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.

Coronary angiography following transcatheter aortic valve replacement: Insights from the SWEDEHEART registry.

BACKGROUND: Transcatheter aortic valve replacement (TAVR) is the most common treatment in patients with symptomatic severe aortic stenosis (AS). As concomitant coronary artery disease is common in AS patients, access to the coronary arteries following TAVR is of increasing importance. OBJECTIVES: This study evaluated the incidence and risk factors for unplanned coronary angiography following TAVR and, using fluoroscopic time as a surrogate, analyzed the complexity of coronary artery cannulation. METHODS: All patients who underwent TAVR in Sweden between 2008 and 2022 were identified using the SWEDEHEART registry. The cumulative incidence of coronary angiography after TAVR was analyzed with mortality as a competing risk. Angiography and PCI complexity were analyzed using fluoroscopic time and compared across different transcatheter heart valve designs. RESULTS: Out of 9806 patients, 566 subsequently required coronary angiography. The incidence was highest for three-vessel and/or left main disease. Younger age, the extent of prior coronary artery disease, and peripheral vascular disease were associated with an increased risk of coronary angiography. Fluoroscopy time was increased in TAVR patients compared to the control group with the longest fluoroscopy times observed in cases involving supra-annular and self-expanding valves. CONCLUSIONS: The incidence of coronary angiography following TAVR is still low. Younger patients and patients with concomitant coronary artery disease have a higher risk. Procedural time is longer in patients with a previous THV replacement. As TAVR is emerging as the first-line treatment in patients with longer life expectancy, facilitating coronary access is an important factor when considering which THV device to implant.

Underlying reasons for sex difference in survival following out-of-hospital cardiac arrest: a mediation analysis.

AIMS: Previous studies have indicated a poorer survival among women following out-of-hospital cardiac arrest (OHCA), but the mechanisms explaining this difference remain largely uncertain.This study aimed to assess the survival after OHCA among women and men and explore the role of potential mediators, such as resuscitation characteristics, prior comorbidity, and socioeconomic factors. METHODS AND RESULTS: This was a population-based cohort study including emergency medical service-treated OHCA reported to the Swedish Registry for Cardiopulmonary Resuscitation in 2010-2020, linked to nationwide Swedish healthcare registries. The relative risks (RR) of 30-day survival were compared among women and men, and a mediation analysis was performed to investigate the importance of potential mediators. Total of 43 226 OHCAs were included, of which 14 249 (33.0%) were women. Women were older and had a lower proportion of shockable initial rhythm. The crude 30-day survival among women was 6.2% compared to 10.7% for men [RR 0.58, 95% confidence interval (CI) = 0.54-0.62]. Stepwise adjustment for shockable initial rhythm attenuated the association to RR 0.85 (95% CI = 0.79-0.91). Further adjustments for age and resuscitation factors attenuated the survival difference to null (RR 0.98; 95% CI = 0.92-1.05). Mediation analysis showed that shockable initial rhythm explained ∼50% of the negative association of female sex on survival. Older age and lower disposable income were the second and third most important variables, respectively. CONCLUSION: Women have a lower crude 30-day survival following OHCA compared to men. The poor prognosis is largely explained by a lower proportion of shockable initial rhythm, older age at presentation, and lower income.

Importance of hospital and clinical factors for early mortality in Takotsubo syndrome: Insights from the Swedish Coronary Angiography and Angioplasty Registry.

BACKGROUND: Takotsubo syndrome (TTS) is an acute heart failure syndrome with symptoms similar to acute myocardial infarction. TTS is often triggered by acute emotional or physical stress and is a significant cause of morbidity and mortality. Predictors of mortality in patients with TS are not well understood, and there is a need to identify high-risk patients and tailor treatment accordingly. This study aimed to assess the importance of various clinical factors in predicting 30-day mortality in TTS patients using a machine learning algorithm. METHODS: We analyzed data from the nationwide Swedish Coronary Angiography and Angioplasty Registry (SCAAR) for all patients with TTS in Sweden between 2015 and 2022. Gradient boosting was used to assess the relative importance of variables in predicting 30-day mortality in TTS patients. RESULTS: Of 3,180 patients hospitalized with TTS, 76.0% were women. The median age was 71.0 years (interquartile range 62-77). The crude all-cause mortality rate was 3.2% at 30 days. Machine learning algorithms by gradient boosting identified treating hospitals as the most important predictor of 30-day mortality. This factor was followed in significance by the clinical indication for angiography, creatinine level, Killip class, and age. Other less important factors included weight, height, and certain medical conditions such as hyperlipidemia and smoking status. CONCLUSIONS: Using machine learning with gradient boosting, we analyzed all Swedish patients diagnosed with TTS over seven years and found that the treating hospital was the most significant predictor of 30-day mortality.

Aetiology and predictors of outcome in non-shockable in-hospital cardiac arrest: A retrospective cohort study from the Swedish Registry for Cardiopulmonary Resuscitation.

BACKGROUND: Non-shockable in-hospital cardiac arrest (IHCA) is a condition with diverse aetiology, predictive factors, and outcome. This study aimed to compare IHCA with initial asystole or pulseless electrical activity (PEA), focusing specifically on their aetiologies and the significance of predictive factors. METHODS: Using the Swedish Registry of Cardiopulmonary Resuscitation, adult non-shockable IHCA cases from 2018 to 2022 (n = 5788) were analysed. Exposure was initial rhythm, while survival to hospital discharge was the primary outcome. A random forest model with 28 variables was used to generate permutation-based variable importance for outcome prediction. RESULTS: Overall, 60% of patients (n = 3486) were male and the median age was 75 years (IQR 67-81). The most frequent arrest location (46%) was on general wards. Comorbidities were present in 79% of cases and the most prevalent comorbidity was heart failure (33%). Initial rhythm was PEA in 47% (n = 2702) of patients, and asystole in 53% (n = 3086). The most frequent aetiologies in both PEA and asystole were cardiac ischemia (24% vs. 19%, absolute difference [AD]: 5.4%; 95% confidence interval [CI] 3.0% to 7.7%), and respiratory failure (14% vs. 13%, no significant difference). Survival was higher in asystole (24%) than in PEA (17%) (AD: 7.3%; 95% CI 5.2% to 9.4%). Cardiopulmonary resuscitation (CPR) durations were longer in PEA, 18 vs 15 min (AD 4.9 min, 95% CI 4.0-5.9 min). The duration of CPR was the single most important predictor of survival across all subgroup and sensitivity analyses. Aetiology ranked as the second most important predictor in most analyses, except in the asystole subgroup where responsiveness at cardiac arrest team arrival took precedence. CONCLUSIONS: In this nationwide registry study of non-shockable IHCA comparing asystole to PEA, cardiac ischemia and respiratory failure were the predominant aetiologies. Duration of CPR was the most important predictor of survival, followed by aetiology. Asystole was associated with higher survival compared to PEA, possibly due to shorter CPR durations and a larger proportion of reversible aetiologies.

ICURE: Intensive care unit (ICU) risk evaluation for 30-day mortality. Developing and evaluating a multivariable machine learning prediction model for patients admitted to the general ICU in Sweden.

BACKGROUND: A prediction model that estimates mortality at admission to the intensive care unit (ICU) is of potential benefit to both patients and society. Logistic regression models like Simplified Acute Physiology Score 3 (SAPS 3) and APACHE are the traditional ICU mortality prediction models. With the emergence of machine learning (machine learning) and artificial intelligence, new possibilities arise to create prediction models that have the potential to sharpen predictive accuracy and reduce the likelihood of misclassification in the prediction of 30-day mortality. METHODS: We used the Swedish Intensive Care Registry (SIR) to identify and include all patients ≥18 years of age admitted to general ICUs in Sweden from 2008 to 2022 with SAPS 3 score registered. Only data collected within 1 h of ICU admission was used. We had 153 candidate predictors including baseline characteristics, previous medical conditions, blood works, physiological parameters, cause of admission, and initial treatment. We stratified the data randomly on the outcome variable 30-day mortality and created a training set (80% of data) and a test set (20% of data). We evaluated several hundred prediction models using multiple ML frameworks including random forest, gradient boosting, neural networks, and logistic regression models. Model performance was evaluated by comparing the receiver operator characteristic area under the curve (AUC-ROC). The best performing model was fine-tuned by optimizing hyperparameters. The model's calibration was evaluated by a calibration belt. Ultimately, we simplified the best performing model with the top 1-20 predictors. RESULTS: We included 296,344 first-time ICU admissions. We found age, Glasgow Coma Scale, creatinine, systolic blood pressure, and pH being the most important predictors. The AUC-ROC was 0.884 in test data using all predictors, specificity 95.2%, sensitivity 47.0%, negative predictive value of 87.9% and positive predictive value of 70.7%. The final model showed excellent calibration. The ICU risk evaluation for 30-day mortality (ICURE) prediction model performed equally well to the SAPS 3 score with only eight variables and improved further with the addition of more variables. CONCLUSION: The ICURE prediction model predicts 30-day mortality rate at first-time ICU admission superiorly compared to the established SAPS 3 score.

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.

Fatty liver disease, heart rate and cardiac remodelling: Evidence from the UK Biobank.

BACKGROUND AND AIMS: Growing evidence supports an association between fatty liver disease (FLD) and cardiac dysfunction and remodelling, leading to cardiovascular disease and heart failure. Herein, we investigated the independent contribution of FLD to cardiac dysfunction and remodelling in participants from the UK Biobank with cardiac magnetic resonance (CMR) data available. METHODS: A total of 18 848 Europeans without chronic viral hepatitis and valvular heart diseases, with liver magnetic resonance imaging and CMR data were included in the analyses. Clinical, laboratory and imaging data were collected using standardized procedures. Multivariable regression models were used to test the association between FLD and CMR endpoints, after adjusting for several cardiometabolic risk factors. Linear regression models with regularization (Least Absolute Shrinkage and Selection Operator [LASSO], Ridge and Elastic Net) were used to generate predictive models for heart-related endpoints. RESULTS: FLD was independently associated with higher average heart rate, higher cardiac remodelling (higher eccentricity ratio and lower remodelling index), lower left and right ventricular volumes (end-systolic, end-diastolic and stroke volumes) as well as with lower left and right atrial maximal volumes (p < 0.001). FLD was the strongest positive predictor for average heart rate, followed by age, hypertension and type 2 diabetes. Male sex was the strongest positive predictor for eccentricity ratio followed by FLD, age, hypertension and BMI. For LV volumes, FLD was the strongest negative predictor along with age. CONCLUSIONS: FLD is an independent predictor of higher heart rate and early cardiac remodelling associated with reduced ventricular volumes.

Trends in survival after cardiac arrest: a Swedish nationwide study over 30 years.

AIMS: Trends in characteristics, management, and survival in out-of-hospital cardiac arrest (OHCA) and in-hospital cardiac arrest (IHCA) were studied in the Swedish Cardiopulmonary Resuscitation Registry (SCRR). METHODS AND RESULTS: The SCRR was used to study 106 296 cases of OHCA (1990-2020) and 30 032 cases of IHCA (2004-20) in whom resuscitation was attempted. In OHCA, survival increased from 5.7% in 1990 to 10.1% in 2011 and remained unchanged thereafter. Odds ratios [ORs, 95% confidence interval (CI)] for survival in 2017-20 vs. 1990-93 were 2.17 (1.93-2.43) overall, 2.36 (2.07-2.71) for men, and 1.67 (1.34-2.10) for women. Survival increased for all aetiologies, except trauma, suffocation, and drowning. OR for cardiac aetiology in 2017-20 vs. 1990-93 was 0.45 (0.42-0.48). Bystander cardiopulmonary resuscitation increased from 30.9% to 82.2%. Shockable rhythm decreased from 39.5% in 1990 to 17.4% in 2020. Use of targeted temperature management decreased from 42.1% (2010) to 18.2% (2020). In IHCA, OR for survival in 2017-20 vs. 2004-07 was 1.18 (1.06-1.31), showing a non-linear trend with probability of survival increasing by 46.6% during 2011-20. Myocardial ischaemia or infarction as aetiology decreased during 2004-20 from 67.4% to 28.3% [OR 0.30 (0.27-0.34)]. Shockable rhythm decreased from 37.4% to 23.0% [OR 0.57 (0.51-0.64)]. Approximately 90% of survivors (IHCA and OHCA) had no or mild neurological sequelae. CONCLUSION: Survival increased 2.2-fold in OHCA during 1990-2020 but without any improvement in the final decade, and 1.2-fold in IHCA during 2004-20, with rapid improvement the last decade. Cardiac aetiology and shockable rhythms were halved. Neurological outcome has not improved.

Inequalities in Income and Education Are Associated With Survival Differences After Out-of-Hospital Cardiac Arrest: Nationwide Observational Study.

BACKGROUND: Despite the acknowledged importance of socioeconomic factors as regards cardiovascular disease onset and survival, the relationship between individual-level socioeconomic factors and survival after out-of-hospital cardiac arrest is not established. Our aim was to investigate whether socioeconomic variables are associated with 30-day survival after out-of-hospital cardiac arrest. METHODS: We linked data from the Swedish Registry for Cardiopulmonary Resuscitation with individual-level data on socioeconomic factors (ie, educational level and disposable income) from Statistics Sweden. Confounding and mediating variables included demographic factors, comorbidity, and Utstein resuscitation variables. Outcome was 30-day survival. Multiple modified Poisson regression was used for the main analyses. RESULTS: A total of 31 373 out-of-hospital cardiac arrests occurring in 2010 to 2017 were included. Crude 30-day survival rates by income quintiles were as follows: Q1 (low), 414/6277 (6.6%); Q2, 339/6276 (5.4%); Q3, 423/6275 (6.7%); Q4, 652/6273 (10.4%); and Q5 (high), 928/6272 (14.8%). In adjusted analysis, the chance of survival by income level followed a gradient-like increase, with a risk ratio of 1.86 (95% CI, 1.65-2.09) in the highest-income quintile versus the lowest. This association remained after adjusting for comorbidity, resuscitation factors, and initial rhythm. A higher educational level was associated with improved 30-day survival, with the risk ratio associated with postsecondary education ≥4 years being 1.51 (95% CI, 1.30-1.74). Survival disparities by income and educational level were observed in both men and women. CONCLUSIONS: In this nationwide observational study using individual-level socioeconomic data, higher income and higher educational level were associated with better 30-day survival after out-of-hospital cardiac arrest in both sexes.

Better outcomes from exercise-related out-of-hospital cardiac arrest in males and in the young: findings from the Swedish Registry of Cardiopulmonary Resuscitation.

BACKGROUND: Survival from out-of-hospital cardiac arrest (OHCA) is higher if the arrest is witnessed and occurs during exercise, however, there is contradicting data on prognosis with regards to sex and age. The purpose of this study was to compare the outcomes and circumstances of exercise-related OHCA in different age groups and between sexes in a large unselected population. METHODS: Data from exercise-related OHCAs reported to the Swedish Registry of Cardiopulmonary Resuscitation from 2011 to 2014 and from 2016 to 2018 were analysed. All cases of exercise-related OHCA in which emergency medical services attempted resuscitation were included. The primary outcome was survival to 30 days. RESULTS: In total, 635 cases of exercise-related OHCA outside of the home were identified. The overall 30-day survival rate was 44.5% with highest survival rate in the age group 0-35 years, compared with 36-65 years and >65 years (59.6% vs 46.0% and 40.4%, p=0.01). A subgroup analysis of 0-25 years showed a survival rate of 68.8%. Exercise-related OHCA in females (9.1% of total) were witnessed to a lower extent (66.7% vs 79.6%, p=0.03) and median time to cardiopulmonary resuscitation (CPR) was longer (2.0 vs 1.0 min, p=0.001) than in males. Females also had lower rates of ventricular fibrillation (43.4% vs 64.7%, p=0.003) and a lower 30-day survival rate (29.3% vs 46.0%, p=0.02). CONCLUSION: In exercise-related OHCA, younger victims have a higher survival rate. Exercise-related OHCA in females was rare, however, survival rates were lower compared with males and partly explained by a lower proportion of witnessed events, longer time to CPR and lower frequency of a shockable rhythm.

The role of admission electrocardiogram in predicting outcome in patients hospitalized for COVID-19.

BACKGROUND: Abnormal electrocardiogram (ECG) has been associated with poor outcome in patients hospitalized for COVID-19. However, the independent association between admission ECG and the risk of a poor outcome remains to be established. Our aim was to determine if abnormal admission ECG predicts treatment at intensive care unit or in-hospital death within 30 days in patients hospitalized for COVID-19. METHODS: We analyzed the propensity weighted association between abnormal admission ECG and outcome in patients hospitalized for COVID-19 (March to May 2020). All adult patients hospitalized for COVID-19 at the three centers of Sahlgrenska University Hospital (Gothenburg, Sweden) were eligible for inclusion (N = 439). Patients with available admission ECG within six hours from admission were included. RESULTS: 238 patients (age 62 ± 16 years, 74% male) were included. 103 patients had normal ECG and 135 patients had abnormal ECG. 99 patients were admitted to intensive care unit or died in-hospital within 30 days. Abnormal ECG was associated with increased risk of the outcome (odds ratio 2.11 [95% confidence interval 1.21-3.66]). CONCLUSIONS: Abnormal admission ECG was associated with increased risk of treatment at intensive care unit or in-hospital death within 30 days; and could be considered a high-risk criterion in patients hospitalized for COVID-19.

Cardiac arrest in COVID-19: characteristics and outcomes of in- and out-of-hospital cardiac arrest. A report from the Swedish Registry for Cardiopulmonary Resuscitation.

AIM: To study the characteristics and outcome among cardiac arrest cases with COVID-19 and differences between the pre-pandemic and the pandemic period in out-of-hospital cardiac arrest (OHCA) and in-hospital cardiac arrest (IHCA). METHOD AND RESULTS: We included all patients reported to the Swedish Registry for Cardiopulmonary Resuscitation from 1 January to 20 July 2020. We defined 16 March 2020 as the start of the pandemic. We assessed overall and 30-day mortality using Cox regression and logistic regression, respectively. We studied 1946 cases of OHCA and 1080 cases of IHCA during the entire period. During the pandemic, 88 (10.0%) of OHCAs and 72 (16.1%) of IHCAs had ongoing COVID-19. With regards to OHCA during the pandemic, the odds ratio for 30-day mortality in COVID-19-positive cases, compared with COVID-19-negative cases, was 3.40 [95% confidence interval (CI) 1.31-11.64]; the corresponding hazard ratio was 1.45 (95% CI 1.13-1.85). Adjusted 30-day survival was 4.7% for patients with COVID-19, 9.8% for patients without COVID-19, and 7.6% in the pre-pandemic period. With regards to IHCA during the pandemic, the odds ratio for COVID-19-positive cases, compared with COVID-19-negative cases, was 2.27 (95% CI 1.27-4.24); the corresponding hazard ratio was 1.48 (95% CI 1.09-2.01). Adjusted 30-day survival was 23.1% in COVID-19-positive cases, 39.5% in patients without COVID-19, and 36.4% in the pre-pandemic period. CONCLUSION: During the pandemic phase, COVID-19 was involved in at least 10% of all OHCAs and 16% of IHCAs, and, among COVID-19 cases, 30-day mortality was increased 3.4-fold in OHCA and 2.3-fold in IHCA.

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 BAriatic surgery SUbstitution and nutrition (BASUN) population: a data-driven exploration of predictors for obesity.

BACKGROUND: The development of obesity is most likely due to a combination of biological and environmental factors some of which might still be unidentified. We used a machine learning technique to examine the relative importance of more than 100 clinical variables as predictors for BMI. METHODS: BASUN is a prospective non-randomized cohort study of 971 individuals that received medical or surgical treatment (treatment choice was based on patient's preferences and clinical criteria, not randomization) for obesity in the Västra Götaland county in Sweden between 2015 and 2017 with planned follow-up for 10 years. This study includes demographic data, BMI, blood tests, and questionnaires before obesity treatment that cover three main areas: gastrointestinal symptoms and eating habits, physical activity and quality of life, and psychological health. We used random forest, with conditional variable importance, to study the relative importance of roughly 100 predictors of BMI, covering 15 domains. We quantified the predictive value of each individual predictor, as well as each domain. RESULTS: The participants received medical (n = 382) or surgical treatment for obesity (Roux-en-Y gastric bypass, n = 388; sleeve gastrectomy, n = 201). There were minor differences between these groups before treatment with regard to anthropometrics, laboratory measures and results from questionnaires. The 10 individual variables with the strongest predictive value, in order of decreasing strength, were country of birth, marital status, sex, calcium levels, age, levels of TSH and HbA1c, AUDIT score, BE tendencies according to QEWPR, and TG levels. The strongest domains predicting BMI were: Socioeconomic status, Demographics, Biomarkers (notably TSH), Lifestyle/habits, Biomarkers for cardiovascular disease and diabetes, and Potential anxiety and depression. CONCLUSIONS: Lifestyle, habits, age, sex and socioeconomic status are some of the strongest predictors for BMI levels. Potential anxiety and / or depression and other characteristics captured using questionnaires have strong predictive value. These results confirm previously suggested associations and advocate prospective studies to examine the value of better characterization of patients eligible for obesity treatment, and consequently to evaluate the treatment effects in groups of patients. TRIAL REGISTRATION: March 03, 2015; NCT03152617 .

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.).

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.