HbA1c Is Disproportionately Higher in Women and Older People With Type 1 Diabetes Compared With Flash Glucose Monitoring Metrics of Glycemic Control.

AIMS: Discrepancy between HbA1c and glucose exposure may have significant clinical implications. We sought to assess predictors of disparity between HbA1c and flash monitoring metrics and how these relate to microvascular complications. METHODS: We conducted a cross-sectional study of adults with type 1 diabetes (n = 518). We assessed the relationship between clinic HbA1c and flash monitoring metrics, predictors of discrepancy between these measurements, and whether discrepancy was associated with microvascular complications. RESULTS: Actual HbA1c and estimated HbA1c were strongly correlated (r = .779, P < .001). The likelihood of having a higher actual HbA1c than estimated HbA1c was greater with increasing age (OR = 1.055 per year, P < .001) and lower in men (OR = .208, P < .001). HbA1c was significantly lower in men (58 mmol/mol [51-67]) (7.5% [6.8-8.3]) compared to women (61 mmol/mol [54-70], P = .021) (7.7% [7.1-8.6]), despite no significant differences in any flash monitoring metrics. Whereas HbA1c was not different between younger (≤39 years) and older individuals (>39 years) despite significantly higher glucose exposure, in younger people, based on multiple flash monitoring metrics. Having a lower estimated than actual HbA1c was independently associated with a lower prevalence of retinopathy (OR = .55, P = .004). CONCLUSIONS: HbA1c appears to overestimate glucose exposure in women and older people with type 1 diabetes. This has potentially important clinical implications, as is hinted at by the independent relationship with retinopathy prevalence. It may also be of relevance when considering the use of HbA1c for the diagnosis of diabetes.

Flash monitor initiation is associated with improvements in HbA1c levels and DKA rates among people with type 1 diabetes in Scotland: a retrospective nationwide observational study.

AIMS/HYPOTHESIS: We assessed the real-world effect of flash monitor (FM) usage on HbA1c levels and diabetic ketoacidosis (DKA) and severe hospitalised hypoglycaemia (SHH) rates among people with type 1 diabetes in Scotland and across sociodemographic strata within this population. METHODS: This study was retrospective, observational and registry based. Using the national diabetes registry, 14,682 individuals using an FM at any point between 2014 and mid-2020 were identified. Within-person change from baseline in HbA1c following FM initiation was modelled using linear mixed models accounting for within-person pre-exposure trajectory. DKA and SHH events were captured through linkage to hospital admission and mortality data. The difference in DKA and SHH rates between FM-exposed and -unexposed person-time was assessed among users, using generalised linear mixed models with a Poisson likelihood. In a sensitivity analysis, we tested whether changes in these outcomes were seen in an age-, sex- and baseline HbA1c-matched sample of non-users over the same time period. RESULTS: Prevalence of ever-FM use was 45.9% by mid-2020, with large variations by age and socioeconomic status: 64.3% among children aged <13 years vs 32.7% among those aged ≥65 years; and 54.4% vs 36.2% in the least-deprived vs most-deprived quintile. Overall, the median (IQR) within-person change in HbA1c in the year following FM initiation was -2.5 (-9.0, 2.5) mmol/mol (-0.2 [-0.8, 0.2]%). The change varied widely by pre-usage HbA1c: -15.5 (-31.0, -4.0) mmol/mol (-1.4 [-2.8, -0.4]%) in those with HbA1c > 84 mmol/mol [9.8%] and 1.0 (-2.0, 5.5) mmol/mol (0.1 [-0.2, 0.5]%) in those with HbA1c < 54 mmol/mol (7.1%); the corresponding estimated fold change (95% CI) was 0.77 (0.76, 0.78) and 1.08 (1.07, 1.09). Significant reductions in HbA1c were found in all age bands, sexes and socioeconomic strata, and regardless of prior/current pump use, completion of a diabetes education programme or early FM adoption. Variation between the strata of these factors beyond that driven by differing HbA1c at baseline was slight. No change in HbA1c in matched non-users was observed in the same time period (median [IQR] within-person change = 0.5 [-5.0, 5.5] mmol/mol [0.0 (-0.5, 0.5)%]). DKA rates decreased after FM initiation overall and in all strata apart from the adolescents. Estimated overall reduction in DKA event rates (rate ratio) was 0.59 [95% credible interval (CrI) 0.53, 0.64]) after FM vs before FM initiation, accounting for pre-exposure trend. Finally, among those at higher risk for SHH, estimated reduction in event rates was rate ratio 0.25 (95%CrI 0.20, 0.32) after FM vs before FM initiation. CONCLUSIONS/INTERPRETATION: FM initiation is associated with clinically important reductions in HbA1c and striking reduction in DKA rate. Increasing uptake among the socioeconomically disadvantaged offers considerable potential for tightening the current socioeconomic disparities in glycaemia-related outcomes.

International comparison of glycaemic control in people with type 1 diabetes: an update and extension.

AIMS: To update and extend a previous cross-sectional international comparison of glycaemic control in people with type 1 diabetes. METHODS: Data were obtained for 520,392 children and adults with type 1 diabetes from 17 population and five clinic-based data sources in countries or regions between 2016 and 2020. Median HbA1c (IQR) and proportions of individuals with HbA1c < 58 mmol/mol (<7.5%), 58-74 mmol/mol (7.5-8.9%) and ≥75 mmol/mol (≥9.0%) were compared between populations for individuals aged <15, 15-24 and ≥25 years. Logistic regression was used to estimate the odds ratio (OR) of HbA1c < 58 mmol/mol (<7.5%) relative to ≥58 mmol/mol (≥7.5%), stratified and adjusted for sex, age and data source. Where possible, changes in the proportion of individuals in each HbA1c category compared to previous estimates were calculated. RESULTS: Median HbA1c varied from 55 to 79 mmol/mol (7.2 to 9.4%) across data sources and age groups so a pooled estimate was deemed inappropriate. OR (95% CI) for HbA1c < 58 mmol/mol (<7.5%) were 0.91 (0.90-0.92) for women compared to men, 1.68 (1.65-1.71) for people aged <15 years and 0.81 (0.79-0.82) aged15-24 years compared to those aged ≥25 years. Differences between populations persisted after adjusting for sex, age and data source. In general, compared to our previous analysis, the proportion of people with an HbA1c  < 58 mmol/l (<7.5%) increased and proportions of people with HbA1c ≥ 75 mmol/mol (≥9.0%) decreased. CONCLUSIONS: Glycaemic control of type 1 diabetes continues to vary substantially between age groups and data sources. While some improvement over time has been observed, glycaemic control remains sub-optimal for most people with Type 1 diabetes.

Rising Rates and Widening Socioeconomic Disparities in Diabetic Ketoacidosis in Type 1 Diabetes in Scotland: A Nationwide Retrospective Cohort Observational Study.

OBJECTIVE: Whether advances in the management of type 1 diabetes are reducing rates of diabetic ketoacidosis (DKA) is unclear. We investigated time trends in DKA rates in a national cohort of individuals with type 1 diabetes monitored for 14 years, overall and by socioeconomic characteristics. RESEARCH DESIGN AND METHODS: All individuals in Scotland with type 1 diabetes who were alive and at least 1 year old between 1 January 2004 and 31 December 2018 were identified using the national register (N = 37,939). DKA deaths and hospital admissions were obtained through linkage to Scottish national death and morbidity records. Bayesian regression was used to test for DKA time trends and association with risk markers, including socioeconomic deprivation. RESULTS: There were 30,427 DKA admissions and 472 DKA deaths observed over 393,223 person-years at risk. DKA event rates increased over the study period (incidence rate ratio [IRR] per year 1.058 [95% credibility interval 1.054-1.061]). Males had lower rates than females (IRR male-to-female 0.814 [0.776-0.855]). DKA incidence rose in all age-groups other than 10- to 19-year-olds, in whom rates were the highest, but fell over the study. There was a large socioeconomic differential (IRR least-to-most deprived quintile 0.446 [0.406-0.490]), which increased during follow-up. Insulin pump use or completion of structured education were associated with lower DKA rates, and antidepressant and methadone prescription were associated with higher DKA rates. CONCLUSIONS: DKA incidence has risen since 2004, except in 10- to 19-year-olds. Of particular concern are the strong and widening socioeconomic disparities in DKA outcomes. Efforts to prevent DKA, especially in vulnerable groups, require strengthening.

Marked improvements in glycaemic outcomes following insulin pump therapy initiation in people with type 1 diabetes: a nationwide observational study in Scotland.

AIMS/HYPOTHESIS: Our aim was to assess the use of continuous subcutaneous insulin infusion (CSII) in people with type 1 diabetes in Scotland and its association with glycaemic control, as measured by HbA1c levels, frequency of diabetic ketoacidosis (DKA) and severe hospitalised hypoglycaemia (SHH), overall and stratified by baseline HbA1c. METHODS: We included 4684 individuals with type 1 diabetes from the national Scottish register, who commenced CSII between 2004 and 2019. We presented crude within-person differences from baseline HbA1c over time since initiation, crude DKA and SHH event-rates pre-/post-CSII exposure. We then used mixed models to assess the significance of CSII exposure, taking into account: (1) the diffuse nature of the intervention (i.e. structured education often precedes initiation); (2) repeated within-person measurements; and (3) background time-trends occurring pre-intervention. RESULTS: HbA1c decreased after CSII initiation, with a median within-person change of -5.5 mmol/mol (IQR -12.0, 0.0) (-0.5% [IQR -1.1, 0.0]). Within-person changes were most substantial in those with the highest baseline HbA1c, with median -21.0 mmol/mol (-30.0, -11.0) (-1.9% [-2.7, -1.0]) change in those with a baseline >84 mmol/mol (9.8%) within a year of exposure, that was sustained: -19.0 mmol/mol (-27.6, -6.5) (-1.7% [-2.5, -0.6]) at ≥5 years. Statistical significance and magnitude of change were supported by the mixed models results. The crude DKA event-rate was significantly lower in post-CSII person-time compared with pre-CSII person-time: 49.6 events (95% CI 46.3, 53.1) per 1000 person-years vs 67.9 (64.1, 71.9); rate ratio from Bayesian mixed models adjusting for pre-exposure trend: 0.61 (95% credible interval [CrI] 0.47, 0.77; posterior probability of reduction pp = 1.00). The crude overall SHH event-rate in post-CSII vs pre-CSII person-time was also lower: 17.8 events (95% CI 15.8, 19.9) per 1000 person-years post-exposure vs 25.8 (23.5, 28.3) pre-exposure; rate ratio from Bayesian mixed models adjusting for pre-exposure trend: 0.67 (95% CrI 0.45, 1.01; pp = 0.97). CONCLUSIONS/INTERPRETATION: CSII therapy was associated with marked falls in HbA1c especially in those with high baseline HbA1c. CSII was independently associated with reduced DKA and SHH rates. CSII appears to be an effective option for intensive insulin therapy in people with diabetes for improving suboptimal glycaemic control.

The association of polypharmacy and high-risk drug classes with adverse health outcomes in the Scottish population with type 1 diabetes.

AIMS/HYPOTHESIS: The aim of this work was to map the number of prescribed drugs over age, sex and area-based socioeconomic deprivation, and to examine the association between the number of drugs and particular high-risk drug classes with adverse health outcomes among a national cohort of individuals with type 1 diabetes. METHODS: Utilising linked healthcare records from the population-based diabetes register of Scotland, we identified 28,245 individuals with a diagnosis of type 1 diabetes on 1 January 2017. For this population, we obtained information on health status, predominantly reflecting diabetes-related complications, and information on the total number of drugs and particular high-risk drug classes prescribed. We then studied the association of these baseline-level features with hospital admissions for falls, diabetic ketoacidosis (DKA), and hypoglycaemia or death within the subsequent year using multivariate Cox proportional hazards models. RESULTS: Not considering insulin and treatment for hypoglycaemia, the mean number of prescribed drugs was 4.00 (SD 4.35). The proportion of individuals being prescribed five or more drugs at baseline consistently increased with age (proportion [95% CI]: 0-19 years 2.04% [1.60, 2.49]; 40-49 years 28.50% [27.08, 29.93]; 80+ years 76.04% [67.73, 84.84]). Controlling for age, sex, area-based socioeconomic deprivation and health status, each additional drug at baseline was associated with an increase in the hazard for hospitalisation for falls, hypoglycaemia and death but not for DKA admissions (HR [95% CI]: falls 1.03 [1.01, 1.06]; DKA 1.01 [1.00, 1.03]; hypoglycaemia 1.05 [1.02, 1.07]; death 1.04 [1.02, 1.06]). We found a number of drug classes to be associated with an increased hazard of one or more of these adverse health outcomes, including antithrombotic/anticoagulant agents, corticosteroids, opioids, antiepileptics, antipsychotics, hypnotics and sedatives, and antidepressants. CONCLUSIONS: Polypharmacy is common among the Scottish population with type 1 diabetes and is strongly patterned by sociodemographic factors. The number of prescribed drugs and the prescription of particular high-risk drug classes are strong markers of an increased risk of adverse health outcomes, including acute complications of diabetes.

Socioeconomic deprivation, technology use, C-peptide, smoking and other predictors of glycaemic control in adults with type 1 diabetes.

AIMS: Intensive glycaemic control is associated with substantial health benefits in people with type 1 diabetes. We sought to examine clinical and demographic factors associated with meeting glycaemic targets in type 1 diabetes. METHODS: We conducted a cross-sectional analysis of 4594 individuals with type 1 diabetes. The primary outcome of the study was assessing factors associated with meeting HbA1c targets. Secondary endpoints included factors associated with continuous subcutaneous insulin infusion (CSII) use and persistent C-peptide secretion. RESULTS: Socioeconomic deprivation was strongly associated with a lower likelihood of achieving an HbA1c <58 mmol/mol (7.5%) (20% in the most deprived quintile vs. 40% in the least deprived, p < 0.001). In multivariate analysis, absence of smoking history (OR 3.06, p < 0.001), flash monitoring (OR 1.49, p < 0.001), CSII (1.43, p = 0.022) and longer diabetes duration (OR 1.02 per year, p = 0.004) were independently associated with achieving HbA1c <58 mmol/mol (7.5%), whereas increasing age (OR 0.99 per year, p = 0.004) and C-peptide <50 pM (OR 0.58, p < 0.001) were associated with a lower likelihood of meeting this target. Low C-peptide (<50 pM) was less likely in men (OR 0.55, p < 0.001) and never smokers (0.44, p < 0.001) in multivariate analysis. CONCLUSIONS: Lower levels of deprivation, non-smoking, higher C-peptide, technology use, lower BMI and male gender were all associated with a higher likelihood of meeting HbA1c targets. Access to proven diabetes treatments is lower in the most deprived individuals. Urgent efforts are required to provide treatments which are effective across the socioeconomic gradient.

Impact of routine clinic measurement of serum C-peptide in people with a clinician-diagnosis of type 1 diabetes.

AIMS/HYPOTHESIS: The aim of this study was to determine the impact of the routine use of serum C-peptide in an out-patient clinic setting on individuals with a clinician-diagnosis of type 1 diabetes. METHODS: In this single-centre study, individuals with type 1 diabetes of at least 3 years duration were offered random serum C-peptide testing at routine clinic review. A C-peptide ≥200 pmol/L prompted further evaluation of the individual using a diagnostic algorithm that included measurement of islet cell antibodies and genetic testing. Where appropriate, a trial of anti-diabetic co-therapies was considered. RESULTS: Serum C-peptide testing was performed in 859 individuals (90% of the eligible cohort), of whom 114 (13.2%) had C-peptide ≥200 pmol/L. The cause of diabetes was reclassified in 58 individuals (6.8% of the tested cohort). The majority of reclassifications were to type 2 diabetes (44 individuals; 5.1%), with a smaller proportion of monogenic diabetes (14 individuals; 1.6%). Overall, 13 individuals (1.5%) successfully discontinued insulin, while a further 16 individuals (1.9%) had improved glycaemic control following the addition of co-therapies. The estimated total cost of the testing programme was £23,262 (~€26,053), that is, £27 (~€30) per individual tested. In current terms, the cost of prior insulin therapy in the individuals with monogenic diabetes who successfully stopped insulin was approximately £57,000 (~€64,000). CONCLUSIONS/INTERPRETATION: Serum C-peptide testing can easily be incorporated into an out-patient clinic setting and could be a cost-effective intervention. C-peptide testing should be strongly considered in individuals with a clinician-diagnosis of type 1 diabetes of at least 3 years duration.

Clinical Impact of Residual C-Peptide Secretion in Type 1 Diabetes on Glycemia and Microvascular Complications.

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); HbA1c 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.

HbA1c response and hospital admissions following commencement of flash glucose monitoring in adults with type 1 diabetes.

INTRODUCTION: Our aim was to assess the effect of introducing flash monitoring in adults with type 1 diabetes with respect to change in hemoglobin A1c (HbA1c) and frequency of hospital admissions. RESEARCH DESIGN AND METHODS: Prospective observational study of adults with type 1 diabetes in our center, in whom a prescription for a flash monitoring sensor was collected. Primary outcome was change in HbA1c between 2016 and after flash monitoring. Rates of hospital admission were compared between the first year after flash monitoring and the corresponding 12-month period 2 years earlier. RESULTS: Approximately half of all adults with type 1 diabetes, attending our center, collected prescriptions for flash monitoring sensors (n=2216). Median fall in HbA1c was -1 (-0.1) mmol/mol (%) (p<0.001) and was greatest in those with baseline HbA1c >75 (9.0) mmol/mol (%): -10 (-0.9) mmol/mol (%), p<0.001. 43% of those with a baseline HbA1c >53 mmol/mol (7%) experienced a ≥5 mmol/mol (0.5%) fall in HbA1c. In addition to higher HbA1c, early commencement within 1 month of NHS-funded flash monitoring (p<0.001), and male gender (p=0.013) were associated with a fall in HbA1c of ≥5 (0.5) mmol/mol (%). Socioeconomic deprivation (p=0.009) and collecting fewer than 2 sensors per month (p=0.002) were associated with lack of response. Overall, hospital admissions did not change but an increase in admissions for hypoglycemia was observed (1.1% vs 0.3%, p=0.026). CONCLUSIONS: Flash monitoring is associated with reduction in HbA1c in individuals with HbA1c >58 mmol/mol. Numerous clinical features are independently associated with HbA1c response. An increase in hypoglycemia admissions occurred following flash monitoring.

Time trends in deaths before age 50 years in people with type 1 diabetes: a nationwide analysis from Scotland 2004-2017.

AIMS/HYPOTHESIS: We aimed to examine whether crude mortality and mortality relative to the general population below 50 years of age have improved in recent years in those with type 1 diabetes. METHODS: Individuals with type 1 diabetes aged below 50 and at least 1 year old at any time between 2004 and 2017 in Scotland were identified using the national register. Death data were obtained by linkage to Scottish national death registrations. Indirect age standardisation was used to calculate sex-specific standardised mortality ratios (SMRs). Poisson regression was used to test for calendar-time effects as incidence rate ratios (IRRs). RESULTS: There were 1138 deaths in 251,143 person-years among 27,935 people with type 1 diabetes. There was a significant decline in mortality rate over time (IRR for calendar year 0.983 [95% CI 0.967, 0.998], p = 0.03), but the SMR remained approximately stable at 3.1 and 3.6 in men and 4.09 and 4.16 in women for 2004 and 2017, respectively. Diabetic ketoacidosis or coma (DKAoC) accounted for 22% of deaths and the rate did not decline significantly (IRR 0.975 [95% CI 0.94, 1.011], p = 0.168); 79.3% of DKAoC deaths occurred out of hospital. Circulatory diseases accounted for 27% of deaths and did decline significantly (IRR 0.946 [95% CI 0.914, 0.979], p = 0.002). CONCLUSIONS/INTERPRETATION: Absolute mortality has fallen, but the relative impact of type 1 diabetes on mortality below 50 years has not improved. There is scope to improve prevention of premature circulatory diseases and DKAoC and to develop more effective strategies for enabling people with type 1 diabetes to avoid clinically significant hyper- or hypoglycaemia. Graphical abstract.

Preserved C-peptide secretion is associated with fewer low-glucose events and lower glucose variability on flash glucose monitoring in adults with type 1 diabetes.

AIMS/HYPOTHESIS: We aimed to assess whether persistence of C-peptide secretion is associated with less glucose variability and fewer low-glucose events in adults with type 1 diabetes who use flash monitoring. METHODS: We performed a cross-sectional study of 290 adults attending a university teaching hospital diabetes clinic, with type 1 diabetes, who use flash monitoring and in whom a random plasma C-peptide was available in the past 2 years. Variables relating to flash monitoring were compared between individuals with low C-peptide (<10 pmol/l) and those with persistent C-peptide (either 10-200 pmol/l or 10-50 pmol/l). In addition, the relationship between self-reported hypoglycaemia and C-peptide was assessed (n = 167). Data are median (interquartile range). RESULTS: Individuals with preserved C-peptide secretion (10-200 pmol/l) had shorter duration of diabetes (15 [9-24] vs 25 [15-34] years, p < 0.001) and older age at diagnosis (23 [14-28] vs 15 [9-25] years, p < 0.001), although current age did not differ in this cohort. Preserved C-peptide was associated with lower time with glucose <3.9 mmol/l (3% [2-6%] vs 5% [3-9%], p < 0.001), fewer low-glucose events per 2 week period (7 [4-10] vs 10 [5-16], p < 0.001), lower SD of glucose (3.8 [3.4-4.2] vs 4.1 [3.5-4.7] mmol/l, p = 0.017) and lower CV of glucose (38.0 [35.0-41.6] vs 41.8 [36.5-45.8], p < 0.001). These differences were also present in those with C-peptide 10-50 pmol/l and associations were independent of diabetes duration and estimated HbA1c in logistic regression analysis. Preserved C-peptide was also associated with lower rates of self-reported asymptomatic hypoglycaemia (8.0% vs 22.8% in the past month, p = 0.028). CONCLUSIONS/INTERPRETATION: Preserved C-peptide secretion is associated with fewer low-glucose events and lower glucose variability on flash monitoring. This suggests that individuals with preserved C-peptide may more safely achieve intensive glycaemic targets.

Comparison of serum and urinary biomarker panels with albumin/creatinine ratio in the prediction of renal function decline in type 1 diabetes.

AIMS/HYPOTHESIS: We examined whether candidate biomarkers in serum or urine can improve the prediction of renal disease progression in type 1 diabetes beyond prior eGFR, comparing their performance with urinary albumin/creatinine ratio (ACR). METHODS: From the population-representative Scottish Diabetes Research Network Type 1 Bioresource (SDRNT1BIO) we sampled 50% and 25% of those with starting eGFR below and above 75 ml min-1 [1.73 m]-2, respectively (N = 1629), and with median 5.1 years of follow-up. Multiplexed ELISAs and single molecule array technology were used to measure nine serum biomarkers and 13 urine biomarkers based on our and others' prior work using large discovery and candidate studies. Associations with final eGFR and with progression to <30 ml min-1 [1.73] m-2, both adjusted for baseline eGFR, were tested using linear and logistic regression models. Parsimonious biomarker panels were identified using a penalised Bayesian approach, and their performance was evaluated through tenfold cross-validation and compared with using urinary ACR and other clinical record data. RESULTS: Seven serum and seven urine biomarkers were strongly associated with either final eGFR or progression to <30 ml min-1 [1.73 m]-2, adjusting for baseline eGFR and other covariates (all at p<2.3 × 10-3). Of these, associations of four serum biomarkers were independent of ACR for both outcomes. The strongest associations with both final eGFR and progression to <30 ml min-1 [1.73 m]-2 were for serum TNF receptor 1, kidney injury molecule 1, CD27 antigen, α-1-microglobulin and syndecan-1. These serum associations were also significant in normoalbuminuric participants for both outcomes. On top of baseline covariates, the r2 for prediction of final eGFR increased from 0.702 to 0.743 for serum biomarkers, and from 0.702 to 0.721 for ACR alone. The area under the receiver operating characteristic curve for progression to <30 ml min-1 [1.73 m]-2 increased from 0.876 to 0.953 for serum biomarkers, and to 0.911 for ACR alone. Other urinary biomarkers did not outperform ACR. CONCLUSIONS/INTERPRETATION: A parsimonious panel of serum biomarkers easily measurable along with serum creatinine may outperform ACR for predicting renal disease progression in type 1 diabetes, potentially obviating the need for urine testing.

Predicting renal disease progression in a large contemporary cohort with type 1 diabetes mellitus.

AIMS/HYPOTHESIS: The aim of this study was to provide data from a contemporary population-representative cohort on rates and predictors of renal decline in type 1 diabetes. METHODS: We used data from a cohort of 5777 people with type 1 diabetes aged 16 and older, diagnosed before the age of 50, and representative of the adult population with type 1 diabetes in Scotland (Scottish Diabetes Research Network Type 1 Bioresource; SDRNT1BIO). We measured serum creatinine and urinary albumin/creatinine ratio (ACR) at recruitment and linked the data to the national electronic healthcare records. RESULTS: Median age was 44.1 years and diabetes duration 20.9 years. The prevalence of CKD stages G1, G2, G3 and G4 and end-stage renal disease (ESRD) was 64.0%, 29.3%, 5.4%, 0.6%, 0.7%, respectively. Micro/macroalbuminuria prevalence was 8.6% and 3.0%, respectively. The incidence rate of ESRD was 2.5 (95% CI 1.9, 3.2) per 1000 person-years. The majority (59%) of those with chronic kidney disease stages G3-G5 did not have albuminuria on the day of recruitment or previously. Over 11.6 years of observation, the median annual decline in eGFR was modest at -1.3 ml min-1 [1.73 m]-2 year-1 (interquartile range [IQR]: -2.2, -0.4). However, 14% experienced a more significant loss of at least 3 ml min-1 [1.73 m]-2. These decliners had more cardiovascular disease (OR 1.9, p = 5 × 10-5) and retinopathy (OR 1.3 p = 0.02). Adding HbA1c, prior cardiovascular disease, recent mean eGFR and prior trajectory of eGFR to a model with age, sex, diabetes duration, current eGFR and ACR maximised the prediction of final eGFR (r2 increment from 0.698 to 0.745, p < 10-16). Attempting to model nonlinearity in eGFR decline or to detect latent classes of decliners did not improve prediction. CONCLUSIONS: These data show much lower levels of kidney disease than historical estimates. However, early identification of those destined to experience significant decline in eGFR remains challenging.

Persistent C-peptide secretion in Type 1 diabetes and its relationship to the genetic architecture of diabetes.

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.

Marked improvement in HbA1c following commencement of flash glucose monitoring in people with type 1 diabetes.

AIMS/HYPOTHESIS: Minimal evidence supports the efficacy of flash monitoring in lowering HbA1c. We sought to assess the impact of introducing flash monitoring in our centre. METHODS: We undertook a prospective observational study to assess change in HbA1c in 900 individuals with type 1 diabetes following flash monitoring (comparator group of 518 with no flash monitoring). Secondary outcomes included changes in hypoglycaemia, quality of life, flash monitoring data and hospital admissions. RESULTS: Those with baseline HbA1c ≥58 mmol/mol (7.5%) achieved a median -7 mmol/mol (interquartile range [IQR] -13 to -1) (0.6% [-1.2 to -0.1]%) change in HbA1c (p < 0.001). The percentage achieving HbA1c <58 mmol/mol rose from 34.2% to 50.9% (p < 0.001). Median follow-up was 245 days (IQR 182 to 330). Individuals not using flash monitoring experienced no change in HbA1c across a similar timescale (p = 0.508). Higher HbA1c (p < 0.001), younger age at diagnosis (p = 0.003) and lower social deprivation (p = 0.024) were independently associated with an HbA1c fall of ≥5 mmol/mol (0.5%). More symptomatic (OR 1.9, p < 0.001) and asymptomatic (OR 1.4, p < 0.001) hypoglycaemia was reported after flash monitoring. Following flash monitoring, regimen-related and emotional components of the diabetes distress scale improved although the proportion with elevated anxiety (OR 1.2, p = 0.028) and depression (OR 2.0, p < 0.001) scores increased. Blood glucose test strip use fell from 3.8 to 0.6 per day (p < 0.001). Diabetic ketoacidosis admissions fell significantly following flash monitoring (p = 0.043). CONCLUSIONS/INTERPRETATION: Flash monitoring is associated with significant improvements in HbA1c and fewer diabetic ketoacidosis admissions. Higher rates of hypoglycaemia may relate to greater recognition of hitherto unrecognised events. Impact upon quality of life parameters was mixed but overall treatment satisfaction was overwhelmingly positive.

The effect of dapagliflozin on glycaemic control and other cardiovascular disease risk factors in type 2 diabetes mellitus: a real-world observational study.

AIMS/HYPOTHESIS: Dapagliflozin, a sodium-glucose cotransporter 2 (SGLT2) inhibitor, is indicated for improving glycaemic control in type 2 diabetes mellitus. Whether its effects on HbA1c and other variables, including safety outcomes, in clinical trials are obtained in real-world practice needs to be established. METHODS: We used data from the comprehensive national diabetes register, the Scottish Care Information-Diabetes (SCI-Diabetes) collaboration database, available from 2004 to mid-2016. Data within this database were linked to mortality data from the General Registrar, available from the Information Services Division (ISD) of the National Health Service in Scotland. We calculated crude within-person differences between pre- and post-drug-initiation values of HbA1c, BMI, body weight, systolic blood pressure (SBP) and eGFR. We used mixed-effects regression models to adjust for within-person time trajectories in these measures. For completeness, we evaluated safety outcomes, cardiovascular disease events, lower-limb amputation and diabetic ketoacidosis, focusing on cumulative exposure effects, using Cox proportional hazard models, though power to detect such effects was limited. RESULTS: Among 8566 people exposed to dapagliflozin over a median of 210 days the crude within-person change in HbA1c was -10.41 mmol/mol (-0.95%) after 3 months' exposure. The crude change after 12 months was -12.99 mmol/mol (-1.19%) but considering the expected rise over time in HbA1c gave a dapagliflozin-exposure-effect estimate of -15.14 mmol/mol (95% CI -15.87, -14.41) (-1.39% [95% CI -1.45, -1.32]) at 12 months that was maintained thereafter. A drop in SBP of -4.32 mmHg (95% CI -4.84, -3.79) on exposure within the first 3 months was also maintained thereafter. Reductions in BMI and body weight stabilised by 6 months at -0.82 kg/m2 (95% CI -0.87, -0.77) and -2.20 kg (95% CI -2.34, -2.06) and were maintained thereafter. eGFR declined initially by -1.81 ml min-1 [1.73 m]-2 (95% CI -2.10, -1.52) at 3 months but varied thereafter. There were no significant effects of cumulative drug exposure on safety outcomes. CONCLUSIONS/INTERPRETATION: Dapagliflozin exposure was associated with reductions in HbA1c, SBP, body weight and BMI that were at least as large as in clinical trials. Dapagliflozin also prevented the expected rise in HbA1c and SBP over the period of study.

Performance of Cardiovascular Disease Risk Scores in People Diagnosed With Type 2 Diabetes: External Validation Using Data From the National Scottish Diabetes Register.

OBJECTIVE: To evaluate the performance of five cardiovascular disease (CVD) risk scores developed in diabetes populations and compare their performance to QRISK2. RESEARCH DESIGN AND METHODS: A cohort of people diagnosed with type 2 diabetes between 2004 and 2016 was identified from the Scottish national diabetes register. CVD events were identified using linked hospital and death records. Five-year risk of CVD was estimated using each of QRISK2, ADVANCE (Action in Diabetes and Vascular disease: preterAx and diamicroN-MR Controlled Evaluation), Cardiovascular Health Study (CHS), New Zealand Diabetes Cohort Study (NZ DCS), Fremantle Diabetes Study, and Swedish National Diabetes Register (NDR) risk scores. Discrimination and calibration were assessed using the Harrell C statistic and calibration plots, respectively. RESULTS: The external validation cohort consisted of 181,399 people with type 2 diabetes and no history of CVD. There were 14,081 incident CVD events within 5 years of follow-up. The 5-year observed risk of CVD was 9.7% (95% CI 9.6, 9.9). C statistics varied between 0.66 and 0.67 for all risk scores. QRISK2 overestimated risk, classifying 87% to be at high risk for developing CVD within 5 years; ADVANCE underestimated risk, and the Swedish NDR risk score calibrated well to observed risk. CONCLUSIONS: None of the risk scores performed well among people with newly diagnosed type 2 diabetes. Using these risk scores to predict 5-year CVD risk in this population may not be appropriate.