Assisting the implementation of screening for type 1 diabetes by using artificial intelligence on publicly available data.

The type 1 diabetes community is coalescing around the benefits and advantages of early screening for disease risk. To be accepted by healthcare providers, regulatory authorities and payers, screening programmes need to show that the testing variables allow accurate risk prediction and that individualised risk-informed monitoring plans are established, as well as operational feasibility, cost-effectiveness and acceptance at population level. Artificial intelligence (AI) has the potential to contribute to solving these issues, starting with the identification and stratification of at-risk individuals. ASSET (AI for Sustainable Prevention of Autoimmunity in the Society; www.asset.healthcare ) is a public/private consortium that was established to contribute to research around screening for type 1 diabetes and particularly to how AI can drive the implementation of a precision medicine approach to disease prevention. ASSET will additionally focus on issues pertaining to operational implementation of screening. The authors of this article, researchers and clinicians active in the field of type 1 diabetes, met in an open forum to independently debate key issues around screening for type 1 diabetes and to advise ASSET. The potential use of AI in the analysis of longitudinal data from observational cohort studies to inform the design of improved, more individualised screening programmes was also discussed. A key issue was whether AI would allow the research community and industry to capitalise on large publicly available data repositories to design screening programmes that allow the early detection of individuals at high risk and enable clinical evaluation of preventive therapies. Overall, AI has the potential to revolutionise type 1 diabetes screening, in particular to help identify individuals who are at increased risk of disease and aid in the design of appropriate follow-up plans. We hope that this initiative will stimulate further research on this very timely topic.

Association of glucagon-like peptide-1 receptor agonists with serious liver events among patients with type 2 diabetes: A Scandinavian cohort study.

BACKGROUND AND AIMS: Clinical trials suggest that glucagon-like peptide-1 (GLP-1) receptor agonists may have beneficial effects on NAFLD, but the impact on hard hepatic end points is unknown. We assessed the association between the use of GLP-1 receptor agonists and the risk of serious liver events in routine clinical practice. APPROACH AND RESULTS: Cohort study using data from nationwide registers in Sweden, Denmark, and Norway, 2007-2020, including 91,479 initiators of GLP-1 receptor agonists and 244,004 initiators of the active comparator, dipeptidyl peptidase-4 inhibitors, without a history of chronic liver disease other than NAFLD/NASH. The primary outcome was serious liver events: a composite of incident compensated and decompensated cirrhosis and HCC. Secondary outcomes were the individual components of the primary outcome. Cox regression was used to estimate HRs, using propensity score weighting to control for confounding. Users of GLP-1 receptor agonists had 608 serious liver events (adjusted incidence rate: 16.9 events per 10,000 person-years), compared with 1770 events among users of dipeptidyl peptidase-4 inhibitors (19.2 events per 10,000 person-years). The adjusted HR was 0.85 (95% CI: 0.75 to 0.97), and the rate difference was -2.1 (-4.4 to 0.1) events per 10,000 person-years. In secondary outcome analyses, the adjusted HR was 0.85 (0.75 to 0.97) for compensated and decompensated cirrhosis and 1.05 (0.80 to 1.39) for HCC. CONCLUSIONS: The use of GLP-1 receptor agonists was associated with a significantly reduced risk of serious liver events, driven by a reduction of compensated and decompensated cirrhosis.

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.

Implantable cardioverter defibrillator and cardiac resynchronization treatment in people with type 2 diabetes: a comparison with age- and sex matched controls from the general population.

BACKGROUND: Increased risk of severe tachyarrhythmias is reported in patients with type 2 diabetes mellitus (T2DM). The aim of this study was to explore if treatment with cardiac implantable electronic device (CIED) such as implantable cardioverter defibrillator (ICD), cardiac resynchronization therapy- pacemaker and -defibrillator (CRT-P/CRT-D) differed in patients with vs. without T2DM. A secondary aim was to identify patient characteristics indicating an increased CIED treatment. METHOD: 416 162 adult patients with T2DM from the Swedish National Diabetes Registry and 2 081 087 controls from the Swedish population, matched for age, sex and living area, were included between 1/1/1998 and 31/12/2012 and followed until 31/12/2013. They were compared regarding prevalence of ventricular tachycardia (VT) at baseline and the risk of receiving a CIED during follow-up. Multivariable Cox regression analysis was performed to estimate the risk of CIED-treatment and factors identifying patients with such risk. RESULTS: Ventricular fibrillation (VF) (0.1% vs 0.0004%) and (VT) (0.2% vs. 0.1%) were more frequent among patients with T2DM compared to controls. CIED-treatment was significantly increased in patients with T2DM both in unadjusted and adjusted analyses. HR and 95% CI, after adjustment for sex, age, marital status, income, education, country of birth, coronary artery disease and congestive heart failure, were 1.32 [1.21-1.45] for ICD, 1.74 [1.55-1.95] for CRT-P and 1.69 [1.43-1.99] for CRT-D. Blood-pressure and lipid lowering therapies were independent risk factors associated to receiving CIED, while female sex was protective. CONCLUSIONS: Although the proportion of VT/VF was low, patients with T2DM had a higher prevalence of these conditions and increased risk for treatment with CIED compared to controls. This underlines the importance of recognizing that T2DM patients have an increased need of CIED.

Use of DPP4 Inhibitors and GLP-1 Receptor Agonists and Risk of Intestinal Obstruction: Scandinavian Cohort Study.

BACKGROUND & AIMS: Concerns have been raised that the incretin-based diabetes drugs dipeptidyl peptidase 4 (DPP4) inhibitors and glucagon-like peptide 1 (GLP-1) receptor agonists may increase the risk of intestinal obstruction. We aimed to assess the association between use of DPP4 inhibitors and GLP-1 receptor agonists and the risk of intestinal obstruction. METHODS: Using data from nationwide registers in Sweden, Denmark, and Norway, 2013-2021, we conducted 2 cohort studies, one for DPP4 inhibitors and one for GLP-1 receptor agonists, to investigate the risk of intestinal obstruction as compared with an active comparator drug class (sodium-glucose co-transporter 2 [SGLT2] inhibitors). RESULTS: Among 19,0321 new users of DPP4 inhibitors (median (interquartile range [IQR]) follow-up time, 1.3 [0.6-2.6] years) and 139,315 new users of SGLT2 inhibitors (median [IQR] follow-up time, 0.8 [0.4-1.7] years), 919 intestinal obstruction events occurred. Use of DPP4 inhibitors, as compared with SGLT2 inhibitors, was not associated with a statistically significant increase in risk of intestinal obstruction (adjusted incidence rate, 2.0 vs 1.8 per 1000 person-years; hazard ratio, 1.13; 95% confidence interval, 0.96-1.34). Among 121,254 new users of GLP-1 receptor agonists (median [standard deviation] follow-up time, 0.9 [0.4-1.9] years) and 185,027 new users of SGLT2 inhibitors (median [IQR] follow-up time, 0.8 [0.4-1.8] years), 557 intestinal obstruction events occurred. Use of GLP-1 receptor agonists was not associated with a statistically significant increase in risk of intestinal obstruction (adjusted incidence rate, 1.3 vs 1.6 per 1000 person-years; hazard ratio, 0.83; 95% confidence interval, 0.69-1.01). CONCLUSIONS: In this analysis of nationwide data from 3 countries, previous safety signals indicating an increased risk of intestinal obstruction with use of DPP4 inhibitors and GLP-1 receptor agonists were not confirmed.

The comparative cardiovascular and renal effectiveness of sodium-glucose co-transporter-2 inhibitors and glucagon-like peptide-1 receptor agonists: A Scandinavian cohort study.

AIM: To assess the comparative cardiovascular and renal effectiveness of sodium-glucose co-transporter-2 (SGLT2) inhibitors versus glucagon-like peptide-1 (GLP-1) receptor agonists in routine clinical practice. MATERIALS AND METHODS: A cohort study of nationwide registers from Sweden, Denmark, and Norway, including 87 525 new users of SGLT2 inhibitors and 63 921 new users of GLP-1 receptor agonists, was conducted using data from 2013-2018. Co-primary outcomes, analysed using an intention-to-treat exposure definition, were major adverse cardiovascular events (MACE; myocardial infarction, stroke, and cardiovascular death), heart failure (hospitalization or death because of heart failure), and serious renal events (renal replacement therapy, hospitalization for renal events, and death from renal causes). RESULTS: Use of SGLT2 inhibitors versus GLP-1 receptor agonists was associated with a higher risk of MACE (adjusted incidence rate: 15.2 vs. 14.4 events per 1000 person-years; HR 1.07 [95% CI 1.01-1.15]), a similar risk of heart failure (6.0 vs. 6.0 events per 1000 person-years; HR 1.02 [0.92-1.12]), and a lower risk of serious renal events (2.9 vs. 4.0 events per 1000 person-years; HR 0.76 [0.66-0.87]). In as-treated analyses, the HR (95% CI) was 1.11 (1.00-1.24) for MACE, 0.88 (0.74-1.04) for heart failure, and 0.60 (0.47-0.77) for serious renal events. In secondary outcome analyses, use of SGLT2 inhibitors versus GLP-1 receptor agonists was not associated with statistically significant differences for the risk of myocardial infarction (HR 1.09 [95% CI 1.00-1.19]), cardiovascular death (HR 0.97 [95% CI 0.84-1.12]), death from renal causes (HR 0.75 [95% CI 0.41-1.35]), or any cause death (HR 1.01 [95% CI 0.94-1.09]), while the risk of stroke was higher (HR 1.14 [95% CI 1.03-1.26]), and the risk of renal replacement therapy (HR 0.74 [95% CI 0.56-0.97]) and hospitalization for renal events (HR 0.75 [95% CI 0.65-0.88]) were lower among users of SGLT2 inhibitors. CONCLUSIONS: Use of SGLT2 inhibitors versus GLP-1 receptor agonists was associated with a similar risk of heart failure and a lower risk of serious renal events, while use of GLP-1 receptor agonists versus SGLT2 inhibitors was associated with a slightly lower risk of MACE. In as-treated analyses, the associations with MACE and serious renal events increased in magnitude, and the HR for heart failure tended towards a protective association for SGLT2 inhibitors.

Childhood-onset type 1 diabetes and attention-deficit/hyperactivity disorder with educational attainment: A population-based sibling-comparison study.

AIM: To examine the association of childhood-onset type 1 diabetes (T1D) and attention-deficit/hyperactivity disorder (ADHD) with educational outcomes from compulsory school to university. METHODS: Using multiple Swedish nationwide registers, we followed up on 1,474,941 individuals born in Sweden from 1981-1995 to December 31, 2013. Associations of T1D and ADHD with achieving educational milestones (from compulsory school to university) and school performances were estimated using logistic and linear regression models and sibling comparison models. RESULTS: Compared to their peers, children with both T1D and ADHD were less likely to achieve any of the educational attainments, including completing compulsory school (adjusted OR [aOR] [95% CI]: 0.43 [0.26, 0.72]), be eligible to and finishing upper secondary school (0.26 [0.19, 0.36], 0.24 [0.17, 0.35], respectively), and starting university (0.38 [0.17, 0.90]). The odds of achieving these educational milestones were substantially lower in children with ADHD alone (aORs: 0.14-0.44), but were slightly worse or no differences in children with T1D alone (aORs: 0.86-1.08). All associations above remained similar in the sibling comparison models. CONCLUSION: Children and adolescents with both T1D and ADHD had long-term educational underachievement, with ADHD being the major contributor. Our findings suggest the importance of assessing ADHD in children with T1D and targeted support for minimising the education gap between the affected children and their peers.

Poor glycaemic control is associated with increased risk of neurodevelopmental disorders in childhood-onset type 1 diabetes: a population-based cohort study.

AIMS/HYPOTHESIS: The aim of this study was to investigate the effect of childhood-onset type 1 diabetes on the risk of subsequent neurodevelopmental disorders, and the role of glycaemic control in this association. We hypothesised that individuals with poor glycaemic control may be at a higher risk of neurodevelopmental disorders compared with the general population, as well as compared with individuals with type 1 diabetes with adequate glycaemic control. METHODS: This Swedish population-based cohort study was conducted using data from health registers from 1973 to 2013. We identified 8430 patients with childhood-onset type 1 diabetes (diagnosed before age 18 years) with a median age of diabetes onset of 9.6 (IQR 5.9-12.9) and 84,300 reference individuals from the general population, matched for sex, birth year and birth county. Cox models were used to estimate the effect of HbA1c on the risk of subsequent neurodevelopmental disorders, including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders (ASD) and intellectual disability. RESULTS: During a median follow-up period of 5.6 years, 398 (4.7%) individuals with type 1 diabetes received a diagnosis of any neurodevelopmental disorder compared with 3066 (3.6%) in the general population, corresponding to an adjusted HR (HRadjusted) of 1.31 (95% CI 1.18, 1.46) after additionally adjusting for other psychiatric morbidity prior to inclusion, parental psychiatric morbidity and parental highest education level. The risk of any neurodevelopmental disorder increased with HbA1c levels and the highest risk was observed in patients with mean HbA1c >8.6% (>70 mmol/mol) (HRadjusted 1.90 [95% CI 1.51, 2.37]) compared with reference individuals without type 1 diabetes. In addition, when compared with patients with diabetes with HbA1c <7.5% (<58 mmol/mol), patients with HbA1c >8.6% (>70 mmol/mol) had the highest risk of any neurodevelopmental disorder (HRadjusted 3.71 [95% CI 2.75, 5.02]) and of specific neurodevelopmental disorders including ADHD (HRadjusted 4.16 [95% CI 2.92, 5.94]), ASD (HRadjusted 2.84 [95% CI 1.52, 5.28]) and intellectual disability (HRadjusted 3.93 [95% CI 1.38, 11.22]). CONCLUSIONS/INTERPRETATION: Childhood-onset type 1 diabetes is associated with an increased risk of neurodevelopmental disorders, with the highest risk seen in individuals with poor glycaemic control. Routine neurodevelopmental follow-up visits should be considered in type 1 diabetes, especially in patients with poor glycaemic control.

Comparison between data-driven clusters and models based on clinical features to predict outcomes in type 2 diabetes: nationwide observational study.

AIMS/HYPOTHESIS: Research using data-driven cluster analysis has proposed five novel subgroups of diabetes based on six measured variables in individuals with newly diagnosed diabetes. Our aim was (1) to validate the existence of differing clusters within type 2 diabetes, and (2) to compare the cluster method with an alternative strategy based on traditional methods to predict diabetes outcomes. METHODS: We used data from the Swedish National Diabetes Register and included 114,231 individuals with newly diagnosed type 2 diabetes. k-means clustering was used to identify clusters based on nine continuous variables (age at diagnosis, HbA1c, BMI, systolic and diastolic BP, LDL- and HDL-cholesterol, triacylglycerol and eGFR). The elbow method was used to determine the optimal number of clusters and Cox regression models were used to evaluate mortality risk and risk of CVD events. The prediction models were compared using concordance statistics. RESULTS: The elbow plot, with values of k ranging from 1 to 10, showed a smooth curve without any clear cut-off points, making the optimal value of k unclear. The appearance of the plot was very similar to the elbow plot made from a simulated dataset consisting only of one cluster. In prediction models for mortality, concordance was 0.63 (95% CI 0.63, 0.64) for two clusters, 0.66 (95% CI 0.65, 0.66) for four clusters, 0.77 (95% CI 0.76, 0.77) for the ordinary Cox model and 0.78 (95% CI 0.77, 0.78) for the Cox model with smoothing splines. In prediction models for CVD events, the concordance was 0.64 (95% CI 0.63, 0.65) for two clusters, 0.66 (95% CI 0.65, 0.67) for four clusters, 0.77 (95% CI 0.77, 0.78) for the ordinary Cox model and 0.78 (95% CI 0.77, 0.78) for the Cox model with splines for all variables. CONCLUSIONS/INTERPRETATION: This nationwide observational study found no evidence supporting the existence of a specific number of distinct clusters within type 2 diabetes. The results from this study suggest that a prediction model approach using simple clinical features to predict risk of diabetes complications would be more useful than a cluster sub-stratification.

Use of incretin-based drugs and risk of cholangiocarcinoma: Scandinavian cohort study.

AIMS/HYPOTHESIS: Concerns have been raised regarding a potential association of use of the incretin-based drugs dipeptidyl peptidase 4 (DPP4) inhibitors and glucagon-like peptide-1 (GLP-1)-receptor agonists with risk of cholangiocarcinoma. We examined this association in nationwide data from three countries. METHODS: We used data from nationwide registers in Sweden, Denmark and Norway, 2007-2018, to conduct two cohort studies, one for DPP4 inhibitors and one for GLP-1-receptor agonists, to investigate the risk of incident cholangiocarcinoma compared with an active-comparator drug class (sulfonylureas). The cohorts included patients initiating treatment episodes with DPP4 inhibitors vs sulfonylureas, and GLP-1-receptor agonists vs sulfonylureas. We used Cox regression models, adjusted for potential confounders, to estimate hazard ratios from day 366 after treatment initiation to account for cancer latency. RESULTS: The main analyses of DPP4 inhibitors included 1,414,144 person-years of follow-up from 222,577 patients receiving DPP4 inhibitors (median [IQR] follow-up time, 4.5 [2.6-7.0] years) and 123,908 patients receiving sulfonylureas (median [IQR] follow-up time, 5.1 [2.9-7.8] years) during which 350 cholangiocarcinoma events occurred. Use of DPP4 inhibitors, compared with sulfonylureas, was not associated with a statistically significant increase in risk of cholangiocarcinoma (incidence rate 26 vs 23 per 100,000 person-years; adjusted HR, 1.15 [95% CI 0.90, 1.46]; absolute rate difference 3 [95% CI -3, 10] events per 100,000 person-years). The main analyses of GLP-1-receptor agonists included 1,036,587 person-years of follow-up from 96,813 patients receiving GLP-1-receptor agonists (median [IQR] follow-up time, 4.4 [2.4-6.9] years) and 142,578 patients receiving sulfonylureas (median [IQR] follow-up time, 5.5 [3.2-8.1] years) during which 249 cholangiocarcinoma events occurred. Use of GLP-1-receptor agonists was not associated with a statistically significant increase in risk of cholangiocarcinoma (incidence rate 26 vs 23 per 100,000 person-years; adjusted HR, 1.25 [95% CI 0.89, 1.76]; absolute rate difference 3 [95% CI -5, 13] events per 100,000 patient-years). CONCLUSIONS/INTERPRETATION: In this analysis using nationwide data from three countries, use of DPP4 inhibitors and GLP-1-receptor agonists, compared with sulfonylureas, was not associated with a significantly increased risk of cholangiocarcinoma.

Development and validation of a cardiovascular risk prediction model in type 1 diabetes.

AIMS/HYPOTHESIS: We aimed to report current rates of CVD in type 1 diabetes and to develop a CVD risk prediction tool for type 1 diabetes. METHODS: A cohort of 27,527 people with type 1 diabetes without prior CVD was derived from the national register in Scotland. Incident CVD events during 199,552 person-years of follow-up were ascertained using hospital admissions and death registers. A Poisson regression model of CVD was developed and then validated in the Swedish National Diabetes Register (n = 33,183). We compared the percentage with a high 10 year CVD risk (i.e., ≥10%) using the model with the percentage eligible for statins using current guidelines by age. RESULTS: The age-standardised rate of CVD per 100,000 person-years was 4070 and 3429 in men and women, respectively, with type 1 diabetes in Scotland, and 4014 and 3956 in men and women in Sweden. The final model was well calibrated (Hosmer-Lemeshow test p > 0.05) and included a further 22 terms over a base model of age, sex and diabetes duration (C statistic 0.82; 95% CI 0.81, 0.83). The model increased the base model C statistic from 0.66 to 0.80, from 0.60 to 0.75 and from 0.62 to 0.68 in those aged <40, 40-59 and ≥ 60 years, respectively (all p values <0.005). The model required minimal calibration in Sweden and had a C statistic of 0.85. Under current guidelines, >90% of those aged 20-39 years and 100% of those ≥40 years with type 1 diabetes were eligible for statins, but it was not until age 65 upwards that 100% had a modelled risk of CVD ≥10% in 10 years. CONCLUSIONS/INTERPRETATION: A prediction tool such as that developed here can provide individualised risk predictions. This 10 year CVD risk prediction tool could facilitate patient discussions regarding appropriate statin prescribing. Apart from 10 year risk, such discussions may also consider longer-term CVD risk, the potential for greater benefits from early vs later statin intervention, the potential impact on quality of life of an early CVD event and evidence on safety, all of which could influence treatment decisions, particularly in younger people with type 1 diabetes.

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.).

The burden of poor glycaemic control in people with newly diagnosed type 2 diabetes in Sweden: A health economic modelling analysis based on nationwide data.

AIM: To evaluate the economic and clinical burden associated with poor glycaemic control in Sweden, in people with type 2 diabetes (T2D) initiating first-line glucose-lowering therapy. MATERIALS AND METHODS: Population data were obtained from Swedish national registers. Immediate glycaemic control was compared with delays in achieving control of 1 and 3 years, with outcomes projected over 3, 10 and 50 years in the validated IQVIA CORE Diabetes Model. Glycaemic control was defined as glycated haemoglobin (HbA1c) targets of 52, 48 and 42 mmol/mol, as recommended in Swedish guidelines, according to age and disease duration. Costs (expressed in 2019 Swedish krona [SEK]) were accounted from a Swedish societal perspective. RESULTS: Immediate glycaemic control was associated with population-level cost savings of up to SEK 279 million and SEK 673 million versus delays of 1 and 3 years, respectively, as well as small population-level life expectancy benefits of up to 1305 and 2590 life years gained. Reduced levels of burden were a result of lower incidence and delayed time to onset of diabetes-related complications. CONCLUSIONS: Even in people with T2D initiating first-line glucose-lowering therapy, the economic burden of poor glycaemic control in Sweden is substantial, but could be reduced by early and effective treatment to achieve glycaemic targets.

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.).

Maternal Glycemic Control in Type 1 Diabetes and the Risk for Preterm Birth: A Population-Based Cohort Study.

Background: Maternal type 1 diabetes (T1D) has been linked to preterm birth and other adverse pregnancy outcomes. How these risks vary with glycated hemoglobin (or hemoglobin A1c [HbA1c]) levels is unclear. Objective: To examine preterm birth risk according to periconceptional HbA1c levels in women with T1D. Design: Population-based cohort study. Setting: Sweden, 2003 to 2014. Patients: 2474 singletons born to women with T1D and 1 165 216 reference infants born to women without diabetes. Measurements: Risk for preterm birth (<37 gestational weeks). Secondary outcomes were neonatal death, large for gestational age, macrosomia, infant birth injury, hypoglycemia, respiratory distress, 5-minute Apgar score less than 7, and stillbirth. Results: Preterm birth occurred in 552 (22.3%) of 2474 infants born to mothers with T1D versus 54 287 (4.7%) in 1 165 216 infants born to mothers without diabetes. The incidence of preterm birth was 13.2% in women with a periconceptional HbA1c level below 6.5% (adjusted risk ratio [aRR] vs. women without T1D, 2.83 [95% CI, 2.28 to 3.52]), 20.6% in those with a level from 6.5% to less than 7.8% (aRR, 4.22 [CI, 3.74 to 4.75]), 28.3% in those with a level from 7.8% to less than 9.1% (aRR, 5.56 [CI, 4.84 to 6.38]), and 37.5% in those with a level of 9.1% or higher (aRR, 6.91 [CI, 5.85 to 8.17]). The corresponding aRRs for medically indicated preterm birth (n = 320) were 5.26 (CI, 3.83 to 7.22), 7.42 (CI, 6.21 to 8.86), 11.75 (CI, 9.72 to 14.20), and 17.51 (CI, 14.14 to 21.69), respectively. The corresponding aRRs for spontaneous preterm birth (n = 223) were 1.81 (CI, 1.31 to 2.52), 2.86 (CI, 2.38 to 3.44), 2.88 (CI, 2.23 to 3.71), and 2.80 (CI, 1.94 to 4.03), respectively. Increasing HbA1c levels were associated with the study's secondary outcomes: large for gestational age, hypoglycemia, respiratory distress, low Apgar score, neonatal death, and stillbirth. Limitation: Because HbA1c levels were registered annually at routine visits, they were not available for all pregnant women with T1D. Conclusion: The risk for preterm birth was strongly linked to periconceptional HbA1c levels. Women with HbA1c levels consistent with recommended target levels also were at increased risk. Primary Funding Source: Swedish Diabetes Foundation.

Prediction of individual life-years gained without cardiovascular events from lipid, blood pressure, glucose, and aspirin treatment based on data of more than 500 000 patients with Type 2 diabetes mellitus.

AIMS: Although group-level effectiveness of lipid, blood pressure, glucose, and aspirin treatment for prevention of cardiovascular disease (CVD) has been proven by trials, important differences in absolute effectiveness exist between individuals. We aim to develop and validate a prediction tool for individualizing lifelong CVD prevention in people with Type 2 diabetes mellitus (T2DM) predicting life-years gained without myocardial infarction or stroke. METHODS AND RESULTS: We developed and validated the Diabetes Lifetime-perspective prediction (DIAL) model, consisting of two complementary competing risk adjusted Cox proportional hazards functions using data from people with T2DM registered in the Swedish National Diabetes Registry (n = 389 366). Competing outcomes were (i) CVD events (vascular mortality, myocardial infarction, or stroke) and (ii) non-vascular mortality. Predictors were age, sex, smoking, systolic blood pressure, body mass index, haemoglobin A1c, estimated glomerular filtration rate, non- high-density lipoprotein cholesterol, albuminuria, T2DM duration, insulin treatment, and history of CVD. External validation was performed using data from the ADVANCE, ACCORD, ASCOT and ALLHAT-LLT-trials, the SMART and EPIC-NL cohorts, and the Scottish diabetes register (total n = 197 785). Predicted and observed CVD-free survival showed good agreement in all validation sets. C-statistics for prediction of CVD were 0.83 (95% confidence interval: 0.83-0.84) and 0.64-0.65 for internal and external validation, respectively. We provide an interactive calculator at www.U-Prevent.com that combines model predictions with relative treatment effects from trials to predict individual benefit from preventive treatment. CONCLUSION: Cardiovascular disease-free life expectancy and effects of lifelong prevention in terms of CVD-free life-years gained can be estimated for people with T2DM using readily available clinical characteristics. Predictions of individual-level treatment effects facilitate translation of trial results to individual patients.

Correction to: Short-term progression of cardiometabolic risk factors in relation to age at type 2 diabetes diagnosis: a longitudinal observational study of 100,606 individuals from the Swedish National Diabetes Register.

Unfortunately, the symbols in Fig. 1 were incorrectly described in the legend.

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.