Effects of pre-existing type 1 diabetes mellitus on survival outcome following out-of-hospital cardiac arrest: a registry-based observational study in Sweden.

BACKGROUND: It has been estimated that 80% of cases of out-of-hospital cardiac arrest (OHCA) are due to cardiac causes. It is well-documented that diabetes is a risk factor for conditions associated with sudden cardiac arrest. Type 1 diabetes (T1D) displays a threefold to fivefold increased risk of cardiovascular disease and death compared with the general population. OBJECTIVE: This study aims to assess the characteristics and survival outcomes of individuals with and without T1D who experienced an OHCA. Design: A registry-based nationwide observational study with two cohorts, patients with T1D and patients without T1D. Setting: All emergency medical services and hospitals in Sweden were included in the study. PARTICIPANTS: Using the Swedish Cardiopulmonary Resuscitation Registry, we enrolled 54 568 cases of OHCA where cardiopulmonary resuscitation was attempted between 2010 and 2020. Among them, 448 patients with T1D were identified using International Classification of Diseases-code: E10. METHODS: Survival analysis was performed using Kaplan-Meier and logistic regression. Multiple regression was adjusted for age, sex, cause of arrest, prevalence of T1D and time to cardiopulmonary resuscitation. MAIN OUTCOME MEASURES: The outcomes were discharge status (alive vs dead), 30 days survival and neurological outcome at discharge. RESULTS: There were no significant differences in patients discharged alive with T1D 37.3% versus, 46% among cases without T1D. There was also no difference in neurological outcome. Kaplan-Meier curves yielded no significant difference in long-term survival. Multiple regression showed no significant association with survival after accounting for covariates, OR 0.99 (95% CI 0.96 to 1.02), p value=0.7. Baseline characteristics indicate that patients with T1D were 5 years younger at OHCA occurrence and had proportionally fewer cases of heart disease as the cause of arrest (57.6% vs 62.7%). CONCLUSION: We conclude, with the current sample size, that there is no statistically significant difference in long-term or short-term survival between patients with and without T1D following OHCA.

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.

Global burden of type 1 diabetes in adults aged 65 years and older, 1990-2019: population based study.

OBJECTIVES: To estimate the burden, trends, and inequalities of type 1 diabetes mellitus (T1DM) among older adults at global, regional, and national level from 1990 to 2019. DESIGN: Population based study. POPULATION: Adults aged ≥65 years from 21 regions and 204 countries and territories (Global Burden of Disease and Risk Factors Study 2019)from 1990 to 2019. MAIN OUTCOME MEASURES: Primary outcomes were T1DM related age standardised prevalence, mortality, disability adjusted life years (DALYs), and average annual percentage change. RESULTS: The global age standardised prevalence of T1DM among adults aged ≥65 years increased from 400 (95% uncertainty interval (UI) 332 to 476) per 100 000 population in 1990 to 514 (417 to 624) per 100 000 population in 2019, with an average annual trend of 0.86% (95% confidence interval (CI) 0.79% to 0.93%); while mortality decreased from 4.74 (95% UI 3.44 to 5.9) per 100 000 population to 3.54 (2.91 to 4.59) per 100 000 population, with an average annual trend of -1.00% (95% CI -1.09% to -0.91%), and age standardised DALYs decreased from 113 (95% UI 89 to 137) per 100 000 population to 103 (85 to 127) per 100 000 population, with an average annual trend of -0.33% (95% CI -0.41% to -0.25%). The most significant decrease in DALYs was observed among those aged <79 years: 65-69 (-0.44% per year (95% CI -0.53% to -0.34%)), 70-74 (-0.34% per year (-0.41% to -0.27%)), and 75-79 years (-0.42% per year (-0.58% to -0.26%)). Mortality fell 13 times faster in countries with a high sociodemographic index versus countries with a low-middle sociodemographic index (-2.17% per year (95% CI -2.31% to -2.02%) v -0.16% per year (-0.45% to 0.12%)). While the highest prevalence remained in high income North America, Australasia, and western Europe, the highest DALY rates were found in southern sub-Saharan Africa, Oceania, and the Caribbean. A high fasting plasma glucose level remained the highest risk factor for DALYs among older adults during 1990-2019. CONCLUSIONS: The life expectancy of older people with T1DM has increased since the 1990s along with a considerable decrease in associated mortality and DALYs. T1DM related mortality and DALYs were lower in women aged ≥65 years, those living in regions with a high sociodemographic index, and those aged <79 years. Management of high fasting plasma glucose remains a major challenge for older people with T1DM, and targeted clinical guidelines are needed.

Suicidal Ideation, Suicide Attempts, and Suicide Deaths in Adolescents and Young Adults With Type 1 Diabetes: A Systematic Review and Meta-analysis.

BACKGROUND: Evidence is lacking on the risk of suicide-related behaviors (suicidal ideation, suicide attempt, suicide death) in youth with type 1 diabetes (T1D). PURPOSE: We aimed to 1) determine the prevalence of suicidal ideation, suicide attempts, and suicide deaths in adolescents and young adults (AYA) with T1D aged 10-24 years; 2) compare suicide-related behavior prevalence in youth with and without T1D; and 3) identify factors associated with suicide-related behaviors. DATA SOURCES: A systematic search was conducted in MEDLINE, Embase, and PsycInfo up to 3 September 2023. STUDY SELECTION: We included observational studies where investigators reported the prevalence of suicide-related behaviors among AYA aged 10-24 years with T1D. DATA EXTRACTION: We collected data on study characteristics, data on prevalence of suicide-related behaviors, and data on associated factors. DATA SYNTHESIS: We included 31 studies. In AYA with versus without T1D, pooled prevalence of suicidal ideation was 15.4% (95% CI 10.0-21.7; n = 18 studies) vs. 11.5% (0.4-33.3; n = 4), respectively, and suicide attempts 3.5% (1.3-6.7; n = 8) vs. 2.0% (0.0-6.4; n = 5). Prevalence of suicide deaths ranged from 0.04% to 4.4% among youth with T1D. Difficulties with T1D self-management were frequently reported to be associated with higher rates of suicide-related behaviors. However, findings on the association of glycemic levels and suicide-related behaviors were inconsistent. LIMITATIONS: There was a considerable level of heterogeneity in meta-analysis of both suicidal ideation and suicide attempts. CONCLUSIONS: Suicidal ideation and suicide attempts are prevalent in AYA with T1D. Current evidence does not suggest that these rates are higher among AYA with T1D than rates among those without.

Physical activity trajectories and all-cause mortality in type 1 diabetes: A nationwide longitudinal study.

AIMS: To identify physical activity trajectories, explore the factors associated with them and assess their relationship with all-cause mortality. METHODS: This was a population-based longitudinal cohort study, with data from all specialist care units for type 1 diabetes in Sweden. A total of 48.921 adult patients were included, each with at least 3 registrations of physical activity, and a maximum follow-up of 14 years. The main outcomes were the longitudinal physical activity trajectories and all-cause mortality. RESULTS: Of 48.921 patients, 55.9% were males and mean (SD) age was 39.7(16.7). Four physical activity trajectories were identified: Steady Low (10.8%), Decreaser (12.7%), Increaser (20.7%) and Steady High (55.8%). Female sex, higher education, higher income, normal BMI, fewer comorbidities and foot free from diabetic disease were significantly associated with sustained high physical activity. Compared to the steady low group, the decreaser, increaser, and steady high physical activity groups exhibited lower adjusted risk of all-cause mortality (53-73% reduction). CONCLUSIONS: Consistently low physical activity is associated with higher all-cause mortality. This study underscores the importance of identifying patients at risk of low physical activity and tailoring personalized approaches to promote sustained physical activity in type 1 diabetes, ultimately improving outcomes.

Trends in Survival After First Myocardial Infarction in People With Diabetes.

BACKGROUND: The aim of this study was to investigate temporal trends in survival and subsequent cardiovascular events in a nationwide myocardial infarction population with and without diabetes. METHODS AND RESULTS: Between 2006 and 2020, we identified 2527 individuals with type 1 diabetes, 48 321 individuals with type 2 diabetes and 243 170 individuals without diabetes with first myocardial infarction in national health care registries. Outcomes were trends in all-cause death after 30 and 365 days, cardiovascular death and major adverse cardiovascular events (ie, nonfatal stroke, nonfatal myocardial infarction, cardiovascular death, and heart failure hospitalization). Pseudo-observations were used to estimate the mortality risk, with 95% CIs, using linear regression, adjusted for age and sex. Individuals with type 1 diabetes were younger (62±12.2 years) and more often women (43.6%) compared with individuals with type 2 diabetes (75±10.8 years; women, 38.1%), and individuals without diabetes (73±13.2 years; women, 38.4%). Early death decreased in people without diabetes from 23.1% to 17.5%, (annual change -0.48% [95% CI, -0.52% to -0.44%]) and in people with type 2 diabetes from 22.6% to 19.3% (annual change, -0.33% [95% CI, -0.43% to -0.24%]), with no such significant trend in people with type 1 diabetes from 23.8% to 21.7% (annual change, -0.18% [95% CI, -0.53% to 0.17%]). Similar trends were observed with regard to 1-year death, cardiovascular death, and major adverse cardiovascular events. CONCLUSIONS: During the past 15 years, the trend in survival and major adverse cardiovascular events in people with first myocardial infarction without diabetes and with type 2 diabetes have improved significantly. In contrast, a similar improvement was not seen in people with type 1 diabetes.

Impact of Pretransplant C-Reactive Protein, Neutrophiles, Platelets, and Albumin Levels on Recipient Survival After Simultaneous Pancreas and Kidney Transplantation.

BACKGROUND: Long-lasting diabetes mellitus type 1 and end-stage renal disease induce severe metabolic and immunologic deterioration. Pretransplant C-reactive protein (CRP) and albumin (ALB) levels impact kidney transplantation. We evaluated the effects of preoperative CRP, ALB, neutrophils (NEU), and platelet (PLT) counts on 1- and 5-year recipient survival after simultaneous pancreas and kidney transplantation (SPK). METHODS: Among 103 SPK recipients, the parameters were as follows: CRP (mean: 4.5 ± 4.97 mg/L); NEU (mean: 5.12 ± 2.13 × 103/mm3); PLT (mean: 244 ± 84 × 103/mm3); ALB (mean 4.5 ± 0.75 g/dL) were obtained before transplantation. Cox regression, uni-, multivariate analysis for 1- and 5-year survivals were performed with 95% CIs, and the area under the receiver operating characteristic (ROC) curve (AUC) was assessed. RESULTS: In Cox regression, ALB <3.65 g/dL significantly affected 1- and 5-year survivors with hazard ratios of 8 (95% CI, 1.5-38.28; P < .05) and 3.13 (95% CI, 1.45-6.73; P < .05), respectively. In univariate analysis, we found significantly decreased 1-year survival when PLT <180×103/mm3, ALB <3.65 g/dL, NEU >5.8×103/mm3 and CRP >2.25 mg/L with odds ratios (OR) of 6.75 (95% CI, 2.12-21.15); 4.05 (95% CI, 1.3-12.09); 2.97 (95% CI, 1.02-8.64) and 5.51 (95% CI, 1.67-18.19), respectively. Independent factors for 5-year survival were CRP, ALB, and PLT with OR of 4.72 (95% CI, 1.67-13.29), 3.31 (95% CI, 1.18-9.25), and 4.2 (95% CI, 1.39-12.68), respectively. In multivariate analysis, we built 2 models for 1-year survival. Model 1 (ALB+PLT) with ORs of 3.12 (95% CI, 0.97-10.07) and 5.55 (95% CI, 1.67-18.4); and model 2 (CRP+PLT) with ORs of 5.51 (95% CI, 1.5-17.3) and 4.3 (95% CI, 1.2-15.06), respectively. The AUC for models 1 and 2 were 0.74 and 0.759, respectively. CONCLUSIONS: NEU, PLT, ALB, and CRP levels assessed before transplantation are independent factors for 1- and 5-year SPK recipient survival.

Perceptions Related to Death in Adolescents and Their Parents During the Management of Type 1 Diabetes: A Thematic Analysis.

BACKGROUND: Type 1 diabetes (T1D) is associated with an increased risk of premature death compared to those without T1D, yet perceptions of dying have not been well studied. The purpose of this secondary analysis of existing data was to explore the fears of adolescents with T1D and their parents related to the possibility of death due to T1D. METHOD: A reflexive thematic analysis was used to examine data from interviews conducted with adolescents with T1D and their parents who participated in a primary grounded theory study of interdependence in T1D management. FINDINGS: Three themes were generated from the data including: (1) Facing the Reality of Death, (2) Fearing Highs and Lows, and (3) Finding a Way through Fears. Participants indicated they see death as a consequence of failing to optimally manage T1D. CONCLUSION: Additional investigation is needed to explore the fear of death in adolescents with T1D and any fear their parents may have of their adolescents' mortality.

Type 1 and type 2 diabetes mortality burden: Predictions for 2030 based on Bayesian age-period-cohort analysis of China and global mortality burden from 1990 to 2019.

AIMS: This study assessed diabetes (type 1 and type 2) mortality in China and globally from 1990 to 2019, predicting the next decade's trends. MATERIALS AND METHODS: Data came from the Global Burden of Disease (GBD) database. The annual percentage change (AAPC) in age-standardized mortality rates (ASMR) for diabetes (type 1 and type 2) during 1990-2019 was calculated. A Bayesian age-period-cohort (BAPC) model predicted diabetes (type 1 and type 2) mortality from 2020 to 2030. RESULTS: In China, type 1 diabetes deaths declined from 6,005 to 4,504 cases (AAPC -2.827), while type 2 diabetes deaths rose from 64,084 to 168,388 cases (AAPC -0.763) from 1990 to 2019. Globally, type 1 diabetes deaths increased from 55,417 to 78,236 cases (AAPC 0.223), and type 2 diabetes deaths increased from 606,407 to 1,472,934 cases (AAPC 0.365). Both China and global trends showed declining type 1 diabetes ASMR. However, female type 2 diabetes ASMR in China initially increased and then decreased, while males had a rebound trend. Peak type 1 diabetes deaths were in the 40-44 age group, and type 2 diabetes peaked in those over 70. BAPC predicted declining diabetes (type 1 and type 2) mortality burden in China and globally over the next 10 years. CONCLUSIONS: Type 2 diabetes mortality remained high in China and globally despite decreasing type 1 diabetes mortality over 30 years. Predictions suggest a gradual decrease in diabetes mortality over the next decade, highlighting the need for continued focus on type 2 diabetes prevention and treatment.

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.

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.

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.

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.

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.

Comparison of the performances of survival analysis regression models for analysis of conception modes and risk of type-1 diabetes among 1985-2015 Swedish birth cohort.

The goal is to examine the risk of conception mode-type-1 diabetes using different survival analysis modelling approaches and examine if there are differentials in the risk of type-1 diabetes between children from fresh and frozen-thawed embryo transfers. We aimed to compare the performances and fitness of different survival analysis regression models with the Cox proportional hazard (CPH) model used in an earlier study. The effect of conception modes and other prognostic factors on type-1 diabetes among children conceived either spontaneously or by assisted reproductive technology (ART) and its sub-groups was modelled in the earlier study. We used the information on all singleton children from the Swedish Medical Birth Register hosted by the Swedish National Board of Health and Welfare, 1985 to 2015. The main explanatory variable was the mode of conception. We applied the CPH, parametric and flexible parametric survival regression (FPSR) models to the data at 5% significance level. Loglikelihood, Akaike and Bayesian information criteria were used to assess model fit. Among the 3,138,540 singletons, 47,938 (1.5%) were conceived through ART (11,211 frozen-thawed transfer and 36,727 fresh embryo transfer). In total, 18,118 (0.58%) of the children had type-1 diabetes, higher among (0.58%) those conceived spontaneously than the ART-conceived (0.42%). The median (Interquartile range (IQR)) age at onset of type-1 diabetes among spontaneously conceived children was 10 (14-6) years, 8(5-12) for ART, 6 (4-10) years for frozen-thawed embryo transfer and 9 (5-12) years for fresh embryo transfer. The estimates from the CPH, FPSR and parametric PH models are similar. There was no significant difference in the risk of type-1 diabetes among ART- and spontaneously conceived children; FPSR: (adjusted Hazard Ratio (aHR) = 1.070; 95% Confidence Interval (CI):0.929-1.232, p = 0.346) vs CPH: (aHR = 1.068; 95%CI: 0.927-1.230, p = 0.361). A sub-analysis showed that the adjusted hazard of type-1 diabetes was 37% (aHR = 1.368; 95%CI: 1.013-1.847, p = 0.041) higher among children from frozen-thawed embryo transfer than among children from spontaneous conception. The hazard of type-1 diabetes was higher among children whose mothers do not smoke (aHR = 1.296; 95%CI:1.240-1.354, p<0.001) and of diabetic mothers (aHR = 6.419; 95%CI:5.852-7.041, p<0.001) and fathers (aHR = 8.808; 95%CI:8.221-9.437, p<0.001). The estimates from the CPH, parametric models and the FPSR model were close. This is an indication that the models performed similarly and any of them can be used to model the data. We couldn't establish that ART increases the risk of type-1 diabetes except when it is subdivided into its two subtypes. There is evidence of a greater risk of type-1 diabetes when conception is through frozen-thawed transfer.

Advanced glycation end products as predictors of renal function in youth with type 1 diabetes.

To examine if skin autofluorescence (sAF) differed in early adulthood between individuals with type 1 diabetes and age-matched controls and to ascertain if sAF aligned with risk for kidney disease. Young adults with type 1 diabetes (N = 100; 20.0 ± 2.8 years; M:F 54:46; FBG-11.6 ± 4.9 mmol/mol; diabetes duration 10.7 ± 5.2 years; BMI 24.5(5.3) kg/m2) and healthy controls (N = 299; 20.3 ± 1.8 years; M:F-83:116; FBG 5.2 ± 0.8 mmol/L; BMI 22.5(3.3) kg/m2) were recruited. Skin autofluorescence (sAF) and circulating AGEs were measured. In a subset of both groups, kidney function was estimated by GFRCKD-EPI CysC and uACR, and DKD risk defined by uACR tertiles. Youth with type 1 diabetes had higher sAF and BMI, and were taller than controls. For sAF, 13.6% of variance was explained by diabetes duration, height and BMI (Pmodel = 1.5 × 10-12). In the sub-set examining kidney function, eGFR and sAF were higher in type 1 diabetes versus controls. eGFR and sAF predicted 24.5% of variance in DKD risk (Pmodel = 2.2 × 10-9), which increased with diabetes duration (51%; Pmodel < 2.2 × 10-16) and random blood glucose concentrations (56%; Pmodel < 2.2 × 10-16). HbA1C and circulating fructosamine albumin were higher in individuals with type 1 diabetes at high versus low DKD risk. eGFR was independently associated with DKD risk in all models. Higher eGFR and longer diabetes duration are associated with DKD risk in youth with type 1 diabetes. sAF, circulating AGEs, and urinary AGEs were not independent predictors of DKD risk. Changes in eGFR should be monitored early, in addition to uACR, for determining DKD risk in type 1 diabetes.

The pattern-recognition molecule H-ficolin in relation to diabetic kidney disease, mortality, and cardiovascular events in type 1 diabetes.

H-ficolin recognizes patterns on microorganisms and stressed cells and can activate the lectin pathway of the complement system. We aimed to assess H-ficolin in relation to the progression of diabetic kidney disease (DKD), all-cause mortality, diabetes-related mortality, and cardiovascular events. Event rates per 10-unit H-ficolin-increase were compared in an observational follow-up of 2,410 individuals with type 1 diabetes from the FinnDiane Study. DKD progression occurred in 400 individuals. The unadjusted hazard ratio (HR) for progression was 1.29 (1.18-1.40) and 1.16 (1.05-1.29) after adjustment for diabetes duration, sex, HbA1c, systolic blood pressure, and smoking status. After adding triglycerides to the model, the HR decreased to 1.07 (0.97-1.18). In all, 486 individuals died, including 268 deaths of cardiovascular causes and 192 deaths of complications to diabetes. HRs for all-cause mortality and cardiovascular mortality were 1.13 (1.04-1.22) and 1.05 (0.93-1.17), respectively, in unadjusted analyses. These estimates lost statistical significance in adjusted models. However, the unadjusted HR for diabetes-related mortality was 1.19 (1.05-1.35) and 1.18 (1.02-1.37) with the most stringent adjustment level. Our results, therefore, indicate that H-ficolin predicts diabetes-related mortality, but neither all-cause mortality nor fatal/non-fatal cardiovascular events. Furthermore, H-ficolin is associated with DKD progression, however, not independently of the fully adjusted model.