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Aim: To describe the association between socio‐economic status and prevalence of key cardiovascular risk factors in people with type 2 diabetes in Scotland. Methods: A cross‐sectional study of 264 011 people with type 2 diabetes in Scotland in 2016 identified from the population‐based diabetes register. Socio‐economic status was defined using quintiles of the area‐based Scottish Index of Multiple Deprivation (SIMD) with quintile (Q)1 and Q5 used to identify the most‐ and least‐deprived fifths of the population, respectively. Logistic regression models adjusted for age, sex, health board, history of cardiovascular disease and duration of diabetes were used to estimate odds ratios (ORs) for Q1 compared with Q5 for each risk factor. Results: The mean (sd) age of the study population was 66.7 (12.8) years, 56% were men, 24% were in Q1 and 15% were in Q5. Crude prevalence in Q1/Q5 was 24%/8.8% for smoking, 62%/49% for BMI ≥ 30 kg/m2, 44%/40% for HbA1c ≥ 58 mmol/mol (7.5%), 31%/31% for systolic blood pressure (SBP) ≥ 140 mmHg, and 24%/25% for total cholesterol ≥ 5 mmol/l, respectively. ORs [95% confidence intervals (CI)] were 3.08 (2.95–3.21) for current smoking, 1.48 (1.44–1.52) for BMI ≥ 30 kg/m2, 1.11 (1.08–1.15) for HbA1c ≥ 58 mmol/mol (7.5%), 1.03 (1.00–1.06) for SBP ≥ 140 mmHg and 0.87 (0.84–0.90) for total cholesterol ≥ 5 mmol/l. Conclusions: Socio‐economic deprivation is associated with higher prevalence of smoking, BMI ≥ 30 kg/m2 and HbA1c ≥ 58 mmol/mol (7.5%), and lower prevalence of total cholesterol ≥ 5 mmol/l among people with type 2 diabetes in Scotland. Effective approaches to reducing inequalities are required as well as reducing risk factor prevalence across the whole population. What's new?: Socio‐economic deprivation is associated with increased risk of cardiovascular disease in people with diabetes.This study, using a national database of quarter of a million people, found that socio‐economic deprivation is strongly positively associated with smoking and obesity, modestly positively associated with above‐target HbA1c, and modestly negatively associated with above‐target cholesterol, with no evidence of an association with above‐target blood pressure.Inequalities appear to have widened over time.Our findings may enable more effective interventions to reduce these inequalities by targeted approaches in subgroups of the population. [ABSTRACT FROM AUTHOR]

Aims: To describe the prevalence of major cardiovascular disease (CVD) and risk factor control in a contemporary population with Type 2 diabetes. Methods: We used data from the national registry in Scotland, Scottish Care Information‐Diabetes, linked to hospital admissions. Using descriptive statistics and logistic regression we described associations of risk factors with CVD. CVD was defined based on diagnostic codes in primary or secondary care data for ischaemic heart disease, cerebrovascular disease peripheral arterial disease, heart failure, cardiac arrhythmia, hypertensive heart disease and revascularization procedures. Results: Among 248 400 people with Type 2 diabetes with a median age of 67.5 years (IQR 58.2, 76.1) and median diabetes duration of 7.8 years (3.8, 13.0), 32% had prior CVD (35% of men, 29% of women). Median HbA1c overall was 55 mmol/mol (7.2%), median SBP was 132 mmHg, median total cholesterol was 4.1 mmol/l and mean BMI was 32 kg/m2. Overall two‐thirds (65% of men, 68% of women) have two or more of the following CVD risk factor thresholds: HbA1c ≥ 53 mmol/mol (7%), SBP > 130 mmHg or DBP > 80 mmHg, total cholesterol ≥ 5 mmol/l or BMI ≥ 30 kg/m2, or were currently smoking. Overall 84% were taking anti‐hypertensives and 75% a statin. Use of metformin was common at 58%, but other diabetes drugs that reduce CVD were rarely used. Conclusions: There continues to be a high prevalence of CVD among people with Type 2 diabetes and a high level of unmet need for risk factor control. This implies substantial scope for reducing the excess risk of CVD in diabetes through improved management of known risk factors. What's new?: There have been substantial advances in the management and prevention of cardiovascular disease in diabetes. To understand where unmet needs lie, it is important to understand the current burden of cardiovascular disease and the levels of treated and untreated risk factors.In this paper, we show that there continues to be a high prevalence of cardiovascular disease among people with Type 2 diabetes and a high level of unmet need for risk factor control. This implies substantial scope for reducing the excess risk of cardiovascular disease in diabetes through improved management of known risk factors. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: Whether hypoglycaemia increases the risk of other adverse outcomes in diabetes remains controversial, especially for hypoglycaemia episodes not requiring assistance from another person. An objective of the Hypoglycaemia REdefining SOLutions for better liVEs (Hypo-RESOLVE) project was to create and use a dataset of pooled clinical trials in people with type 1 or type 2 diabetes to examine the association of exposure to all hypoglycaemia episodes across the range of severity with incident event outcomes: death, CVD, neuropathy, kidney disease, retinal disorders and depression. We also examined the change in continuous outcomes that occurred following a hypoglycaemia episode: change in eGFR, HbA 1c , blood glucose, blood glucose variability and weight., Methods: Data from 84 trials with 39,373 participants were pooled. For event outcomes, time-updated Cox regression models adjusted for age, sex, diabetes duration and HbA 1c were fitted to assess association between: (1) outcome and cumulative exposure to hypoglycaemia episodes; and (2) outcomes where an acute effect might be expected (i.e. death, acute CVD, retinal disorders) and any hypoglycaemia exposure within the last 10 days. Exposures to any hypoglycaemia episode and to episodes of given severity (levels 1, 2 and 3) were examined. Further adjustment was then made for a wider set of potential confounders. The within-person change in continuous outcomes was also summarised (median of 40.4 weeks for type 1 diabetes and 26 weeks for type 2 diabetes). Analyses were conducted separately by type of diabetes., Results: The maximally adjusted association analysis for type 1 diabetes found that cumulative exposure to hypoglycaemia episodes of any level was associated with higher risks of neuropathy, kidney disease, retinal disorders and depression, with risk ratios ranging from 1.55 (p=0.002) to 2.81 (p=0.002). Associations of a similar direction were found when level 1 episodes were examined separately but were significant for depression only. For type 2 diabetes cumulative exposure to hypoglycaemia episodes of any level was associated with higher risks of death, acute CVD, kidney disease, retinal disorders and depression, with risk ratios ranging from 2.35 (p<0.0001) to 3.00 (p<0.0001). These associations remained significant when level 1 episodes were examined separately. There was evidence of an association between hypoglycaemia episodes of any kind in the previous 10 days and death, acute CVD and retinal disorders in both type 1 and type 2 diabetes, with rate ratios ranging from 1.32 (p=0.017) to 2.68 (p<0.0001). These associations varied in magnitude and significance when examined separately by hypoglycaemia level. Within the range of hypoglycaemia defined by levels 1, 2 and 3, we could not find any evidence of a threshold at which risk of these consequences suddenly became pronounced., Conclusions/interpretation: These data are consistent with hypoglycaemia being associated with an increased risk of adverse events across several body systems in diabetes. These associations are not confined to severe hypoglycaemia requiring assistance., (© 2024. The Author(s).)

Aims/hypothesis: The objective of the Hypoglycaemia REdefining SOLutions for better liVES (Hypo-RESOLVE) project is to use a dataset of pooled clinical trials across pharmaceutical and device companies in people with type 1 or type 2 diabetes to examine factors associated with incident hypoglycaemia events and to quantify the prediction of these events., Methods: Data from 90 trials with 46,254 participants were pooled. Analyses were done for type 1 and type 2 diabetes separately. Poisson mixed models, adjusted for age, sex, diabetes duration and trial identifier were fitted to assess the association of clinical variables with hypoglycaemia event counts. Tree-based gradient-boosting algorithms (XGBoost) were fitted using training data and their predictive performance in terms of area under the receiver operating characteristic curve (AUC) evaluated on test data. Baseline models including age, sex and diabetes duration were compared with models that further included a score of hypoglycaemia in the first 6 weeks from study entry, and full models that included further clinical variables. The relative predictive importance of each covariate was assessed using XGBoost's importance procedure. Prediction across the entire trial duration for each trial (mean of 34.8 weeks for type 1 diabetes and 25.3 weeks for type 2 diabetes) was assessed., Results: For both type 1 and type 2 diabetes, variables associated with more frequent hypoglycaemia included female sex, white ethnicity, longer diabetes duration, treatment with human as opposed to analogue-only insulin, higher glucose variability, higher score for hypoglycaemia across the 6 week baseline period, lower BP, lower lipid levels and treatment with psychoactive drugs. Prediction of any hypoglycaemia event of any severity was greater than prediction of hypoglycaemia requiring assistance (level 3 hypoglycaemia), for which events were sparser. For prediction of level 1 or worse hypoglycaemia during the whole follow-up period, the AUC was 0.835 (95% CI 0.826, 0.844) in type 1 diabetes and 0.840 (95% CI 0.831, 0.848) in type 2 diabetes. For level 3 hypoglycaemia, the AUC was lower at 0.689 (95% CI 0.667, 0.712) for type 1 diabetes and 0.705 (95% CI 0.662, 0.748) for type 2 diabetes. Compared with the baseline models, almost all the improvement in prediction could be captured by the individual's hypoglycaemia history, glucose variability and blood glucose over a 6 week baseline period., Conclusions/interpretation: Although hypoglycaemia rates show large variation according to sociodemographic and clinical characteristics and treatment history, looking at a 6 week period of hypoglycaemia events and glucose measurements predicts future hypoglycaemia risk., (© 2024. The Author(s).)

Background: Diabetes is a major public health issue. Because lifetime risk, life expectancy, and years of life lost are meaningful metrics for clinical decision making, we aimed to estimate these measures for type 2 diabetes in the high-income setting., Methods: For this multinational, population-based study, we sourced data from 24 databases for 23 jurisdictions (either whole countries or regions of a country): Australia; Austria; Canada; Denmark; Finland; France; Germany; Hong Kong; Hungary; Israel; Italy; Japan; Latvia; Lithuania; the Netherlands; Norway; Scotland; Singapore; South Korea; Spain; Taiwan; the UK; and the USA. Our main outcomes were lifetime risk of type 2 diabetes, life expectancy in people with and without type 2 diabetes, and years of life lost to type 2 diabetes. We modelled the incidence and mortality of type 2 diabetes in people with and without type 2 diabetes in sex-stratified, age-adjusted, and calendar year-adjusted Poisson models for each jurisdiction. Using incidence and mortality, we constructed life tables for people of both sexes aged 20-100 years for each jurisdiction and at two timepoints 5 years apart in the period 2005-19 where possible. Life expectancy from a given age was computed as the area under the survival curves and lifetime lost was calculated as the difference between the expected lifetime of people with versus without type 2 diabetes at a given age. Lifetime risk was calculated as the proportion of each cohort who developed type 2 diabetes between the ages of 20 years and 100 years. We estimated 95% CIs using parametric bootstrapping., Findings: Across all study cohorts from the 23 jurisdictions (total person-years 1 577 234 194), there were 5 119 585 incident cases of type 2 diabetes, 4 007 064 deaths in those with type 2 diabetes, and 11 854 043 deaths in those without type 2 diabetes. The lifetime risk of type 2 diabetes ranged from 16·3% (95% CI 15·6-17·0) for Scottish women to 59·6% (58·5-60·8) for Singaporean men. Lifetime risk declined with time in 11 of the 15 jurisdictions for which two timepoints were studied. Among people with type 2 diabetes, the highest life expectancies were found for both sexes in Japan in 2017-18, where life expectancy at age 20 years was 59·2 years (95% CI 59·2-59·3) for men and 64·1 years (64·0-64·2) for women. The lowest life expectancy at age 20 years with type 2 diabetes was observed in 2013-14 in Lithuania (43·7 years [42·7-44·6]) for men and in 2010-11 in Latvia (54·2 years [53·4-54·9]) for women. Life expectancy in people with type 2 diabetes increased with time for both sexes in all jurisdictions, except for Spain and Scotland. The life expectancy gap between those with and without type 2 diabetes declined substantially in Latvia from 2010-11 to 2015-16 and in the USA from 2009-10 to 2014-15. Years of life lost to type 2 diabetes ranged from 2·5 years (Latvia; 2015-16) to 12·9 years (Israel Clalit Health Services; 2015-16) for 20-year-old men and from 3·1 years (Finland; 2011-12) to 11·2 years (Israel Clalit Health Services; 2010-11 and 2015-16) for 20-year-old women. With time, the expected number of years of life lost to type 2 diabetes decreased in some jurisdictions and increased in others. The greatest decrease in years of life lost to type 2 diabetes occurred in the USA between 2009-10 and 2014-15 for 20-year-old men (a decrease of 2·7 years)., Interpretation: Despite declining lifetime risk and improvements in life expectancy for those with type 2 diabetes in many high-income jurisdictions, the burden of type 2 diabetes remains substantial. Public health strategies might benefit from tailored approaches to continue to improve health outcomes for people with diabetes., Funding: US Centers for Disease Control and Prevention and Diabetes Australia., Competing Interests: Declaration of interests SKP is currently a full-time employee of AstraZeneca. All other authors declare no competing interests., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Introduction: Participants in randomised controlled trials (trials) are generally younger and healthier than many individuals encountered in clinical practice. Consequently, the applicability of trial findings is often uncertain. To address this, results from trials can be calibrated to more representative data sources. In a network meta-analysis, using a novel approach which allows the inclusion of trials whether or not individual-level participant data (IPD) is available, we will calibrate trials for three drug classes (sodium glucose cotransporter 2 (SGLT2) inhibitors, glucagon-like peptide-1 (GLP1) receptor analogues and dipeptidyl peptidase-4 (DPP4) inhibitors) to the Scottish diabetes register., Methods and Analysis: Medline and EMBASE databases, the US clinical trials registry (clinicaltrials.gov) and the Chinese Clinical Trial Registry (chictr.org.cn) will be searched from 1 January 2002. Two independent reviewers will apply eligibility criteria to identify trials for inclusion. Included trials will be phase 3 or 4 trials of SGLT2 inhibitors, GLP1 receptor analogues or DPP4 inhibitors, with placebo or active comparators, in participants with type 2 diabetes, with at least one of glycaemic control, change in body weight or major adverse cardiovascular event as outcomes. Unregistered trials will be excluded.We have identified a target population from the population-based Scottish diabetes register. The chosen cohort comprises people in Scotland with type 2 diabetes who either (1) require further treatment due to poor glycaemic control where any of the three drug classes may be suitable, or (2) who have adequate glycaemic control but are already on one of the three drug classes of interest or insulin., Ethics and Dissemination: Ethical approval for IPD use was obtained from the University of Glasgow MVLS College Ethics Committee (Project: 200160070). The Scottish diabetes register has approval from the Scottish A Research Ethics Committee (11/AL/0225) and operates with Public Benefit and Privacy Panel for Health and Social Care approval (1617-0147)., Prospero Registration Number: CRD42020184174., Competing Interests: Competing interests: DMcA, EB, DP, SD, NW report funding for the present manuscript from the Medical Research Council (MRC) (MR/T017112/1). DMcA reports funding from the Wellcome Trust. PH reports funding from the MRC. AA reports departmental support for a randomized controlled trial from NovoNordisk to look at a GLP-agonist in a disease area other than diabetes. LB reports investment funds with shares held in various companies including Novo Nordisk and Astrazeneca, however these are chosen at the discretion of the fund manager and will fluctuate over time. No stocks/funds were chosen to benefit specifically from any company with a relationship to this manuscript. JP reports institutional grants via Merck KGaA and Novo Nordisk (co-fund with JDRF), institutional supply of investigational medicinal product for clinical trials from AstraZeneca, and personal fees from Boehringer Ingelheim (via IQVIA and via ACI Clinical), Biocon, Novo Nordisk and Merck. JP is also a member of an advisory board for Novo Nordisk and has an unpaid leadership role for Novo Nordisk UK Research Foundation (former Chair of Board of Trustees). NS reports institutional grants from AstraZeneca, Boehringer Ingelheim, Novartis and Roche Diagnostics and personal fees from Abbott Laboratories, Afimmune, Amgen, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Hanmi Pharmaceuticals, Janssen, Merck Sharp & Dohme, Novartis, Novo Nordisk, Pfizer, and Sanofi. LT reports MRC, Wellcome and NIHR funding, funding from GSK for an epidemiological study of kidney disease (no personal payment received) and reports consulting for Bayer in relation to an observational study of chronic kidney disease (no personal payment received). LT is also a member of the MHRA Expert advisory group (Women’s Health) and a member of 3 non-industry funded (NIHR/MRC) trial advisory committees (unpaid). NW reports honoraria for training and masterclasses on statistical methodology from Association of British Pharmaceutical Industries, Campbell Ireland, Centre for Global Development, NICE International and NICE Scientific Advice. All other authors report no competing interests., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Background: Defective alleles within the PRF1 gene, encoding the pore-forming protein perforin, in combination with environmental factors, cause familial type 2 hemophagocytic lymphohistiocytosis (FHL2), a rare, severe autosomal recessive childhood disorder characterized by massive release of cytokines-cytokine storm., Objective: The aim of this study was to determine the function of hypomorph PRF1:p.A91V g.72360387 G > A on multiple sclerosis (MS) and type 1 diabetes (T1D)., Methods: We cross-compare the association data for PRF1:p.A91V mutation derived from GWAS on adult MS and pediatric T1D in Sardinians. The novel association with T1D was replicated in metanalysis in 12,584 cases and 17,692 controls from Sardinia, the United Kingdom, and Scotland. To dissect this mutation function, we searched through the coincident association immunophenotypes in additional set of general population Sardinians., Results: We report that PRF1:p.A91V , is associated with increase of lymphocyte levels, especially within the cytotoxic memory T-cells, at general population level with reduced interleukin 7 receptor expression on these cells. The minor allele increased risk of MS, in 2903 cases and 2880 controls from Sardinia p  = 2.06 × 10 -4 , odds ratio OR = 1.29, replicating a previous finding, whereas it protects from T1D p  = 1.04 × 10 -5 , OR = 0.82., Conclusion: Our results indicate opposing contributions of the cytotoxic T-cell compartment to MS and T1D pathogenesis.

Background: Clinically vulnerable individuals have been advised to shield themselves during the COVID-19 epidemic. The objectives of this study were to investigate (1) the rate ratio of severe COVID-19 associated with eligibility for the shielding programme in Scotland across the first and second waves of the epidemic and (2) the relation of severe COVID-19 to transmission-related factors in those in shielding and the general population., Methods: In a matched case-control design, all 178,578 diagnosed cases of COVID-19 in Scotland from 1 March 2020 to 18 February 2021 were matched for age, sex and primary care practice to 1,744,283 controls from the general population. This dataset (REACT-SCOT) was linked to the list of 212,702 individuals identified as eligible for shielding. Severe COVID-19 was defined as cases that entered critical care or were fatal. Rate ratios were estimated by conditional logistic regression., Results: With those without risk conditions as reference category, the univariate rate ratio for severe COVID-19 was 3.21 (95% CI 3.01 to 3.41) in those with moderate risk conditions and 6.3 (95% CI 5.8 to 6.8) in those eligible for shielding. The highest rate was in solid organ transplant recipients: rate ratio 13.4 (95% CI 9.6 to 18.8). Risk of severe COVID-19 increased with the number of adults but decreased with the number of school-age children in the household. Severe COVID-19 was strongly associated with recent exposure to hospital (defined as 5 to 14 days before presentation date): rate ratio 12.3 (95% CI 11.5 to 13.2) overall. The population attributable risk fraction for recent exposure to hospital peaked at 50% in May 2020 and again at 65% in December 2020., Conclusions: The effectiveness of shielding vulnerable individuals was limited by the inability to control transmission in hospital and from other adults in the household. Mitigating the impact of the epidemic requires control of nosocomial transmission.

Objective: To quantify the relationship of residual C-peptide secretion to glycemic outcomes and microvascular complications in type 1 diabetes., Research Design and Methods: C-peptide was measured in an untimed blood sample in the Scottish Diabetes Research Network Type 1 Bioresource (SDRNT1BIO) cohort of 6,076 people with type 1 diabetes monitored for an average of 5.2 years., Results: In regression models adjusted for age at onset and duration, effect sizes for C-peptide ≥200 vs. <5 pmol/L were as follows: insulin dose at baseline, 27% lower ( P = 2 × 10 -39 ); HbA 1c during follow-up, 4.9 mmol/mol lower ( P = 3 × 10 -13 ); hazard ratio for hospital admission for diabetic ketoacidosis during follow-up, 0.44 ( P = 0.0001); odds ratio for incident retinopathy, 0.51 ( P = 0.0003). Effects on the risk of serious hypoglycemic episodes were detectable at lower levels of C-peptide, and the form of the relationship was continuous down to the limit of detection (3 pmol/L). In regression models contrasting C-peptide 30 to <200 pmol/L with <5 pmol/L, the odds ratio for self-report of at least one serious hypoglycemic episode in the last year was 0.56 ( P = 6 × 10 -8 ), and the hazard ratio for hospital admission for hypoglycemia during follow-up was 0.52 ( P = 0.03)., Conclusions: These results in a large representative cohort suggest that even minimal residual C-peptide secretion could have clinical benefit in type 1 diabetes, in contrast to a follow-up study of the Diabetes Control and Complications Trial (DCCT) intensively treated cohort where an effect on hypoglycemia was seen only at C-peptide levels ≥130 pmol/L. This has obvious implications for the design and evaluation of trials of interventions to preserve or restore pancreatic islet function in type 1 diabetes., (© 2020 by the American Diabetes Association.)

Aim: To compare costs for three groups of people with type 2 diabetes, those at high risk of future cardiovascular disease, those without cardiovascular disease and those with established cardiovascular disease, and to also compare costs incurred by people with type 2 diabetes with an incident cardiovascular disease event with those who remain incident event-free over a 3-year period., Methods: Data about people with type 2 diabetes in Scotland were obtained from the Scottish Care Information Diabetes registry. Data linkage was used to retrieve information on healthcare utilization, care home use and deaths. Productivity effects were estimated for those of non-pensionable age. We estimated costs over 12 months (prevalent cardiovascular disease) and 3 years from incident cardiovascular disease event., Results: Mean annual cost per person with established cardiovascular disease was £6900, £3300 for a person at high risk of future cardiovascular disease, and £2500 for a person without cardiovascular disease and not at high risk. In year 1, the cost of an incident cardiovascular disease event was £16 700 compared with £2100 for people without an incident event. Over 2 years, the cumulative costs were £21 500 and £4200, and by year 3, £25 000 and £5900, respectively., Conclusions: Cardiovascular disease in people with type 2 diabetes places a significant financial burden on healthcare and the wider economy. Our results emphasize the financial consequences of cardiovascular disease prevention strategies., (© 2020 Diabetes UK.)

Background: National guidelines in most countries set screening intervals for diabetic retinopathy (DR) that are insufficiently informed by contemporary incidence rates. This has unspecified implications for interval disease risks (IDs) of referable DR, disparities in ID between groups or individuals, time spent in referable state before screening (sojourn time), and workload. We explored the effect of various screening schedules on these outcomes and developed an open-access interactive policy tool informed by contemporary DR incidence rates., Methods and Findings: Scottish Diabetic Retinopathy Screening Programme data from 1 January 2007 to 31 December 2016 were linked to diabetes registry data. This yielded 128,606 screening examinations in people with type 1 diabetes (T1D) and 1,384,360 examinations in people with type 2 diabetes (T2D). Among those with T1D, 47% of those without and 44% of those with referable DR were female, mean diabetes duration was 21 and 23 years, respectively, and mean age was 26 and 24 years, respectively. Among those with T2D, 44% of those without and 42% of those with referable DR were female, mean diabetes duration was 9 and 14 years, respectively, and mean age was 58 and 52 years, respectively. Individual probability of developing referable DR was estimated using a generalised linear model and was used to calculate the intervals needed to achieve various IDs across prior grade strata, or at the individual level, and the resultant workload and sojourn time. The current policy in Scotland-screening people with no or mild disease annually and moderate disease every 6 months-yielded large differences in ID by prior grade (13.2%, 3.6%, and 0.6% annually for moderate, mild, and no prior DR strata, respectively, in T1D) and diabetes type (2.4% in T1D and 0.6% in T2D overall). Maintaining these overall risks but equalising risk across prior grade strata would require extremely short intervals in those with moderate DR (1-2 months) and very long intervals in those with no prior DR (35-47 months), with little change in workload or average sojourn time. Changing to intervals of 12, 9, and 3 months in T1D and to 24, 9, and 3 months in T2D for no, mild, and moderate DR strata, respectively, would substantially reduce disparity in ID across strata and between diabetes types whilst reducing workload by 26% and increasing sojourn time by 2.3 months. Including clinical risk factor data gave a small but significant increment in prediction of referable DR beyond grade (increase in C-statistic of 0.013 in T1D and 0.016 in T2D, both p < 0.001). However, using this model to derive personalised intervals did not have substantial workload or sojourn time benefits over stratum-specific intervals. The main limitation is that the results are pertinent only to countries that share broadly similar rates of retinal disease and risk factor distributions to Scotland., Conclusions: Changing current policies could reduce disparities in ID and achieve substantial reductions in workload within the range of IDs likely to be deemed acceptable. Our tool should facilitate more rational policy setting for screening., Competing Interests: The authors have declared that no competing interests exist.

Background: The objective of this cross-sectional study was to explore the relationship of detectable C-peptide secretion in type 1 diabetes to clinical features and to the genetic architecture of diabetes., Methods: C-peptide was measured in an untimed serum sample in the SDRNT1BIO cohort of 6076 Scottish people with clinically diagnosed type 1 diabetes or latent autoimmune diabetes of adulthood. Risk scores at loci previously associated with type 1 and type 2 diabetes were calculated from publicly available summary statistics., Results: Prevalence of detectable C-peptide varied from 19% in those with onset before age 15 and duration greater than 15 years to 92% in those with onset after age 35 and duration less than 5 years. Twenty-nine percent of variance in C-peptide levels was accounted for by associations with male gender, late age at onset and short duration. The SNP heritability of residual C-peptide secretion adjusted for gender, age at onset and duration was estimated as 26%. Genotypic risk score for type 1 diabetes was inversely associated with detectable C-peptide secretion: the most strongly associated loci were the HLA and INS gene regions. A risk score for type 1 diabetes based on the HLA DR3 and DQ8-DR4 serotypes was strongly associated with early age at onset and inversely associated with C-peptide persistence. For C-peptide but not age at onset, there were strong associations with risk scores for type 1 and type 2 diabetes that were based on SNPs in the HLA region but not accounted for by HLA serotype., Conclusions: Persistence of C-peptide secretion varies widely in people clinically diagnosed as type 1 diabetes. C-peptide persistence is influenced by variants in the HLA region that are different from those determining risk of early-onset type 1 diabetes. Known risk loci for diabetes account for only a small proportion of the genetic effects on C-peptide persistence.

Aims/hypothesis: The aim of this work was to examine whether glycaemic control has improved in those with type 1 diabetes in Scotland between 2004 and 2016, and whether any trends differed by sociodemographic factors., Methods: We analysed records from 30,717 people with type 1 diabetes, registered anytime between 2004 and 2016 in the national diabetes database, which contained repeated measures of HbA 1c . An additive mixed regression model was used to estimate calendar time and other effects on HbA 1c ., Results: Overall, median (IQR) HbA 1c decreased from 72 (21) mmol/mol [8.7 (4.1)%] in 2004 to 68 (21) mmol/mol (8.4 [4.1]%) in 2016. However, all of the improvement across the period occurred in the latter 4 years: the regression model showed that the only period of significant change in HbA 1c was 2012-2016 where there was a fall of 3 (95% CI 1.82, 3.43) mmol/mol. The largest reductions in HbA 1c in this period were seen in children, from 69 (16) mmol/mol (8.5 [3.6]%) to 63 (14) mmol/mol (7.9 [3.4]%), and adolescents, from 75 (25) mmol/mol (9.0 [4.4]%) to 70 (23) mmol/mol (8.6 [4.3]%). Socioeconomic status (according to Scottish Index of Multiple Deprivation) affected the HbA 1c values: from the regression model, the 20% of people living in the most-deprived areas had HbA 1c levels on average 8.0 (95% CI 7.4, 8.9) mmol/mol higher than those of the 20% of people living in the least-deprived areas. However this difference did not change significantly over time. From the regression model HbA 1c was on average 1.7 (95% CI 1.6, 1.8) mmol/mol higher in women than in men. This sex difference did not narrow over time., Conclusions/interpretation: In this high-income country, we identified a modest but important improvement in HbA 1c since 2012 that was most marked in children and adolescents. These changes coincided with national initiatives to reduce HbA 1c including an expansion of pump therapy. However, in most people, overall glycaemic control remains far from target levels and further improvement is badly needed, particularly in those from more-deprived areas.

Background: Recent clinical trials of new glucose-lowering treatments have drawn attention to the importance of hospitalization for heart failure as a complication of diabetes mellitus. However, the epidemiology is not well described, particularly for type 1 diabetes mellitus. We examined the incidence and case-fatality of heart failure hospitalizations in the entire population aged ≥30 years resident in Scotland during 2004 to 2013., Methods: Date and type of diabetes mellitus diagnosis were linked to heart failure hospitalizations and deaths using the national Scottish registers. Incidence rates and case-fatality were estimated in regression models (quasi-Poisson and logistic regression respectively). All estimates are adjusted for age, sex, socioeconomic status, and calendar-year., Results: Over the 10-year period of the study, among 3.25 million people there were 91, 429, 22 959, and 1313 incident heart failure events among those without diabetes mellitus, with type 2, and type 1 diabetes mellitus, respectively. The crude incidence rates of heart failure hospitalization were therefore 2.4, 12.4, and 5.6 per 1000 person-years for these 3 groups. Heart failure hospitalization incidence was higher in people with diabetes mellitus, regardless of type, than in people without. Relative differences were smallest for older men, in whom the difference was nonetheless large (men aged 80, rate ratio 1.78; 95% CI, 1.45-2.19). Rates declined similarly, by 0.2% per calendar-year, in people with type 2 diabetes mellitus and without diabetes mellitus. Rates fell faster, however, in those with type 1 diabetes mellitus (2.2% per calendar-year, rate ratio for type 1/calendar-year interaction 0.978; 95% CI, 0.959-0.998). Thirty-day case-fatality was similar among people with type 2 diabetes mellitus and without diabetes mellitus, but was higher in type 1 diabetes mellitus for men (odds ratio, 0.96; 95% CI, 0.95-0.96) and women (odds ratio, 0.98; 95% CI, 0.97-0.98). Case-fatality declined over time for all groups (3.3% per calendar-year, odds ratio per calendar-year 0.967; 95% CI, 0.961-0.973)., Conclusions: Despite falling incidence, particularly in type 1 diabetes mellitus, heart failure remains ≈2-fold higher than in people without diabetes mellitus, with higher case-fatality in those with type 1 diabetes mellitus. These findings support the view that heart failure is an under-recognized and important complication in diabetes mellitus, particularly for type 1 disease.

Aims/hypothesis: Our aim was to investigate amputation-free survival in people at high risk for foot ulceration in diabetes ('high-risk foot'), and to compare different subcategories of high-risk foot., Methods: Overall, 17,353 people with diabetes and high-risk foot from January 2008 to December 2011 were identified from the Scotland-wide diabetes register (Scottish Care Information-Diabetes: N = 247,278). Participants were followed-up for up to 2 years from baseline and were categorised into three groups: (1) those with no previous ulcer, (2) those with an active ulcer or (3) those with a healed previous ulcer. Participants with prior minor or major amputation were excluded. Accelerated failure time models were used to compare amputation-free survival up to 2 years between the three exposure groups., Results: The 2 year amputation-free survival rate in all people with diabetes with high-risk foot was 84.5%. In this study group, 270 people (10.0%) had an amputation and 2424 (90.0%) died during the 2 year follow-up period. People who had active and healed previous ulcers at baseline had significantly lower 2 year amputation-free survival compared with those who had no previous ulcer (both p < 0.0001). The percentage of people who died within 2 years for those with healed ulcer, active ulcer or no baseline ulcer was 22.8%, 16% and 12.1%, respectively., Conclusions/interpretation: In people judged to be at high risk of foot ulceration, the risk of death was up to nine times the risk of amputation. Death rates were higher for people with diabetes who had healed ulcers than for those with active ulcers. However, people with active ulcers had the highest risk of amputation.

Objective: To describe associations between alcoholic liver disease (ALD) or nonalcoholic fatty liver disease (NAFLD) hospital admission and cardiovascular disease (CVD), cancer, and mortality in people with type 2 diabetes mellitus (T2DM)., Research Design and Methods: We performed a retrospective cohort study by using linked population-based routine data from diabetes registry, hospital, cancer, and death records for people aged 40-89 years diagnosed with T2DM in Scotland between 2004 and 2013 who had one or more hospital admission records. Liver disease and outcomes were identified by using ICD-9 and ICD-10 codes. We estimated hazard ratios (HRs) from Cox proportional hazards regression models, adjusting for key risk factors., Results: A total of 134,368 people with T2DM (1,707 with ALD and 1,452 with NAFLD) were studied, with a mean follow-up of 4.3 years for CVD and 4.7 years for mortality. Among those with ALD, NAFLD, or without liver disease hospital records 378, 320, and 21,873 CVD events; 268, 176, and 15,101 cancers; and 724, 221, and 16,203 deaths were reported, respectively. For ALD and NAFLD, respectively, adjusted HRs (95% CIs) compared with the group with no record of liver disease were 1.59 (1.43, 1.76) and 1.70 (1.52, 1.90) for CVD, 40.3 (28.8, 56.5) and 19.12 (11.71, 31.2) for hepatocellular carcinoma (HCC), 1.28 (1.12, 1.47) and 1.10 (0.94, 1.29) for non-HCC cancer, and 4.86 (4.50, 5.24) and 1.60 (1.40, 1.83) for all-cause mortality., Conclusions: Hospital records of ALD or NAFLD are associated to varying degrees with an increased risk of CVD, cancer, and mortality among people with T2DM., (© 2017 by the American Diabetes Association.)

Purpose: To demonstrate a modelling approach that controls for time-invariant allocation bias in estimation of associations of outcome with drug exposure., Methods: We show that in a model that includes terms for both ever-exposure versus never-exposure and cumulative exposure, the parameter for ever-exposure represents the effect of time-invariant allocation bias, and the parameter for cumulative exposure represents the effect of the drug after adjustment for this unmeasured confounding. This assumes no stepwise effect of the drug on the event rate, no reverse causation, and no unmeasured time-varying confounders. We demonstrated this by modelling the effect of statins on cardiovascular disease, for which the true effect has been well characterised in randomised trials, using time-updated Cox regression models in a national cohort of Type 2 diabetes patients., Results: The crude hazard ratio associated with ever-use of statins was 1.13 in a standard cohort analysis comparing exposed with unexposed person-time intervals. When ever-never use and cumulative exposure are modelled jointly, the effect of statins can be estimated from the cumulative exposure parameter (hazard ratio 0.97 per year of exposure, 95% CI 0.97 to 0.98). The ever-exposed term (hazard ratio 1.20, 1.16 to 1.23) in this model can be interpreted as estimating the allocation bias., Conclusions: Where stepwise effects on the risk of adverse events are unlikely, as for instance for effects on risk of cancer, joint modelling of ever-never and cumulative exposure can be used to study the effects of multiple drugs and to distinguish causal effects from confounding by allocation., (Copyright © 2017 John Wiley & Sons, Ltd.)

Background: Whether metformin precipitates lactic acidosis in patients with chronic kidney disease (CKD) remains under debate. We examined whether metformin use was associated with an increased risk of acute kidney injury (AKI) as a proxy for lactic acidosis and whether survival among those with AKI varied by metformin exposure., Methods: All individuals with type 2 diabetes and available prescribing data between 2004 and 2013 in Tayside, Scotland were included. The electronic health record for diabetes which includes issued prescriptions was linked to laboratory biochemistry, hospital admission, death register and Scottish Renal Registry data. AKI events were defined using the Kidney Disease Improving Global Outcomes criteria with a rise in serum creatinine of at least  26.5 μmol/l or a rise of greater than 150% from baseline for all hospital admissions. Cox Regression Analyses were used to examine whether person-time periods in which current metformin exposure occurred were associated with an increased rate of first AKI compared to unexposed periods. Cox regression was also used to compare 28 day survival rates following first AKI events in those exposed to metformin versus those not exposed., Results: Twenty-five thousand one-hundred fourty-eight patients were included with a total person-time of 126,904 person years. 4944 (19.7%) people had at least one episode of AKI during the study period. There were 32.4 cases of first AKI/1000pyrs in current metformin exposed person-time periods compared to 44.9 cases/1000pyrs in unexposed periods. After adjustment for age, sex, diabetes duration, calendar time, number of diabetes drugs and baseline renal function, current metformin use was not associated with AKI incidence, HR 0.94 (95% CI 0.87, 1.02, p = 0.15). Among those with incident AKI, being on metformin at admission was associated with a higher rate of survival at 28 days (HR 0.81, 95% CI 0.69, 0.94, p = 0.006) even after adjustment for age, sex, pre-admission eGFR, HbA 1c and diabetes duration., Conclusions: Contrary to common perceptions, we found no evidence that metformin increases incidence of AKI and was associated with higher 28 day survival following incident AKI.