Twenty Years of Cardiovascular Complications and Risk Factors in Patients With Type 2 Diabetes: A Nationwide Swedish Cohort Study.

BACKGROUND: The goal of this work was to investigate trends (2001-2019) for cardiovascular events and cardiometabolic risk factor levels in individuals with type 2 diabetes (T2D) and matched control subjects. METHODS: This study included 679 072 individuals with T2D from the Swedish National Diabetes Register and 2 643 800 matched control subjects. Incident outcomes comprised coronary artery disease, acute myocardial infarction, cerebrovascular disease, and heart failure (HF). Trends in time to first event for each outcome were analyzed with Cox regression and standardized incidence rates. In the group with T2D, Cox regression was also used to assess risk factor levels beyond target and outcomes, as well as the relative importance of each risk factor to each model. RESULTS: Among individuals with T2D, incidence rates per 10 000 person-years in 2001 and 2019 were as follows: acute myocardial infarction, 73.9 (95% CI, 65.4-86.8) and 41.0 (95% CI, 39.5-42.6); coronary artery disease, 205.1 (95% CI, 186.8-227.5) and 80.2 (95% CI, 78.2-82.3); cerebrovascular disease, 83.9 (95% CI, 73.6-98.5) and 46.2 (95% CI, 44.9-47.6); and HF, 98.3 (95% CI, 89.4-112.0) and 75.9 (95% CI, 74.4-77.5). The incidence for HF plateaued around 2013, a trend that then persisted. In individuals with T2D, glycated hemoglobin, systolic blood pressure, estimated glomerular filtration rate, and lipids were independently associated with outcomes. Body mass index alone potentially explained >30% of HF risk in T2D. For those with T2D with no risk factor beyond target, there was no excess cardiovascular risk compared with control subjects except for HF, with increased hazard with T2D even when no risk factor was above target (hazard ratio, 1.50 [95% CI, 1.35-1.67]). Risk for coronary artery disease and cerebrovascular disease increased in a stepwise fashion for each risk factor not within target. Glycated hemoglobin was most prognostically important for incident atherosclerotic events, as was body mass index for incident of HF. CONCLUSIONS: Risk and rates for atherosclerotic complications and HF are generally decreasing among individuals with T2D, although HF incidence has notably plateaued in recent years. Modifiable risk factors within target levels were associated with lower risks for outcomes. This was particularly notable for systolic blood pressure and glycated hemoglobin for atherosclerotic outcomes and body mass index for heart failure.

Risk factors for and risk of all-cause and atherosclerotic cardiovascular disease mortality in people with type 2 diabetes and peripheral artery disease: an observational, register-based cohort study.

BACKGROUND: Type 2 diabetes (T2D) and peripheral artery disease (PAD) are recognized as independent risk factors contributing to excess mortality. Contemporary observational studies exploring the associations of risk factors, and risk of all-cause and atherosclerotic cardiovascular disease mortality in persons with T2D following the onset of incident peripheral artery disease are limited. The objectives of this study were to investigate the associations of risk factors, and assess mortality risks in people with T2D compared with controls without T2D after the onset of PAD. METHODS: All persons with T2D (n = 150,215) registered in the Swedish National Diabetes Register between 2005 and 2009 were included, along with 346,423 controls without T2D matched for sex and age. Data were retrieved from several national registries, capturing information on risk factors, onset of incident peripheral artery disease, other comorbidities, socioeconomic factors, and outcomes. To compare persons with T2D and controls following the onset of peripheral artery disease regarding the risk of all-cause, and atherosclerotic cardiovascular disease mortality, Cox proportional hazard models and Kaplan-Meier curves were employed. A gradient-boosting model was utilized to estimate the relative statistical contribution of risk factors to the modeling of incident mortality risk in people with both T2D and peripheral artery disease. RESULTS: Crude rates of incident all-cause mortality were higher in individuals with T2D compared with controls, following the onset of PAD (600.4 (95% CI, 581.4-619.8) per 10,000 person-years versus 549.1 (95% CI, 532.1-566.5) per 10,000 person-years). Persons with T2D had an adjusted hazard ratio (HR) for all-cause mortality of 1.12 (95% CI, 1.05-1.19, P < 0.01) compared with controls after onset of incident PAD. The comparable adjusted HR for cardiovascular mortality was 1.13 (95% CI, 1.07-1.19, P < 0.01). High age and hyperglycemia at baseline played a significant role in contributing to the predictive models for incident all-cause and cardiovascular mortality among individuals with both T2D and PAD. CONCLUSIONS: The presence of T2D with concomitant PAD is related to an increased risk of both all-cause and cardiovascular mortality compared with individuals with only PAD. This argues for implementing optimized and intensive treatment strategies for individuals with both conditions.

Triglyceride-rich lipoprotein remnants, low-density lipoproteins, and risk of coronary heart disease: a UK Biobank study.

AIMS: The strength of the relationship of triglyceride-rich lipoproteins (TRL) with risk of coronary heart disease (CHD) compared with low-density lipoprotein (LDL) is yet to be resolved. METHODS AND RESULTS: Single-nucleotide polymorphisms (SNPs) associated with TRL/remnant cholesterol (TRL/remnant-C) and LDL cholesterol (LDL-C) were identified in the UK Biobank population. In a multivariable Mendelian randomization analysis, TRL/remnant-C was strongly and independently associated with CHD in a model adjusted for apolipoprotein B (apoB). Likewise, in a multivariable model, TRL/remnant-C and LDL-C also exhibited independent associations with CHD with odds ratios per 1 mmol/L higher cholesterol of 2.59 [95% confidence interval (CI): 1.99-3.36] and 1.37 [95% CI: 1.27-1.48], respectively. To examine the per-particle atherogenicity of TRL/remnants and LDL, SNPs were categorized into two clusters with differing effects on TRL/remnant-C and LDL-C. Cluster 1 contained SNPs in genes related to receptor-mediated lipoprotein removal that affected LDL-C more than TRL/remnant-C, whereas cluster 2 contained SNPs in genes related to lipolysis that had a much greater effect on TRL/remnant-C. The CHD odds ratio per standard deviation (Sd) higher apoB for cluster 2 (with the higher TRL/remnant to LDL ratio) was 1.76 (95% CI: 1.58-1.96), which was significantly greater than the CHD odds ratio per Sd higher apoB in cluster 1 [1.33 (95% CI: 1.26-1.40)]. A concordant result was obtained by using polygenic scores for each cluster to relate apoB to CHD risk. CONCLUSION: Distinct SNP clusters appear to impact differentially on remnant particles and LDL. Our findings are consistent with TRL/remnants having a substantially greater atherogenicity per particle than LDL.

Left-Sided Degenerative Valvular Heart Disease in Type 1 and Type 2 Diabetes.

BACKGROUND: The role of diabetes in the development of valvular heart disease, and, in particular, the relation with risk factor control, has not been extensively studied. METHODS: We included 715 143 patients with diabetes registered in the Swedish National Diabetes Register and compared them with 2 732 333 matched controls randomly selected from the general population. First, trends were analyzed with incidence rates and Cox regression, which was also used to assess diabetes as a risk factor compared with controls, and, second, separately in patients with diabetes according to the presence of 5 risk factors. RESULTS: The incidence of valvular outcomes is increasing among patients with diabetes and the general population. In type 2 diabetes, systolic blood pressure, body mass index, and renal function were associated with valvular lesions. Hazard ratios for patients with type 2 diabetes who had nearly all risk factors within target ranges, compared with controls, were as follows: aortic stenosis 1.34 (95% CI, 1.31-1.38), aortic regurgitation 0.67 (95% CI, 0.64-0.70), mitral stenosis 1.95 (95% CI, 1.76-2.20), and mitral regurgitation 0.82 (95% CI, 0.79-0.85). Hazard ratios for patients with type 1 diabetes and nearly optimal risk factor control were as follows: aortic stenosis 2.01 (95% CI, 1.58-2.56), aortic regurgitation 0.63 (95% CI, 0.43-0.94), and mitral stenosis 3.47 (95% CI, 1.37-8.84). Excess risk in patients with type 2 diabetes for stenotic lesions showed hazard ratios for aortic stenosis 1.62 (95% CI, 1.59-1.65), mitral stenosis 2.28 (95% CI, 2.08-2.50), and excess risk in patients with type 1 diabetes showed hazard ratios of 2.59 (95% CI, 2.21-3.05) and 11.43 (95% CI, 6.18-21.15), respectively. Risk for aortic and mitral regurgitation was lower in type 2 diabetes: 0.81 (95% CI, 0.78-0.84) and 0.95 (95% CI, 0.92-0.98), respectively. CONCLUSIONS: Individuals with type 1 and 2 diabetes have greater risk for stenotic lesions, whereas risk for valvular regurgitation was lower in patients with type 2 diabetes. Patients with well-controlled cardiovascular risk factors continued to display higher risk for valvular stenosis, without a clear stepwise decrease in risk between various degrees of risk factor control.

Risk Factors, Mortality, and Cardiovascular Outcomes in Patients with Type 2 Diabetes.

BACKGROUND: Patients with diabetes are at higher risk for death and cardiovascular outcomes than the general population. We investigated whether the excess risk of death and cardiovascular events among patients with type 2 diabetes could be reduced or eliminated. METHODS: In a cohort study, we included 271,174 patients with type 2 diabetes who were registered in the Swedish National Diabetes Register and matched them with 1,355,870 controls on the basis of age, sex, and county. We assessed patients with diabetes according to age categories and according to the presence of five risk factors (elevated glycated hemoglobin level, elevated low-density lipoprotein cholesterol level, albuminuria, smoking, and elevated blood pressure). Cox regression was used to study the excess risk of outcomes (death, acute myocardial infarction, stroke, and hospitalization for heart failure) associated with smoking and the number of variables outside target ranges. We also examined the relationship between various risk factors and cardiovascular outcomes. RESULTS: The median follow-up among all the study participants was 5.7 years, during which 175,345 deaths occurred. Among patients with type 2 diabetes, the excess risk of outcomes decreased stepwise for each risk-factor variable within the target range. Among patients with diabetes who had all five variables within target ranges, the hazard ratio for death from any cause, as compared with controls, was 1.06 (95% confidence interval [CI], 1.00 to 1.12), the hazard ratio for acute myocardial infarction was 0.84 (95% CI, 0.75 to 0.93), and the hazard ratio for stroke was 0.95 (95% CI, 0.84 to 1.07). The risk of hospitalization for heart failure was consistently higher among patients with diabetes than among controls (hazard ratio, 1.45; 95% CI, 1.34 to 1.57). In patients with type 2 diabetes, a glycated hemoglobin level outside the target range was the strongest predictor of stroke and acute myocardial infarction; smoking was the strongest predictor of death. CONCLUSIONS: Patients with type 2 diabetes who had five risk-factor variables within the target ranges appeared to have little or no excess risk of death, myocardial infarction, or stroke, as compared with the general population. (Funded by the Swedish Association of Local Authorities and Regions and others.).

Age at Diagnosis of Type 2 Diabetes Mellitus and Associations With Cardiovascular and Mortality Risks.

BACKGROUND: Risk of cardiovascular disease (CVD) and mortality for patients with versus without type 2 diabetes mellitus (T2DM) appears to vary by the age at T2DM diagnosis, but few population studies have analyzed mortality and CVD outcomes associations across the full age range. METHODS: With use of the Swedish National Diabetes Registry, everyone with T2DM registered in the Registry between 1998 and 2012 was included. Controls were randomly selected from the general population matched for age, sex, and county. The analysis cohort comprised 318 083 patients with T2DM matched with just <1.6 million controls. Participants were followed from 1998 to 2013 for CVD outcomes and to 2014 for mortality. Outcomes of interest were total mortality, cardiovascular mortality, noncardiovascular mortality, coronary heart disease, acute myocardial infarction, stroke, heart failure, and atrial fibrillation. We also examined life expectancy by age at diagnosis. We conducted the primary analyses using Cox proportional hazards models in those with no previous CVD and repeated the work in the entire cohort. RESULTS: Over a median follow-up period of 5.63 years, patients with T2DM diagnosed at ≤40 years had the highest excess risk for most outcomes relative to controls with adjusted hazard ratio (95% CI) of 2.05 (1.81-2.33) for total mortality, 2.72 (2.13-3.48) for cardiovascular-related mortality, 1.95 (1.68-2.25) for noncardiovascular mortality, 4.77 (3.86-5.89) for heart failure, and 4.33 (3.82-4.91) for coronary heart disease. All risks attenuated progressively with each increasing decade at diagnostic age; by the time T2DM was diagnosed at >80 years, the adjusted hazard ratios for CVD and non-CVD mortality were <1, with excess risks for other CVD outcomes substantially attenuated. Moreover, survival in those diagnosed beyond 80 was the same as controls, whereas it was more than a decade less when T2DM was diagnosed in adolescence. Finally, hazard ratios for most outcomes were numerically greater in younger women with T2DM. CONCLUSIONS: Age at diagnosis of T2DM is prognostically important for survival and cardiovascular risks, with implications for determining the timing and intensity of risk factor interventions for clinical decision making and for guideline-directed care. These observations amplify support for preventing/delaying T2DM onset in younger individuals.

Relative Prognostic Importance and Optimal Levels of Risk Factors for Mortality and Cardiovascular Outcomes in Type 1 Diabetes Mellitus.

BACKGROUND: The strength of association and optimal levels for risk factors related to excess risk of death and cardiovascular outcomes in type 1 diabetes mellitus have been sparsely studied. METHODS: In a national observational cohort study from the Swedish National Diabetes Register from 1998 to 2014, we assessed relative prognostic importance of 17 risk factors for death and cardiovascular outcomes in individuals with type 1 diabetes mellitus. We used Cox regression and machine learning analyses. In addition, we examined optimal cut point levels for glycohemoglobin, systolic blood pressure, and low-density lipoprotein cholesterol. Patients with type 1 diabetes mellitus were followed up until death or study end on December 31, 2013. The primary outcomes were death resulting from all causes, fatal/nonfatal acute myocardial infarction, fatal/nonfatal stroke, and hospitalization for heart failure. RESULTS: Of 32 611 patients with type 1 diabetes mellitus, 1809 (5.5%) died during follow-up over 10.4 years. The strongest predictors for death and cardiovascular outcomes were glycohemoglobin, albuminuria, duration of diabetes mellitus, systolic blood pressure, and low-density lipoprotein cholesterol. Glycohemoglobin displayed ≈2% higher risk for each 1-mmol/mol increase (equating to ≈22% per 1% glycohemoglobin difference), whereas low-density lipoprotein cholesterol was associated with 35% to 50% greater risk for each 1-mmol/L increase. Microalbuminuria or macroalbuminuria was associated with 2 to 4 times greater risk for cardiovascular complications and death. Glycohemoglobin <53 mmol/mol (7.0%), systolic blood pressure <140 mm Hg, and low-density lipoprotein cholesterol <2.5 mmol/L were associated with significantly lower risk for outcomes observed. CONCLUSIONS: Glycohemoglobin, albuminuria, duration of diabetes mellitus, systolic blood pressure, and low-density lipoprotein cholesterol appear to be the most important predictors for mortality and cardiovascular outcomes in patients with type 1 diabetes mellitus. Lower levels for glycohemoglobin, systolic blood pressure, and low-density lipoprotein cholesterol than contemporary guideline target levels appear to be associated with significantly lower risk for outcomes.

Mortality and Cardiovascular Disease in Type 1 and Type 2 Diabetes.

BACKGROUND: Long-term trends in excess risk of death and cardiovascular outcomes have not been extensively studied in persons with type 1 diabetes or type 2 diabetes. METHODS: We included patients registered in the Swedish National Diabetes Register from 1998 through 2012 and followed them through 2014. Trends in deaths and cardiovascular events were estimated with Cox regression and standardized incidence rates. For each patient, controls who were matched for age, sex, and county were randomly selected from the general population. RESULTS: Among patients with type 1 diabetes, absolute changes during the study period in the incidence rates of sentinel outcomes per 10,000 person-years were as follows: death from any cause, -31.4 (95% confidence interval [CI], -56.1 to -6.7); death from cardiovascular disease, -26.0 (95% CI, -42.6 to -9.4); death from coronary heart disease, -21.7 (95% CI, -37.1 to -6.4); and hospitalization for cardiovascular disease, -45.7 (95% CI, -71.4 to -20.1). Absolute changes per 10,000 person-years among patients with type 2 diabetes were as follows: death from any cause, -69.6 (95% CI, -95.9 to -43.2); death from cardiovascular disease, -110.0 (95% CI, -128.9 to -91.1); death from coronary heart disease, -91.9 (95% CI, -108.9 to -75.0); and hospitalization for cardiovascular disease, -203.6 (95% CI, -230.9 to -176.3). Patients with type 1 diabetes had roughly 40% greater reduction in cardiovascular outcomes than controls, and patients with type 2 diabetes had roughly 20% greater reduction than controls. Reductions in fatal outcomes were similar in patients with type 1 diabetes and controls, whereas patients with type 2 diabetes had smaller reductions in fatal outcomes than controls. CONCLUSIONS: In Sweden from 1998 through 2014, mortality and the incidence of cardiovascular outcomes declined substantially among persons with diabetes, although fatal outcomes declined less among those with type 2 diabetes than among controls. (Funded by the Swedish Association of Local Authorities and Regions and others.).

Excess mortality and cardiovascular disease in young adults with type 1 diabetes in relation to age at onset: a nationwide, register-based cohort study.

BACKGROUND: People with type 1 diabetes are at elevated risk of mortality and cardiovascular disease, yet current guidelines do not consider age of onset as an important risk stratifier. We aimed to examine how age at diagnosis of type 1 diabetes relates to excess mortality and cardiovascular risk. METHODS: We did a nationwide, register-based cohort study of individuals with type 1 diabetes in the Swedish National Diabetes Register and matched controls from the general population. We included patients with at least one registration between Jan 1, 1998, and Dec 31, 2012. Using Cox regression, and with adjustment for diabetes duration, we estimated the excess risk of all-cause mortality, cardiovascular mortality, non-cardiovascular mortality, acute myocardial infarction, stroke, cardiovascular disease (a composite of acute myocardial infarction and stroke), coronary heart disease, heart failure, and atrial fibrillation. Individuals with type 1 diabetes were categorised into five groups, according to age at diagnosis: 0-10 years, 11-15 years, 16-20 years, 21-25 years, and 26-30 years. FINDINGS: 27 195 individuals with type 1 diabetes and 135 178 matched controls were selected for this study. 959 individuals with type 1 diabetes and 1501 controls died during follow-up (median follow-up was 10 years). Patients who developed type 1 diabetes at 0-10 years of age had hazard ratios of 4·11 (95% CI 3·24-5·22) for all-cause mortality, 7·38 (3·65-14·94) for cardiovascular mortality, 3·96 (3·06-5·11) for non-cardiovascular mortality, 11·44 (7·95-16·44) for cardiovascular disease, 30·50 (19·98-46·57) for coronary heart disease, 30·95 (17·59-54·45) for acute myocardial infarction, 6·45 (4·04-10·31) for stroke, 12·90 (7·39-22·51) for heart failure, and 1·17 (0·62-2·20) for atrial fibrillation. Corresponding hazard ratios for individuals who developed type 1 diabetes aged 26-30 years were 2·83 (95% CI 2·38-3·37) for all-cause mortality, 3·64 (2·34-5·66) for cardiovascular mortality, 2·78 (2·29-3·38) for non-cardiovascular mortality, 3·85 (3·05-4·87) for cardiovascular disease, 6·08 (4·71-7·84) for coronary heart disease, 5·77 (4·08-8·16) for acute myocardial infarction, 3·22 (2·35-4·42) for stroke, 5·07 (3·55-7·22) for heart failure, and 1·18 (0·79-1·77) for atrial fibrillation; hence the excess risk differed by up to five times across the diagnosis age groups. The highest overall incidence rate, noted for all-cause mortality, was 1·9 (95% CI 1·71-2·11) per 100 000 person-years for people with type 1 diabetes. Development of type 1 diabetes before 10 years of age resulted in a loss of 17·7 life-years (95% CI 14·5-20·4) for women and 14·2 life-years (12·1-18·2) for men. INTERPRETATION: Age at onset of type 1 diabetes is an important determinant of survival, as well as all cardiovascular outcomes, with highest excess risk in women. Greater focus on cardioprotection might be warranted in people with early-onset type 1 diabetes. FUNDING: Swedish Heart and Lung Foundation.

Range of Risk Factor Levels: Control, Mortality, and Cardiovascular Outcomes in Type 1 Diabetes Mellitus.

BACKGROUND: Individuals with type 1 diabetes mellitus (T1DM) have a high risk of cardiovascular complications, but it is unknown to what extent fulfilling all cardiovascular treatment goals is associated with residual risk of mortality and cardiovascular outcomes in those with T1DM compared with the general population. METHODS: We included all patients ≥18 years of age with T1DM who were registered in the Swedish National Diabetes Register from January 1, 1998, through December 31, 2014, a total of 33 333 patients, each matched for age and sex with 5 controls without diabetes mellitus randomly selected from the population. Patients with T1DM were categorized according to number of risk factors not at target: glycohemoglobin, blood pressure, albuminuria, smoking, and low-density lipoprotein cholesterol. Risk of all-cause mortality, acute myocardial infarction, heart failure hospitalization, and stroke was examined in relation to the number of risk factors at target. RESULTS: The mean follow-up was 10.4 years in the diabetes group. Overall, 2074 of 33 333 patients with diabetes mellitus and 4141 of 166 529 controls died. Risk for all outcomes increased stepwise for each additional risk factor not at target. Adjusted hazard ratios for patients achieving all risk factor targets compared with controls were 1.31 (95% confidence interval [CI], 0.93-1.85) for all-cause mortality, 1.82 (95% CI, 1.15-2.88) for acute myocardial infarction, 1.97 (95% CI, 1.04-3.73) for heart failure hospitalization, and 1.17 (95% CI, 0.51-2.68) for stroke. The hazard ratio for patients versus controls with none of the risk factors meeting target was 7.33 (95% CI, 5.08-10.57) for all-cause mortality, 12.34 (95% CI, 7.91-19.48) for acute myocardial infarction, 15.09 (95% CI, 9.87-23.09) for heart failure hospitalization, and 12.02 (95% CI, 7.66-18.85) for stroke. CONCLUSIONS: A steep-graded association exists between decreasing number of cardiovascular risk factors at target and major adverse cardiovascular outcomes among patients with T1DM. However, risks for all outcomes were numerically higher for patients with T1DM compared with controls, even when all risk factors were at target, with risk for acute myocardial infarction and heart failure hospitalization statistically significantly higher.

Recent trends in life expectancy for people with type 1 diabetes in Sweden.

AIMS/HYPOTHESIS: People with type 1 diabetes have reduced life expectancy (LE) compared with the general population. Our aim is to quantify mortality changes from 2002 to 2011 in people with type 1 diabetes in Sweden. METHODS: This study uses health records from the Swedish National Diabetes Register (NDR) linked with death records. Abridged period life tables for those with type 1 diabetes aged 20 years and older were derived for 2002-06 and 2007-11 using Chiang's method. Cox proportional hazard models were used to assess trends in overall and cause-specific mortality. RESULTS: There were 27,841 persons aged 20 years and older identified in the NDR as living with type 1 diabetes between 2002 and 2011, contributing 194,685 person-years of follow-up and 2,018 deaths. For men with type 1 diabetes, the remaining LE at age 20 increased significantly from 47.7 (95% CI 46.6, 48.9) in 2002-06 to 49.7 years (95% CI 48.9, 50.6) in 2007-11. For women with type 1 diabetes there was no significant change, with an LE at age 20 of 51.7 years (95% CI 50.3, 53.2) in 2002-06 and 51.9 years (95% CI 50.9, 52.9) in 2007-11. Cardiovascular mortality significantly reduced, with a per year HR of 0.947 (95% CI 0.917, 0.978) for men and 0.952 (95% CI 0.916, 0.989) for women. CONCLUSIONS/INTERPRETATION: From 2002-06 to 2007-11 the LE at age 20 of Swedes with type 1 diabetes increased by approximately 2 years for men but minimally for women. These recent gains have been driven by reduced cardiovascular mortality.

Non-coronary arterial outcomes in people with type 1 diabetes mellitus: a Swedish retrospective cohort study.

Background: Observational studies on long-term trends, risk factor association and importance are scarce for type 1 diabetes mellitus and peripheral arterial outcomes. We set out to investigate trends in non-coronary complications and their relationships with cardiovascular risk factors in persons with type 1 diabetes mellitus compared to matched controls. Methods: 34,263 persons with type 1 diabetes mellitus from the Swedish National Diabetes Register and 164,063 matched controls were included. Incidence rates of extracranial large artery disease, aortic aneurysm, aortic dissection, lower extremity artery disease, and diabetic foot syndrome were analyzed using standardized incidence rates and Cox regression. Findings: Between 2001 and 2019, type 1 diabetes mellitus incidence rates per 100,000 person-years were as follows: extracranial large artery disease 296.5-84.3, aortic aneurysm 0-9.2, aortic dissection remained at 0, lower extremity artery disease 456.6-311.1, and diabetic foot disease 814.7-77.6. Persons with type 1 diabetes mellitus with cardiometabolic risk factors at target range did not exhibit excess risk of extracranial large artery disease [HR 0.83 (95% CI, 0.20-3.36)] or lower extremity artery disease [HR 0.94 (95% CI, 0.30-2.93)], compared to controls. Persons with type 1 diabetes with all risk factors at baseline, had substantially elevated risk for diabetic foot disease [HR 29.44 (95% CI, 3.83-226.04)], compared to persons with type 1 diabetes with no risk factors. Persons with type 1 diabetes mellitus continued to display a lower risk for aortic aneurysm, even with three cardiovascular risk factors at baseline [HR 0.31 (95% CI, 0.15-0.67)]. Relative importance analyses demonstrated that education, glycated hemoglobin (HbA1c), duration of diabetes and lipids explained 54% of extracranial large artery disease, while HbA1c, smoking and systolic blood pressure explained 50% of lower extremity artery disease and HbA1c alone contributed to 41% of diabetic foot disease. Income, duration of diabetes and body mass index explained 66% of the contribution to aortic aneurysm. Interpretation: Peripheral arterial complications decreased in persons with type 1 diabetes mellitus, except for aortic aneurysm which remained low. Besides glycemic control, traditional cardiovascular risk factors were associated with incident outcomes. Risk of these outcomes increased with additional risk factors present. Persons with type 1 diabetes mellitus exhibited a lower risk of aortic aneurysm compared to controls, despite presence of cardiovascular risk factors. Funding: Swedish Governmental and the county support of research and education of doctors, the Swedish Heart and Lung Foundation, Sweden and Åke-Wibergs grant.

Non-coronary peripheral arterial complications in people with type 2 diabetes: a Swedish retrospective cohort study.

Background: Few studies have explored long-term trends and risk factors for peripheral arterial complications in type 2 diabetes compared to the general population. Our research focuses on identifying optimal risk factors, their significance, risk associated with multifactorial risk factor control, and trends for these complications in diabetic patients versus general controls. Methods: This study included persons with type 2 diabetes mellitus entered into the Swedish National Diabetes Register 2001-2019 and controls matched for age-, sex- and county of residence. Outcomes comprised of extracranial large artery disease, aortic aneurysm, aortic dissection, lower extremity arterial disease and diabetes foot disease. Standardized incidence rates and Cox regression were used for analyses. Findings: The study comprises 655,250 persons with type 2 diabetes mellitus; average age 64.2; 43.8% women. Among persons with type 2 diabetes mellitus, the incidence rates per 100,000 person years for each non-coronary peripheral arterial complication event changed between 2001 and 2019 as follows: extracranial large artery disease 170.0-84.9; aortic aneurysm 40.6-69.2; aortic dissection 9.3 to 5.6; lower extremity artery disease from 338.8 to 190.8; and diabetic foot disease from 309.8 to 226.8. Baseline hemoglobin A1c (HbA1c), systolic blood pressure (SBP), smoking status and lipid levels were independently associated with all outcomes in the type 2 diabetes mellitus cohort. Within the cohort with type 2 diabetes mellitus, the risk for extracranial large artery disease and lower extremity artery disease increased in a stepwise fashion for each risk factor not within target. Excess risk for non-coronary peripheral arterial complications in the entire cohort for persons with type 2 diabetes mellitus, compared to matched controls, were as follows: extracranial large artery disease adjusted hazard ratio (HR) 1.69 (95% confidence interval (CI), 1.65-1.73), aortic aneurysm HR 0.89 (95% CI, 0.87-0.92), aortic dissection HR 0.51 (95% CI, 0.46-0.57) and lower extremity artery disease HR 2.59 (95% CI, 2.55-2.64). Interpretation: The incidence of non-coronary peripheral arterial complications has declined significantly among persons with type 2 diabetes mellitus, with the exception of aortic aneurysm. HbA1c, smoking and blood pressure demonstrated greatest relative contribution for outcomes and lower levels of cardiometabolic risk factors are associated with reduced relative risk of outcomes. Funding: Swedish Governmental and the County support of research and education of doctors, the Swedish Heart-Lung Foundation and Åke-Wibergs grant.

Early ICD implantation following out-of-hospital cardiac arrest: a retrospective cohort study from the Swedish Registry for Cardiopulmonary Resuscitation.

BACKGROUND: It is unclear whether an implantable cardioverter-defibrillator (ICD) is generally beneficial in survivors of out-of-hospital cardiac arrest (OHCA). OBJECTIVE: We studied the association between ICD implantation prior to discharge and survival in patients with cardiac aetiology or initial shockable rhythm in OHCA. DESIGN: We conducted a retrospective cohort study in the Swedish Registry for Cardiopulmonary Resuscitation. Treatment associations were estimated using propensity scores. We used gradient boosting, Bayesian additive regression trees, neural networks, extreme gradient boosting and logistic regression to generate multiple propensity scores. We selected the model yielding maximum covariate balance to obtain weights, which were used in a Cox regression to calculate HRs for death or recurrent cardiac arrest. PARTICIPANTS: All cases discharged alive during 2010 to 2020 with a cardiac aetiology or initial shockable rhythm were included. A total of 959 individuals were discharged with an ICD, and 2046 were discharged without one. RESULTS: Among those experiencing events, 25% did so within 90 days in the ICD group, compared with 52% in the other group. All HRs favoured ICD implantation. The overall HR (95% CI) for ICD versus no ICD was 0.38 (0.26 to 0.56). The HR was 0.42 (0.28 to 0.63) in cases with initial shockable rhythm; 0.18 (0.06 to 0.58) in non-shockable rhythm; 0.32 (0.20 to 0.53) in cases with a history of coronary artery disease; 0.36 (0.22 to 0.61) in heart failure and 0.30 (0.13 to 0.69) in those with diabetes. Similar associations were noted in all subgroups. CONCLUSION: Among survivors of OHCA, those discharged with an ICD had approximately 60% lower risk of death or recurrent cardiac arrest. A randomised trial is warranted to study this further.

Association between exercise load, resting heart rate, and maximum heart rate and risk of future ST-segment elevation myocardial infarction (STEMI).

OBJECTIVE: This study aimed to examine the association between exercise workload, resting heart rate (RHR), maximum heart rate and the risk of developing ST-segment elevation myocardial infarction (STEMI). METHODS: The study included all participants from the UK Biobank who had undergone submaximal exercise stress testing. Patients with a history of STEMI were excluded. The allowed exercise load for each participant was calculated based on clinical characteristics and risk categories. We studied the participants who exercised to reach 50% or 35% of their expected maximum exercise tolerance. STEMI was adjudicated by the UK Biobank. We used Cox regression analysis to study how exercise tolerance and RHR were related to the risk of STEMI. RESULTS: A total of 66 949 participants were studied, of whom 274 developed STEMI during a median follow-up of 7.7 years. After adjusting for age, sex, blood pressure, smoking, forced vital capacity, forced expiratory volume in 1 s, peak expiratory flow and diabetes, we noted a significant association between RHR and the risk of STEMI (p=0.015). The HR for STEMI in the highest RHR quartile (>90 beats/min) compared with that in the lowest quartile was 2.92 (95% CI 1.26 to 6.77). Neither the maximum achieved exercise load nor the ratio of the maximum heart rate to the maximum load was significantly associated with the risk of STEMI. However, a non-significant but stepwise inverse association was noted between the maximum load and the risk of STEMI. CONCLUSION: RHR is an independent predictor of future STEMI. An RHR of >90 beats/min is associated with an almost threefold increase in the risk of STEMI.

No obesity paradox in out-of-hospital cardiac arrest: Data from the Swedish registry of cardiopulmonary resuscitation.

Background: Although an "obesity paradox", which states an increased chance of survival for patients with obesity after myocardial infarction has been proposed, it is less clear whether this phenomenon even exists in patients suffering out-of-hospital cardiac arrest (OHCA) and if diabetes, which is often associated with obesity, implies an additional risk. Objective: To investigate if and how obesity, with or without diabetes, affects the survival of patients with OHCA. Methods: This study included 55,483 patients with OHCA reported to the Swedish Registry of Cardiopulmonary Resuscitation between 2010 and 2020. Patients were classified in five groups: obesity only (Ob), type 1 diabetes only (T1D), type 2 diabetes only (T2D), obesity and any diabetes (ObD), or belonging to the group other (OTH). Patient characteristics and outcomes were studied using descriptive statistics, logistic, and Cox proportional regression. Results: Obesity only was found in 2.7% of the study cohort, while 3.2% had obesity and any type of diabetes. Ob patients were significantly younger than all other patients (p ≤ 0.001); the 30 day-survival was 9.6% in Ob, and 10.6%, 7.3%, 6.9%, and 12.7% in T1D, T2D, ObD, and OTH, respectively, with OR (95% CI) of 0.69 (0.57-0.82), 0.78 (0.56-1.05), 0.65 (0.59-0.71), and 0.55 (0.45-0.66) for Ob, T1D, T2D, and ObD, respectively (reference group OTH). No time-related trends in 30-days survival were found. Conclusion: Obesity was present in 6% of the population and was associated with younger age and a 30% reduction in survival; a combination of obesity and diabetes further reduced the survival rate.

Predicting survival and neurological outcome in out-of-hospital cardiac arrest using machine learning: the SCARS model.

BACKGROUND: A prediction model that estimates survival and neurological outcome in out-of-hospital cardiac arrest patients has the potential to improve clinical management in emergency rooms. METHODS: We used the Swedish Registry for Cardiopulmonary Resuscitation to study all out-of-hospital cardiac arrest (OHCA) cases in Sweden from 2010 to 2020. We had 393 candidate predictors describing the circumstances at cardiac arrest, critical time intervals, patient demographics, initial presentation, spatiotemporal data, socioeconomic status, medications, and comorbidities before arrest. To develop, evaluate and test an array of prediction models, we created stratified (on the outcome measure) random samples of our study population. We created a training set (60% of data), evaluation set (20% of data), and test set (20% of data). We assessed the 30-day survival and cerebral performance category (CPC) score at discharge using several machine learning frameworks with hyperparameter tuning. Parsimonious models with the top 1 to 20 strongest predictors were tested. We calibrated the decision threshold to assess the cut-off yielding 95% sensitivity for survival. The final model was deployed as a web application. FINDINGS: We included 55,615 cases of OHCA. Initial presentation, prehospital interventions, and critical time intervals variables were the most important. At a sensitivity of 95%, specificity was 89%, positive predictive value 52%, and negative predictive value 99% in test data to predict 30-day survival. The area under the receiver characteristic curve was 0.97 in test data using all 393 predictors or only the ten most important predictors. The final model showed excellent calibration. The web application allowed for near-instantaneous survival calculations. INTERPRETATION: Thirty-day survival and neurological outcome in OHCA can rapidly and reliably be estimated during ongoing cardiopulmonary resuscitation in the emergency room using a machine learning model incorporating widely available variables. FUNDING: Swedish Research Council (2019-02019); Swedish state under the agreement between the Swedish government, and the county councils (ALFGBG-971482); The Wallenberg Centre for Molecular and Translational Medicine.