CKD prevalence was 4.91% and incidence 2.10 per 1000 patient-years. Regarding treatments, 69.2% were taking renin-angiotensin system inhibitors (only 4.2% at maximal doses) and 3.5% of diabetic patients SGLT-2 inhibitors. During the two years of follow-up, rates of heart failure, all-cause death, myocardial infarction, stroke, and CKD were 17.9, 12.1, 7.2, 6.3, and 5.9 events per 100 patient-years, respectively. During this period, 44% of patients were hospitalized, and 6.8% died during hospitalization. Cardiovascular outcomes were more common in the DAPA-CKD-like population.

Conclusions

In Spain, CKD population is older and comorbidities, including diabetes and heart failure, are common. Cardiovascular and renal outcomes are frequent. There is room for improvement in CKD management, particularly through the use of drugs with proven cardiovascular and renal benefit.

Keywords:
DAPA-CKD
Death
Chronic kidney disease
Hospitalization
Medication
Outcome
Resumen
Objetivos

Describir la epidemiología, el perfil clínico, los tratamientos y los eventos cardiovasculares y renales, tras 2 años de seguimiento en una población contemporánea con enfermedad renal crónica (ERC) en España. También se analizó en la población tipo DAPA-CKD (pacientes que cumplían la mayoría de criterios del estudio DAPA-CKD).

Métodos

Estudio observacional, retrospectivo, poblacional, empleando la base de datos BIG-PAC. La población con ERC se definió como pacientes ≥18 años, con al menos un código diagnóstico de ERC antes de la fecha índice (01/01/2018). La ERC se definió como filtrado glomerular estimado (FGe)<60ml/min/1,73m2 (CKD-EPI) o albuminuria >30mg/g.

Resultados

Se identificaron 56.435 pacientes con ERC, tras exclusiones (76,4 años, 52,2% varones, cociente albúmina-creatinina 390,8mg/g, FGe 49,7ml/min/1,73m2). La prevalencia fue del 4,91% y la incidencia 2,10/1.000 pacientes/año. El 69,2% tomaba inhibidores del sistema renina-angiotensina (solo el 4,2% a dosis máximas) y el 3,5% de los diabéticos inhibidores SGLT-2. Tras 2 años, las tasas de insuficiencia cardiaca, muerte, infarto de miocardio, ictus y ERC fueron 17,9; 12,1; 7,2; 6,3; 5,9 eventos/100 pacientes/año, respectivamente. Además, el 44% hospitalizaron y el 6,8% murieron durante la hospitalización. Los eventos cardiovasculares fueron más frecuentes en la población tipo DAPA-CKD.

Conclusiones

En España, la población con ERC es mayor, y las comorbilidades, incluyendo diabetes e insuficiencia cardiaca, comunes. Los eventos cardiovasculares y renales son frecuentes. Hay margen de mejora en el manejo de la ERC, especialmente a través del empleo de fármacos con beneficio cardiovascular y renal.

Palabras clave:
DAPA-CKD
Muerte
Enfermedad renal crónica
Hospitalización
Medicación
Eventos
Texto completo
Introduction

Chronic kidney disease (CKD) has a major effect on global health, increasing both, morbidity and mortality.1 CKD significantly reduces lifespan, increases the risk of cardiovascular disease and may evolve into end-stage renal disease.2 In addition, it has been estimated that in 2017, nearly 700 million persons had CKD, 1.2 million people died from CKD, and CKD resulted in 35.8 million DALYs (disability-adjusted life-years) worldwide, being diabetic nephropathy responsible for almost a third of DALYs.1,3 Overall, life expectancy is markedly reduced as renal function declines or albuminuria develops.1–4 Of note, it is expected that these numbers will increase in the following years due to the aging of population, and the increased prevalence of hypertension and diabetes.5 Despite all these data, the awareness about the impact of CKD in real-world is low among patients and health-care providers.6

Fortunately, the development of CKD complications can be delayed or prevented with the apropriate treatment.7 Until recently, the only classes of drugs with proven benefit on slowing the decline of renal function were renin angiotensin system inhibitors, including angiotensin-converting enzyme inhibitors (ACEi) and angiotensin-receptor blockers (ARBs).8,9 However, in the last years, several sodium-glucose cotransporter-2 (SGLT-2) inhibitors have shown a positive impact on renal outcomes among patients with CKD,10,11 even in the absence of type 2 diabetes (T2D).10 In DAPA-CKD trial, patients with and without T2D, an eGFR of 25 to 75mL/min/1.73m2 and a urinary albumin-to-creatinine ratio (UACR) of 200 to 5000mg/g were included.10 As a result, this is an unique population in which nephroprotection with SGLT-2 inhibitors has been demonstrated, regardless the presence with T2D.

Despite the fact that healthcare system planning requires careful assessment of CKD epidemiology,1 and some data from Spain were published some years ago,12–14 current data for prevalence, morbidity, mortality and management of CKD are scarce, and more information is warranted.

The aims of this study were to describe the epidemiology, clinical characteristics and the therapeutic management of the CKD population in a recent cohort of patients in Spain, stratified by the presence of T2D and CKD stage, and to determine cardiovascular and renal outcomes during two years of follow-up. This was also analyzed in a population who met the most relevant inclusion criteria of the DAPA-CKD (Dapagliflozin and Prevention of Adverse Outcomes in Chronic Kidney Disease) trial10 (DAPA-CKD like population) with the aim of understanding the study population in real-world settings, in terms of baseline characteristics and cardiorenal events.

Methods

This was an observational cohort study, comprising cross-sectional and longitudinal retrospective analyses using secondary data captured in electronic health records from seven Spanish regions, from the BIG-PAC® database. BIG-PAC® database included information from non-selected 1.8 million persons of primary health centers and referral hospitals within the Spanish national health system. Before export to BIG-PAC®, data were rigorously anonymized and dissociated, making not possible individual identification. Previous studies have demonstrated its representativeness of the Spanish population.15 The study was approved by the Investigation Ethics Committee of Consorci Sanitari from Terrassa. No informed consent was provided, as this was a secondary data study and data were fully anonymized and dissociated from patients.

The study population was defined as all patients ≥18 years of age with at least one diagnostic code of CKD (Supplementary Table 1) or having laboratory results meeting the definition of any stage of CKD prior to the index date (January 1st, 2018). CKD stages 1–5 were defined according to the eGFR (calculated by the CKD-Epidemiology Collaboration equation) and the urine albumin-to-creatinine ratio (UACR) criteria: CKD stage 1: eGFR ≥90mL/min/1.73m2 and UACR ≥30mg/g (3–30mg/mmol) or ICD (International Classification of Diseases)-10 N18.1; CKD stage 2 (mild): eGFR 60–89mL/min/1.73m2 and UACR ≥30mg/g (3–30mg/mmol) or ICD-10 N18.2; CKD stage 3a (mild to moderate): eGFR 45–59mL/min/1.73m2 or ICD-10 N18.3; CKD stage 3b (moderate to severe): eGFR 30–44mL/min/1.73m2 or ICD-10 N18.3; CKD stage 4 (severe): eGFR 15–29mL/min/1.73m2 or ICD-10 N18.4; CKD stage 5 (kidney failure): eGFR <15mL/min/1.73m2 or ICD-10 N18.1; CKD unspecified: no eGFR data available and ICD code N18.9.16 In addition, CKD was classified as hypertensive and diabetic CKD.

T2D was defined as all patients filling a prescription of any antidiabetic medication, T2D diagnostic code or HbA1c>7% prior to index date, excluding type 1 diabetes. The DAPA-CKD like population included those patients ≥18 years, with or without T2D, but not type 1 diabetes, who had an eGFR of 25 to 75mL/min/1.73m2 and a UACR of 200 to 5000mg/g, on stable treatment with ACEi or ARBs for at least 4 weeks.10

Comorbidities were searched for in all available data prior to index date, and a minimum of 1 year of data before index date was required. The main comorbidities included myocardial infarction (MI), heart failure (HF), atrial fibrillation (AF), stroke, peripheral artery disease (PAD), diabetes, hyperkalemia, and gout. ICD-9 and ICD-10 codes (https://eciemaps.mscbs.gob.es) were considered for the diagnosis of comorbidities (Supplementary Table 1).

The information about treatment was recorded from the registries for dispensing medicines, according to the Anatomical Therapeutic Chemical Classification System (Supplementary Table 1).17 Treatment for hypertension (ACEi, ARBs, direct renin inhibitors, aldosterone antagonists, sacubitril/valsartan, beta blockers, diuretics, calcium channel blockers), antidiabetic medications (SGLT-2 inhibitors, metformin, sulfonylureas, DPP-4 [dipeptidyl peptidase 4] inhibitors, GLP-1 [glucagon-like peptide-1] receptor agonists, meglitinides, glitazones, acarbose, miglitol, insulin), antithrombotic therapy (warfarin, aspirin, P2Y12 receptor antagonists) and statins were recorded. The prescription of a drug in a specific patient was based only on medical criteria (routine practice).

Baseline characteristics (total CKD population and by T2D status and CKD stage), including demographics, comorbidities and medications were determined at index date (January 1st, 2018). In addition, prevalence and incidence of CKD was calculated in the overall population and according to T2D status. Incidence was calculated as all newly diagnosed patients during 2018 divided by the number of patients without CKD in the population at the beginning of 2018 and expressed in cases per 1000 patient-years. Prevalence was calculated as all patients with a CKD diagnosis at the end of 2018, divided by all individuals in the total population covered by the database at that time.

Cardiovascular events were defined as a main diagnosis during a hospital visit or stay occurred during 2 years after index date (i.e. at any time during 2018 or 2019) (Supplementary Table 1). Outcomes included all-cause death and hospitalizations due to MI, stroke, HF, CKD, and PAD, or CKD complications. In the case of CKD, these were hospitalizations due to CKD complications that were defined as decline of eGFR ≥50% at any time during follow-up, kidney transplantation or dialysis. All-cause death was defined as death of any cause. Since the cause of death was not available in the database, cardiovascular death was not reported. Outcomes were calculated in the overall CKD population and in the DAPA-CKD-like population, according to the presence of T2D, and were stratified by CKD stage. In addition, the following variables were also assessed for the total CKD group and by the presence of T2D: hospitalization rates, hospital readmission rates, mortality rates during hospitalization and mortality rates after first hospitalization.

Statistical analysis

Categorical variables were described by their absolute (n) and relative frequencies (%). Continuous variables were described using the mean and standard deviation. Event rates were presented as events and events per 100 patient-years. Categorical variables were compared with the Chi-square test or the Fisher exact test when appropriate. When two means were compared, the t-student test was used. Analyses of events were performed for the index date of 1st January 2018 with 2 years of follow-up. Time to first event was analyzed with the contrast t-student test for independent samples. Follow-up was censored at observation period, or death end unless an event has occurred. A level of statistical significance of 0.05 was applied in all the statistical tests. The data were analyzed using the statistical package SPSS v25.0 (SPSS Inc., Chicago, Illinois, USA).

Results

Out of 1.827.435 persons included in the BIG-PAC® database in 2018, 1,405,746 people were attended during the 2015–2017 period, of whom 1,175,426 were 18 years or older. At index date, 57,860 patients had CKD. As 1425 patients were excluded due to inconsistent data, 56,435 patients (97.6%) comprised the CKD study population (75% with a diagnostic code, 25% based on laboratory values, Fig. 1). The incidence of CKD in 2018 was 2.10 per 1000 patient-years and the prevalence was 4.91%. T2D patients had a CKD prevalence about 19 fold that of those without T2D (55.3% vs. 2.9%).

Fig. 1.

Flowchart modern population (2018).

(0,09MB).

The baseline clinical characteristics of the CKD population according to the presence of T2D and CKD stage are presented in Table 1. Overall, mean age was 76.4 years, 52.2% of patients were men, mean UACR was 390.8mg/g and mean eGFR 49.7mL/min/1.73m2. Overall, 20.6% of patients had a history of HF, 14.3% MI, and 10.6% stroke. With regard to treatments, 69.2% were taking renin angiotensin system inhibitors, but only 4.2% of patients at maximal doses. A total of 25,770 (45.7%) patients had T2D. Patients with T2D were younger (75.9 vs. 76.9 years; P<0.001), but UACR (390.8 vs. 345.2mg/g, P<0.001), and HbA1c (7.6 vs. 6.1%; P<0.001) were higher and eGFR lower (47.6 vs. 49.8mL/min/1.73m2, P<0.001) compared to those without T2D. In addition, comorbidities were more common among patients with T2D. Moreover, more T2D patients were taking renin-angiotensin system inhibitors (76.9% vs. 62.7%; P<0.001) (Table 1).

Table 1.

Baseline clinical characteristics of the CKD population at index date (1st January 2018) and according to the presence of type 2 diabetes and CKD stage.

  Diabetes statusCKD stageTotal
  Non T2D  T2D  P  Stage 1  Stage 2  P2 vs. 1  Stage 3a  P3a vs. 1  Stage 3b  P3b vs 1  Stage 4  P4 vs. 1  Stage 5  P5 vs. 1  Unspecified  PUnsp. vs. 1   
  (n=30,665;54.3%)  (n=25,770;45.7%)    (n=;2755;4.9%)  (n=;9650;17.1%)    (n=17,865;31.7%)    (n=15,415;27.3%)    (n=4620;8.2%)    (n=2,060;3.7%)    (n=4070;7.2%)     
Age, years  76.9  75.9  <0.001  71.3  75.1  <0.001  77.6  <0.001  78.6  <0.001  79.5  <0.001  80.3  <0.001  64.2  <0.001  76.4 
≥85 years, n (%)  9455 (30.8)  5450 (21.1)  <0.001  540 (19.6)  1990 (20.6)  0.250  5045 (28.2)  <0.001  4635 (30.1)  <0.001  1395 (30.2)  <0.001  1090 (52.9)  <0.001  210 (5.2)  <0.001  14,905 (26.4) 
Sex, female, n (%)  15,461 (50.4)  11,956 (46.4)  <0.001  1275 (46.3)  4620 (47.9)  0.138  8534 (47.8)  <0.001  7586 (49.2)  <0.001  2197 (47.6)  0.279  1120 (54.4)  <0.001  2085 (51.2)  <0.001  26,957 (47.8) 
Physical examination and laboratory tests
BMI, kg/m2  28.3  29.4    29.1  29.3    28.7    28.5    28.2    27.9    29.6    28.8 
SBP, mmHg  136.7  138.7  0.003  136.2  138.1  0.379  138.2  0.222  138.5  0.165  136.2  0.999  134.8  0.548  138.6    137.6 
UACR  345.2  390.8  <0.001  107.1  126.7  <0.001  249.6  <0.001  252.2  <0.001  1623.1  <0.001  1640.0  <0.001  121.2    390.8 
UACR A1  139 (0.5)  123 (0.5)  0.999  –  –  –    –  –  262 (6.4)  <0.001 
UACR A2  20,838 (68.0)  12,682 (49.2)  <0.001  2755 (100)  9650 (100)    11,014 (61.7)  <0.001  9412 (61.1)  <0.001  523 (11.3)  <0.001  50 (2.4)  <0.001  116 (2.9)  <0.001  33,520 (59.4) 
UACR A3  9688 (31.6)  12,965 (50.3)  <0.001    6851 (38.4)  <0.001  6003 (38.9)  <0.001  4097 (88.7)  <0.001  2010 (97.6)  <0.001  3692 (90.7)  <0.001  22,653 (40.1) 
eGFR*  49.8  47.6  <0.001  94.5  74.8  <0.001  52.0  <0.001  36.9  <0.001  22.1  <0.001  8.9  <0.001  <0.001  49.7 
eGFR ≥90*, n (%)  1549 (5.1)  1206 (4.7)  <0.001  2755 (100)  –  –  –  –  –  –  2755 (4.9) 
eGFR 60–89*, n (%)  5341 (17.4)  4309 (16.7)  <0.001  9650 (100)  –  –  –  –  –  –  9650 (17.1) 
eGFR 45–59*, n (%)  9947 (32.4)  7918 (30.7)  <0.001  –  17,865 (100)  –  –  –  –  –  17,865 (31.7) 
eGFR 30–44*, n (%)  8240 (26.9)  7175 (27.8)  <0.001  –  –  15,415 (100)  –  –  –  –  15,414 (27.3) 
eGFR 15–29*, n (%)  2379 (7.8)  2241 (8.7)  <0.001  –  –  –  4620 (100)  –  –  –  4621 (8.2) 
eGFR <15*, n (%)  936 (3.1)  1124 (4.4)  <0.001  –  –  –  –  2060 (100)  –  –  2060 (3.7) 
HbA1c, %  6.1  7.6  <0.001  6.7  6.7  0.999  6.8  0.224  6.8  0.227  6.8  0.299  6.9  0.170  6.9  0.170  6.8 
Creatinine, mg/dL  1.3  1.3  0.887  0.7  1.0  <0.001  1.2  <0.001  1.6  <0.001  2.1  <0.001  0.5  <0.001  0.9  <0.001  1.3 
Uric acid, g/dL  6.1  7.2  <0.001  6.5  6.7  0.123  6.6  0.225  6.6  0.225  6.7  0.038  6.5  0.895  6.6  0.253  6.6 
Comorbidities,n(%)
CKD – Chronic  30,665 (100)  25,770 (100)  –  2755 (100)  9650 (100)  –  17,865 (100)  –  15,415 (100)  –  4620 (100)  –  2060 (100)  –  4070 (100)  –  56,435 (100) 
Stage 1  1549 (5.1)  1206 (4.7)  <0.001  2755 (100)  –  –  –  –  –  –  2755 (4.9) 
Stage 2  5341 (17.4)  4309 (16.7)  <0.001  9650 (100)  –  –  –  –  –  –  9650 (17.1) 
Stage 3a  9947 (32.4)  7918 (30.7)  <0.001  –  17,865 (100)  –  –  –  –  –  17,865 (31.7) 
Stage 3b  8240 (26.9)  7175 (27.8)  <0.001  –  –  15,415 (100)  –  –  –  –  15,415 (27.3) 
Stage 4  2379 (7.8)  2241 (8.7)  <0.001  –  –  –  4620 (100)  –  –  –  4620 (8.2) 
Stage 5  936 (3.1)  1124 (4.4)  <0.001  –  –  –  –  2060 (100)  –  –  2060 (3.7) 
Not staged  2273 (7.4)  1797 (7.0)  <0.001  –  –  –  –  –  4070 (100)  –  4070 (7.2) 
Unspecified  8979 (28.4)  912 (3.5)  <0.001  380 (13.8)  1410 (14.6)  0.205  3241 (18.1)  <0.001  2745 (17.8)  <0.001  710 (15.4)  0.061  265 (12.9)  0.365  1140 (28.0)  <0.001  9891 (17.5) 
CKD – Diabetic  531 (1.7)  15,759 (61.2)  <0.001  820 (29.8)  2925 (30.3)  0.614  4770 (26.7)  <0.001  4315 (28.0)  0.053  1380 (29.9)  0.928  635 (30.8)  0.455  1445 (35.5)  <0.001  16,290 (28.9) 
CKDHypertensive  21,155 (69.9)  9099 (35.3)  <0.001  1555 (56.4)  5315 (55.1)  0.226  9854 (55.2)  0.238  8355 (54.2)  0.033  2530 (54.8)  0.181  1160 (56.3)  0.945  1485 (36.5)  <0.001  30,254 (53.6) 
Dialysis  371 (1.2)  554 (2.2)  <0.001  –  –    –  870 (42.2)  <0.001  55 (1.4)  –  925 (1.6) 
CVD  4616 (15.1)  5904 (22.9)  <0.001  405 (14.7)  1510 (15.7)  0.201  3535 (19.8)  <0.001  2900 (18.8)  <0.001  780 (16.9)  <0.001  500 (24.3)  <0.001  890 (21.9)  <0.001  10,519 (18.6) 
Myocardial infarction  3590 (11.7)  4476 (17.4)  <0.001  295 (10.7)  1100 (11.4)  0.305  2685 (15.0)  <0.001  2271 (14.7)  <0.001  705 (15.3)  <0.001  355 (17.2)  <0.001  655 (16.1)  <0.001  8067 (14.3) 
Heart failure  5701 (18.6)  5908 (22.9)  <0.001  350 (12.7)  1400 (14.5)  0.017  3694 (20.7)  <0.001  3285 (21.3)  <0.001  1085 (23.5)  <0.001  565 (27.4)  <0.001  1230 (30.2)  <0.001  11,610 (20.6) 
Stroke  3011 (9.8)  2956 (11.5)  <0.001  170 (6.2)  840 (8.7)  <0.001  1726 (9.7)  <0.001  1941 (12.6)  <0.001  520 (11.3)  <0.001  300 (14.6)  <0.001  470 (11.6)  <0.001  5967 (10.6) 
Atrial fibrillation  4917 (16.0)  4005 (15.5)  <0.001  295 (10.7)  1365 (14.2)  <0.001  3016 (16.9)  <0.001  2681 (17.4)  <0.001  795 (17.2)  <0.001  360 (17.5)  <0.001  410 (10.1)  0.425  8921 (15.8) 
PAD  1254 (4.1)  1446 (5.6)  <0.001  120 (4.4)  385 (4.0)  0.350  790 (4.4)  0.924  825 (5.4)  0.030  270 (5.8)  0.009  125 (6.1)  0.008  185 (4.6)  0.696  2700 (4.8) 
Diabetic CKD  531 (1.7)  15,759 (63.0)  <0.001  820 (29.8)  2925 (30.3)  0.614  4770 (26.7)  <0.001  4315 (28.0)  0.053  1380 (29.9)  0.928  635 (30.8)  0.455  1445 (35.5)  <0.001  16,245 (28.8) 
Diabetes  27,394 (100)  <0.001  1265 (45.9)  4655 (48.2)  0.033  8565 (47.9)  0.050  7581 (49.2)  <0.001  2281 (49.4)  <0.001  1038 (50.4)  <0.001  2009 (49.4)  <0.001  27,394 (48.5) 
Hyperkalemia  1316 (4.3)  1923 (7.5)  <0.001  115 (4.2)  520 (5.4)  0.012  915 (5.1)  0.024  849 (5.5)  0.001  320 (6.9)  <0.001  150 (7.3)  <0.001  370 (9.1)  <0.001  3241 (5.7) 
Gout  9644 (31.5)  8277 (32.1)  <0.001  770 (28.0)  2855 (29.6)  0.104  5801 (32.5)  0.001  5135 (33.3)  <0.001  1545 (33.4)  <0.001  700 (34.0)  <0.001  1115 (27.4)  0.587  17,919 (31.8) 
Medications,n(%)
Antihypertensives  22,017 (71.8)  22,446 (87.1)    2108 (76.5)  7469 (77.4)  0.321  14,292 (80.0)  <0.001  12,517 (81.2)  <0.001  3802 (82.3)  <0.001  1784 (86.6)  <0.001  3111 (76.4)  0.924  43,562 (77.2) 
RAAS inhibitors  19,221 (62.7)  19,825 (76.9)  <0.001  1860 (67.5)  6830 (67.5)  0.999  12,506 (70.0)  <0.001  10,570 (68.6)  0.253  3305 (71.5)  <0.001  1475 (71.6)  <0.001  2500 (61.4)  <0.001  39,046 (69.2) 
ACEi  9108 (29.7)  8221 (31.9)  <0.001  880 (31.9)  3220 (33.4)  0.140  5265 (29.5)  0.001  4379 (28.4)  <0.001  1560 (33.8)  0.093  745 (36.2)  <0.001  1280 (31.5)  0.727  17,332 (30.7) 
ACEi at maximal doses  473 (1.6)  611 (2.4)  <0.001  30 (1.1)  60 (0.6)  0.001  409 (2.3)  0.001  445 (2.9)  <0.001  85 (1.8)  0.018  55 (2.7)  0.003  –  1086 (1.9) 
ARBs  11,076 (36.1)  12,790 (49.6)  <0.001  1115 (40.5)  3955 (41.0)  0.001  7830 (43.8)  <0.001  6726 (43.6)  <0.001  2050 (44.4)  0.001  885 (43.0)  <0.001  1305 (32.1)  <0.001  23,866 (42.3) 
ARBs at maximal doses  593 (1.9)  729 (2.8)  <0.001  –  481 (2.7)  <0.001  651 (4.2)  <0.001  190 (4.1)  <0.001  –  –  1318 (2.3) 
Aldosterone antagonists  1553 (5.1)  1781 (6.9)  <0.001  115 (4.2)  425 (4.4)  0.798  1090 (6.1)  0.001  994 (6.5)  <0.001  330 (7.1)  <0.001  175 (8.5)  <0.001  205 (5.0)  0.125  3336 (5.9) 
Direct renin inhibitors  84 (0.3)  41 (0.2)  0.001  5 (0.2)  10 (0.1)  0.379  50 (0.3)  0.361  5 (0.0)  0.002  20 (0.4)  0.145  20 (1.0)  <0.001  15 (0.4)  0.151  127 (0.2) 
ARNI  1729 (5.6)  1850 (7.2)  <0.001  175 (6.4)  535 (5.5)  0.072  1209 (6.8)  0.436  1000 (6.5)  0.844  255 (5.5)  0.111  185 (9.0)  <0.001  220 (5.4)  0.083  3580 (6.3) 
Beta blockers  10,929 (35.6)  10,731 (41.6)  <0.001  790 (28.7)  3000 (31.1)  <0.001  6765 (37.9)  <0.001  5915 (38.4)  <0.001  1735 (37.6)  <0.001  825 (40.1)  <0.001  1305 (32.1)  <0.001  20,335 (36.0) 
Diuretics  11,030 (36.0)  11,430 (44.4)  <0.001  780 (28.3)  3310 (34.3)  <0.001  7370 (41.3)  <0.001  6620 (42.9)  <0.001  2080 (45.0)  <0.001  975 (47.3)  <0.001  1325 (32.6)  <0.001  22,460 (39.8) 
Thiazide diuretics  839 (2.7)  876 (3.4)  <0.001  70 (2.5)  355 (3.7)  0.002  550 (3.1)  0.087  475 (3.1)  0.090  135 (2.9)  0.309  50 (2.4)  0.825  80 (2.0)  0.167  1716 (3.0) 
Loop diuretics  9799 (32.0)  10,321 (40.1)  <0.001  680 (24.7)  2815 (29.2)  <0.001  6610 (37.0)  <0.001  5975 (38.8)  <0.001  1935 (41.9)  <0.001  895 (43.5)  <0.001  1210 (29.7)  <0.001  20,122 (35.7) 
Potassium sparing diuretics  1718 (5.6)  1979 (7.7)  <0.001  140 (5.1)  510 (5.3)  0.798  1226 (6.9)  <0.001  1141 (7.4)  <0.001  320 (6.9)  0.002  165 (8.0)  <0.001  195 (4.8)  0.574  3693 (6.6) 
CCB  8255 (26.9)  9305 (36.1)  <0.001  760 (27.6)  2920 (30.3)  <0.001  5545 (31.0)  <0.001  4905 (31.8)  <0.001  1475 (31.9)  <0.001  695 (33.7)  <0.001  1260 (31.0)  <0.001  17,560 (31.1) 
Dihydropyridines  7666 (25.0)  8659 (33.6)  <0.001  700 (25.4)  2715 (28.1)  <0.001  5145 (28.8)  <0.001  4540 (29.5)  <0.001  1390 (30.1)  <0.001  655 (31.8)  <0.001  1180 (29.0)  <0.001  16,325 (28.9) 
Non-dihydropyridines  684 (2.2)  739 (2.9)  <0.001  70 (2.5)  225 (2.3)  0.798  439 (2.5)  0.985  419 (2.7)  0.549  120 (2.6)  0.793  50 (2.4)  0.825  100 (2.5)  0.999  1426 (2.5) 
Antidiabetics  322 (1.0)  21,050 (81.7)  <0.001  1071 (38.9)  3925 (40.7)  0.089  6570 (36.8)  <0.001  6073 (39.4)  0.621  2054 (44.5)  <0.001  1057 (51.3)  <0.001  1497 (33.4)  <0.001  21,372 (37.9) 
Metformin  12,375 (48.0)  <0.001  541 (19.6)  2356 (24.4)  <0.001  3526 (19.7)  0.902  3240 (21.0)  0.095  1497 (32.4)  <0.001  718 (34.9)  <0.001  497 (12.2)  <0.001  12,375 (21.9) 
Sulfonylurea  2962 (11.5)  <0.001  178 (6.5)  691 (7.2)  0.205  850 (4.8)  <0.001  701 (4.5)  0.001  256 (5.5)  0.078  169 (8.2)  0.024  117 (2.9)  <0.001  2962 (5.2) 
DPP4 inhibitors  9864 (38.3)  <0.001  437 (15.9)  1711 (17.7)  0.028  2856 (16.0)  0.894  2823 (18.3)  <0.001  905 (19.6)  <0.001  465 (22.6)  <0.001  667 (16.4)  0.582  9864 (17.5) 
SGLT-2 inhibitors  889 (3.5)  <0.001  55 (2.0)  163 (1.7)  0.292  201 (1.1)  0.001  205 (1.3)  0.004  163 (3.5)  0.002  65 (3.2)  0.009  37 (0.9)  <0.001  889 (1.6) 
GLP-1 receptor agonists  750 (2.9)  <0.001  44 (1.6)  116 (1.2)  0.101  224 (1.3)  0.202  157 (1.0)  0.005  123 (2.7)  0.002  72 (3.5)  <0.001  14 (0.3)  <0.001  750 (1.3) 
Metiglinides  3551 (13.8)  <0.001  127 (4.6)  529 (5.5)  0.063  1188 (6.6)  <0.001  1087 (7.1)  0.001  124 (2.7)  <0.001  132 (6.4)  0.006  364 (8.9)  <0.001  3551 (6.3) 
Glitazones  430 (1.7)  <0.001  38 (1.4)  39 (0.4)  <0.001  84 (0.5)  <0.001  143 (0.9)  1.000  54 (1.2)  0.459  48 (2.3)  0.020  24 (0.6)  0.001  430 (0.8) 
Acarbose  549 (2.1)  <0.001  31 (1.1)  58 (0.6)  0.010  130 (0.7)  0.238  175 (1.1)  0.999  62 (1.3)  0.459  51 (2.5)  0.350  42 (1.0)  0.690  549 (1.0) 
Insulin  322 (1.0)  5154 (20.0)  <0.001  223 (8.1)  852 (8.8)  0.249  1631 (9.1)  0.087  1525 (9.9)  0.003  509 (11.0)  <0.001  259 (12.6)  <0.001  477 (11.7)  <0.001  5476 (9.7) 
Statins  14,187 (46.3)  16,189 (62.8)  <0.001  1430 (51.9)  5245 (54.4)  <0.001  9770 (54.7)  <0.001  8306 (53.9)  <0.001  2485 (53.8)  0.114  1125 (54.6)  <0.001  2015 (49.5)  <0.001  30,375 (53.8) 
Warfarin  3789 (12.4)  3551 (26.9)  <0.001  260 (9.4)  1155 (12.0)  <0.001  2415 (13.5)  <0.001  2090 (13.6)  <0.001  645 (14.0)  <0.001  275 (13.4)  <0.001  500 (12.3)  <0.001  7341 (13.0) 
Low dose aspirin  7775 (25.4)  6924 (26.9)  <0.001  580 (21.1)  2380 (24.7)  <0.001  4815 (27.0)  <0.001  4009 (26.0)  <0.001  1335 (28.9)  <0.001  565 (27.4)  <0.001  1015 (24.9)  <0.001  14,698 (26.1) 
Receptor P2Y12 antagonists  1380 (4.5)  2265 (8.8)  <0.001  140 (5.1)  555 (5.8)  0.225  1090 (6.1)  0.039  1115 (7.2)  <0.001  330 (7.1)  <0.001  200 (9.7)  <0.001  215 (5.3)  0.716  3645 (6.5) 

ACEi: angiotensin-converting enzyme inhibitors; ARBs: angiotensin receptor blockers; ARNI: angiotensin receptor and neprilysin inhibition; BMI: body mass index; CCB: Calcium channel blockers; CVD: cardiovascular disease; CKD: chronic kidney disease; DPP4: dipeptidyl peptidase 4; eGFR: estimated glomerular filtration rate; * mL/min/1.73m2; GLP-1: glucagon-like peptide-1; PAD: peripheral artery disease; RAAS: renin angiotensin system; SBP: systolic blood pressure; SGLT-2: sodium-glucose Cotransporter-2; UACR: Urine albumin-to-Creatinine Ratio.

Overall, 70.8% of patients had stage ≥3 CKD. Age increased as renal function worsened (from 71.3 years in patients with stage 1 CKD to 80.3 years among stage 5 CKD patients; P<0.001), as well as UACR (from 107.1mg/g to 1640.0mg/g; P<0.001) and the proportion of patients treated with renin-angiotensin system inhibitors (from 67.5% to 71.6%; P<0.001). Similarly, comorbidities increased as renal function decreased (Table 1).

After 2 years of follow-up, eGFR was 49.5±12.4mL/min/1.73m2 and UACR 401.8±195.6mg/g, 1.1% of patients underwent dialysis and 0.5% kidney transplantation. During this period, rates of hospitalizations due to HF, all-cause death, MI, stroke, CKD and PAD were 17.9, 12.1, 7.2, 6.3, 5.9 and 3.1 events per 100 patient-years, respectively. With regard to CKD endpoints, rates of decline of eGFR ≥50%, end-stage kidney disease, dialysis, and kidney transplantation were 3.8, 1.7, 1.1 and 0.5 events per 100 patient-years, respectively. Rates of the combined endpoint of CKD and/or HF were 20.8 events per 100 patient-years. Rates of all-cause death, cardiovascular and renal outcomes were significantly higher, and time to first HF hospitalization shorter, among patients with T2D, compared to those without T2D. Similarly, rates of all-cause death, cardiovascular and renal outcomes increased as CKD stage worsened. For instance, rates of combined endpoint of CKD and/or HF increased from 13.3 events per 100 patient-years in patients with stage 1 CKD to 26.4 events per 100 patient-years among stage 5 CKD patients (Table 2).

Table 2.

Event rates after 2 years of follow-up in the overall population and according to the presence of type 2 diabetes and CKD stage.

  Diabetes statusCKD stageTotal (n=56,435) 
  Non T2D (n=30,665)  T2D  P  Stage 1 (n=2755)  Stage 2 (n=9650)  P2 vs. 1  Stage 3a (n=17,865)  P3a vs. 1  Stage 3b (n=15,415)  P3b vs. 1  Stage 4 (n=4620)  P4 vs. 1  Stage 5 (n=2060)  P5 vs. 1  Unspecified (n=4070)  PUnsp. vs. 1   
    (n=25,770)                               
All-cause death
Events  2998  3022    35  605    2120    1985    660    310    305    6020 
Events per 100 patient-year  10.3  12.6  <0.001  1.3  6.5  <0.001  12.7  <0.001  13.8  <0.001  15.6  <0.001  16.6  <0.001  7.8  <0.001  12.1 
Time to first event, days  397±159  357±143  <0.001  489.5±196  414±166  <0.001  377±151  <0.001  339±136  <0.001  264±105  <0.001  225.9±90  <0.001  527±211  <0.001  377±148 
Myocardial infarction
Events  2015  1835    175  650    1190    1040    315    205    275    3850 
Events per 100 patient-year  6.7  7.2  <0.001  6.4  6.8  0.459  6.8  0.436  6.8  0.441  6.9  0.401  10.3  0.001  6.9  0.418  7.2 
Time to first event, days  308±148  291±140  <0.001  390.2±187  330±158  <0.001  300±144  <0.001  270±130  <0.001  210±101  <0.001  180.1±86  <0.001  420±202  <0.001  300±144 
Stroke
Events  1640  1690    115  475    1025    1005    320    170    220    3330 
Events per 100 patient-year  5.5  6.8  <0.001  4.3  5.1  0.087  5.9  0.001  6.8  0.001  7.2  0.001  8.7  <0.001  5.6  0.016  6.3 
Time to first event, days  309±217  298±209  <0.001  397.2±278  336±235  <0.001  306±214  <0.001  275±192  <0.001  214±150  <0.001  183±128  <0.001  428±299  <0.001  306±214 
Heart failure
Events  4723  4497    295  1240    3040    2805    860    430    550    9220 
Events per 100 patient-year  16.9  19.5  <0.001  11.4  13.8  <0.001  18.9  <0.001  20.4  <0.001  20.9  <0.001  24.0  <0.001  14.7  0.001  17.9 
Time to first event, days  264±123  242±135  <0.001  351±193  297±163  <0.001  270±148  <0.001  243±134  <0.001  189±104  <0.001  162±89  <0.001  378±208  0.001  261±148 
CKD
Events  1390  1247    65  210    665    555    200    802    140    2637 
Events per 100 patient-year  6.1  5.3  <0.001  3.2  2.9  0.413  4.3  0.001  4.3  0.001  4.9  0.001  41.2  <0.001  42  0.034  5.9 
Time to first event, days  356±145  274±178  <0.001  414±211  350±179  <0.001  318±162  <0.001  287±146  <0.001  223±114  <0.001  191±97  <0.001  446±227  <0.001  318±166 
Decline of eGFR ≥50%*
Events  1068  907    69  211    669    558    208    115    145    1975 
Events per 100 patient-year  3.6  3.6  0.904  2.5  2.3  0.541  4.0  <0.001  3.7  0.002  4.7  <0.001  5.6  <0.001  3.6  0.011  3.8 
ESKD (kidney transplantation or dialysis)
Events  340  352    –  –  –  –  692  –  –  692 
Events per 100 patient-year  1.1  1.4  <0.001          38.1      1.65 
Dialysis
Events  245  235    –  –  –  –  480  –  –  480 
Events per 100 patient-year  0.8  0.9  0.013          26.9      1.1 
Time to first event, days  285±137  269±124  –  –  –    –    –    –    271±126    –    271±126 
Kidney transplantation
Events  95  117    –  –  –  –  212  –  –  212 
Events per 100 patient-year  0.3  0.5  0.001          11.2      0.5 
Time to first event, days  366±162  306±144  –  –  –    –    –    –    328±147    –    328±147 
PAD
Events  737  828    55  245    530    440    155    75    65    1565 
Events per 100 patient-year  2.5  3.3  <0.001  2.0  2.6  0.07  3.0  0.003  2.9  0.008  3.4  0.001  3.8  <0.001  1.6  0.218  3.1 
Time to first event, days  282±141  232±116  <0.001  339±169  286±143  <0.001  260±130  <0.001  234±117  <0.001  182±91  <0.001  156±78  <0.001  365±182  <0.001  260±130 
Cardiorenal disease (CKD and/or HF)
Events  5405  5180    345  1385    3445    3165    1055    505    685    10,585 
Events per 100 patient-year  19.2  22.1  <0.001  13.3  15.5  <0.001  21.5  <0.001  23.2  <0.001  24.5  <0.001  26.4  <0.001  18.6  <0.001  20.8 
Time to first event, days  358±163  276±171  <0.001  382±198  324±180  <0.001  294±165  <0.001  2893±147  <0.001  225±101  <0.001  194±84  <0.001  446±206  <0.001  321±142 
*

From baseline to the lowest available during follow up; CKD: chronic kidney disease; eGFR: estimated glomerular filtration rate; ESKD: end stage kidney disease; HF: heart failure; PAD: peripheral artery disease.

After 2 years of follow-up, 44% of patients were hospitalized, of whom 37.1% were hospitalized due to heart failure, 32.7% were re-hospitalized and 15.4% of patients died during hospitalization (Table 3). The proportion of patients who were hospitalized and that of patients requiring re-hospitalization were higher in T2D patients than in patients without T2D (47.7% vs. 40.8%; P<0.001, and 16.6% vs. 12.5%; P<0.001, respectively). However, mortality during hospitalization was slightly lower among patients with T2D (6.6% vs. 6.9%; P<0.001) (Table 3).

Table 3.

Hospitalization and mortality rates after 2 years of follow-up in the overall CKD population and according to the presence of type 2 diabetes.

  No T2D (n=30,665;54.3%)  T2D (n=25,770;45.7%)  Total (n=56,435;100%)  P 
Percentage of patients on maximal doses of ACE-I or ARB, n (%)  1064 (3.5)  1326 (5.2)  2390 (4.2)  <0.001 
Hospitalization, n (%)  12,514 (40.8)  12,287 (47.7)  24,801 (44.0)  <0.001 
Hospitalization due to heart failure, n (%)  4723 (15.4)  4497 (17.5)  9220 (16.3)  <0.001 
Hospital readmission, n (%)  3836 (12.5)  4284 (16.6)  8120 (14.4)  <0.001 
Mortality during hospitalization, n (%)  2115 (6.9)  1700 (6.6)  3815 (6.8)  <0.001 
Mortality after first hospitalization, n (%)  885 (2.9)  1320 (5.1)  2205 (3.9)  <0.001 

ACEi: angiotensin-converting enzyme inhibitors; ARBs: angiotensin receptor blockers; CKD: chronic kidney disease; T2D: type 2 diabetes.

A specific analysis was performed in the DAPA-CKD like population (n=7224). In this subpopulation, mean age was 77.0 years, 52.6% were men, mean UACR was 391.5mg/g and mean eGFR 49.8mL/min/1.73m2. Overall, 21.1% of patients had a history of HF, 12.4% MI, and 11.3% prior stroke. With regard to treatments, all patients were taking renin-angiotensin system inhibitors, but only 13.5% of patients at maximal doses. A total of 3426 (47.4%) patients had T2D. Patients with T2D were older (77.1 vs. 76.3 years; P=0.045), and had higher UACR (423.8 vs. 352.4mg/g), and HbA1c (7.6 vs. 5.9%; P<0.001), but without significant differences in eGFR (49.5 vs. 50.0mL/min/1.73m2). In addition, comorbidities were more common among patients with T2D compared to those without T2D. Overall, in the DAPA-CKD like population, 95.6% had stage 3 or 4 CKD. UACR increased as renal function worsened (from 129.3 in patients with stage 2 CKD to 1713.4mg/g among stage 4 CKD patients; P<0.001), as well as comorbidities. In addition, the proportion of patients at maximal doses of ACEi or ARBs also increased as stage CKD worsened (from 9.8% in patients with stage 2 CKD to 17.1% among stage 4 CKD patients; P<0.001) (Table 4).

Table 4.

Baseline clinical characteristics of the DAPA-CKD population at index date (1st January 2018) and according to the presence of type 2 diabetes and CKD stage.

  Diabetes statusCKD stageTotal 
  Non T2D  T2D  P  Stage 1  Stage 2  Stage 3a  P3a vs. 2  Stage 3b  P3bs2  Stage 4  P4 vs. 2  Stage 5  Unspecified  (n = 7224%) 
  (n=3798;52.6%)  (n=3426;47.4%)    (n=0)  (n=315;4.4%)  (n=3242;44.9%)    (n=2771;38.4%)    (n=896;12.4%)    (n=0)  (n=0)   
Age, years  76.3  77.1    NA  77.0  76.8    80.5    79.4    NA  NA  77.0 
≥85 years, n (%)  1162 (30.6)  893 (26.1)  0.045  NA  64 (20.3)  889 (27.4)  0.007  828 (29.9)  0.001  274 (30.6)  0.001  NA  NA  2055 (26.3) 
Sex, female, n (%)  1894 (49.9)  1606 (46.9)  0.011  NA  153 (48.6)  1545 (47.7)  0.760  1376 (49.7)  0.711  426 (47.5)  0.737  NA  NA  3424 (47.4) 
Physical examination and laboratory tests
SBP, mmHg  136.5  139.9  <0.001  NA  138.5  138.1    138.7    136.4    NA  NA  138.1 
UACR  352.4  423.8  <0.001  NA  129.3  256.3    258.1    1713.4    NA  NA  391.5 
UACR A1  –  NA        NA  NA 
UACR A2  2386 (62.8)  2245 (61.4)  0.221  NA  315 (100)  2150 (66.3)  <0.001  1826 (65.9)    340 (38.0)    NA  NA  4631 (64.1) 
UACR A3  1312 (37.2)  1281 (38.6)  0.221  NA  1092 (33.7)    945 (34.1)    556 (62.1)    NA  NA  2593 (35.9) 
eGFR*  50.0  49.5  0.724  NA  75.0  51.9    37.1    22.2    NA  NA  49.8 
eGFR ≥90*, n (%)  –  NA        NA  NA 
eGFR 60–89*, n (%)  177 (4.7)  138 (4.0)  0.146  NA  315 (100)        NA  NA  315 (4.4) 
eGFR 45–59*, n (%)  1810 (47.7)  1432 (41.8)  <0.001  NA  3242 (100)        NA  NA  3242 (44.9) 
eGFR 30–44*, n (%)  1358 (35.8)  1413 (41.2)  <0.001  NA    2771 (100)      NA  NA  2771 (38.4) 
eGFR 15–29*, n (%)  453 (11.9)  443 (12.9)  0.197  NA      896 (100)    NA  NA  896 (12.4) 
eGFR <15*, n (%)  –  NA        NA  NA 
HbA1c, %  5.9  7.6  <0.001  NA  6.6  6.6  0.999  6.6  0.999  7.1  0.764  NA  NA  7.0 
Creatinine, mg/dL  1.1  1.2  <0.001  NA  1.0  1.3  0.650  1.6  0.685  2.2  0.178  NA  NA  1.1 
Uric acid, g/dL  5.9  6.9  <0.001  NA  7.0  6.8  0.893  6.3  0.730  7.0  0.999  NA  NA  6.4 
Comorbidities,N(%)
CKD – Chronic  3798 (100)  3426 (100)  –  NA  315 (100)  3242 (100)    2771 (100)    896 (100)    NA  NA  7224 (100) 
Stage 1  –  NA        NA  NA 
Stage 2  177 (4.7)  138 (4.0)  0.146  NA  315 (100)        NA  NA  315 (17.2) 
Stage 3a  1810 (47.7)  1432 (41.8)  <0.001  NA  3242 (100)        NA  NA  3242 (31.8) 
Stage 3b  1358 (35.8)  1413 (41.2)  <0.001  NA    2771 (100)      NA  NA  2771 (27.5) 
Stage 4  453 (11.9)  443 (12.9)  0.197  NA      896 (100)    NA  NA  896 (7.9) 
Stage 5  –  NA        NA  NA 
Not staged  –  NA        NA  NA 
Unspecified  1122 (29.5)  166 (4.8)  <0.001  NA  46 (14.6)  587 (18.1)  0.121  510 (18.4)  0.096  145 (16.2)  0.503  NA  NA  1288 (17.8) 
CKDDiabetic  8 (0.2)  1991 (58.1)  <0.001  NA  98 (31.1)  878 (27.1)  0.129  756 (27.3)  0.153  267 (29.8)  0.665  NA  NA  1999 (27.7) 
CKDHypertensive  2668 (70.2)  1269 (37.0)  <0.001  NA  171 (54.3)  1777 (54.8)  0.865  1505 (54.3)  0.999  484 (54.0)  0.927  NA  NA  3937 (54.5) 
Dialysis  –  NA  –  –  –  NA  NA 
CVD  633 (16.7)  714 (20.8)  0.001  NA  50 (15.9)  621 (19.2)  0.153  527 (19.0)  0.181  149 (16.6)  0.773  NA  NA  1347 (20.5) 
Myocardial infarction  423 (11.1)  524 (15.3)  0.001  NA  38 (12.1)  408 (12.6)  0.798  367 (13.2)  0.583  134 (15.0)  0.205  NA  NA  947 (12.4) 
Heart failure  713 (18.8)  814 (23.8)  <0.001  NA  43 (13.7)  664 (20.5)  0.004  609 (22.0)  0.001  211 (23.5)  <0.001  NA  NA  1527 (21.1) 
Stroke  384 (10.1)  401 (11.7)  0.029  NA  27 (8.6)  322 (9.9)  0.459  342 (12.3)  0.055  94 (10.5)  0.334  NA  NA  785 (11.3) 
Atrial Fibrillation  674 (17.8)  588 (17.2)  0.503  NA  44 (14.0)  560 (17.3)  0.137  500 (18.0)  0.077  158 (17.6)  0.140  NA  NA  1262 (17.0) 
PAD  162 (4.3)  208 (6.1)  0.001  NA  15 (4.8)  169 (5.2)  0.759  136 (4.9)  0.938  50 (5.6)  0.589  NA  NA  370 (6.1) 
Diabetic CKD  8 (0.2)  1991 (58.1)  <0.001  NA  98 (31.1)  878 (27.1)  0.129  756 (27.3)  0.153  267 (29.8)  0.665  NA  NA  1999 (36.9) 
Diabetes  3658 (100)  <0.001  NA  162 (51.4)  1611 (49.7)  0.565  1383 (49.9)  0.614  502 (56.0)  0.158  NA  NA  3658 (50.6) 
Hyperkalemia  153 (4.0)  204 (6.0)  <0.001  NA  15 (4.8)  142 (4.4)  0.742  138 (5.0)  0.877  62 (6.9)  0.189  NA  NA  357 (7.3) 
Gout  1227 (32.3)  1127 (32.9)  0.587  NA  91 (28.9)  1045 (32.2)  0.230  916 (33.1)  0.132  302 (33.7)  0.118  NA  NA  2354 (32.7) 
Medications,n(%)
Antihypertensives  2881 (75.9)  3035 (88.6)  <0.001  NA  240 (76.3)  2577 (79.5)  0.182  2317 (83.6)  0.001  782 (87.3)  <0.001  NA  NA  5916 (81.9) 
RAAS inhibitors  3798 (100)  3426 (100)  –  NA  315 (100)  3242 (100)  –  2771 (100)  –  896 (100)  –  NA  NA  7224 (100) 
ACEi  1607 (42.3)  1394 (40.7)  0.168  NA  101 (32.1)  1199 (37.0)  0.085  1255 (45.3)  <0.001  446 (49.8)  <0.001  NA  NA  3001 (41.5) 
ACEi at maximal doses  220 (5.8)  216 (6.3)  0.373  NA  14 (4.4)  182 (5.6)  0.372  172 (6.2)  0.203  68 (7.6)  0.052  NA  NA  436 (6.0) 
ARBs  2191 (57.7)  2032 (59.3)  0.168  NA  145 (46.0)  1687 (52.0)  0.042  1587 (57.3)  <0.001  804 (89.7)  <0.001  NA  NA  4223 (58.5) 
ARBs at maximal doses  273 (7.2)  271 (7.9)  0.260  NA  17 (5.4)  215 (6.6)  0.409  227 (8.2)  0.081  85 (9.5)  0.024  NA  NA  544 (7.5) 
Aldoster one antagonists  212 (5.6)  281 (8.2)  <0.001  NA  17 (5.4)  192 (5.9)  0.718  200 (7.2)  0.236  84 (9.4)  0.027  NA  NA  493 (6.8) 
Direct renin inhibitors  45 (1.2)  53 (1.6)  0.147  NA  3 (1.0)  40 (1.2)  0.754  41 (1.5)  0.482  14 (1.6)  0.443  NA  NA  98 (1.4) 
ARNI  241 (6.4)  267 (7.8)  0.020  NA  16 (5.1)  201 (6.2)  0.436  209 (7.5)  0.120  82 (9.2)  0.022  NA  NA  508 (7.0) 
Beta blockers  1216 (32.0)  1485 (43.4)  <0.001  NA  91 (28.9)  1139 (35.1)  0.027  1119 (40.4)  <0.001  352 (39.3)  <0.001  NA  NA  2701 (37.4) 
Diuretics  1385 (36.5)  1571 (45.9)  <0.001  NA  94 (29.8)  1167 (36.0)  0.028  1202 (43.4)  <0.001  493 (55.0)  <0.001  NA  NA  2956 (40.9) 
Thiazide diuretics  153 (4.0)  171 (5.0)  0.040  NA  11 (3.5)  125 (3.9)  0.725  124 (4.5)  0.412  64 (7.1)  0.022  NA  NA  324 (4.5) 
Loop diuretics  1237 (32.6)  1400 (40.9)  <0.001  NA  84 (26.7)  1089 (33.6)  0.013  1062 (38.3)  <0.001  402 (44.9)  <0.001  NA  NA  2637 (36.5) 
Potassium sparing diuretics  265 (7.0)  318 (9.3)  <0.001  NA  19 (6.0)  222 (6.9)  0.545  230 (8.3)  0.155  112 (12.5)  0.001  NA  NA  583 (8.1) 
CCB  1064 (28.0)  1292 (37.7)  <0.001  NA  84 (26.7)  909 (28.0)  0.623  994 (35.9)  0.001  369 (41.2)  <0.001  NA  NA  2356 (32.6) 
Dihydropyridines  972 (25.6)  1203 (35.1)  <0.001  NA  74 (23.5)  849 (26.2)  0.297  909 (32.8)  0.001  343 (38.3)  <0.001  NA  NA  2175 (30.1) 
Non-dihydropyridines  134 (3.5)  120 (3.5)  0.999  NA  8 (2.5)  100 (3.1)  0.554  98 (3.5)  0.353  48 (5.4)  0.035  NA  NA  254 (3.5) 
Antidiabetics  106 (2.8)  2846 (83.1)  <0.001  NA  91 (28.9)  1156 (35.7)  0.016  1258 (45.4)  <0.001  447 (49.9)  <0.001  NA  NA  2952 (40.9) 
Metformin  1676 (48.9)  <0.001  NA  45 (14.3)  686 (21.2)  0.004  689 (24.9)  <0.001  256 (28.6)  <0.001  NA  NA  1676 (23.2) 
Sulfonylurea  448 (13.1)  <0.001  NA  12 (3.8)  184 (5.7)  0.159  185 (6.7)  0.005  67 (7.5)  0.022  NA  NA  448 (6.2) 
DPP4 inhibitors  1359 (39.7)  <0.001  NA  51 (16.2)  543 (16.7)  0.820  531 (19.2)  0.197  234 (26.1)  <0.001  NA  NA  1359 (18.8) 
SGLT-2 inhibitors  163 (4.8)  <0.001  NA  6 (1.9)  64 (2.0)  0.904  69 (2.5)  0.513  24 (2.7)  0.433  NA  NA  163 (2.3) 
GLP-1 receptor agonists  127 (3.7)  <0.001  NA  4 (1.3)  55 (1.7)  0.596  49 (1.8)  0.521  19 (2.1)  0.370  NA  NA  127 (1.8) 
Metiglinides  496 (14.5)  <0.001  NA  16 (5.1)  198 (6.1)  0.476  205 (7.4)  0.134  77 (8.6)  0.045  NA  NA  496 (6.9) 
Glitazones  105 (3.1)  <0.001  NA  3 (1.0)  44 (1.4)  0.559  37 (1.3)  0.652  21 (2.3)  0.152  NA  NA  105 (1.5) 
Acarbose  111 (3.2)  <0.001  NA  6 (1.9)  42 (1.3)  0.379  39 (1.4)  0.482  24 (2.7)  0.433  NA  NA  111 (1.5) 
Insulin  106 (2.8)  723 (21.1)  <0.001  NA  28 (8.9)  335 (10.3)  0.433  312 (11.3)  0.198  154 (17.2)  <0.001  NA  NA  829 (11.5) 
Statins  1791 (47.2)  2183 (63.7)  <0.001  NA  118 (37.5)  1694 (52.3)  <0.001  1570 (56.7)  <0.001  592 (66.1)  <0.001  NA  NA  3974 (55.0) 
Warfarin  504 (13.3)  496 (14.5)  0.141  NA  36 (11.4)  386 (11.9)  0.793  422 (15.2)  0.072  156 (17.4)  0.012  NA  NA  1000 (13.8) 
Low dose aspirin  982 (25.9)  969 (28.3)  <0.001  NA  63 (20.0)  806 (24.9)  0.053  801 (28.9)  0.001  281 (31.4)  <0.001  NA  NA  1951 (27.0) 
Receptor P2Y12 antagonists  46 (1.2)  79 (2.3)  <0.001  NA  4 (1.3)  48 (1.5)  0.779  50 (1.8)  0.521  23 (2.6)  0.182  NA  NA  125 (1.7) 

ACEi: angiotensin-converting enzyme inhibitors; ARBs: angiotensin receptor blockers; ARNI: angiotensin receptor and neprilysin inhibition; BMI: body mass index; CCB: Calcium channel blockers; CVD: cardiovascular disease; CKD: chronic kidney disease; DPP4: dipeptidyl peptidase 4; eGFR: estimated glomerular filtration rate; * mL/min/1.73m2; GLP-1: glucagon-like peptide-1; NA: not applicable; PAD: peripheral artery disease; RAAS: renin angiotensin system; SBP: systolic blood pressure; SGLT-2: sodium-glucose Cotransporter-2; UACR: Urine albumin-to-Creatinine Ratio.

In the DAPA-CKD-like population, after 2 years of follow-up, rates of HF, all-cause death, MI, stroke, CKD and PAD were 21.4, 15.3, 8.2, 8.3, 4.2 and 3.2 events per 100 patient-years, respectively. With regard to CKD endpoints, rates of decline of eGFR ≥50% were 4.4 events per 100 patient-years, but no cases of end-stage kidney disease, dialysis, and kidney transplantation were reported. Rates of the combined endpoint of CKD and/or HF were 26.4 events per 100 patient-years. Except for MI, rates of all-cause death, cardiovascular and renal outcomes were significantly higher among patients with T2D, compared to those without T2D. Similarly, rates of all-cause death, cardiovascular and renal outcomes increased as CKD stage worsened. For example, rates of combined endpoint of CKD and/or HF increased from 18.1 events per 100 patient-years in patients with stage 2 CKD to 29.0 events per 100 patient-years among stage 4 CKD patients (Table 5).

Table 5.

Event rates after 2 years of follow-up in the DAPA-CKD population and according to the presence of type 2 diabetes and CKD stage.

  Diabetes statusCKD stage
  Non T2D (n=3798;52.6%)  T2D (n=3426;47.4%)  P  Stage 1 (n=0)  Stage 2 (n=315;4.4%)  Stage 3a (n=3242;44.9%)  P3a vs. 2  Stage 3b (n=2771;38.4%)  P3b vs. 2  Stage 4 (n=896;12.4%)  P4 vs. 2  Stage 5 (n=0)  Unspecified (n=0)  Total (n=7224;100% 
All-cause death
Events  512  530      24  459    417    142        1042 
Events per 100 patient-year  14.1  15.8  <0.001  NA  7.8  14.4  0.001  15.2  <0.001  16.0  <0.001  NA  NA  15.3 
Time to first event, days  411±155  363±148  <0.001    507±201  389±153  <0.001  351±140  <0.001  273±111  <0.001      389±154 
Myocardial infarction
Events  313  251      22  251    218    73        564 
Events per 100 patient-year  8.3  7.4  <0.001  NA  7.1  7.8  0.657  8.1  0.535  8.3  0.500  NA  NA  8.2 
Time to first event, days  288±135  262±129  <0.001    359±181  273±138  <0.001  249±124  <0.001  191±96  <0.001      276±139 
Stroke
Events  241  303      20  210    229    85        544 
Events per 100 patient-year  6.5  9.0  <0.001  NA  6.4  6.6  0.891  8.8  0.220  10.8  0.023  NA  NA  8.3 
Time to first event, days  286±178  221±155  <0.001    385±269  297±210  <0.001  268±187  <0.001  208±141  <0.001      297±208 
Heart failure
Events  750  746      49  616    626    205        1496 
Events per 100 patient-year  19.9  22.0  <0.001  NA  15.6  19.4  <0.001  23.1  0.003  23.1  <0.001  NA  NA  21.4 
Time to first event, days  293±161  249±137  <0.001    306±168  235±128  <0.001  213±117  <0.001  164±91  <0.001      265±128 
CKD
Events  127  139      113    105    40        266 
Events per 100 patient-year  3.4  4.2  <0.001  NA  2.6  3.6  0.357  3.9  0.251  4.7  <0.001  NA  NA  4.2 
Time to first event, days  362±146  281±178  <0.001    405±196  315±156  <0.001  285±141  <0.001  228±115  <0.001      304±151 
Decline of eGFR ≥50%*
Events  129  142    NA  115    107    41    NA  NA  2710 
Events per 100 patient-year  3.4  4.3  <0.001    2.6  3.6  0.357  4.0  0.220  4.7  0.016      4.4 
ESKD (kidney transplantation or dialysis)
Events  –  NA  –  –  –  NA  NA 
Events per 100 patient–year      –  –  –     
Dialysis
Events               
Events per 100 patient-year  –  NA  –  –  –  NA  NA 
Time to first event, days  –  –      –  –  –  –  –  –  –      – 
Kidney transplantation
Events               
Events per 100 patient-year  –  NA  –  –  –  NA  NA 
Time to first event, days  –  –      –  –  –  –  –  –  –      – 
PAD
Events  86  123      68    92    45        209 
Events per 100 patient-year  2.3  3.6  <0.001  NA  1.3  2.1  0.336  3.3  0.052  5.0  0.004  NA  NA  3.2 
Time to first event, days  331±164  272±137  <0.001    398±196  304±150  <0.001  275±136  <0.001  210±106  <0.001      304±151 
Cardiorenal disease (CKD and/or HF)
Events  865  862      53  717    724    233        1727 
Events per 100 patient-year  24.2  27.3  <0.001  NA  18.1  23.2  <0.001  28.6  0.001  29.0  <0.001  NA  NA  26.4 
Time to first event, days  322±193  264±159  <0.001    385±230  295±178  <0.001  268±160  <0.001  206±124  <0.001      296±177 
*

From baseline to the lowest available during follow up; CKD: chronic kidney disease; eGFR: estimated glomerular filtration rate; ESKD: end stage kidney disease; HF: heart failure; PAD: peripheral artery disease.

Discussion

In our study, the prevalence of CKD was nearly 5% with an older population than in previous studies. Comorbidities such as HF and T2D were common, meaning that these greatly increase the risk of having CKD. In the last years, a number of studies have analyzed the prevalence of CKD worldwide. For instance, a study that estimated CKD prevalence in the European adult general population showed considerable differences between countries, from 3% to 17%, when considering CKD stages 1–5 and from 1% to 6%, when considering CKD stages 3–5. It is important to emphasize that the CKD prevalence stratified by diabetes, hypertension, and obesity status followed the same pattern as the overall prevalence.2 As a result, to understand differences in CKD prevalence between countries, not only age, but also the distribution of risk factors should be considered. In Spain, the Hortega study was a cross-sectional study that collected data from 1997 to 2000 and showed that the prevalence of stage 2 CKD affected at least one third of the general population whereas stage 3 CKD ranged from 3% to almost 9% of individuals.12 The EPIRCE study was an epidemiologic, general population-based, cross-sectional study that included a randomly selected Spanish sample aged 20 years or older from January 2004 to January 2008. In this study, the overall prevalence of CKD stages 3–5 was 6.8%, but when the UACR was added to the diagnostic criteria, the prevalence rose to 9.2%.13 A more recent study performed in 11,505 individuals representative of the Spanish adult population and recruited from June 2008 to October 2010, showed a prevalence of CKD of 15%. The prevalence of CKD increased with age, and the presence of previous cardiovascular disease of cardiovascular risk factors.14 On the other hand, underdiagnosis is a commonly observed issue in the early detection of CKD, as shown in a cross-sectional study performed in the Basic Health Area of Balaguer (Lleida), in which an initial prevalence of 3.98% was increased up to 6.00% after performing a review of CKD diagnostic criteria, denoting the existence of diagnostic and coding errors.4

Our data were provided by BIG-PAC®. This electronic database has been validated as an information source for studies of epidemiology, therapeutic adaptation and health/non-healthcare resource use and it has been demonstrated its representativeness of the Spanish population.15,18 As a result, our data suggest that the prevalence of CKD could have changed in the last years in Spain. However, there are many reasons that may explain these differences beyond a real change in the CKD prevalence. Among these reasons, differences in the methodology of the studies, not only for the inclusion of patients (i.e. population based study vs. database studies), but also in the way CKD prevalence was determined (i.e. the use of one-off testing for assessment of eGFR or albuminuria to define the prevalence of CKD, the use of CKD-EPI equation vs. other formula, population based study [i.e. EPIRCE] vs. database-based study, etc.) could have played a role.12–14,19–21 Moreover, in our study, due to its retrospective design, some relevant data (i.e. albuminuria) could not be documented in all patients, leading to an underdiagnosis of CKD. In fact, previous studies have also shown an underdiagnosis of CKD of database studies compared to population based studies.4 On the other hand, it is likely that the higher use of CKD prevention treatments have had some impact on changes in CKD prevalence.1 In the EPIRCE study, 11% of patients had diabetes and 5% ischemic heart disease.13 In the work of Gorostidi et al., 17% had diabetes and 6% previous cardiovascular disease.14 In our study, approximately half of patients had T2D, 21% a history of HF, and 14% prior MI. Around 70% of patients were taking renin-angiotensin system inhibitors and this proportion increased as renal function worsened. Different guidelines recommend the use of renin-angiotensin system inhibitors for the prevention or delay of cardiovascular and renal diseases.22–24 Despite the high use of renin angiotensin system inhibitors, only 4% of patients were taking them at maximal doses. It is likely that the risk of hyperkalemia, particularly in those patients with advanced CKD could have played a role.25 However, it is important to mention that different studies have shown that the use of higher-dose compared with lower-dose angiotensin receptor blockers or the use of neprilysin inhibitors may be associated with better cardiovascular and renal outcomes.18,26–28 In addition, it has been reported that the use of guidelines recommended drugs is associated not only with a reduction of morbidity and mortality, but also with a reduction of healthcare costs.18

There is a clear relationship between CKD and HF.24 Fortunately, a number of clinical trials have shown in the last years that among patients with T2D, SGLT-2 inhibitors are associated with a reduction in the risk of major adverse cardiovascular events, and particularly with a decrease in the risk for HF hospitalization and kidney outcomes.29 In DECLARE-TIMI 58 trial, dapagliflozin prevented and reduced progression of kidney disease among T2D patients at high risk for cardiovascular events, in both, patients with normal or impaired renal function.30 In our study, only 3.5% of patients with T2D were taking SGLT-2 inhibitors. As a result, it is very likely that a higher prescription of guidelines recommended drugs would translate into a higher reduction in CKD prevalence. Likewise, the DAPA-CKD trial,10 aimed to assess the long-term efficacy and safety of the SGLT2 inhibitor dapagliflozin in patients with CKD, with or without T2D, was prematurely interrupted due to the beneficial effects on renal outcomes and the composite of death from cardiovascular causes or hospitalization for HF. In the CREDENCE (Canagliflozin and Renal Events in Diabetes with Established Nephropathy Clinical Evaluation) trial,11 canagliflozin reduced the risk of kidney failure and cardiovascular events in patients with T2D and CKD. Therefore, a higher use of SGLT2 inhibitors with proven efficacy among CKD population, regardless the presence of T2D, could delay the progression of renal disease and may reduce the incidence of CKD complications. In our study, cardiovascular outcomes were more common in the DAPA-CKD like subpopulation than in the general CKD population, suggesting that these patients would benefit more from this treatment.

Individuals with CKD are at increased risk of all-cause and cardiovascular premature death, and may progress to end-stage renal disease. In addition, CKD translates into increased health system costs.31–33 In our study, after 2 years of follow-up, rates of cardiovascular and renal outcomes were high, reaching nearly 21 events per 100 patient-years in the combined endpoint of CKD and/or HF. Moreover, during the study period, 44% of patients were hospitalized, 16% were hospitalized due to heart failure, and around 7% of patients died during hospitalization. Furthermore, rates of mortality, cardiovascular, particularly HF, and renal outcomes were significantly higher in the subgroup of patients with T2D. Therefore, it is necessary to implement a comprehensive management to prevent or delay the development of CKD (primary prevention) and its complications (secondary prevention), including end-stage renal disease that implies not only improving cardiovascular risk factors control, but also the use of guidelines recommended drugs, such as renin-angiotensin system blockers and SLGT-2 inhibitors.7–11,22 Unfortunately, our data showed that there is much room for improvement and more efforts are required to enhance the therapeutic approach of these patients.

Limitations

This was an observational retrospective cohort study that used secondary data from electronic health records. Therefore, only indirect causality may be suggested. Moreover, due to the retrospective design of the study, some relevant data (i.e. albuminuria) could not be documented in all patients, leading to an underdiagnosis of CKD. On the contrary, time of evolution of CKD was not recorded and this could lead to an overdiagnosis of CKD in some individuals, as the definition of CKD requires at least 3 months of functional or structural renal impairment.7 However, although all these limitations could interfere with the prevalence of CKD, the high number of patients included, as well as the robustness of the data may allow to determine the value of the study. On the other hand, although data came from 7 Spanish regions, previous studies have shown that these data are representative of the Spanish population.15

Conclusions

Our data show that CKD in Spain is a relevant clinical condition with poor prognosis and suboptimal treatment. Population was older and comorbidities such as T2D and HF were common. Nearly 30% of patients with CKD are not taking renin angiotensin system blockers, and only 4% at maximal doses. Less than 4% of T2D patients are being treated with SGLT-2 inhibitors. Cardiovascular and renal outcomes are frequent, and markedly increase with the presence of T2D and with renal function decline. As the use of guidelines recommended treatments prevents or delays cardiovascular and renal progression, improving CKD management, particularly through the use of drugs with proven cardiovascular and renal benefit, is mandatory.

Funding

This study was funded by AstraZeneca, Spain. The funding body played no role in the design, data collection, analysis, interpretation of or in writing the manuscript.

Conflict of interests

The authors declare that they have no conflict of interest.

Appendix A
Supplementary data

The following are the supplementary data to this article:

References
[1]
GBD, Chronic Kidney Disease Collaboration.
Global, regional, and national burden of chronic kidney disease, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017.
[2]
K. Brück, V.S. Stel, G. Gambaro, S. Hallan, H. Völzke, J. Ärnlöv, European CKD Burden Consortium, et al.
CKD prevalence varies across the European general population.
J Am Soc Nephrol, 27 (2016), pp. 2135-2147
[3]
A.C. Webster, E.V. Nagler, R.L. Morton, P. Masson.
Chronic kidney disease.
Lancet, 389 (2017), pp. 1238-1252
[4]
C. García Serrano, L. Aran Solé, A. Vilela Pájaro, G. Amat Camats, S. Ortiz Congost, M. Giralt Peiró.
Underdiagnosis identification of chronic kidney disease in primary care.
Enferm Nefrol, 22 (2019), pp. 302-307
[5]
Global, regional, and national age–sex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.
[6]
V. Jha, G. Garcia-Garcia, K. Iseki, Z. Li, S. Naicker, B. Plattner, et al.
Chronic kidney disease: global dimension and perspectives.
[7]
Kidney Disease, Improving Global Outcomes (KDIGO), CKD Work Group.
KDIGO 2012 clinical practice guideline for the evaluation, management of chronic kidney disease.
Kidney Int Suppl, 3 (2013), pp. 1-150
[8]
P. Ruggenenti, A. Perna, G. Gherardi, G. Garini, C. Zoccali, M. Salvadori, et al.
Renoprotective properties of ACE-inhibition in non-diabetic nephropathies with non-nephrotic proteinuria.
[9]
E.J. Lewis, L.G. Hunsicker, W.R. Clarke, T. Berl, M.A. Pohl, J.B. Lewis, et al.
Renoprotective effect of the angiotensin- receptor antagonist irbesartan in patients with nephropathy due to type 2 diabetes.
N Engl J Med, 345 (2001), pp. 851-860
[10]
H.J.L. Heerspink, B.V. Stefánsson, R. Correa-Rotter, G.M. Chertow, T. Greene, F.F. Hou, DAPA-CKD Trial Committees and Investigators, et al.
Dapagliflozin in patients with chronic kidney disease.
N Engl J Med, 383 (2020), pp. 1436-1446
[11]
V. Perkovic, M.J. Jardine, B. Neal, S. Bompoint, H.J.L. Heerspink, D.M. Charytan, CREDENCE Trial Investigators, et al.
Canagliflozin and renal outcomes in type 2 diabetes and nephropathy.
N Engl J Med, 380 (2019), pp. 2295-2306
[12]
F. Simal, J.C. Martín Escudero, J. Bellido, D. Arzua, F.J. Mena, I. González Melgosa, et al.
Prevalence of mild to moderate chronic kidney disease in the general population of Spain. Hortega study.
Nefrologia, 24 (2004), pp. 336-337
[13]
A. Otero, A. de Francisco, P. Gayoso, F. García, EPIRCE Study Group.
Prevalence of chronic renal disease in Spain: results of the EPIRCE study.
[14]
M. Gorostidi, M. Sánchez-Martínez, L.M. Ruilope, A. Graciani, J.J. de la Cruz, R. Santamaría, et al.
Chronic kidney disease in Spain: prevalence and impact of accumulation of cardiovascular risk factors.
Nefrologia, 38 (2018), pp. 606-615
[15]
A. Sicras-Mainar, A. Sicras-Navarro, B. Palacios, L. Varela, J.F. Delgado.
Epidemiology and treatment of heart failure in Spain: the HF-PATHWAYS study.
[16]
KDIGO.
Chapter 1: Definition and classification of CKD.
Kidney Int Suppl (2011), 3 (2013), pp. 19-62
[17]
The Anatomical Therapeutic Chemical Classification System with Defined Daily Doses (ATC/DDD): World Health Organization. Available from: https://www.who.int/classifications-/atcddd/en/ [accessed 10.06.20].
[18]
C. Escobar, L. Varela, B. Palacios, M. Capel, A. Sicras, A. Sicras, et al.
Costs and healthcare utilisation of patients with heart failure in Spain.
BMC Health Serv Res, 20 (2020), pp. 964
[19]
V.S. Stel, K. Brück, S. Fraser, C. Zoccali, Z.A. Massy, K.J. Jager.
International differences in chronic kidney disease prevalence: a key public health and epidemiologic research issue.
Nephrol Dial Transplant, 32 (2017), pp. ii129-ii135
[20]
K. Brück, K.J. Jager, E. Dounousi, A. Kainz, D. Nitsch, J. Ärnlöv, European CKD Burden Consortium, et al.
Methodology used in studies reporting chronic kidney disease prevalence: a systematic literature review.
Nephrol Dial Transplant, 30 (2015),
[21]
R.J. Glassock, D.G. Warnock, P. Delanaye.
The global burden of chronic kidney disease: estimates, variability and pitfalls.
Nat Rev Nephrol, 13 (2017), pp. 104-114
[22]
I.H. de Boer, M.L. Caramori, J.C.N. Chan, H.J.L. Heerspink, C. Hurst, K. Khunti, et al.
Executive summary of the 2020 KDIGO Diabetes Management in CKD Guideline: evidence-based advances in monitoring and treatment.
Kidney Int, 98 (2020), pp. 839-848
[23]
J. Knuuti, W. Wijns, A. Saraste, D. Capodanno, E. Barbato, C. Funck-Brentano, ESC Scientific Document Group, et al.
2019 ESC guidelines for the diagnosis and management of chronic coronary syndromes.
Eur Heart J, 41 (2020), pp. 407-477
[24]
P. Ponikowski, A.A. Voors, S.D. Anker, H. Bueno, J.G. Cleland, A.J. Coats, et al.
Authors/Task Force Members; Document Reviewers. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution of the Heart Failure Association (HFA) of the ESC.
Eur J Heart Fail, 18 (2016), pp. 891-975
[25]
S. Erraez, M. López-Mesa, P. Gómez-Fernández.
Mineralcorticoid receptor blockers in chronic kidney disease.
Nefrologia, (2020),
[26]
C.L. Blacklock, J.A. Hirst, K.S. Taylor, R.J. Stevens, N.W. Roberts, A.J. Farmer.
Evidence for a dose effect of renin-angiotensin system inhibition on progression of microalbuminuria in Type 2 diabetes: a meta-analysis.
Diabet Med, 28 (2011), pp. 1182-1187
[27]
M. Epstein, N.L. Reaven, S.E. Funk, K.J. McGaughey, N. Oestreicher, J. Knispel.
Evaluation of the treatment gap between clinical guidelines and the utilization of renin-angiotensin-aldosterone system inhibitors.
Am J Manag Care, 21 (2015), pp. S212-S220
[28]
K. Balakumaran, A. Patil, S. Marsh, J. Ingrassia, C.L. Kuo, D.L. Jacoby, et al.
Evaluation of a guideline directed medical therapy titration program in patients with heart failure with reduced ejection fraction.
Int J Cardiol Heart Vasc, 22 (2018), pp. 1-5
[29]
D.K. McGuire, W.J. Shih, F. Cosentino, B. Charbonnel, D.Z.I. Cherney, S. Dagogo-Jack, et al.
Association of SGLT2 inhibitors with cardiovascular and kidney outcomes in patients with type 2 diabetes: a meta-analysis.
JAMA Cardiol, 7 (2020), pp. e204511
[30]
O. Mosenzon, S.D. Wiviott, A. Cahn, A. Rozenberg, I. Yanuv, E.L. Goodrich, et al.
Effects of dapagliflozin on development and progression of kidney disease in patients with type 2 diabetes: an analysis from the DECLARE-TIMI 58 randomised trial.
Lancet Diabetes Endocrinol, 7 (2019), pp. 606-617
[31]
R.T. Gansevoort, R. Correa-Rotter, B.R. Hemmelgarn, T.H. Jafar, H.J. Heerspink, J.F. Mann, et al.
Chronic kidney disease and cardiovascular risk: epidemiology, mechanisms, and prevention.
[32]
J. Coresh, T.C. Turin, K. Matsushita, Y. Sang, S.H. Ballew, L.J. Appel, et al.
Decline in estimated glomerular filtration rate and subsequent risk of end-stage renal disease and mortality.
JAMA, 311 (2014), pp. 2518-2531
[33]
A.N. Karopadi, G. Mason, E. Rettore, C. Ronco.
Cost of peritoneal dialysis and haemodialysis across the world.
Nephrol Dial Transplant, 28 (2013), pp. 2553-2569
Copyright © 2021. Sociedad Española de Nefrología
Idiomas
Nefrología

Suscríbase a la newsletter

Opciones de artículo
Herramientas
Material suplementario
es en

¿Es usted profesional sanitario apto para prescribir o dispensar medicamentos?

Are you a health professional able to prescribe or dispense drugs?