Objective: To examine the persistence of the original treatment effects 10 years after the Diabetes Control and Complications Trial (DCCT) in the follow-up Epidemiology of Diabetes Interventions and Complications (EDIC) study. In the DCCT, intensive therapy aimed at nearnormal glycemia reduced the risk of microvascular complications of type 1 diabetes mellitus compared with conventional therapy.Methods: Retinopathy was evaluated by fundus photography in 1211 subjects at EDIC year 10. Further 3-step progression on the Early Treatment Diabetic Retinopathy Study scale from DCCT closeout was the primary outcome.Results: After 10 years of EDIC follow-up, there was no significant difference in mean glycated hemoglobin levels (8.07% vs 7.98%) between the original treatment groups. Nevertheless, compared with the former conven-tional treatment group, the former intensive group had significantly lower incidences from DCCT close of further retinopathy progression and proliferative retinopathy or worse (hazard reductions, 53%-56%; PϽ.001). The risk (hazard) reductions at 10 years of EDIC were attenuated compared with the 70% to 71% over the first 4 years of EDIC (PϽ.001). The persistent beneficial effects of former intensive therapy were largely explained by the difference in glycated hemoglobin levels during DCCT. Conclusion:The persistent difference in diabetic retinopathy between former intensive and conventional therapy ("metabolic memory") continues for at least 10 years but may be waning.

BackgroundAtrial fibrillation (AF) is the most common sustained heart arrhythmia. However, as many cases are asymptomatic, a large proportion of patients remain undiagnosed until serious complications arise. Efficient, cost-effective detection of the undiagnosed may be supported by risk-prediction models relating patient factors to AF risk. However, there exists a need for an implementable risk model that is contemporaneous and informed by routinely collected patient data, reflecting the real-world pathology of AF.MethodsThis study sought to develop and evaluate novel and conventional statistical and machine learning models for risk-predication of AF. This was a retrospective, cohort study of adults (aged ≥30 years) without a history of AF, listed on the Clinical Practice Research Datalink, from January 2006 to December 2016. Models evaluated included published risk models (Framingham, ARIC, CHARGE-AF), machine learning models, which evaluated baseline and time-updated information (neural network, LASSO, random forests, support vector machines), and Cox regression.ResultsAnalysis of 2,994,837 individuals (3.2% AF) identified time-varying neural networks as the optimal model achieving an AUROC of 0.827 vs. 0.725, with number needed to screen of 9 vs. 13 patients at 75% sensitivity, when compared with the best existing model CHARGE-AF. The optimal model confirmed known baseline risk factors (age, previous cardiovascular disease, antihypertensive medication usage) and identified additional time-varying predictors (proximity of cardiovascular events, body mass index (both levels and changes), pulse pressure, and the frequency of blood pressure measurements).ConclusionThe optimal time-varying machine learning model exhibited greater predictive performance than existing AF risk models and reflected known and new patient risk factors for AF.

AimsInsulin is normally added to oral glucose-lowering drugs in people with type 2 diabetes when glycaemic control becomes suboptimal. We evaluated outcomes in people starting insulin therapy with neutral protamine Hagedorn (NPH), detemir, glargine or premixed insulins.MethodsInsulin-naïve people with type 2 diabetes (n = 8009), ≥ 35 years old, HbA1c ≥ 6.5% and begun on NPH (n = 1463), detemir (n = 357), glargine (n = 2197) or premix (n = 3992), were identified from a UK database of primary care records (The Health Improvement Network). Unadjusted and multivariate-adjusted analyses were conducted, with persistence of insulin therapy assessed by survival analysis.ResultsIn the study population (n = 4337), baseline HbA1c was 9.5 ± 1.6%, falling to 8.4 ± 1.5% over 12 months (change −1.1 ± 1.8%, p < 0.001). Compared with NPH, people taking detemir, glargine and premix had an adjusted reduction in HbA1c from baseline, of 0.00% (p = 0.99), 0.19% (p < 0.001) and 0.03% (p = 0.51). Body weight increased by 2.8 kg overall (p < 0.001), and by 2.3, 1.7, 1.9, and 3.3 kg on NPH, detemir, glargine and premix (p < 0.001 for all groups); insulin dose at 12 months was 0.70 (overall), 0.64, 0.61, 0.56 and 0.76 U/kg/day. After 36 months, 57% of people on NPH, 67% on glargine and 83% on premix remained on their initially prescribed insulin.Discussion and ConclusionIn routine clinical practice, people with type 2 diabetes commenced on NPH experienced a modest disadvantage in glycaemic control after 12 months compared with other insulins. When comparing the insulins, glargine achieved best HbA1c reduction, while premix showed greatest weight gain and the highest dose requirement, but had the best persistence of therapy.

ObjectiveUsing primary care data obtained from the UK Clinical Practice Research Datalink, this retrospective cohort study examined the relationships between medication adherence and clinical outcomes in patients with type 2 diabetes.Research design and methodsData were extracted for patients treated between 2008 and 2016, and stratified by oral antihyperglycemic agent (OHA) line of therapy (mono, dual or triple therapy). Patients were monitored for up to 365 days; associations between medication possession ratio (MPR) and outcomes at 1 year (glycated hemoglobin A1c (HbA1c), weight and hypoglycemia incidence) were assessed using linear regression modeling and descriptive analyses.ResultsIn total, 33 849 patients were included in the study (n=23 925 OHA monotherapy; n=8406 OHA dual therapy; n=1518 OHA triple therapy). One-year change in HbA1c was greater among adherent (−0.90 to −1.14%; −9.8 to −12.5 mmol/mol) compared with non-adherent patients (−0.49 to −0.69%; −5.4 to −7.5 mmol/mol). On average, adherent patients had higher hypoglycemia event rates than non-adherent patients (rate ratios of 1.24, 1.10 and 2.06 for OHA mono, dual and triple therapy cohorts, respectively) and experienced greater weight change from baseline. A 10% improvement in MPR was associated with −0.09% (−1.0 mmol/mol), −0.09% (−1.0 mmol/mol) and −0.21% (−2.3 mmol/mol) changes in HbA1c for OHA mono, dual and triple therapy cohorts, respectively.ConclusionsFor patients with type 2 diabetes, increasing medication adherence can bring about meaningful improvements in HbA1c control as the requirement for treatment escalation increases. Regimens associated with weight loss and the avoidance of hypoglycemia were generally associated with better medication adherence and improved glycemic control.