In T1DM without CVD, the LIFE-T1D model predicted lifetime risk for CVD and non-CVD mortality.

SOURCE CITATION: Helmink MAG, Hageman SHJ, Eliasson B, et al. Lifetime and 10-year cardiovascular risk prediction in individuals with type 1 diabetes: the LIFE-T1D model. Diabetes Obes Metab. 2024;26:2229-2238. 38456579.

Major cardiovascular events and death in parents of children with type 1 diabetes: a register-based matched cohort study in Sweden.

AIMS/HYPOTHESIS: Parenting a child with type 1 diabetes has been associated with stress-related symptoms. This study aimed to elucidate the potential impact on parental risk of major cardiovascular events (MCE) and death. METHODS: In this register-based study, we included the parents of 18,871 children, born 1987-2020 and diagnosed with type 1 diabetes in Sweden at <18 years. The median parental age at the child's diagnosis was 39.0 and 41.0 years for mothers and fathers, respectively. The cohort also encompassed 714,970 population-based matched parental control participants and 12,497 parental siblings. Cox proportional hazard regression models were employed to investigate the associations between having a child with type 1 diabetes and incident MCE and all-cause death, and, as secondary outcomes, acute coronary syndrome and ischaemic heart disease (IHD). We adjusted for potential confounders including parental type 1 diabetes and country of birth. RESULTS: During follow-up (median 12 years, range 0-35), we detected no associations between parenting a child with type 1 diabetes and MCE in mothers (adjusted HR [aHR] 1.02; 95% CI 0.90, 1.15) or in fathers (aHR 1.01; 95% CI 0.94, 1.08). We noted an increased hazard of IHD in exposed mothers (aHR 1.21; 95% CI 1.05, 1.41) with no corresponding signal in fathers (aHR 0.97; 95% CI 0.89, 1.05). Parental sibling analysis did not confirm the association in exposed mothers (aHR 1.01; 95% CI 0.73, 1.41). We further observed a slightly increased hazard of all-cause death in exposed fathers (aHR 1.09; 95% CI 1.01, 1.18), with a similar but non-significant estimate noted in exposed mothers (aHR 1.07; 95% CI 0.96, 1.20). The estimates from the sibling analyses of all-cause death in fathers and mothers were 1.12 (95% CI 0.90, 1.38) and 0.73 (95% CI 0.55, 0.96), respectively. CONCLUSIONS/INTERPRETATION: Having a child diagnosed with type 1 diabetes in Sweden was not associated with MCE, but possibly with all-cause mortality. Further studies are needed to disentangle potential underlying mechanisms, and to investigate parental health outcomes across the full lifespan.

Unseen threat: how subclinical atherosclerosis increases mortality risk in patients with type 1 diabetes.

BACKGROUND: Cardiovascular disease (CVD), particularly ischemic heart disease, remains the leading cause of death and morbidity in patients with type 1 diabetes. Detecting subclinical atherosclerosis could enhance cardiovascular risk stratification and enable individualised therapies. The aim of this study is to investigate the prevalence and predictors of subclinical atherosclerosis in patients with type 1 diabetes without overt cardiovascular disease (CVD) and to assess its impact on patient survival over a follow-up period of at least 5 years. METHODS: This observational study included 507 patients treated at the Diabetes Unit of the Hospital of Girona Doctor Josep Trueta between 2015 and 2023. The inclusion criteria for patients were as follows: those aged 18 and older with diabetes for a minimum of 10 years or those aged 40 and older with a diabetes for at least 5 years. Subclinical atherosclerosis was identified via ultrasound imaging of the carotid and femoral arteries. Clinical and biochemical evaluations were also conducted. Major cardiovascular events (MACE) and deaths from other causes were monitored, and survival analysis was performed using Kaplan‒Meier methods. RESULTS: Subclinical atherosclerosis was detected in 218 patients (43%). Multivariate analysis revealed that the male sex, diabetic nephropathy, tobacco exposure, higher HbA1c levels, older age, and longer diabetes duration were significant predictors. During a mean follow-up of 70.64 ± 27.08 months, 19 patients experienced MACE, and 13 died from any cause. The probability of MACE or death was greater in patients with subclinical atherosclerosis, with a hazard ratio (HR) of 25.1 (95% CI 5.81-108, p < 0.001) for MACE and an odds ratio (OR) of 7.57 (95% CI 1.97-53.9, p = 0.004) for death. CONCLUSION: Subclinical atherosclerosis is independently associated with increased overall mortality and MACE in patients with type 1 diabetes. Identifying clinical predictors can improve risk stratification and personalised therapeutic strategies to prevent MACEs in this high-risk population.

Excessive occupational sitting increases risk of cardiovascular events among working individuals with type 1 diabetes in the prospective Finnish Diabetic Nephropathy Study.

BACKGROUND: Sedentary behavior, such as excessive sitting, increases risk of cardiovascular disease and premature mortality in the general population, but this has not been assessed in type 1 diabetes. Occupational sitting is increasingly ubiquitous and often constitutes the largest portion of daily sitting time. Our aim was to identify clinical factors associated with excessive occupational sitting in type 1 diabetes and, in a prospective setting, to explore its association with cardiovascular events and all-cause mortality, independent of leisure-time physical activity. METHODS: An observational follow-up study of 1,704 individuals (mean age 38.9 ± 10.1 years) from the Finnish Diabetic Nephropathy Study. Excessive occupational sitting, defined as ≥ 6 h of daily workplace sitting, was assessed using a validated self-report questionnaire. Data on cardiovascular events and mortality were retrieved from national registries. Multivariable logistic regression identified independently associated factors, while Kaplan-Meier curves and Cox proportional hazard models were used for prospective analyses. RESULTS: Factors independently and positively associated with excessive occupational sitting included a high occupational category [OR 6.53, 95% CI (4.09‒10.40)] and older age [1.02 (1.00‒1.03)], whereas negatively associated factors included current smoking [0.68 (0.50‒0.92)], moderate albuminuria [0.55 (0.38‒0.80)], and high leisure-time physical activity [0.52 (0.36‒0.74)]. During a median follow-up of 12.5 (6.5-16.4) years, 163 individuals (9.6%) suffered cardiovascular events, and during a median follow-up of 13.7 (9.4-16.6) years, 108 (6.3%) deaths occurred. Excessive occupational sitting increased cardiovascular event risk (hazard ratio [HR] 1.55 [95% CI 1.10‒2.18]) after adjustment for confounders and other covariates. Furthermore, in a stratified multivariable analysis among current smokers, excessive occupational sitting increased the risk of all-cause mortality (2.06 [1.02‒4.20]). CONCLUSIONS: Excessive occupational sitting is associated with a higher risk of cardiovascular events and all-cause mortality in individuals with type 1 diabetes. This association persists regardless of leisure-time physical activity, after adjusting for independently associated variables identified in our cross-sectional analyses. These findings underscore the need to update physical activity guidelines to better address sedentary behavior and improve outcomes for individuals with type 1 diabetes. Targeting occupational sitting should be considered a key focus for interventions aimed at reducing overall sedentary time.

A high-volume study on the impact of diabetes mellitus on clinical outcomes after surgical and percutaneous cardiac interventions.

BACKGROUND: Type I and type II diabetes mellitus (DM) patients have a higher prevalence of cardiovascular diseases, as well as a higher mortality risk of cardiovascular diseases and interventions. This study provides an update on the impact of DM on clinical outcomes, including mortality, complications and reinterventions, using data on percutaneous and surgical cardiac interventions in the Netherlands. METHODS: This is a retrospective, nearby nationwide study using real-world observational data registered by the Netherlands Heart Registration (NHR) between 2015 and 2020. Patients treated for combined or isolated coronary artery disease (CAD) and aortic valve disease (AVD) were studied. Bivariate analyses and multivariate logistic regression models were used to evaluate the association between DM and clinical outcomes both unadjusted and adjusted for baseline characteristics. RESULTS: 241,360 patients underwent the following interventions; percutaneous coronary intervention(N = 177,556), coronary artery bypass grafting(N = 39,069), transcatheter aortic valve implantation(N = 11,819), aortic valve replacement(N = 8,028) and combined CABG and AVR(N = 4,888). The incidence of DM type I and II was 21.1%, 26.7%, 17.8%, 27.6% and 27% respectively. For all procedures, there are statistically significant differences between patients living with and without diabetes, adjusted for baseline characteristics, at the expense of patients with diabetes for 30-days mortality after PCI (OR = 1.68; p <.001); 120-days mortality after CABG (OR = 1.35; p <.001), AVR (OR = 1.5; p <.03) and CABG + AVR (OR = 1.42; p =.02); and 1-year mortality after CABG (OR = 1.43; p <.001), TAVI (OR = 1.21; p =.01) and PCI (OR = 1.68; p <.001). CONCLUSION: Patients with DM remain to have unfavourable outcomes compared to nondiabetic patients which calls for a critical reappraisal of existing care pathways aimed at diabetic patients within the cardiovascular field.

An observational study of therapeutic procedures and in-hospital outcomes among patients admitted for acute myocardial infarction in Spain, 2016-2022: the role of diabetes mellitus.

BACKGROUND: We used the Spanish national hospital discharge data from 2016 to 2022 to analyze procedures and hospital outcomes among patients aged ≥ 18 years admitted for ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI) according to diabetes mellitus (DM) status (non-diabetic, type 1-DM or type 2-DM). METHODS: We built logistic regression models for STEMI/NSTEMI stratified by DM status to identify variables associated with in-hospital mortality (IHM). We analyzed the effect of DM on IHM. RESULTS: Spanish hospitals reported 201,950 STEMIs (72.7% non-diabetic, 0.5% type 1-DM, and 26.8% type 2-DM; 26.3% female) and 167,285 NSTEMIs (61.6% non-diabetic, 0.6% type 1-DM, and 37.8% type 2-DM; 30.9% female). In STEMI, the frequency of percutaneous coronary intervention (PCI) increased among non-diabetic people (60.4% vs. 68.6%; p < 0.001) and people with type 2-DM (53.6% vs. 66.1%; p < 0.001). In NSTEMI, the frequency of PCI increased among non-diabetic people (43.7% vs. 45.7%; p < 0.001) and people with type 2-DM (39.1% vs. 42.8%; p < 0.001). In NSTEMI, the frequency of coronary artery by-pass grafting (CABG) increased among non-diabetic people (2.8% vs. 3.5%; p < 0.001) and people with type 2-DM (3.7% vs. 5.0%; p < 0.001). In the entire population, lower IHM was associated with undergoing PCI (odds ratio [OR] [95% confidence interval] = 0.34 [0.32-0.35] in STEMI; 0.24 [0.23-0.26] in NSTEMI) or CABG (0.33 [0.27-0.40] in STEMI; 0.45 [0.38-0.53] in NSTEMI). IHM decreased over time in STEMI (OR = 0.86 [0.80-0.93]). Type 2-DM was associated with higher IHM in STEMI (OR = 1.06 [1.01-1.11]). CONCLUSIONS: PCI and CABG were associated with lower IHM in people admitted for STEMI/NSTEMI. Type 2-DM was associated with IHM in STEMI.

Trends in hospitalization for cardio-renal disease and mortality in people with type 1 diabetes in England, 2009-2019.

AIM: To assess mortality and complication trends in people with type 1 diabetes during the 11 years before the SARS-CoV2 pandemic (2009-2019). MATERIALS AND METHODS: Sequential cohorts of people in England with type 1 diabetes aged ≥20 years from the National Diabetes Audit (2006/2007 to 2016/2017) were analysed. Discretized Poisson regression models, adjusted for age, sex, ethnicity, socioeconomic deprivation and duration of diabetes, were used to calculate mortality and hospitalization rates. RESULTS: Demographic characteristics changed little; average diabetes duration increased. All-cause mortality was unchanged. Cardiovascular and kidney disease mortality declined. Mortality from respiratory disease, diabetes and dementia increased in younger people (aged 20-74 years) as did mortality from liver disease and dementia in the elderly (aged ≥75 years). Younger Asian and Black people had lower all-cause mortality than those of White ethnicity; elderly Mixed, Asian and Black people had lower all-cause mortality. People from more deprived areas had higher all-cause mortality. The deprivation gradient for mortality was steeper at younger ages. In younger people, rates of hospitalization increased for myocardial infarction, stroke, heart failure and kidney disease but only for kidney disease in the elderly. Rates of a composite measure of cardiovascular hospitalizations increased in younger people (rate ratio [RR] 1.07, 95% confidence interval [CI] 1.03-1.11) but declined in the elderly (RR 0.91, 95% CI 0.86-0.95). CONCLUSION: Between 2009 and 2019, hospitalizations for cardiovascular disease increased at younger ages (20-74 years) and hospitalizations for kidney disease increased at all ages, but mortality from cardiovascular and kidney disease declined. All-cause mortality rates were unchanged.

Mortality patterns in Dutch diabetes outpatients.

AIM: Diabetes mellitus is a major cause of death. Outpatients with diabetes have more complications than patients in general practice; mortality patterns have only been studied in the total diabetes population. This study aims to assess mortality, causes, and predictors in outpatients with diabetes. MATERIALS AND METHODS: A cohort study, included people with diabetes mellitus from the nationwide Dutch Paediatric and Adult Registry of Diabetes (DPARD) visiting diabetes outpatient clinics in 2016-2020. DPARD data were linked to Statistics Netherlands (CBS), comprising data on mortality, ethnicity and education. All-cause and cardiovascular mortality rates were estimated using Cox proportional hazard regression. RESULTS: During a median follow-up of 3.1 years among 12 992 people with diabetes, mortality rates per 10 000 person-years were 67.7 in adult type 1 diabetes and 324.2 in type 2 diabetes. The major cause of non-cardiovascular death was malignancy. During the pandemic years of influenza (2018) and COVID (2020), mortality rates peaked. Age, smoking and an estimated glomerular filtration rate of <60 ml/min were associated with all-cause mortality. In type 2 diabetes, additional factors were male sex, body mass index <20 kg/m2, diabetes duration <1 year and hypertension. CONCLUSIONS: Mortality among Dutch outpatients with diabetes is high. Smoking and renal failure were associated with mortality in both types. Further focus on early detection and treatment of mortality-associated factors may improve clinical outcomes.

All-cause, premature, and cardiovascular death attributable to socioeconomic and ethnic disparities among New Zealanders with type 1 diabetes 1994-2019: a multi-linked population-based cohort study.

BACKGROUND: New Zealand (NZ) research into type 1 diabetes mellitus (T1DM) mortality can inform policy and future research. In this study we aimed to quantify the magnitude to which ethnicity and socioeconomic disparities influenced mortality at the population level among people with Type 1 diabetes (T1DM) in Auckland, New Zealand (NZ). METHODS: The cohort data were derived from the primary care diabetes audit program the Diabetes Care Support Service (DCSS), and linked with national primary care, pharmaceutical claims, hospitalisation, and death registration databases. People with T1DM enrolled in DCSS between 1994-2018 were included. All-cause, premature, and cardiovascular mortalities were estimated by Poisson regression models with adjustment for population-level confounders. The mortality rates ratio (MRR) was standardized against the DCSS type 2 diabetes population. Mortality rates were compared by ethnic group (NZ European (NZE) and non-NZE) and socioeconomic deprivation quintile. The population attributable fraction (PAF) was estimated for ethnic and socioeconomic disparities by Cox regression adjusting for demographic, lifestyle, and clinical covariates. The adjusted slope index inequality (SII) and relative index of inequality (RII) were used to measure the socioeconomic disparity in mortalities. RESULTS: Overall, 2395 people with T1DM (median age 34.6 years; 45% female; 69% NZE) were enrolled, among whom the all-cause, premature and CVD mortalities were 6.69 (95% confidence interval: 5.93-7.53), 3.30 (2.77-3.90) and 1.77 (1.39-2.23) per 1,000 person-years over 25 years. The overall MRR was 0.39 (0.34-0.45), 0.65 (0.52-0.80), and 0.31 (0.24-0.41) for all-cause, premature and CVD mortality, respectively. PAF attributable to ethnicity disparity was not significantly different for mortality. The adjusted PAF indicated that 25.74 (0.84-44.39)% of all-cause mortality, 25.88 (0.69-44.69)% of premature mortality, 55.89 (1.20-80.31)% of CVD mortality could be attributed to socioeconomic inequality. The SII was 8.04 (6.30-9.78), 4.81 (3.60-6.02), 2.70 (1.82-3.59) per 1,000 person-years and RII was 2.20 (1.94-2.46), 2.46 (2.09-2.82), and 2.53 (2.03-3.03) for all-cause, premature and CVD mortality, respectively. CONCLUSIONS: Our results suggest that socioeconomic disparities were responsible for a substantial proportion of all-cause, premature and CVD mortality in people with T1DM in Auckland, NZ. Reducing socioeconomic barriers to management and self-management would likely improve clinical outcomes.

Risk of cancer in young and middle-aged adults with childhood-onset type 1 diabetes in Sweden-A prospective cohort study.

AIMS/HYPOTHESIS: In persons with type 1 diabetes, the risk of cancer remains controversial. We wanted to examine the excess risk of cancer in a large population-based cohort diagnosed with type 1 diabetes before 15 years of age. STUDY POPULATION AND METHODS: From 1 July 1977 to 31 December 2013, we prospectively and on a national scale included 18,724 persons (53% men) with childhood-onset type 1 diabetes. For each person with type 1 diabetes, we selected four referents, matched for the date at birth and municipality of living at the time when the case developed diabetes. Cases and referents were linked to national registers of cancer and of the cause of death. RESULTS: A total of 125 persons (61% women) with diabetes had 135 different cancers, all diagnosed after the diabetes diagnosis. The median duration from diabetes diagnosis to first cancer diagnosis was 19 years (interquartile range 10-26). The median age at cancer diagnosis in the diabetes group was 28 years (interquartile range 20-35). The overall standardized incidence ratio (95%), using the Swedish general population as referents for women with diabetes was 1.28 (1.02, 1.58) and when comparing women with diabetes with matched referents, we found a hazard ratio of 1.42 (1.10, 1.85). No elevated risk was seen for men. Cancers of the breast and testis were the most common types in women and men respectively. CONCLUSIONS: Women with childhood-onset type 1 diabetes had a small but significantly elevated risk of cancer. No such tendency was seen for men. The reason behind this is unclear.

Mortality amongst children and adolescents with type 1 diabetes in sub-Saharan Africa: The case study of the Changing Diabetes in Children program in Cameroon.

INTRODUCTION: Type 1 diabetes in Africa has been associated with high mortality attributed mainly to poor insulin access. Free insulin provision programs for people with type 1 diabetes have been introduced across Africa recently. We aimed to determine the mortality rate and associated factors in a cohort of children and adolescents with type 1 diabetes who receive free insulin treatment in sub-Saharan Africa. METHODS: We conducted a retrospective analysis using the Changing Diabetes in Children (CDiC) medical records in Cameroon between 2011 and 2015. RESULTS: The overall mortality rate was 33.0 per 1000 person-years (95% CI 25.2-43.2). Most deaths (71.7%) occurred outside of the hospital setting, and the cause of death was known only in 13/53 (24.5%). Mortality was substantially higher in CDiC participants followed up in regional clinics compared to the main urban CDiC clinic in Yaounde; 41 per 1000 years (95% CI 30.8-56.0) versus 17.5 per 1000 years (95% CI 9.4-32.5), and in those with no formal education compared to those who had some level of education; 68.0 per 1000 years (95% CI 45.1-102.2) versus 23.6 per 1000 years (95% CI 16.5-33.8). In Cox proportional multivariable analysis, urban place of care (HR = 0.23, 95% CI 0.09-0.57; p = 0.002) and formal education (HR = 0.42, 95% CI 0.22-0.79; p = 0.007) were independently associated with mortality. CONCLUSION: Despite free insulin provision, mortality remains high in children and adolescents with type 1 diabetes in Cameroon and is substantially higher in rural settings and those with no formal education.

Time trend in excess mortality in children with type 1 diabetes from 1987 to 2016 in mainland France.

BACKGROUND: Mortality risk for children with type 1 diabetes (T1D) is unknown in France and their causes of death are not well documented. AIM: To determine the standardized mortality ratios (SMRs) and causes of death in children aged 1-14 years with T1D from 1987 to 2016. METHODS: The French Center for Epidemiology on Medical Causes of Death collected all death certificates in mainland France. SMRs, corrected SMRs (accounting for missing cases of deaths unrelated to diabetes), and 95% confidence intervals were calculated. RESULTS: Of 146 deaths with the contribution of diabetes, 97 were due to T1D. Mean age at death of the subjects with T1D was 8.8 ± 4.1 years (54% males). The cause of death was diabetic ketoacidosis (DKA) in 58% of the cases (70% in subjects 1-4 years), hypoglycemia or dead-in-bed syndrome in 4%, related to diabetes but not described in 24%, and unrelated to diabetes in 14%. The SMRs showed a significant decrease across the years, except for the 1-4 age group. In the last decade (2007-2016), the crude and corrected SMRs were significantly different from 1 in the 1-4 age group (5.4 [2.3; 10.7] and 6.1 [2.8; 11.5]), no longer significant in the 5-9 age group (1.7 [0.6; 4.0] and 2.1 [0.8; 4.5]) and borderline significant in the 10-14 age group (1.7 [0.8; 3.2] and 2.3 [1.2; 4.0]). CONCLUSIONS: Children with T1D aged 1-4 years still had a high mortality rate. Their needs for early recognition and safe management of diabetes are not being met.

Development of a life expectancy table for individuals with type 1 diabetes.

AIMS/HYPOTHESIS: Tables reporting life expectancies by common risk factors are available for individuals with type 2 diabetes; however, there is currently no published equivalent for individuals with type 1 diabetes. We aimed to develop a life expectancy table using a recently published simulation model for individuals with type 1 diabetes. METHODS: The simulation model was developed using data from a real-world population of patients with type 1 diabetes selected from the Swedish National Diabetes Register. The following six important risk factors were included in the life table: sex; age; current smoking status; BMI; eGFR; and HbA1c. For each of 1024 cells in the life expectancy table, a synthetic cohort containing 1000 individuals was created, with other risk factors assigned values representative of the real-world population. The simulations were executed for all synthetic cohorts and life expectancy for each cell was calculated as mean survival time of the individuals in the respective cohort. RESULTS: There was a substantial variation in life expectancy across patients with different risk factor levels. Life expectancy of 20-year-old men varied from 29.3 years to 50.6 years, constituting a gap of 21.3 years between those with worst and best risk factor levels. In 20-year-old women, this gap was 18.9 years (life expectancy range 35.0-53.9 years). The variation in life expectancy was a function of the combination of risk factor values, with HbA1c and eGFR consistently showing a negative and positive correlation, respectively, with life expectancy at any level combination of other risk factors. Individuals with the lowest level (20 kg/m2) and highest level of BMI (35 kg/m2) had a lower life expectancy compared with those with a BMI of 25 kg/m2. Non-smokers and women had a higher life expectancy than smokers and men, respectively, with the difference in life expectancy ranging from 0.4 years to 2.7 years between non-smokers and smokers, and from 1.9 years to 5.9 years between women and men, depending on levels of other risk factors. CONCLUSIONS/INTERPRETATION: The life expectancy table generated in this study shows a substantial variation in life expectancy across individuals with different modifiable risk factors. The table allows for rapid communications of risk in an easily understood format between healthcare professionals, health economists, researchers, policy makers and patients. Particularly, it supports clinicians in their discussion with patients about the benefits of improving risk factors.

Association of diabetes type and chronic diabetes complications with early exit from the labour force: register-based study of people with diabetes in Finland.

AIMS/HYPOTHESIS: Diabetes and diabetes complications are a cause of substantial morbidity, resulting in early exits from the labour force and lost productivity. The aim of this study was to examine differences in early exits between people with type 1 and 2 diabetes and to assess the role of chronic diabetes complications on early exit. We also estimated the economic burden of lost productivity due to early exits. METHODS: People of working age (age 17-64) with diabetes in 1998-2011 in Finland were detected using national registers (Ntype 1 = 45,756, Ntype 2 = 299,931). For the open cohort, data on pensions and deaths, healthcare usage, medications and basic demographics were collected from the registers. The outcome of the study was early exit from the labour force defined as pension other than old age pension beginning before age 65, or death before age 65. We analysed the early exit outcome and its risk factors using the Kaplan-Meier method and extended Cox regression models. We fitted linear regression models to investigate the risk factors of lost working years and productivity costs among people with early exit. RESULTS: The difference in median age at early exit from the labour force between type 1 (54.0) and type 2 (58.3) diabetes groups was 4.3 years. The risk of early exit among people with type 1 diabetes increased faster after age 40 compared with people with type 2 diabetes. Each of the diabetes complications was associated with an increase in the hazard of early exit regardless of diabetes type compared with people without the complication, with eye-related complications as an exception. Diabetes complications partly but not completely explained the difference between diabetes types. The mean lost working years was 6.0 years greater in the type 1 diabetes group than in the type 2 diabetes group among people with early exit. Mean productivity costs of people with type 1 diabetes and early exit were found to be 1.4-fold greater compared with people with type 2 diabetes. The total productivity costs of incidences of early exits in the type 2 diabetes group were notably higher compared with the type 1 group during the time period (€14,400 million, €2800 million). CONCLUSIONS/INTERPRETATION: We found a marked difference in the patterns of risk of early exit between people with type 1 and type 2 diabetes. The difference was largest close to statutory retirement age. On average, exits in the type 1 diabetes group occurred at an earlier age and resulted in higher mean lost working years and mean productivity costs. The potential of prevention, timely diagnosis and management of diabetes is substantial in terms of avoiding reductions in individual well-being and productivity.

The impact of central obesity on the risk of hospitalization or death due to heart failure in type 1 diabetes: a 16-year cohort study.

BACKGROUND: Obesity and type 2 diabetes are well-known risk factors for heart failure (HF). Although obesity has increased in type 1 diabetes, studies regarding HF in this population are scarce. Therefore, we investigated the impact of body fat distribution on the risk of HF hospitalization or death in adults with type 1 diabetes at different stages of diabetic nephropathy (DN). METHODS: From 5401 adults with type 1 diabetes in the Finnish Diabetic Nephropathy Study, 4668 were included in this analysis. The outcome was HF hospitalization or death identified from the Finnish Care Register for Health Care or the Causes of Death Register until the end of 2017. DN was based on urinary albumin excretion rate. A body mass index (BMI) ≥ 30 kg/m2 defined general obesity, whilst WHtR ≥ 0.5 central obesity. Multivariable Cox regression was used to explore the associations between central obesity, general obesity and the outcome. Then, subgroup analyses were performed by DN stages. Z statistic was used for ranking the association. RESULTS: During a median follow-up of 16.4 (IQR 12.4-18.5) years, 323 incident cases occurred. From 308 hospitalizations due to HF, 35 resulted in death. Further 15 deaths occurred without previous hospitalization. The WHtR showed a stronger association with the outcome [HR 1.51, 95% CI (1.26-1.81), z = 4.40] than BMI [HR 1.05, 95% CI (1.01-1.08), z = 2.71]. HbA1c [HR 1.35, 95% CI (1.24-1.46), z = 7.19] was the most relevant modifiable risk factor for the outcome whereas WHtR was the third. Individuals with microalbuminuria but no central obesity had a similar risk of the outcome as those with normoalbuminuria. General obesity was associated with the outcome only at the macroalbuminuria stage. CONCLUSIONS: Central obesity associates with an increased risk of heart failure hospitalization or death in adults with type 1 diabetes, and WHtR may be a clinically useful screening tool.

Reduction in cardiovascular mortality following severe hypoglycemia in individuals with type 2 diabetes: the role of a pragmatic and structured intervention : Structured intervention for community hypoglycemia.

BACKGROUND: Mortality in individuals with diabetes with severe hypoglycemia requiring ambulance services intervention is high and it is unclear whether this is modifiable. Our aim was to characterise this high-risk group and assess the impact of nurse-led intervention on mortality. METHODS: In this single centre study, patients with diabetes and hypoglycemia requiring ambulance call out were randomized to nurse led support (intensive arm) or managed using existing pathways (standard arm). A third group agreed to have their data collected longitudinally (observational arm). The primary outcome was all-cause mortality comparing intensive with combined standard and observational arms as well as standard arm alone. RESULTS: Of 828 individuals identified, 323 agreed to participate with 132 assigned to intensive, 130 to standard and 61 to observational arms. Mean follow up period was 42.6 ± 15.6 months. Mortality in type 1 diabetes (n = 158) was similar across study arms but in type 2 diabetes (n = 160) this was reduced to 33% in the intensive arm compared with 51% in the combined arm (p = 0.025) and 50% in the standard arm (p = 0.06). Cardiovascular deaths, the leading cause of mortality, was lower in the intensive arm compared with combined and standard study arms (p < 0.01). CONCLUSIONS: Medium-term mortality following severe hypoglycemia requiring the assistance of emergency services is high in those with type 2 diabetes. In individuals with type 2 diabetes, nurse-led individualized intervention reduces cardiovascular mortality compared with standard care. Large-scale multicentre studies are warranted to further investigate this approach. Trial registration The trial was retrospectively registered on http://www.clinicaltrials.gov with reference NCT04422145.

Mortality in 98 type 1 diabetes mellitus and type 2 diabetes mellitus: Foot ulcer location is an independent risk determinant.

INTRODUCTION: We previously demonstrated in both a longitudinal study and in meta-analysis (pooled relative-risk RR, 2.45) that all-cause mortality is significantly higher in people with diabetes foot ulceration (DFU) than with those without a foot ulcer. In this prospective study, we looked at the factors linked to mortality after presentation to podiatry with DFU. METHODS: Ninety-eight individuals recruited consecutively from the Salford Royal Hospital Multidisciplinary Foot Clinic in Spring 2016 were followed up for up to 48 months. Data concerning health outcomes were extracted from the electronic patient record (EPR). RESULTS: Seventeen people (17) had type 1 diabetes mellitus, and 81 had type 2 diabetes mellitus. Thirty-one were women. The mean age (range) was 63.6 (28-90) years with maximum diabetes duration 45 years. Mean HbA1c was 72 (95% CI: 67-77) mmol/mol; 97% had neuropathy (International Working Group on the Diabetic Foot (IWGDF) monofilament); 62% had vascular insufficiency (Doppler studies); 69% of ulcers were forefoot, and 23% of ulcers were hind foot in location. Forty of 98 (40%) patients died in follow-up with 27% of death certificates including sepsis (not foot-related) and 35% renal failure as cause of death. Multivariate regression analysis indicated a 6.3 (95% CI: 3.9-8.1) fold increased risk of death with hind foot ulcer, independent of age/BMI/gender/HbA1c/eGFR/total cholesterol level. CONCLUSION: This prospective study has indicated a very high long-term mortality rate in individuals with DFU, greater for those with a hind foot ulcer and shown a close relation between risk of sepsis/renal failure and DFU mortality, highlighting again the importance of addressing all risk factors as soon as people present with a foot ulcer.

Overall and Cause-Specific Mortality in Patients With Type 1 Diabetes Mellitus: A Population-Based Cohort Study in Taiwan From 1998 Through 2014.

BACKGROUND: To investigate all-cause and cause-specific mortality in Taiwanese patients with type 1 diabetes. METHODS: A cohort of 17,203 patients with type 1 diabetes were identified from Taiwan's National Health Insurance claims in the period of 1998-2014. Person-years were accumulated for each individual from date of type 1 diabetes registration to date of death or the last day of 2014. Age, sex, and calendar year standardized mortality ratios (SMRs) were calculated with reference to the general population. RESULTS: In up to 17 years of follow-up, 4,916 patients died from 182,523 person-years. Diabetes (30.15%), cancer (20.48%), circulatory diseases (13.14%), and renal diseases (11.45%) were the leading underlying causes of death. Mortality rate (26.93 per 1,000 person-years) from type 1 diabetes in Taiwan was high, the cause of death with the highest mortality rate was diabetes (8.12 per 1,000 person-years), followed by cancer (5.52 per 1,000 person-years), and circulatory diseases (3.54 per 1,000 person-years). The all-cause SMR was significantly elevated at 4.16 (95% confidence interval, 4.04-4.28), with a greater all-cause SMR noted in females than in males (4.62 vs 3.79). The cause-specific SMR was highly elevated for diabetes (SMR, 16.45), followed by renal disease (SMR, 14.48), chronic hepatitis and liver cirrhosis (SMR, 4.91) and infection (SMR, 4.59). All-cause SMRs were also significantly increased for all ages, with the greatest figure noted for 15-24 years (SMR, 8.46). CONCLUSIONS: Type 1 diabetes in both genders and all ages was associated with significantly elevated SMRs for all-cause and mostly for diabetes per se and renal disease.

(Ultra-)long-acting insulin analogues for people with type 1 diabetes mellitus.

BACKGROUND: People with type 1 diabetes mellitus (T1DM) need treatment with insulin for survival. Whether any particular type of (ultra-)long-acting insulin provides benefit especially regarding risk of diabetes complications and hypoglycaemia is unknown. OBJECTIVES: To compare the effects of long-term treatment with (ultra-)long-acting insulin analogues to NPH insulin (neutral protamine Hagedorn) or another (ultra-)long-acting insulin analogue in people with type 1 diabetes mellitus. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials, MEDLINE, Scopus, ClinicalTrials.gov, the World Health Organization (WHO) International Clinical Trials Registry Platform and the reference lists of systematic reviews, articles and health technology assessment reports. We explored the US Food and Drug Administration (FDA) and European Medical Agency (EMA) web pages. We asked pharmaceutical companies, EMA and investigators for additional data and clinical study reports (CSRs). The date of the last search of all databases was 24 August 2020. SELECTION CRITERIA: We included randomised controlled trials (RCTs) with a duration of 24 weeks or more comparing one (ultra-)long-acting insulin to NPH insulin or another (ultra-)long-acting insulin in people with T1DM. DATA COLLECTION AND ANALYSIS: Two review authors assessed risk of bias using the new Cochrane 'Risk of bias' 2 (RoB 2) tool and extracted data. Our main outcomes were all-cause mortality, health-related quality of life (QoL), severe hypoglycaemia, non-fatal myocardial infarction/stroke (NFMI/NFS), severe nocturnal hypoglycaemia, serious adverse events (SAEs) and glycosylated haemoglobin A1c (HbA1c). We used a random-effects model to perform meta-analyses and calculated risk ratios (RRs) and odds ratios (ORs) for dichotomous outcomes and mean differences (MDs) for continuous outcomes, using 95% confidence intervals (CIs) and 95% prediction intervals for effect estimates. We evaluated the certainty of the evidence applying the GRADE instrument. MAIN RESULTS: We included 26 RCTs. Two studies were unpublished. We obtained CSRs, clinical study synopses or both as well as medical reviews from regulatory agencies on 23 studies which contributed to better analysis of risk of bias and improved data extraction. A total of 8784 participants were randomised: 2428 participants were allocated to NPH insulin, 2889 participants to insulin detemir, 2095 participants to insulin glargine and 1372 participants to insulin degludec. Eight studies contributing 21% of all participants comprised children. The duration of the intervention varied from 24 weeks to 104 weeks. Insulin degludec versus NPH insulin: we identified no studies comparing insulin degludec with NPH insulin. Insulin detemir versus NPH insulin (9 RCTs): five deaths reported in two studies including adults occurred in the insulin detemir group (Peto OR 4.97, 95% CI 0.79 to 31.38; 9 studies, 3334 participants; moderate-certainty evidence). Three studies with 870 participants reported QoL showing no true beneficial or harmful effect for either intervention (low-certainty evidence). There was a reduction in severe hypoglycaemia in favour of insulin detemir: 171/2019 participants (8.5%) in the insulin detemir group compared with 138/1200 participants (11.5%) in the NPH insulin group experienced severe hypoglycaemia (RR 0.69, 95% CI 0.52 to 0.92; 8 studies, 3219 participants; moderate-certainty evidence). The 95% prediction interval ranged between 0.34 and 1.39. Only 1/331 participants in the insulin detemir group compared with 0/164 participants in the NPH insulin group experienced a NFMI (1 study, 495 participants; low-certainty evidence). No study reported NFS. A total of 165/2094 participants (7.9%) in the insulin detemir group compared with 102/1238 participants (8.2%) in the NPH insulin group experienced SAEs (RR 0.95, 95% CI 0.75 to 1.21; 9 studies, 3332 participants; moderate-certainty evidence). Severe nocturnal hypoglycaemia was observed in 70/1823 participants (3.8%) in the insulin detemir group compared with 60/1102 participants (5.4%) in the NPH insulin group (RR 0.67, 95% CI 0.39 to 1.17; 7 studies, 2925 participants; moderate-certainty evidence). The MD in HbA1c comparing insulin detemir with NPH insulin was 0.01%, 95% CI -0.1 to 0.1; 8 studies, 3122 participants; moderate-certainty evidence. Insulin glargine versus NPH insulin (9 RCTs): one adult died in the NPH insulin group (Peto OR 0.14, 95% CI 0.00 to 6.98; 8 studies, 2175 participants; moderate-certainty evidence). Four studies with 1013 participants reported QoL showing no true beneficial effect or harmful effect for either intervention (low-certainty evidence). Severe hypoglycaemia was observed in 122/1191 participants (10.2%) in the insulin glargine group compared with 145/1159 participants (12.5%) in the NPH insulin group (RR 0.84, 95% CI 0.67 to 1.04; 9 studies, 2350 participants; moderate-certainty evidence). No participant experienced a NFMI and one participant in the NPH insulin group experienced a NFS in the single study reporting this outcome (585 participants; low-certainty evidence). A total of 109/1131 participants (9.6%) in the insulin glargine group compared with 110/1098 participants (10.0%) in the NPH insulin group experienced SAEs (RR 1.08, 95% CI 0.63 to 1.84; 8 studies, 2229 participants; moderate-certainty evidence). Severe nocturnal hypoglycaemia was observed in 69/938 participants (7.4%) in the insulin glargine group compared with 83/955 participants (8.7%) in the NPH insulin group (RR 0.83, 95% CI 0.62 to 1.12; 6 studies, 1893 participants; moderate-certainty evidence). The MD in HbA1c comparing insulin glargine with NPH insulin was 0.02%, 95% CI -0.1 to 0.1; 9 studies, 2285 participants; moderate-certainty evidence. Insulin detemir versus insulin glargine (2 RCTs),insulin degludec versus insulin detemir (2 RCTs), insulin degludec versus insulin glargine (4 RCTs): there was no evidence of a clinically relevant difference for all main outcomes comparing (ultra-)long-acting insulin analogues with each other. For all outcomes none of the comparisons indicated differences in tests of interaction for children versus adults. AUTHORS' CONCLUSIONS: Comparing insulin detemir with NPH insulin for T1DM showed lower risk of severe hypoglycaemia in favour of insulin detemir (moderate-certainty evidence). However, the 95% prediction interval indicated inconsistency in this finding. Both insulin detemir and insulin glargine compared with NPH insulin did not show benefits or harms for severe nocturnal hypoglycaemia. For all other main outcomes with overall low risk of bias and comparing insulin analogues with each other, there was no true beneficial or harmful effect for any intervention. Data on patient-important outcomes such as QoL, macrovascular and microvascular diabetic complications were sparse or missing. No clinically relevant differences were found between children and adults.

Insulin Use, Diabetes Control, and Outcomes in Patients with COVID-19.

Background: The novel coronavirus (SARS CoV-2) has caused significant morbidity and mortality in patients with diabetes. However, the effects of diabetes control including insulin use remain uncertain in terms of clinical outcomes of patients with COVID-19.Methods: In this single-center, retrospective observational study, all adult patients admitted to Einstein Medical Center, Philadelphia, from March 1 through April 24, 2020 with a diagnosis of COVID-19 and diabetes were included. Demographic, clinical and laboratory data, insulin dose at home and at the hospital, other anti-hyperglycemic agents use, and outcomes were obtained. Multivariate logistic regression was used to evaluate the factors associated with diabetes control and mortality.Results: Patients who used insulin at home had higher mortality compared to those who did not (35% vs 18% p = .015), this was true even after adjustment for demographics, comorbidities and a1c OR 2.65 95% CI (1.23-5.71) p = .013. However, the mean a1c and the median home requirements of insulin did not significantly differ among patients who died compared to the ones that survived. Patients who died had significantly higher inpatient insulin requirements (highest day insulin requirement recorded in units during hospitalization) 36 (11-86) vs 21 (8-52) p = .043 despite similar baseline a1c and steroid doses received. After adjusting for demographics, comorbidities and a1c, peak insulin requirements remained significantly associated with inpatient mortality OR 1.022 95% CI (1.00-1.04) p = .044.Conclusion: Among diabetic patients infected with COVID-19, insulin therapy at home was significantly independently associated with increased mortality. Peak daily inpatient insulin requirements was also independently associated with increased inpatient mortality.