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.
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.
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.
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.).
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.
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.
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.
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.).
We evaluated the importance of body composition, amount of subcutaneous and visceral fat, liver and heart ectopic fat, adipose tissue distribution and cell size as predictors of cardio-metabolic risk ...in 53 non-obese male individuals. Known family history of type 2 diabetes was identified in 25 individuals. The participants also underwent extensive phenotyping together with measuring different biomarkers and non-targeted serum metabolomics. We used ensemble learning and other machine learning approaches to identify predictors with considerable relative importance and their intricate interactions. Visceral fat and age were strong individual predictors of ectopic fat accumulation in liver and heart along with markers of lipid oxidation and reduced glucose tolerance. Subcutaneous adipose cell size was the strongest individual predictor of whole-body insulin sensitivity and also a marker of visceral and ectopic fat accumulation. The metabolite 3-MOB along with related branched-chain amino acids demonstrated strong predictability for family history of type 2 diabetes.
Abstract
The study of metabolomics has improved our knowledge of the biology behind type 2 diabetes and its related metabolic physiology. We aimed to investigate markers of adipose tissue morphology, ...as well as insulin and glucose metabolism in 53 non-obese male individuals. The participants underwent extensive clinical, biochemical and magnetic resonance imaging phenotyping, and we also investigated non-targeted serum metabolites. We used a multi-modal machine learning approach to evaluate which serum metabolomic compounds predicted markers of glucose and insulin metabolism, adipose tissue morphology and distribution. Fasting glucose was associated with metabolites of intracellular insulin action and beta-cell dysfunction, namely cysteine-s-sulphate and n-acetylgarginine, whereas fasting insulin was predicted by myristoleoylcarnitine, propionylcarnitine and other metabolites of beta-oxidation of fatty acids. OGTT-glucose levels at 30 min were predicted by 7-Hoca, a microbiota derived metabolite, as well as eugenol, a fatty acid. Both insulin clamp and HOMA-IR were predicted by metabolites involved in beta-oxidation of fatty acids and biodegradation of triacylglycerol, namely tartrate and 3-phosphoglycerate, as well as pyruvate, xanthine and liver fat. OGTT glucose area under curve (AUC) and OGTT insulin AUC, was associated with bile acid metabolites, subcutaneous adipocyte cell size, liver fat and fatty chain acids and derivates, such as isovalerylcarnitine. Finally, subcutaneous adipocyte size was associated with long chain fatty acids, markers of sphingolipid metabolism, increasing liver fat and dopamine-sulfate 1. Ectopic liver fat was predicted by methylmalonate, adipocyte cell size, glutathione derived metabolites and fatty chain acids. Ectopic heart fat was predicted visceral fat, gamma-glutamyl tyrosine and 2-acetamidophenol sulfate. Adipocyte cell size, age, alpha-tocopherol and blood pressure were associated with visceral fat. We identified several biomarkers associated with adipose tissue pathophysiology and insulin and glucose metabolism using a multi-modal machine learning approach. Our approach demonstrated the relative importance of serum metabolites and they outperformed traditional clinical and biochemical variables for most endpoints.
Whether infection with SARS-CoV-2 leads to excess risk of requiring hospitalization or intensive care in persons with diabetes has not been reported, nor have risk factors in diabetes associated with ...increased risk for these outcomes.
We included 44,639 and 411,976 adult patients with type 1 and type 2 diabetes alive on Jan 1, 2020, and compared them to controls matched for age, sex, and county of residence (n=204,919 and 1,948,900). Age- and sex-standardized rates for COVID-19 related hospitalizations, admissions to intensive care and death, were estimated and hazard ratios were calculated using Cox regression analyses.
There were 10,486 hospitalizations and 1,416 admissions into intensive care. A total of 1,175 patients with diabetes and 1,820 matched controls died from COVID-19, of these 53•2% had been hospitalized and 10•7% had been in intensive care. Patients with type 2 diabetes, compared to controls, displayed an age- and sex-adjusted hazard ratio (HR) of 2•22, 95%CI 2•13-2•32) of being hospitalized for COVID-19, which decreased to HR 1•40, 95%CI 1•34-1•47) after further adjustment for sociodemographic factors, pharmacological treatment and comorbidities, had higher risk for admission to ICU due to COVID-19 (age- and sex-adjusted HR 2•49, 95%CI 2•22-2•79, decreasing to 1•42, 95%CI 1•25-1•62 after adjustment, and increased risk for death due to COVID-19 (age- and sex-adjusted HR 2•19, 95%CI 2•03-2•36, complete adjustment 1•50, 95%CI 1•39-1•63). Age- and sex-adjusted HR for COVID-19 hospitalization for type 1 diabetes was 2•10, 95%CI 1•72-2•57), decreasing to 1•25, 95%CI 0•3097-1•62) after adjustment• Patients with diabetes type 1 were twice as likely to require intensive care for COVID-19, however, not after adjustment (HR 1•49, 95%CI 0•75-2•92), and more likely to die (HR 2•90, 95% CI 1•6554-5•47) from COVID-19, but not independently of other factors (HR 1•38, 95% CI 0•64-2•99). Among patients with diabetes, elevated glycated hemoglobin levels were associated with higher risk for most outcomes.
In this nationwide study, type 2 diabetes was independently associated with increased risk of hospitalization, admission to intensive care and death for COVID-19. There were few admissions into intensive care and deaths in type 1 diabetes, and although hazards were significantly raised for all three outcomes, there was no independent risk persisting after adjustment for confounding factors.
Survival in left-sided valvular heart disease (VHD; aortic stenosis AS, aortic regurgitation AR, mitral stenosis MS, mitral regurgitation MR) in out-of-hospital cardiac arrest (OHCA) is unknown. We ...studied all cases of OHCA in the Swedish Registry for Cardiopulmonary Resuscitation. All degrees of VHD, diagnosed prior to OHCA, were included. Association between VHD and survival was studied using logistic regression, gradient boosting and Cox regression. We studied time to cardiac arrest, comorbidities, survival, and cerebral performance category (CPC) score. We included 55,615 patients; 1948 with AS (3,5%), 384 AR (0,7%), 17 MS (0,03%), and 704 with MR (1,3%). Patients with MS were not described due to low case number. Time from VHD diagnosis to cardiac arrest was 3.7 years in AS, 4.5 years in AR and 4.1 years in MR. ROSC occurred in 28% with AS, 33% with AR, 36% with MR and 35% without VHD. Survival at 30 days was 5.2%, 10.4%, 9.2%, 11.4% in AS, AR, MR and without VHD, respectively. There were no survivors in people with AS presenting with asystole or PEA. CPC scores did not differ in those with VHD compared with no VHD. Odds ratio (OR) for MR and AR showed no difference in survival, while AS displayed OR 0.58 (95% CI 0.46-0.72), vs no VHD. AS is associated with halved survival in OHCA, while AR and MR do not affect survival. Survivors with AS have neurological outcomes comparable to patients without VHD.
BackgroundIt has been estimated that 80% of cases of out-of-hospital cardiac arrest (OHCA) are due to cardiac causes. It is well-documented that diabetes is a risk factor for conditions associated ...with sudden cardiac arrest. Type 1 diabetes (T1D) displays a threefold to fivefold increased risk of cardiovascular disease and death compared with the general population.ObjectiveThis study aims to assess the characteristics and survival outcomes of individuals with and without T1D who experienced an OHCA. Design: A registry-based nationwide observational study with two cohorts, patients with T1D and patients without T1D. Setting: All emergency medical services and hospitals in Sweden were included in the study.ParticipantsUsing the Swedish Cardiopulmonary Resuscitation Registry, we enrolled 54 568 cases of OHCA where cardiopulmonary resuscitation was attempted between 2010 and 2020. Among them, 448 patients with T1D were identified using International Classification of Diseases-code: E10.MethodsSurvival analysis was performed using Kaplan-Meier and logistic regression. Multiple regression was adjusted for age, sex, cause of arrest, prevalence of T1D and time to cardiopulmonary resuscitation.Main outcome measuresThe outcomes were discharge status (alive vs dead), 30 days survival and neurological outcome at discharge.ResultsThere were no significant differences in patients discharged alive with T1D 37.3% versus, 46% among cases without T1D. There was also no difference in neurological outcome. Kaplan-Meier curves yielded no significant difference in long-term survival. Multiple regression showed no significant association with survival after accounting for covariates, OR 0.99 (95% CI 0.96 to 1.02), p value=0.7. Baseline characteristics indicate that patients with T1D were 5 years younger at OHCA occurrence and had proportionally fewer cases of heart disease as the cause of arrest (57.6% vs 62.7%).ConclusionWe conclude, with the current sample size, that there is no statistically significant difference in long-term or short-term survival between patients with and without T1D following OHCA.
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.
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.
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.
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.
BackgroundIt is unclear whether an implantable cardioverter-defibrillator (ICD) is generally beneficial in survivors of out-of-hospital cardiac arrest (OHCA).ObjectiveWe studied the association ...between ICD implantation prior to discharge and survival in patients with cardiac aetiology or initial shockable rhythm in OHCA.DesignWe 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.ParticipantsAll 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.ResultsAmong 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.ConclusionAmong 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.
The association between type 2 diabetes (T2D) and the development of cardiac arrhythmias and conduction disturbances has not been extensively studied. Arrhythmia was defined as atrial fibrillation ...and flutter (AF/AFl), ventricular tachycardia (VT) and ventricular fibrillation (VF), and conduction abnormality as sinus node disease (SND), atrioventricular (AV) block or pacemaker implantation, and intraventricular conduction blocks (IVCB). Incidence rates and Cox regression were used to compare outcomes, and to assess optimal levels for cardiometabolic risk factors and risk associated with multifactorial risk factor control (i.e., HbA1c, LDL-C, systolic blood pressure (SBP), BMI and eGFR), between patients with versus without T2D. The analyses included data from 617,000 patients with T2D and 2,303,391 matched controls. Patients with diabetes and the general population demonstrated a gradual increase in rates for cardiac conduction abnormalities and virtually all age-groups for AF/AFI showed increased incidence during follow-up. For patients with versus without T2D, risks for cardiac arrhythmias were higher, including for AF/AFl (HR 1.17, 95% CI 1.16-1.18), the composite of SND, AV-block or pacemaker implantation (HR 1.40, 95% CI 1.37-1.43), IVCB (HR 1.23, 95% CI 1.18-1.28) and VT/VF (HR 1.08, 95% CI 1.04-1.13). For patients with T2D who had selected cardiometabolic risk factors within target ranges, compared with controls, risk of arrythmia and conduction abnormalities for T2D vs not were: AF/AFl (HR 1.09, 95% CI 1.05-1.14), the composite of SND, AV-block or pacemaker implantation (HR 1.06, 95% CI 0.94-1.18), IVCB (HR 0.80, 95% CI 0.60-0.98), and for VT/VF (HR 0.97, 95% CI 0.80-1.17). Cox models showed a linear risk increase for SBP and BMI, while eGFR showed a U-shaped association. Individuals with T2D had a higher risk of arrhythmias and conduction abnormalities than controls, but excess risk associated with T2D was virtually not evident among patients with T2D with all risk factors within target range. BMI, SBP and eGFR displayed significant associations with outcomes among patients with T2D.
PDF
