Distribution according to the European Society of Cardiology risk categories and associated risk of all-cause mortality in individuals with type 2 diabetes: A prospective cohort study

doi:10.21203/rs.3.rs-1635977/v1

Background.

Atherosclerotic cardiovascular disease (ASCVD) is the main cause for the excess mortality in type 2 diabetes. In 2019, the European Society of Cardiology (ESC) identified three risk categories, with the very high-risk category including individuals with established ASCVD and/or target organ damage (TOD) and/or ≥ 3 additional ASCVD risk factors. This classification was revised in 2021 manly by excluding the latter group from the very high-risk category. This analysis assessed the distribution according to the two ESC classifications and the associated risk of all-cause mortality in patients with type 2 diabetes from the Renal Insufficiency And Cardiovascular Events Italian Multicentre Study.

Methods.

This observational, prospective study enrolled 15,773 patients in 19 Diabetes Clinics throughout Italy in 2006–2008. Participants were stratified based on the presence of established ASCVD, TOD (renal ± retinal), and ASCVD risk factors at baseline. Vital status was retrieved on 31 October 2015 for 15,656 patients (99.3%).

Results.

Less than 1% of participants fell in the moderate-risk category with both classifications; moreover, approximately one third fell in the high-risk and two thirds in the very high-risk category according to the 2019 classification, whereas the opposite was observed with the 2021 classification. Mortality risk (adjusted hazard ratio [95% confidence interval]) was increased in high-risk (2.805 [0.903–8.719], P = 0.075, and 2.757 [1.311–5.795], P = 0.007) and very high-risk (6.529 [2.105–20.254], P = 0.001, and 6.865 [3.266–14.432], P < 0.0001) versus moderate-risk category according to the 2019 and 2021 classification, respectively. Among patients at very high-risk, risk of death was much lower in those with ≥ 3 additional ASCVD risk factors and almost equal in those with TOD and ASCVD ± TOD, using the 2019 classification, whereas it was much higher in those with ASCVD + TOD and, to a lesser extent, TOD only than in those with ASCVD only, using the 2021 classification.

Conclusions.

Only a few patients with type 2 diabetes fall in the moderate-risk category, suggesting an overestimation of ASCVD risk. Downgrading those with ≥ 3 additional ASCVD risk factors to the high-risk category is consistent with all-cause mortality data. Risk of death is very high in the presence of TOD (namely microangiopathy), possibly due to the association with subclinical ASCVD.

Trial registration.

ClinicalTrials.gov, NCT00715481, 15 July, 2008.

type 2 diabetes

all-cause mortality

atherosclerotic cardiovascular disease

target organ damage

atherosclerotic cardiovascular disease risk factors.

Mortality is approximately twice higher in diabetic than in non-diabetic individuals [1, 2], mainly but not exclusively due to an excess risk of atherosclerotic cardiovascular disease (ASCVD) [3]. However, death rates have consistently decreased over time in people with diabetes [4], mainly due to reduction of ASCVD events such as myocardial infarction and stroke [5]. This is likely related to improved treatment of multiple ASCVD risk factors, including hyperglycaemia, dyslipidaemia, and hypertension [6]. However, the burden from ASCVD remains disproportionately high in diabetic patients, especially in those with type 2 diabetes, thus requiring a systematic estimation of ASCVD risk in order to initiate therapeutic strategies for risk reduction [7].

Among these strategies, two classes of anti-hyperglycaemic drugs, the glucagon-like peptide-1 (GLP-1 receptor agonists and sodium-glucose cotransporter 2 (SGLT-2) inhibitors, have been recently shown to provide cardiorenal protection beyond their glucose-lowering effect in people with type 2 diabetes [8, 9]. Therefore, current guidelines recommend the preferential use of these agents not only in patients with established ASCVD, but also in those at high-risk, though using different definitions of these individuals. In fact, the American Diabetes Association guidelines [10] identifies as high-risk patients those aged ≥ 55 years with coronary, carotid, or lower limb artery stenosis > 50% or left ventricular hypertrophy as well as those with chronic kidney disease (CKD). The 2019 European Society of Cardiology (ESC) guidelines [11] identified three categories according to the 10-year risk of death from ASCVD, i.e., moderate (< 5% risk), high (5–10% risk), and very high (> 10% risk). The highest risk category included patients with established ASCVD, those with severe target organ damage (TOD, including microangiopathy and left ventricular hypertrophy), and those with at least three additional ASCVD risk factors. In 2021, this classification has been revised manly by restricting the definition of very high-risk individuals to patients with ASCVD and/or severe TOD, which included only microvascular disease [12].

The present analysis aimed at assessing the distribution according to the 2019 versus 2021 ESC risk categories and the associated risk of all-cause mortality in the large cohort of individuals with type 2 diabetes from the Renal Insufficiency And Cardiovascular Events (RIACE) Italian Multicentre Study.

Design

The RIACE Italian Multicentre Study is an observational, prospective, cohort study on the impact of estimated glomerular filtration rate (eGFR) on morbidity and mortality in people with type 2 diabetes [13].

Patients

The study population included 15,773 Caucasian patients (after excluding 160 individuals with missing or implausible values), consecutively attending 19 hospital-based, tertiary referral outpatient Diabetes Clinics of the National Health Service throughout Italy in the years 2006–2008. Exclusion criteria were dialysis or renal transplantation.

All-cause mortality

The vital status of study participants on 31 October 2015 was verified by interrogating the Italian Health Card database (http://sistemats1.sanita.finanze.it/wps/portal/), which provides updated and reliable information on all current Italian residents [14].

Baseline measurements

Baseline data were collected using a standardized protocol across participating centres [13].

Participants underwent a structured interview in order to collect the following information: age at the time of the interview, smoking status (never, former, current), known diabetes duration, severe co-morbidities (including chronic obstructive pulmonary disease, chronic liver disease, and cancer), and current glucose-, lipid-, and blood pressure (BP)-lowering treatments.

Body mass index (BMI) was calculated from weight and height, whereas waist circumference was estimated from log-transformed BMI values; BP was measured with a sphygmomanometer with the patients seated with the arm at the heart level.

Haemoglobin A_1c (HbA_1c) was measured by HPLC using DCCT-aligned methods; triglycerides and total and HDL cholesterol were determined in fasting blood samples by colorimetric enzymatic methods. The triglyceride:HDL cholesterol ratio was then calculated by dividing triglyceride for HDL cholesterol levels (both in mg/dl) and LDL cholesterol concentration was estimated using the Friedewald formula.

The presence of diabetic kidney disease (DKD) was assessed by measuring albuminuria and serum creatinine, as previously detailed [13, 15]. Albumin excretion rate was obtained from 24-hour urine collections or calculated from albumin-to-creatinine ratio in early-morning, first-voided urine samples; albumin concentration in urines was measured by immunonephelometry or immunoturbidimetry, in the absence of interfering clinical conditions. Serum (and urine) creatinine was measured by the modified Jaffe method, traceable to IDMS, and eGFR was calculated by the Chronic Kidney Disease Epidemiology Collaboration equation. Patients were then assigned to one of the following DKD phenotypes: no DKD, albuminuria alone (albuminuric DKD with preserved eGFR), reduced eGFR alone (non-albuminuric DKD), or both albuminuria and reduced eGFR (albuminuric DKD with reduced eGFR), as previously reported [16].

The presence of diabetic retinopathy (DR) was assessed in each centre by an expert ophthalmologist by dilated fundoscopy [17]. Patients with mild or moderate non-proliferative DR were classified as having non-advanced DR, whereas those with severe non-proliferative DR, proliferative DR, or maculopathy were grouped into the advanced, sight threatening DR category. DR grade was assigned based on the worse eye.

Previous major acute ASCVD events, including myocardial infarction; stroke; foot ulcer/gangrene/amputation; and coronary, carotid, and lower limb revascularization, were adjudicated based on hospital discharge records by an ad hoc committee in each centre [18].

Statistical analysis

For the purpose of the current analysis, the RIACE participants were classified according to the 2019 or the 2021 ESC risk categories, with minor modifications due to the lack of information on left ventricular hypertrophy and neuropathy, respectively, as illustrated in Additional file 2.

Data are expressed as mean ± SD for continuous variables, and number of cases and percentage for categorical variables. Comparisons among categories were performed by one-way ANOVA for continuous variables and Pearson’s χ² test for categorical variables.

Crude mortality rates were described as events per 1,000 patient-years, with 95% exact Poisson confidence intervals (CIs) and adjusted for age and gender by a Poisson regression model. Kaplan-Meier survival probabilities for all-cause mortality were estimated according to the 2019 or 2021 risk categories and differences were analysed using the log-rank statistic. The hazard ratios (HRs) and their 95% CIs were estimated by Cox proportional hazards regression, using the moderate risk category as reference. These analyses were sequentially adjusted for parameters that were not used for patients’ categorization, i.e., gender and severe comorbidities, including chronic obstructive pulmonary disease, chronic liver disease, and cancer (model 1) or were used only for defining the moderate risk category in the 2021 classification, i.e., glycaemic control (HbA_1c and anti-hyperglycaemic treatment) (model 2). Further adjustments were made for parameters that were used for patients’ categorization, i.e., additional ASCVD risk factors, including age, smoking, diabetes duration, obesity (BMI), dyslipidaemia (triglycerides, total and HDL cholesterol, and lipid-lowering treatment), and hypertension (systolic and diastolic BP, and anti-hypertensive therapy) (model 3), and presence of severe TOD and established ASCVD (model 4).

All p values were two-sided, and a p < 0.05 was considered statistically significant. Statistical analyses were performed using SPSS version 13.0 (SPSS Inc., Chicago, IL, USA).

Valid information on vital status was retrieved for 15,656 participants (99.3% of the cohort). At the time of the census, 3,602 (23.0%) individuals had died; death rate was 31.0 per 1,000 person-years (95% CI 30.0–32.0) over a follow-up of 7.4 ± 2.1 years [2, 16].

Categorization of patients according to the 2019 and 2021 ESC categories and subcategories

The distribution and clinical features of the RIACE participants according to the 2019 and 2021 ESC risk categories and subcategories are shown in Tables 1 and 2, respectively.

Table 1

Baseline clinical features of study participants by 2019 ESC risk categories and subcategories.
Variables	Moderate risk	High risk	Very high risk	P*	TOD	CVD	TOD + ASCVD	P†
N (%)	60 (0.4)	5,612 (35.8)	9,984 (63.8)	NA	4,978 (31.8)	1,386 (8.9)	3,620 (23.1)	NA
Deaths, n (%)	3 (5.0)	710 (12.7)	2,889 (28.9)	< 0.0001	1,072 (21.5)	448 (32.3)	1,369 (37.8)	< 0.0001
Age, years	41.3 ± 7.1	62.6 ± 9.5	69.0 ± 9.9	< 0.0001	68.9 ± 10.3	67.5 ± 9.7	69.7 ± 9.3	< 0.0001
Age > 70 years, n%	0 (0.0)	765 (13.6)	4,740 (47.5)	< 0.0001	2,554 (51.3)	512 (36.9)	1,674 (46.2)	< 0.0001
Gender, n (%)				< 0.0001				< 0.0001
Females	25 (41.7)	2,295 (40.9)	4,434 (44.4)		2,654 (53.3)	607 (43.8)	1,173 (32.4)
Males	35 (58.3)	3,317 (59.1)	5,550 (55.6)		2,324 (46.7)	779 (56.2)	2,447 (67.6)
Smoking, n (%)				< 0.0001				< 0.0001
Never	51 (85.0)	3,523 (62.8)	5,275 (52.8)		2,706 (54.4)	832 (60.0)	1,737 (48.0)
Former	9 (15.0)	1,566 (27.9)	2,832 (28.4)		1,110 (22.3)	344 (24.8)	1,378 (38.1)
Current	0 (0.0)	523 (9.3)	1,877 (18.8)		1,162 (23.3)	210 (15.2)	505 (14.0)
Diabetes duration, years	3.7 ± 2.6	10.7 ± 9.0	14.6 ± 10.5	< 0.0001	12.7 ± 10.1	17.1 ± 10.3	16.4 ± 10.6	< 0.0001
Diabetes duration > 10 years, n (%)	0 (0.0)	2,251 (40.1)	5,620 (56.3)	< 0.0001	2,332 (46.8)	965 (69.6)	2,323 (64.2)	< 0.0001
HbA_1c, %	7.45 ± 1.92	7.34 ± 1.41	7.66 ± 1.54	< 0.0001	7.53 ± 1.48	7.96 ± 1.67	7.73 ± 1.54	< 0.0001
BMI, kg·m^− 2	25.2 ± 2.8	27.2 ± 4.4	30.0 ± 5.3	< 0.0001	31.0 ± 5.4	29.4 ± 5.2	28.8 ± 4.8	< 0.0001
Obesity, n (%)	0 (0.0)	826 (14.7)	4,850 (48.6)	< 0.0001	2,994 (60.1)	553 (39.9)	1,303 (36.0)	< 0.0001
Waist circumference, cm	94.8 ± 5.9	98.9 ± 8.9	104.6 ± 10.6	< 0.0001	106.4 ± 10.8	103.2 ± 10.5	102.5 ± 10.0	< 0.0001
Triglycerides, mmol·l^− 1	1.03 ± 0.58	1.46 ± 0.94	1.64 ± 1.02	< 0.0001	1.64 ± 1.00	1.71 ± 1.11	1.62 ± 1.02	< 0.0001
Total cholesterol, mmol·l^− 1	4.05 ± 0.59	4.75 ± 0.97	4.81 ± 1.00	< 0.0001	4.99 ± 0.95	4.87 ± 1.04	4.53 ± 0.99	< 0.0001
HDL cholesterol, mmol·l^− 1	1.40 ± 0.39	1.33 ± 0.36	1.27 ± 0.35	< 0.0001	1.30 ± 0.35	1.28 ± 0.35	1.23 ± 0.34
TG:HDL ratio	1.87 ± 1.28	2.87 ± 2.47	3.37 ± 2.90	< 0.0001	3.27 ± 2.68	3.51 ± 3.06	3.44 ± 3.12	< 0.0001
Non-HDL cholesterol, mmol·l^− 1	2.65 ± 0.46	3.43 ± 0.93	3.54 ± 0.96	< 0.0001	3.69 ± 0.93	3.59 ± 1.01	3.30 ± 0.94	< 0.0001
LDL cholesterol, mmol·l^− 1	2.18 ± 0.36	2.77 ± 0.84	2.80 ± 0.85	< 0.0001	2.96 ± 0.83	2.81 ± 0.85	2.58 ± 0.83	< 0.0001
Dyslipidemia, n (%)	0 (0.0)	3,893 (69.4)	8,963 (89.8)	< 0.0001	4,699 (94.4)	1,124 (81.1)	3,140 (86.7)	< 0.0001
Systolic BP, mmHg	120.4 ± 11.5	134.1 ± 16.3	140.4 ± 18.5	< 0.0001	141.6 ± 17.8	142.2 ± 19.1	138.0 ± 19.0	< 0.0001
Diastolic BP, mmHg	76.7 ± 9.6	78.4 ± 8.8	79.0 ± 9.7	< 0.0001	80.0 ± 9.6	79.2 ± 10.2	77.5 ± 9.6	< 0.0001
Pulse pressure, mmHg	43.7 ± 8.8	55.7 ± 14.1	61.4 ± 16.2	< 0.0001	61.7 ± 15.8	63.1 ± 16.6	60.5 ± 16.4	< 0.0001
Hypertension, n (%)	0 (0.0)	2,973 (53.0)	9,238 (92.5)	< 0.0001	4,749 (95.4)	1,202 (86.7)	3,287 (90.8)	< 0.0001
Anti-hyperglycemic treatment, n (%)				< 0.0001				< 0.0001
Lifestyle	13 (21.7)	1,052 (18.7)	1,048 (10.5)		697 (14.0)	59 (4.3)	292 (8.1)
Non-insulin	24 (40.0)	3,524 (62.8)	6,071 (60.8)		3,359 (67.5)	674 (48.6)	2,038 (56.3)
Insulin	23 (38.3)	1,036 (18.5)	2,865 (28.7)		922 (18.5)	653 (47.1)	1,290 (35.6)
Lipid-lowering treatment, n (%)	0 (0.0)	1,754 (31.3)	5,484 (54.9)	< 0.0001	2,467 (49.6)	608 (43.9)	2,409 (66.5)	< 0.0001
Anti-hypertensive treatment, n (%)	0 (0.0)	2,569 (45.8)	8,503 (85.2)	< 0.0001	4,260 (85.6)	1,090 (78.6)	3,153 (87.1)	< 0.0001
Anti-platelet treatment, n (%)	3 (5.0)	1,222 (21.8)	5,023 (50.3)	< 0.0001	1,858 (37.3)	590 (42.6)	2,575 (71.1)	< 0.0001
Anti-coagulant treatment, n (%)	0 (0.0)	113 (2.0)	556 (5.6)	< 0.0001	191 (3.8)	48 (3.5)	317 (8.8)	< 0.0001
Albuminuria, mg·day^− 1	10.9 ± 10.8	20.1 ± 32.2	102.0 ± 393.1	< 0.0001	29.9 ± 45.5	302.8 ± 643.8	124.3 ± 491.7	< 0.0001
Serum creatinine, µmol·l^− 1	66.1 ± 15.1	73.3 ± 19.8	85.6 ± 39.8	< 0.0001	76.6 ± 21.8	100.6 ± 71.7	92.3 ± 38.9	< 0.0001
eGFR, ml·min^− 1·1.73m^− 2	108.8 ± 13.8	87.8 ± 17.1	75.8 ± 21.6	< 0.0001	79.6 ± 19.0	71.5 ± 26.4	72.3 ± 22.0	< 0.0001
DKD phenotype, n (%)				< 0.0001				< 0.0001
No DKD	55 (91.7)	4,485 (79.9)	5,444 (54.5)		3,199 (64.3)	475 (34.3)	1,770 (48.9)
Albuminuric DKD with preserved eGFR	5 (8.3)	736 (13.1)	2,225 (22.3)		956 (19.2)	476 (34.3)	793 (21.9)
Nonalbuminuric DKD	0 (0.0)	267 (4.8)	1,209 (12.1)		582 (11.7)	132 (9.5)	495 (13.7)
Albuminuric DKD with reduced eGFR	0 (0.0)	124 (2.2)	1,106 (11.1)		241 (4.8)	303 (21.9)	562 (15.5)
DR, n (%)				0.001				< 0.0001
No DR	59 (98.3)	5,019 (89.4)	7,111 (71.2)		4,323 (86.8)	318 (22.9)	2,470 (68.2)
Non-advanced DR	1 (1.7)	593 (10.6)	1,353 (13.6)		655 (13.2)	78 (5.6)	620 (17.1)
Advanced DR	0 (0.0)	0 (0.0)	1,520 (15.2)		0 (0.0)	990 (71.4)	530 (14.6)
TOD, n (%)	0 (0.0)	0 (0.0)	2,184 (21.9)	< 0.0001	0 (0.0)	1,386 (100.0)	798 (22.0)	< 0.0001
ASCVD, n (%)
Any	0 (0.0)	0 (0.0)	3,620 (36.3)	< 0.0001	0 (0.0)	0 (0.0)	3,620 (100.0)	< 0.0001
Myocardial infarction	0 (0.0)	0 (0.0)	1,742 (17.4)	< 0.0001	0 (0.0)	0 (0.0)	1,742 (48.1)	< 0.0001
Coronary revascularization	0 (0.0)	0 (0.0)	1,579 (15.8)	< 0.0001	0 (0.0)	0 (0.0)	1,579 (43.6)	< 0.0001
Any coronary event	0 (0.0)	0 (0.0)	2,396 (24.0)	< 0.0001	0 (0.0)	0 (0.0)	2,396 (66.2)	< 0.0001
Stroke	0 (0.0)	0 (0.0)	513 (5.1)	< 0.0001	0 (0.0)	0 (0.0)	513 (14.2)	< 0.0001
Carotid revascularization	0 (0.0)	0 (0.0)	856 (8.6)	< 0.0001	0 (0.0)	0 (0.0)	856 (23.6)	< 0.0001
Any carotid event	0 (0.0)	0 (0.0)	1,292 (12.9)	< 0.0001	0 (0.0)	0 (0.0)	1,292 (35.7)	< 0.0001
Ulcer/gangrene/amputation	0 (0.0)	0 (0.0)	556 (5.6)	< 0.0001	0 (0.0)	0 (0.0)	556 (15.4)	< 0.0001
Lower limb revascularization	0 (0.0)	0 (0.0)	450 (4.5)	< 0.0001	0 (0.0)	0 (0.0)	450 (12.4)	< 0.0001
Any peripheral event	0 (0.0)	0 (0.0)	883 (8.8)	< 0.0001	0 (0.0)	0 (0.0)	883 (24.4)	< 0.0001
Comorbidities n (%)
Any	8 (13.3)	933 (16.6)	1,846 (18.5)	0.009	839 (16.9)	237 (17.1)	770 (21.3)	< 0.0001
COPD	1 (1.7)	142 (2.5)	531 (5.3)	< 0.0001	244 (4.9)	70 (5.1)	217 (6.0)	< 0.0001
Chronic liver disease	6 (10.0)	526 (9.4)	829 (8.3)	0.070	331 (6.6)	104 (7.5)	394 (10.9)	< 0.0001
Cancer	3 (5.0)	348 (6.2)	680 (6.8)	0.298	355 (7.1)	85 (6.1)	240 (6.6)	0.345

P value vs moderate-risk for 3-group * and 3-group† comparisons. ESC = European Society of Cardiology; HbA_1c = hemoglobin A_1c; BMI = body mass index; BP = blood pressure; eGFR = estimated glomerular filtration rate; DKD = diabetic kidney disease; DR = diabetic retinopathy; TOD = target organ damage; ASCVD = cardiovascular disease; COPD = chronic obstructive pulmonary disease.

Table 2

Baseline clinical features of study participants by 2021 ESC risk categories and subcategories.
Variables	Moderate risk	High risk	Very high risk	P*	TOD	CVD	TOD + ASCVD	P†
N (%)	126 (0.8)	10,427 (66.6)	5,103 (32.6)	NA	1,483 (9.5)	2,608 (16.7)	1,012 (6.5)	NA
Deaths, n (%)	7 (5.6)	1,639 (15.7)	1,956 (38.3)	< 0.0001	587 (39.6)	779 (29.9)	590 (58.3)	< 0.0001
Age, years	55.6 ± 10.6	65.1 ± 10.3	69.9 ± 9.5	< 0.0001	70.4 ± 10.0	68.7 ± 9.1	72.3 ± 9.4	< 0.0001
Age > 70 years, n%	0 (0.0)	3,088 (29.6)	2,417 (47.4)	< 0.0001	743 (50.1)	1,077 (41.3)	597 (59.0)	< 0.0001
Gender, n (%)				< 0.0001				< 0.0001
Females	39 (31.0)	4,879 (46.8)	1,836 (36.0)		663 (44.7)	830 (31.8)	343 (33.9)
Males	87 (69.0)	5,548 (53.2)	3,267 (64.0)		820 (55.3)	1,778 (68.2)	669 (66.1)
Smoking, n (%)				< 0.0001				< 0.0001
Never	93 (73.8)	6,154 (59.0)	2,602 (51.0)		865 (58.3)	1,242 (47.6)	495 (48.9)
Former	33 (26.2)	2,585 (24.8)	1,789 (35.1)		411 (27.7)	990 (38.0)	388 (38.3)
Current	0 (0.0)	1,688 (16.2)	712 (14.0)		207 (14.0)	376 (14.4)	129 (12.7)
Diabetes duration, years	4.7 ± 2.9	11.7 ± 9.6	16.4 ± 10.6	< 0.0001	16.5 ± 10.7	15.3 ± 10.4	19.2 ± 10.7	< 0.0001
Diabetes duration > 10 years, n (%)	0 (0.0)	4,585 (44.0)	3,286 (64.4)	< 0.0001	963 (64.9)	1,560 (59.8)	763 (75.4)	< 0.0001
HbA_1c, %	6.29 ± 0.64	7.45 ± 1.45	7.77 ± 1.59	< 0.0001	7.87 ± 1.70	7.64 ± 1.46	7.98 ± 1.72	< 0.0001
BMI, kg·m^− 2	25.3 ± 2.8	29.0 ± 5.2	29.0 ± 5.0	< 0.0001	29.4 ± 5.2	28.7 ± 4.8	29.3 ± 5.0	< 0.0001
Obesity, n (%)	0 (0.0)	3,764 (36.1)	1,912 (37.5)	< 0.0001	609 (41.1)	902 (34.6)	401 (39.6)	< 0.0001
Waist circumference, cm	95.2 ± 5.8	102.4 ± 10.5	102.8 ± 10.2	< 0.0001	103.4 ± 10.5	102.2 ± 9.9	103.4 ± 10.3	< 0.0001
Triglycerides, mmol·l^− 1	1.08 ± 0.58	1.53 ± 0.96	1.68 ± 1.06	< 0.0001	1.82 ± 1.12	1.52 ± 0.93	1.88 ± 1.19	< 0.0001
Total cholesterol, mmol·l^− 1	4.01 ± 0.55	4.87 ± 0.96	4.63 ± 1.03	< 0.0001	4.87 ± 1.07	4.51 ± 0.97	4.59 ± 1.05	< 0.0001
HDL cholesterol, mmol·l^− 1	1.39 ± 0.39	1.32 ± 0.35	1.23 ± 0.34	< 0.0001	1.24 ± 0.36	1.25 ± 0.33	1.18 ± 0.35	< 0.0001
Triglycerides:HDL ratio	2.04 ± 1.52	3.01 ± 2.54	3.56 ± 3.15	< 0.0001	3.85 ± 3.23	3.15 ± 2.95	4.18 ± 3.39	< 0.0001
Non-HDL cholesterol, mmol·l^− 1	2.62 ± 0.46	3.55 ± 0.93	3.40 ± 0.98	< 0.0001	3.63 ± 1.03	3.26 ± 0.92	3.42 ± 0.99	< 0.0001
LDL cholesterol, mmol·l^− 1	2.13 ± 0.40	2.86 ± 0.83	2.64 ± 0.85	< 0.0001	2.80 ± 0.88	2.58 ± 0.82	2.58 ± 0.86	< 0.0001
Dyslipidemia, n (%)	0 (0.0)	8,524 (81.7)	4,332 (84.9)	< 0.0001	1,192 (80.4)	2,281 (87.5)	859 (84.9)	< 0.0001
Systolic BP, mmHg	124.7 ± 12.0	137.8 ± 17.4	139.0 ± 19.2	< 0.0001	141.4 ± 19.5	137.1 ± 18.6	140.1 ± 19.8	< 0.0001
Diastolic BP, mmHg	76.9 ± 8.6	79.2 ± 9.2	77.9 ± 9.8	< 0.0001	78.8 ± 10.3	77.7 ± 9.4	76.9 ± 10.0	< 0.0001
Pulse pressure, mmHg	47.9 ± 9.8	58.5 ± 15.2	61.1 ± 16.6	< 0.0001	62.7 ± 17.0	59.4 ± 15.8	63.3 ± 17.4	< 0.0001
Hypertension, n (%)	0 (0.0)	7,577 (72.7)	4,634 (90.8)	< 0.0001	1,347 (90.8)	2,329 (89.3)	958 (94.7)	< 0.0001
Anti-hyperglycemic treatment, n (%)				< 0.0001				< 0.0001
Lifestyle	38 (30.2)	1,682 (16.1)	393 (7.7)		101 (6.8)	235 (9.0)	57 (5.6)
Non-insulin	65 (51.6)	6,742 (64.7)	2,812 (55.1)		774 (52.2)	1,605 (61.5)	433 (42.8)
Insulin	23 (18.3)	2,003 (19.2)	1,898 (37.2)		608 (41.0)	768 (29.4)	522 (51.6)
Lipid-lowering treatment, n (%)	0 (0.0)	4,149 (39.8)	3,089 (60.5)	< 0.0001	680 (45.9)	1,760 (67.5)	649 (64.1)	< 0.0001
Anti-hypertensive treatment, n (%)	0 (0.0)	6,640 (63.7)	4,432 (86.9)	< 0.0001	1,279 (86.2)	2,217 (85.0)	936 (92.5)	< 0.0001
Anti-platelet treatment, n (%)	10 (7.9)	2,999 (28.8)	3,239 (63.5)	< 0.0001	664 (44.8)	1,857 (71.2)	718 (70.9)	< 0.0001
Anti-coagulant treatment, n (%)	0 (0.0)	258 (2.5)	411 (8.1)	< 0.0001	94 (6.3)	188 (7.2)	129 (12.7)	< 0.0001
Albuminuria, mg·day^− 1	10.5 ± 12.1	21.9 ± 35.1	176.8 ± 538.1	< 0.0001	305.1 ± 619.1	27.7 ± 43.5	373.2 ± 880.1	< 0.0001
Serum creatinine, µmol·l^− 1	69.7 ± 16.9	72.1 ± 17.39	9.8 ± 50.1	< 0.0001	118.2 ± 66.9	78.9 ± 18.0	126.9 ± 54.0	< 0.0001
eGFR, ml·min^− 1·1.73m^− 2	96.8 ± 15.8	86.2 ± 16.2	67.7 ± 23.8	< 0.0001	56.6 ± 24.3	80.4 ± 15.9	51.6 ± 21.9	< 0.0001
DKD phenotype, n (%)				< 0.0001				< 0.0001
No DKD	118 (93.7)	8,096 (77.6)	1,770 (34.7)		0 (0.0)	1,770 (67.9)	0 (0.0)
Albuminuric DKD with preserved eGFR	7 (5.6)	1,690 (16.2)	1,269 (24.9)		476 (32.1)	542 (20.8)	251 (24.8)
Nonalbuminuric DKD	1 (0.8)	641 (6.1)	834 (16.3)		339 (22.9)	296 (11.3)	199 (19.7)
Albuminuric DKD with reduced eGFR	0 (0.0)	0 (0.0)	1,230 (24.1)		668 (45.0)	0 (0.0)	562 (55.5)
DR, n (%)				< 0.0001				< 0.0001
No DR	118 (93.7)	8,816 (84.5)	3,255 (63.8)		785 (52.9)	1,984 (76.1)	486 (48.0)
Non-advanced DR	6 (4.8)	1,138 (10.9)	803 (15.7)		183 (12.3)	453 (17.4)	167 (16.5)
Advanced DR	2 (1.6)	473 (4.5)	1,045 (20.5)		515 (34.7)	171 (6.6)	359 (35.5)
TOD, n (%)	0 (0.0)	0 (0.0)	2,495 (48.9)	< 0.0001	1,483 (100.0)	0 (0.0)	1,012 (100.0)	< 0.0001
ASCVD, n (%)
Any	0 (0.0)	0 (0.0)	2,495 (48.9)	< 0.0001	0 (0.0)	2,608 (100.0)	1,012 (100.0)	< 0.0001
Myocardial infarction	0 (0.0)	0 (0.0)	3,620 (70.9)	< 0.0001	0 (0.0)	1,281 (49.1)	461 (45.6)	< 0.0001
Coronary revascularization	0 (0.0)	0 (0.0)	1,742 (34.1)	< 0.0001	0 (0.0)	1,185 (45.4)	394 (38.9)	< 0.0001
Any coronary event	0 (0.0)	0 (0.0)	1,579 (30.9)	< 0.0001	0 (0.0)	1,774 (68.0)	622 (61.5)	< 0.0001
Stroke	0 (0.0)	0 (0.0)	2,396 (47.0)	< 0.0001	0 (0.0)	350 (13.4)	163 (16.1)	< 0.0001
Carotid revascularization	0 (0.0)	0 (0.0)	513 (10.1)	< 0.0001	0 (0.0)	593 (22.7)	263 (26.0)	< 0.0001
Any carotid event	0 (0.0)	0 (0.0)	856 (16.8)	< 0.0001	0 (0.0)	895 (34.3)	397 (39.2)	< 0.0001
Ulcer/gangrene/amputation	0 (0.0)	0 (0.0)	1,292 (25.3)	< 0.0001	0 (0.0)	315 (12.1)	241 (23.8)	< 0.0001
Lower limb revascularization	0 (0.0)	0 (0.0)	556 (10.9)	< 0.0001	0 (0.0)	290 (11.1)	160 (15.8)	< 0.0001
Any peripheral event	0 (0.0)	0 (0.0)	450 (8.8)	< 0.0001	0 (0.0)	554 (21.2)	329 (32.5)	< 0.0001
Comorbidities n (%)
Any	22 (17.5)	1,668 (16.0)	1,097 (21.5)	< 0.0001	327 (22.0)	527 (20.2)	243 (24.0)	< 0.0001
COPD	3 (2.4)	360 (3.5)	311 (6.1)	< 0.0001	94 (6.3)	126 (4.8)	91 (9.0)	< 0.0001
Chronic liver disease	17 (13.5)	811 (7.8)	533 (10.4)	< 0.0001	139 (9.4)	281 (10.8)	113 (11.2)	< 0.0001
Cancer	4 (3.2)	660 (6.3)	367 (7.2)	0.038	127 (8.6)	164 (6.3)	76 (7.5)	0.005

P value vs moderate-risk for 3-group * and 3-group† comparisons. ESC = European Society of Cardiology; HbA_1c = hemoglobin A_1c; BMI = body mass index; BP = blood pressure; eGFR = estimated glomerular filtration rate; DKD = diabetic kidney disease; DR = diabetic retinopathy; TOD = target organ damage; ASCVD = cardiovascular disease; COPD = chronic obstructive pulmonary disease.

Based on the 2019 classification, only 60 patients (0.4%) were assigned to the moderate-risk category, whereas approximately one third fell in the high-risk category and two thirds fell in the very high-risk category. Of the 63.8% participants assigned to the very high-risk category, 31.8% had ≥ 3 additional ASCVD risk factors; 8.9% had TOD, 3.8% with < 3 and 5.1% with ≥ 3 additional ASCVD risk factors; and 23.1% had previous ASCVD event(s), 8.5% with < 3 and 14.6% with ≥ 3 additional ASCVD risk factors, and 18.0% without and 5.1% with TOD.

Based on the 2021 classification, the number of patients assigned to the moderate-risk category increased but remained negligible (126, 0.8%), whereas the proportion of those falling in the high-risk and very high-risk categories was inverted (approximately two thirds and one third, respectively), compared with the 2019 classification. Of the 32.6% participants assigned to the very high-risk category, 9.5% had TOD only, 16.7% had previous ASCVD only and 6.5% had both.

All-cause mortality according to the 2019 ESC risk categories and subcategories

Crude and gender-adjusted mortality rates increased significantly from the moderate-risk to the very high-risk category. When further adjusting for age, no differences were observed among categories and subcategories (Table 3).

Kaplan-Meier estimates (Fig. 1A) and unadjusted HRs (Fig. 1B) showed the same trend, though mortality risk was not significantly different between the moderate-risk and high-risk category. The HRs for mortality were not significantly affected when adjusting for gender, comorbidities and glycaemic control (Fig. 1C-D), but differences disappeared after further adjustment for additional ASCVD risk factors and presence of severe TOD and established ASCVD (not shown).

Within the very high-risk category, death rates (Table 3), Kaplan-Meier estimates (Fig. 2A), and unadjusted (Fig. 2B) and adjusted (Fig. 2C-D) HRs of patients with TOD were almost equal to those of patients with previous ASCVD event(s), the majority of whom had also TOD, and much higher than those of individuals with ≥ 3 additional ASCVD risk factors.

Table 3

Mortality rates by 2019 and 2021 ESC risk categories and subcategories.
	N	Events	Percent events	Events per 1,000 patient-years (95% CI), Unadjusted	P	Events per 1,000 patient-years (95% CI), adjusted by gender	P	Events per 1,000 patient-years (95% CI), adjusted by gender & age		P
ESC risk categories 2019					< 0.0001		< 0.0001		< 0.0001
Moderate	60	3	5.0	6.20 (2.00-19.21)	Ref.	4.42 (1.42–13.79)	Ref.	24.38 (7.80-76.21)		Ref.
High	5,612	710	12.7	16.12 (14.98–17.35)	0.006	11.48 (10.06–13.10)	< 0.0001	9.35 (8.17–10.70)		0.287
Very high	9,984	2,889	28.9	40.36 (38.92–41.86)	< 0.0001	28.99 (25.89–32.45)	< 0.0001	14.46 (12.81–16.33)		0.483
≥ 3 RFs	4,978	1,072	21.5	28.67 (27.01–30.44)	< 0.0001	24.17 (21.48–27.18)	< 0.0001	11.60 (10.22–13.18)		0.312
TOD	1,386	448	32.3	45.49 (41.47–49.90)	< 0.0001	37.90 (32.88–43.70)	< 0.0001	20.92 (18.06–24.23)		0.663
ASCVD	3,620	1,369	37.8	56.25 (53.35–59.31)	< 0.0001	46.28 (40.76–52.54)	< 0.0001	21.49 (18.79–24.58)		0.688
ESC risk categories 2021					< 0.0001		< 0.0001		< 0.0001
Moderate	126	7	5.6	6.87 (3.28–14.40)	Ref.	6.08 (2.87–12.87)	Ref.	7.50 (3.54–15.88)		Ref.
High	10,427	1,639	15.7	20.29 (19.34–21.30)	< 0.0001	18.18 (16.21–20.40)	< 0.0001	11.21 (9.93–12.64)		0.194
Very high	5,103	1,956	38.3	57.00 (54.53–59.58)	< 0.0001	50.67 (44.94–57.13)	< 0.0001	22.47 (19.74–25.57)		< 0.0001
TOD	1,483	587	39.6	58.82 (54.25–63.78)	< 0.0001	51.50 (45.04–58.88)	< 0.0001	22.49 (19.48–25.96)		< 0.0001
ASCVD	2,608	779	29.9	42.17 (39.31–45.24)	< 0.0001	36.55 (31.96–41.81)	< 0.0001	18.15 (15.75–20.91)		< 0.0001
TOD + ASCVD	1,012	590	58.3	100.61 (92-81-109.07)	< 0.0001	87.46 (76.16-100.44)	< 0.0001	34.24 (29.52–39.72)		< 0.0001

ESC = European Society of Cardiology; CI = confidence interval; RFs = risk factors; TOD = target organ damage; ASCVD = cardiovascular disease.

All-cause mortality according to the 2021 ESC risk categories and subcategories

Crude and gender-adjusted mortality rates increased significantly from the moderate-risk to the very high-risk category. When further adjusting for age, no differences were observed between the moderate-risk and high-risk category, whereas differences persisted between the high-risk and very high-risk category (Table 3).

Kaplan-Meier estimates (Fig. 3A) and unadjusted HRs (Fig. 3B) showed the same trend. The HRs for mortality were not significantly affected when adjusting for gender, comorbidities and glycaemic control (Fig. 3C-D). When further adjusting for additional ASCVD risk factors and complications/comorbidities (not shown), mortality risk remained significantly higher only in the very high-risk versus the moderate-risk reference category.

Within the very high-risk category, death rates (Table 3), Kaplan-Meier estimates (Fig. 4A), and unadjusted (Fig. 4B) and adjusted (Fig. 4C-D) HRs were much higher in the subcategories with previous ASCVD event(s) and TOD and, to a lesser extent, TOD only than in the subcategory with previous ASCVD event(s) only. Moreover, when further adjusting for additional ASCVD risk factors and presence of severe TOD and established ASCVD, the HRs for mortality remained significantly higher versus the moderate-risk category only in patients with TOD only or previous ASCVD event(s) and TOD (not shown).

This analysis of patients with type 2 diabetes from the RIACE cohort showed that very few of these individuals fell in the moderate-risk category according to both the 2019 and 2021 ESC classification. Moreover, the proportion of participants in the very high-risk risk category was approximately twice higher than that of participants in the high-risk category according to the 2019 classification, whereas the opposite was found using the 2021 classification, due to the reallocation of patients with at least three additional ASCVD risk factors to the high-risk category. Finally, within the very high-risk category, the mortality risk of individuals with TOD only was almost similar to that of patients with previous ASCVD event(s), with and without TOD, according in the 2019 classification, and higher than that of patients with previous ASCVD event(s) only, according to the 2021 classification.

The distribution of patients with type 2 diabetes according to the 2019 ESC risk categories is consistent with previous reports from diabetes outpatient clinics [19, 20], in which the proportion of individuals at moderate-risk was similar and that of those at very high-risk was even higher than in the RIACE cohort. The reallocation of individuals with at least three additional ASCVD risk factors without TOD or previous ASCVD event(s) to the high-risk category as in the 2021 classification is consistent with our finding that these patients showed a much lower mortality risk than those with TOD and/or previous ASCVD event(s) and closer to those in the high-risk category as in the 2019 classification. The negligible number of patients in the moderate-risk category in both classifications and the assignment of the majority of participants to the very high-risk category in the 2019 classification do not reflect the wide range of ASCVD risk observed in people with type 2 diabetes [21] and are in contrast with the finding that optimal treatment of ASCVD risk factors in these individuals is able to significantly reduce or even eliminate the excess risk of death and ASCVD events compared to non-diabetic controls [22, 23]. This suggests that the ESC stratification systems may overestimate mortality risk in a great number of people with type 2 diabetes. This interpretation is in keeping with a systematic review and network meta-analysis of randomised controlled trials [24] and a clinical practice guideline based on it [25], which stratified adults with type 2 diabetes into five risk categories using the Risk Equations for Complications of Type 2 Diabetes (RECODe) prediction model [26] and assigned those with ≤ 3 and > 3 additional ASCVD risk factors to the very low- and low-risk category, respectively. In both these categories, there was no clear evidence of a positive balance of benefits and harms of GLP-1 receptor agonists and SGLT-2 inhibitors [24], which therefore were not or only weekly recommended in patients with additional ASCVD risk factors but without established ASCVD or CKD [25].

At variance with those of other scientific societies [27, 28], both the 2019 and 2021 ESC guidelines recommend the use of a newly-developed, non-validated risk stratification system based on the presence of ASCVD risk factors, TOD and/or previous ASCVD event(s) instead of one of the ASCVD risk prediction tools that have been developed so far [11, 12], likely due to the numerous limitations of these algorithms, which result in insufficient performance [29]. One limitation is that many of them have been derived from general population samples and not established (or validated) in people with type 2 diabetes. The ESC guidelines do in fact discourage to apply those from the general population to patients with diabetes [11, 12], though comparisons with diabetes-specific algorithms have not univocally shown that the latter ones perform better [29, 30]. Another limitation is the time-period when they were developed, as some of them date back to several years ago and, hence, do not consider the impact of recent therapeutic advances on ASCVD risk. Moreover, most of them focus on specific ASCVD outcomes, especially myocardial infarction and stroke, without considering other ASCVD events, such as heart failure and peripheral artery disease. More importantly, they may not include variables that significantly affect risk, thus not allowing to appropriately classify patients at apparently lower risk such as those without established ASCVD. In fact, many of the most used algorithms, either derived from the general population, such as the Framingham Score [31], the Prospective Cardiovascular Münster Study (PROCAM) Score [32],the Systematic COronary Risk Evaluation: High & Low cardiovascular (SCORE) Risk Charts [33], the Progetto Cuore [34], and the ASCVD Risk Estimator [27], or people with type 2 diabetes, such as the UK Prospective Diabetes Study (UKPDS) Risk Score [35] and the risk equation developed from the Swedish National Diabetes Register [36], do not include measures of TOD. Moreover, the remaining algorithms consider only measure(s) of kidney damage, such as the prediction tool derived from the Hong Kong Diabetes Registry for Coronary Artery Disease (eGFR) [37], the UKPDS model 2 (albuminuria and eGFR) [38], the QRESEARCH Cardiovascular Risk Algorithm (QRISK, CKD stage 3-to-5 in version 3) [39], the EstimatioN oF mORtality risk in type 2 diabetiC patiEnts (ENFORCE), a prediction model for all-cause mortality (albumin:creatinine ratio) [40], and the RECODe, a tool for predicting complications and death (serum creatinine and albumin:creatinine ratio ) [26], which was found to perform better than six of the above algorithms [41]. The results of the present study point to a very high mortality risk associated with severe TOD, which in our analysis was related only to microangiopathy (DKD and DR) for both the 2019 and 2021 classifications, thus supporting the importance of including measures of TOD in the ASCVD risk prediction tools and arguing in favour of the use of the ESC classification system for stratifying patients with type 2 diabetes.

However, other TODs were not considered either in our analysis or in the ESC classification systems. One is peripheral neuropathy, which we could not include in the definition of microvascular disease according to the 2021 ESC guidelines (microalbuminuria plus retinopathy plus neuropathy) [12] because no data were available from the RIACE cohort on this complication. However, though presence of neuropathy is a powerful predictor of all-cause and ASCVD morbidity and mortality, it is generally undiagnosed because procedures are either semi-quantitative and not objective or laborious, time-consuming, and even invasive and, hence, difficult to implement in clinical practice [42]. Another TOD that is not considered in the ESC classifications is non-alcoholic fatty liver disease, which has been shown to independently predict fatal and non-fatal ASCVD events [43]. More importantly, macrovascular disease was not taken into account, as either left ventricular hypertrophy (which was considered in the 2019 classification but not in our analysis because of lack of data) or measures of subclinical atherosclerosis. These measures include (a) coronary, carotid, or lower limb artery stenosis, as assessed by computed tomography angiography or ultrasound, which the ADA guidelines consider an index of high-risk if higher than 50% [10]; (b) functional imaging, i.e., radionuclide myocardial perfusion imaging, stress cardiac magnetic resonance imaging, or exercise or pharmacological stress echocardiography; (c) ankle-brachial index; and (d) coronary artery calcium scoring. All these are considered as risk modifiers, particularly the latter [11], which is recommended for coronary risk assessment in asymptomatic adults at intermediate 10-year risk (10–20%) or low-to-intermediate 10-year risk (6–10%), with calcium score driving reclassification of these individuals to the low-risk or high-risk category [44]. Conversely, the assessment of circulating biomarkers such as C-reactive protein, fibrinogen, or high-sensitivity cardiac troponin T is considered of limited clinical value when added to conventional ASCVD risk factors [45]. The strong, independent association of microangiopathy, especially DKD, with measures of macroangiopathy such as left ventricular hypertrophy [46] and coronary calcification [47] may explain the higher mortality risk observed in patients with TOD only versus those with previous ASCVD event(s) only. It is in fact plausible that, in individuals with TOD due to microangiopathy (DKD and DR), the overall risk of death results from both overt microvascular and subclinical macrovascular disease. Therefore, in patients with type 2 diabetes, the presence of microangiopathy might serve to indicate the need for both noninvasive assessment of subclinical ASCVD and treatment with drugs providing protection from ASCVD and CKD such as GLP-1 receptor agonists and SGLT-2 inhibitors [48].

Strength of our study include the large sample size, the assessment of a wide range of clinical parameters, and the completeness of baseline and follow-up data. In addition, mortality data were not influenced by the use of GLP-1 receptor agonists and SGLT-2 inhibitors, as none these agents were available at the time of enrollment and only a negligible proportion of patients were treated with either one of these agents at the time of the census. However, there are several limitations. First, the lack of information on the causes of death did not allow detecting differences in ASCVD versus non-CVD deaths. Second, results may have been affected by the lack of information on left ventricular hypertrophy and diabetic neuropathy, which were taken into consideration for defining TOD in the 2019 and 2021 classification, respectively [11, 12]. Third, the study findings may not be applicable to the general ambulatory population, as only part of the individuals with type 2 diabetes attend Diabetes Clinics in Italy. Finally, the observational design makes causal interpretation impossible.

Risk stratification of patients with type 2 diabetes from the RIACE cohort showed that only a few of them fell in the moderate-risk category according to both the 2019 and 2021 ESC classifications and that the majority of participants were assigned to the very high-risk category according to 2019 ESC classification, due to the inclusion of those with at least three additional ASCVD risk factors. Reallocating these individuals to the high-risk category as in the 2021 classification was consistent with the observed all-cause mortality data. These findings and the fact that both classifications do not take into account the degree of ASCVD risk factor control suggest that the ESC stratification systems may overestimate mortality risk in patients with type 2 diabetes without TOD and ASCVD. Finally, risk of death was found to be particularly high in the presence TOD (namely microangiopathy), possibly due to the association with subclinical ASCVD.

ASCVD

atherosclerotic cardiovascular disease

ESC

European Society of Cardiology

TOD

target organ damage

GLP-1

glucagon-like peptide-1

SGLT-2

sodium-glucose cotransporter 2

Renal Insufficiency And Cardiovascular Events

eGFR

estimated glomerular filtration rate

BP

blood pressure

BMI

body mass index

HbA_1c

haemoglobin A_1c

DKD

diabetic kidney disease

DR

diabetic retinopathy

Ci

confidence interval

HR

hazard ratio

RECODe

Risk Equations for Complications of Type 2 Diabetes

PROCAM

Prospective Cardiovascular Münster Study

SCORE

Systematic COronary Risk Evaluation: High & Low cardiovascular

UKPDS

UK Prospective Diabetes Study

QRISK

QRESEARCH Cardiovascular Risk Algorithm

ENFORCE

EstimatioN oF mORtality risk in type 2 diabetiC patiEnts.

Ethics approval and consent to participate: The study was conducted in accordance with the Declaration of Helsinki. The research protocol was approved by the ethics committee of the coordinating centre (Sant’Andrea Hospital, Rome, Italy) on 25 September 2006 (number 43/2006) and subsequently by the ethics committee of each participating centre. Participants provided an informed consent.

Consent for publication: Not applicable.

Availability of data and materials: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing interests: EO: consultant fees from Eli Lilly and Novo Nordisk, and lecture fees from Astellas. AS: consultant fees from Axxam, Bayer, and Novo Nordisk, and lecture fees from Eli Lilly, Novo Nordisk, and Sanofi-Aventis. EB: consultant fees from Abbott, Bayer, Becton Dickinson, Boehringer Ingelheim, Daiichi-Sankyo, Eli Lilly, and Novo Nordisk. MVi: lecture fees from MundiPharma and Novo Nordisk. MG: consultant fees from Eli Lilly, and lecture fees from Eli Lilly, Merck Sharp & Dohme, and Novo Nordisk. CF: lecture fees from Abbot, Boehringer Ingelheim, Daiichi Sankyo, Eli Lilly, Merck Sharp & Dohme, Mundipharma, and Theras Lifetech. RT: consultant fees from AstraZeneca, Boehringer Ingelheim, Eli Lilly, Merck Sharp & Dohme, Novo Nordisk, and Sanofi-Aventis, and lecture fees from AstraZeneca, Boehringer Ingelheim, Eli Lilly, and Novo Nordisk. MVe: lecture fees from Lifescan and Novo Nordisk. FC: consultant fees from Boehringer Ingelheim, and lecture fees from AstraZeneca. LL: consultant fees from Abbott, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Medtronic, MOVI, Novo Nordisk, Roche, Sanofi-Aventis, and Terumo, and lecture fees from Abbott, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Medtronic, Menarini, MOVI, MSD, Mundipharma, Novo Nordisk, Roche, Sanofi-Aventis, and Terumo. SM: none. GPu: consultant fees from Abbot, Bayer, and Novo Nordisk, and lecture fees from AstraZeneca, Boehringer Ingelheim, Eli Lilly, and Novo Nordisk.

Funding: This research was supported by the Research Foundation of the Italian Diabetes Society (Diabete Ricerca) and the Diabetes, Endocrinology and Metabolism (DEM) Foundation, and by unconditional grants from Eli-Lilly, Sigma-Tau, Takeda, Chiesi Farmaceutici, and Boehringer-Ingelheim. The funding sources had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

Authors' contributions: EO, AS, and GPu conceived and designed the study. All authors contributed to data acquisition, analysis, or interpretation. EO and GPu drafted the article and had full access to all the data and took responsibility for the integrity of data and accuracy of the data analysis in this study. AS, EB, MVi, MG, CF, RT, MVe, FC, LL, and SM revised the manuscript critically for essential intellectual content. All authors approved the submitted version of the manuscript and agreed to be personally accountable for the individual’s own contributions and to ensure that questions pertaining to the accuracy or integrity of any portion of the work are appropriately investigated and resolved.

Acknowledgments: The Authors thank the RIACE Investigators for participating in this study (see the complete list in the Additional file 1: The RIACE Study Group).

Tancredi M, Rosengren A, Svensson AM, Kosiborod M, Pivodic A, Gudbjörnsdottir S, et al. Excess Mortality among Persons with Type 2 Diabetes. N Engl J Med. 2015;373:1720–1732.
Penno G, Solini A, Bonora E, Orsi E, Fondelli C, Zerbini G, Trevisan R, et al. Defining the contribution of chronic kidney disease to all-cause mortality in patients with type 2 diabetes: the Renal Insufficiency And Cardiovascular Events (RIACE) Italian Multicenter Study. Acta Diabetol. 2018;55:603–612.
Rao Kondapally Seshasai S, Kaptoge S, Thompson A, Di Angelantonio E, Gao P, Sarwar N, et al. Diabetes mellitus, fasting glucose, and risk of cause-specific death. N Engl J Med. 2011;364:829–841.
Gregg EW, Cheng YJ, Saydah S, Cowie C, Garfield S, Geiss L, et al. Trends in death rates among U.S. adults with and without diabetes between 1997 and 2006: findings from the National Health Interview Survey. Diabetes Care. 2012;35:1252–1257.
Gregg EW, Li Y, Wang J, Burrows NR, Ali MK, Rolka D, et al. Changes in diabetes-related complications in the United States, 1990–2010. N Engl J Med. 2014;370:1514–1523.
Afkarian M, Zelnick LR, Hall YN, Heagerty PJ, Tuttle K, Weiss NS, et al. Clinical Manifestations of Kidney Disease Among US Adults With Diabetes, 1988–2014. JAMA. 2016;316:602–610.
Einarson TR, Acs A, Ludwig C, Panton UH. Prevalence of cardiovascular disease in type 2 diabetes: a systematic literature review of scientific evidence from across the world in 2007–2017. Cardiovasc Diabetol. 2018;17:83.
Sattar N, Lee MMY, Kristensen SL, Branch KRH, Del Prato S, Khurmi NS, et al. Cardiovascular, mortality, and kidney outcomes with GLP-1 receptor agonists in patients with type 2 diabetes: a systematic review and meta-analysis of randomised trials. Lancet Diabetes Endocrinol. 2021;9:653–662.
McGuire DK, Shih WJ, Cosentino F, Charbonnel B, Cherney DZI, Dagogo-Jack S, et al. Association of SGLT2 Inhibitors With Cardiovascular and Kidney Outcomes in Patients With Type 2 Diabetes: A Meta-analysis. JAMA Cardiol. 2021;6:148–158.
American Diabetes Association Professional Practice Committee; Draznin B, Aroda VR, Bakris G, Benson G, Brown FM, et al. 9. Pharmacologic Approaches to Glycemic Treatment: Standards of Medical Care in Diabetes-2022. Diabetes Care. 2022;45(Supplement_1):S125-S143.
Cosentino F, Grant PJ, Aboyans V, Bailey CJ, Ceriello A, Delgado V, et al. 2019 ESC Guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD. Eur Heart J. 2020;41:255–323.
Visseren FLJ, Mach F, Smulders YM, Carballo D, Koskinas KC, Bäck M, et al. 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice. Eur Heart J. 2021;42:3227–3337.
Penno G, Solini A, Bonora E, Fondelli C, Orsi E, Zerbini G, et al. Clinical significance of nonalbuminuric renal impairment in type 2 diabetes. J Hypertens. 2011;29:1802–1809.
Orsi E, Solini A, Bonora E, Fondelli C, Trevisan R, Vedovato M, et al. Haemoglobin A1c variability is a strong, independent predictor of all-cause mortality in patients with type 2 diabetes. Diabetes Obes Metab. 2018;20:1885–1893.
Pugliese G, Solini A, Fondelli C, Trevisan R, Vedovato M, Nicolucci A, et al. Reproducibility of albuminuria in type 2 diabetic subjects. Findings from the Renal Insufficiency And Cardiovascular Events (RIACE) study. Nephrol Dial Transplant. 2011;26:3950–3954.
Penno G, Solini A, Orsi E, Bonora E, Fondelli C, Trevisan R, et al. Non-albuminuric renal impairment is a strong predictor of mortality in individuals with type 2 diabetes: the Renal Insufficiency And Cardiovascular Events (RIACE) Italian multicentre study. Diabetologia. 2018;61:2277–2289.
Penno G, Solini A, Zoppini G, Orsi E, Zerbini G, Trevisan R, et al. Rate and determinants of association between advanced retinopathy and chronic kidney disease in patients with type 2 diabetes: the Renal Insufficiency And Cardiovascular Events (RIACE) Italian multicenter study. Diabetes Care. 2012;35:2317–2323.
Solini A, Penno G, Bonora E, Fondelli C, Orsi E, Arosio M, et al. Diverging association of reduced glomerular filtration rate and albuminuria with coronary and noncoronary events in patients with type 2 diabetes: the renal insufficiency and cardiovascular events (RIACE) Italian multicenter study. Diabetes Care. 2012;35:143–149.
Pintaudi B, Scatena A, Piscitelli G, Frison V, Corrao S, Manicardi V, et al. Clinical profiles and quality of care of subjects with type 2 diabetes according to their cardiovascular risk: an observational, retrospective study. Cardiovasc Diabetol. 2021;20:59.
Prausmüller S, Resl M, Arfsten H, Spinka G, Wurm R, Neuhold S, et al. Performance of the recommended ESC/EASD cardiovascular risk stratification model in comparison to SCORE and NT-proBNP as a single biomarker for risk prediction in type 2 diabetes mellitus. Cardiovasc Diabetol. 2021;20:34.
Bertoluci MC, Rocha VZ. Cardiovascular risk assessment in patients with diabetes. Diabetol Metab Syndr. 2017;9:25.
Rawshani A, Rawshani A, Franzén S, Sattar N, Eliasson B, Svensson AM, et al. Risk Factors, Mortality, and Cardiovascular Outcomes in Patients with Type 2 Diabetes. N Engl J Med. 2018;379:633–644.
Wright AK, Suarez-Ortegon MF, Read SH, Kontopantelis E, Buchan I, Emsley R, et al. Risk Factor Control and Cardiovascular Event Risk in People With Type 2 Diabetes in Primary and Secondary Prevention Settings. Circulation. 2020;142:1925–1936.
Palmer SC, Tendal B, Mustafa RA, Vandvik PO, Li S, Hao Q, et al. Sodium-glucose cotransporter protein-2 (SGLT-2) inhibitors and glucagon-like peptide-1 (GLP-1) receptor agonists for type 2 diabetes: systematic review and network meta-analysis of randomised controlled trials. BMJ. 2021;372:m4573.
Li S, Vandvik PO, Lytvyn L, Guyatt GH, Palmer SC, Rodriguez-Gutierrez R, et al. SGLT-2 inhibitors or GLP-1 receptor agonists for adults with type 2 diabetes: a clinical practice guideline. BMJ. 2021;373:n1091.
Basu S, Sussman JB, Berkowitz SA, Hayward RA, Yudkin JS. Development and validation of Risk Equations for Complications Of type 2 Diabetes (RECODe) using individual participant data from randomised trials. Lancet Diabetes Endocrinol. 2017;5:788–798.
Goff DC Jr, Lloyd-Jones DM, Bennett G, Coady S, D'Agostino RB Sr, Gibbons R, et al. 2013 ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2014;63:2935–2959.
The National Institute for Health and Care Excellence. Type 2 diabetes in adults: management. 2 December 2015. https://www.nice.org.uk/guidance/ng28, last accessed 3 March 2022.
Dziopa K, Asselbergs FW, Gratton J, Chaturvedi N, Schmidt AF. Cardiovascular risk prediction in type 2 diabetes: a comparison of 22 risk scores in primary care settings. Diabetologia. 2022;65:644–656.
Echouffo-Tcheugui JB, Kengne AP. Comparative performance of diabetes-specific and general population-based cardiovascular risk assessment models in people with diabetes mellitus. Diabetes Metab. 2013;39:389–396.
Wilson PW, D'Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;97:1837–1847.
Assmann G, Cullen P, Schulte H. Simple scoring scheme for calculating the risk of acute coronary events based on the 10-year follow-up of the prospective cardiovascular Münster (PROCAM) study. Circulation. 2002;105:310–315.
Conroy RM, Pyörälä K, Fitzgerald AP, Sans S, Menotti A, De Backer G, et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J. 2003;24:987–1003.
Ferrario M, Chiodini P, Chambless LE, Cesana G, Vanuzzo D, Panico S, et al. Prediction of coronary events in a low incidence population. Assessing accuracy of the CUORE Cohort Study prediction equation. Int J Epidemiol. 2005;34:413–421.
Stevens RJ, Kothari V, Adler AI, Stratton IM; United Kingdom Prospective Diabetes Study (UKPDS) Group. The UKPDS risk engine: a model for the risk of coronary heart disease in Type II diabetes (UKPDS 56). Clin Sci (Lond). 2001;101:671–679.
Cederholm J, Eeg-Olofsson K, Eliasson B, Zethelius B, Nilsson PM, Gudbjörnsdottir S, et al. Risk prediction of cardiovascular disease in type 2 diabetes: a risk equation from the Swedish National Diabetes Register. Diabetes Care. 2008;31:2038–2043.
Hong Kong Diabetes Registry, Yang X, So WY, Tong PC, Ma RC, Kong AP, et al. Development and validation of an all-cause mortality risk score in type 2 diabetes. Arch Intern Med. 2008;168:451–457.
Hayes AJ, Leal J, Gray AM, Holman RR, Clarke PM. UKPDS outcomes model 2: a new version of a model to simulate lifetime health outcomes of patients with type 2 diabetes mellitus using data from the 30 year United Kingdom Prospective Diabetes Study: UKPDS 82. Diabetologia. 2013;56:1925–1933.
Hippisley-Cox J, Coupland C, Brindle P. Development and validation of QRISK3 risk prediction algorithms to estimate future risk of cardiovascular disease: prospective cohort study. BMJ. 2017;357:j2099.
De Cosmo S, Copetti M, Lamacchia O, Fontana A, Massa M, Morini E, et al. Development and validation of a predicting model of all-cause mortality in patients with type 2 diabetes. Diabetes Care. 2013;36:2830–2835.
Buchan TA, Malik A, Chan C, Chambers J, Suk Y, Zhu JW, et al. Predictive models for cardiovascular and kidney outcomes in patients with type 2 diabetes: systematic review and meta-analyses. Heart. 2021;107:1962–1973.
Ziegler D, Tesfaye S, Spallone V, Gurieva I, Al Kaabi J, Mankovsky B, et al. Screening, diagnosis and management of diabetic sensorimotor polyneuropathy in clinical practice: International expert consensus recommendations. Diabetes Res Clin Pract. 2021 Sep 20:109063.
Mantovani A, Csermely A, Petracca G, Beatrice G, Corey KE, Simon TG, et al. Non-alcoholic fatty liver disease and risk of fatal and non-fatal cardiovascular events: an updated systematic review and meta-analysis. Lancet Gastroenterol Hepatol. 2021;6:903–913.
Greenland P, Alpert JS, Beller GA, Benjamin EJ, Budoff MJ, Fayad ZA, et al. 2010 ACCF/AHA guideline for assessment of cardiovascular risk in asymptomatic adults: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2010;56:e50-e103.
Piepoli MF, Hoes AW, Agewall S, Albus C, Brotons C, Catapano AL, et al. 2016 European Guidelines on cardiovascular disease prevention in clinical practice: The Sixth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of 10 societies and by invited experts) Developed with the special contribution of the European Association for Cardiovascular Prevention & Rehabilitation (EACPR). Eur Heart J. 2016;37:2315–2381.
Middleton RJ, Parfrey PS, Foley RN. Left ventricular hypertrophy in the renal patient. J Am Soc Nephrol. 2001;12:1079–1084.
Budoff MJ, Rader DJ, Reilly MP, Mohler ER 3rd, Lash J, Yang W, et al. Relationship of estimated GFR and coronary artery calcification in the CRIC (Chronic Renal Insufficiency Cohort) Study. Am J Kidney Dis. 2011;58:519–526.
Rangaswami J, Bhalla V, de Boer IH, Staruschenko A, Sharp JA, Singh RR, et al. Cardiorenal Protection With the Newer Antidiabetic Agents in Patients With Diabetes and Chronic Kidney Disease: A Scientific Statement From the American Heart Association. Circulation. 2020;142:e265-e286.

Competing interest reported. EO: consultant fees from Eli Lilly and Novo Nordisk, and lecture fees from Astellas. AS: consultant fees from Axxam, Bayer, and Novo Nordisk, and lecture fees from Eli Lilly, Novo Nordisk, and Sanofi-Aventis. EB: consultant fees from Abbott, Bayer, Becton Dickinson, Boehringer Ingelheim, Daiichi-Sankyo, Eli Lilly, and Novo Nordisk. MVi: lecture fees from MundiPharma and Novo Nordisk. MG: consultant fees from Eli Lilly, and lecture fees from Eli Lilly, Merck Sharp & Dohme, and Novo Nordisk. CF: lecture fees from Abbot, Boehringer Ingelheim, Daiichi Sankyo, Eli Lilly, Merck Sharp & Dohme, Mundipharma, and Theras Lifetech. RT: consultant fees from AstraZeneca, Boehringer Ingelheim, Eli Lilly, Merck Sharp & Dohme, Novo Nordisk, and Sanofi-Aventis, and lecture fees from AstraZeneca, Boehringer Ingelheim, Eli Lilly, and Novo Nordisk. MVe: lecture fees from Lifescan and Novo Nordisk. FC: consultant fees from Boehringer Ingelheim, and lecture fees from AstraZeneca. LL: consultant fees from Abbott, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Medtronic, MOVI, Novo Nordisk, Roche, Sanofi-Aventis, and Terumo, and lecture fees from Abbott, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Medtronic, Menarini, MOVI, MSD, Mundipharma, Novo Nordisk, Roche, Sanofi-Aventis, and Terumo. SM: none.
GPu: consultant fees from Abbot, Bayer, and Novo Nordisk, and lecture fees from AstraZeneca, Boehringer Ingelheim, Eli Lilly, and Novo Nordisk.

Additionalfile1.doc
Additional file 1: The RIACE Study Group.
Additionalfile2.doc
Additional file 2: ESC risk categories.
STROBEchecklistcohort.doc

Distribution according to the European Society of Cardiology risk categories and associated risk of all-cause mortality in individuals with type 2 diabetes: A prospective cohort study

Status:

Version 1

Abstract

Background.

Methods.

Results.

Conclusions.

Trial registration.

Figures

Background

Methods

Design

Patients

All-cause mortality

Baseline measurements

Statistical analysis

Results

Categorization of patients according to the 2019 and 2021 ESC categories and subcategories

All-cause mortality according to the 2019 ESC risk categories and subcategories

All-cause mortality according to the 2021 ESC risk categories and subcategories

Discussion

Conclusion

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1