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.

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.

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.

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.

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.

(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.

Risk of cause-specific death, its sex and age differences, and life expectancy in post-pancreatitis diabetes mellitus.

AIMS: The aim was to investigate sex- and age-stratified risks of cause-specific death and life expectancy in individuals with post-pancreatitis diabetes mellitus (PPDM). METHODS: Nationwide data on mortality in New Zealand were obtained. For two head-to-head comparisons (PPDM versus type 2 diabetes mellitus [T2DM]; PPDM versus type 1 diabetes mellitus [T1DM]), the groups were matched on age, sex, and calendar year of diabetes diagnosis. Multivariable Cox regression analyses were conducted to estimate risks of vascular, cancer, and non-vascular non-cancer mortality. Remaining life expectancy at age of diabetes diagnosis was estimated using the Chiang II method. RESULTS: A total of 15,848 individuals (1,132 PPDM, 3,396 T1DM, and 11,320 T2DM) were included. The risks of vascular mortality and non-vascular non-cancer mortality did not differ significantly between PPDM and T2DM or T1DM. PPDM was associated with a significantly higher risk of cancer mortality compared with T2DM (adjusted hazard ratio, 1.32; 95% confidence interval, 1.08-1.63) or T1DM (adjusted hazard ratio, 1.65; 95% confidence interval, 1.27-2.13). The risk of cancer mortality associated with PPDM (versus T2DM) was significantly higher in women than in men (p for interaction = 0.003). This sex difference in cancer mortality risk was also significant in the comparison between PPDM and T1DM (p for interaction = 0.006). Adults of both sexes with PPDM had the lowest remaining life expectancy (in comparison with T2DM or T1DM) up to 64 years of age. CONCLUSIONS: People with PPDM have a higher risk of cancer mortality compared with those with T2DM or T1DM. This is especially pronounced in women. Young and middle-aged adults with PPDM have a lower life expectancy compared with their counterparts with T2DM or T1DM.

Obesity and Overweight Are Independently Associated with Greater Survival in Critically Ill Diabetic Patients: A Retrospective Cohort Study.

BACKGROUND: The relationship between obesity and the outcomes of critically ill diabetic patients is not completely clear. We aimed to assess the effects of obesity and overweight on the outcomes among diabetic patients in the intensive care unit (ICU). METHODS: Critically ill diabetic patients in the ICU were classified into three groups according to their body mass index. The primary outcomes were 30-day and 90-day mortality. ICU and hospital length of stay (LOS) and incidence and duration of mechanical ventilation were also assessed. Cox regression models were developed to evaluate the relationship between obesity and overweight and mortality. RESULTS: A total of 6108 eligible patients were included. The 30-day and 90-day mortality in the normal weight group were approximately 1.8 times and 1.5 times higher than in the obesity group and overweight group, respectively (P < 0.001, respectively). Meanwhile, the ICU (median (IQ): 2.9 (1.7, 5.3) vs. 2.7 (1.6, 4.8) vs. 2.8 (1.8, 5.0)) and hospital (median (IQ): 8.3 (5.4, 14.0) vs. 7.9 (5.1, 13.0) vs. 8.3 (5.3, 13.6)) LOS in the obesity group and overweight group were not longer than in the normal weight group. Compared with normal weight patients, obese patients had significantly higher incidence of mechanical ventilation (58.8% vs. 64.7%, P < 0.001) but no longer ventilation duration (median (IQ): 19.3 (7.0, 73.1) vs. 19.0 (6.0, 93.7), P = 1). Multivariate Cox regression showed that obese and overweight patients had lower 30-day (HR (95% CI): 0.62 (0.51, 0.75); 0.76 (0.62, 0.92), respectively) and 90-day (HR (95% CI): 0.60 (0.51, 0.70); 0.79 (0.67, 0.93), respectively) mortality risks than normal weight patients. CONCLUSIONS: Obesity and overweight were independently associated with greater survival in critically ill diabetic patients, without increasing the ICU and hospital LOS. Large multicenter prospective studies are needed to confirm our findings and the underlying mechanisms warrant further investigation.

Features of patients that died for COVID-19 in a hospital in the south of Mexico: A observational cohort study.

BACKGROUND: Due to the wide spread of SARS-CoV2 around the world, the risk of death in individuals with metabolic comorbidities has dangerously increased. Mexico has a high number of infected individuals and deaths by COVID-19 as well as an important burden of metabolic diseases; nevertheless, reports about features of Mexican individuals with COVID-19 are scarce. The aim of this study was to evaluate demographic features, clinical characteristics and the pharmacological treatment of individuals who died by COVID-19 in the south of Mexico. METHODS: We performed an observational study including the information of 185 deceased individuals with confirmed diagnoses of COVID-19. Data were retrieved from medical records. Categorical data were expressed as proportions (%) and numerical data were expressed as mean ± standard deviation. Comorbidities and overlapping symptoms were plotted as Venn diagrams. Drug clusters were plotted as dendrograms. RESULTS: The mean age was 59.53 years. There was a male predominance (60.1%). The mean hospital stay was 4.75 ± 4.43 days. The most frequent symptoms were dyspnea (88.77%), fever (71.42%) and dry cough (64.28%). Present comorbidities included diabetes (60.63%), hypertension (59.57%) and obesity (43.61%). The main drugs used for treating COVID-19 were azithromycin (60.6%), hydroxychloroquine (53.0%) and oseltamivir (27.3%). CONCLUSIONS: Mexican individuals who died of COVID-19 had shorter hospital stays, higher frequency of shortness of breath, and higher prevalence of diabetes than individuals from other countries. Also, there was a high frequency of off-label use of drugs for their treatment.

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.