Drug Exposure As a Predictor in Diabetic Retinopathy Risk Prediction Models-A Systematic Review and Meta-Analysis.

PURPOSE: To conduct a systematic review to assess drug exposure handling in diabetic retinopathy (DR) risk prediction models, a network-meta-analysis to identify drugs associated with DR and a meta-analysis to determine which drugs contributed to enhanced model performance. DESIGN: Systematic review and meta-analysis. METHODS: We included studies presenting DR models incorporating drug exposure as a predictor. We searched EMBASE, MEDLINE, and SCOPUS from inception to December 2023. We evaluated the quality of studies using the Prediction model Risk of Bias Assessment Tool and certainty using GRADE. We conducted network meta-analysis and meta-analysis to estimate the odds ratio (OR) and pooled C-statistic, respectively, and 95% confidence intervals (CI) (PROSPERO: CRD42022349764). RESULTS: Of 5,653 records identified, we included 28 studies of 678,837 type 1 or 2 diabetes participants, of which 38,579 (5.7%) had DR. A total of 19, 3, and 7 studies were at high, unclear, and low risk of bias, respectively. Drugs included in models as predictors were: insulin (n = 24), antihypertensives (n = 5), oral antidiabetics (n = 12), lipid-lowering drugs (n = 7), antiplatelets (n = 2). Drug exposure was modelled primarily as a categorical variable (n = 23 studies). Two studies handled drug exposure as time-varying covariates, and one as a time-dependent covariate. Insulin was associated with an increased risk of DR (OR = 2.50; 95% CI: 1.61-3.86). Models that included insulin (n = 9) had a higher pooled C-statistic (C-statistic = 0.84, CI: 0.80-0.88), compared to models (n = 9) that incorporated a combination of drugs alongside insulin (C-statistic = 0.79, CI: 0.74-0.84), as well as models (n = 3) not including insulin (C-statistic = 0.70, CI: 0.64-0.75). Limitations include the high risk of bias and significant heterogeneity in reviewed studies. CONCLUSION: This is the first review assessing drug exposure handling in DR prediction models. Drug exposure was primarily modelled as a categorical variable, with insulin associated with improved model performance. However, due to suboptimal drug handling, associations between other drugs and model performance may have been overlooked. This review proposes the following for future DR prediction models: (1) evaluation of drug exposure as a variable, (2) use of time-varying methodologies, and (3) consideration of drug regimen details. Improving drug exposure handling could potentially unveil novel variables capable of significantly enhancing the predictive capability of prediction models.

Comparison of intramyocellular lipid metabolism in patients with diabetes and male athletes.

Despite opposing insulin sensitivity and cardiometabolic risk, both athletes and patients with type 2 diabetes have increased skeletal myocyte fat storage: the so-called "athlete's paradox". In a parallel non-randomised, non-blinded trial (NCT03065140), we characterised and compared the skeletal myocyte lipid signature of 29 male endurance athletes and 30 patients with diabetes after undergoing deconditioning or endurance training respectively. The primary outcomes were to assess intramyocellular lipid storage of the vastus lateralis in both cohorts and the secondary outcomes were to examine saturated and unsaturated intramyocellular lipid pool turnover. We show that athletes have higher intramyocellular fat saturation with very high palmitate kinetics, which is attenuated by deconditioning. In contrast, type 2 diabetes patients have higher unsaturated intramyocellular fat and blunted palmitate and linoleate kinetics but after endurance training, all were realigned with those of deconditioned athletes. Improved basal insulin sensitivity was further associated with better serum cholesterol/triglycerides, glycaemic control, physical performance, enhanced post insulin receptor pathway signalling and metabolic sensing. We conclude that insulin-resistant, maladapted intramyocellular lipid storage and turnover in patients with type 2 diabetes show reversibility after endurance training through increased contributions of the saturated intramyocellular fatty acid pools. Clinical Trial Registration: NCT03065140: Muscle Fat Compartments and Turnover as Determinant of Insulin Sensitivity (MISTY).

Morning exercise and pre-breakfast metformin interact to reduce glycaemia in people with type 2 diabetes: a randomized crossover trial.

Exercise is recommended in the treatment of type 2 diabetes and can improve insulin sensitivity. However, previous evidence suggests that exercise at different times of the day in people with type 2 diabetes may have opposing outcomes on glycaemia. Metformin is the most commonly prescribed initial pharmacological intervention in type 2 diabetes, and may alter adaptions to exercise. It is unknown if there is an interaction between metformin and diurnal exercise outcomes. We aimed to investigate glycaemic outcomes of moderate intensity morning vs. evening exercise in people with type 2 diabetes being prescribed metformin monotherapy. In this study, nine males and nine females with type 2 diabetes undergoing metformin monotherapy (age 61 ± 8.2 years, mean ± SD) completed a 16-week crossover trial including 2-week baseline recording, 6 weeks randomly assigned to a morning exercise (07.00-10.00 h) or evening exercise (16.00-19.00 h) and a 2-week wash-out period. Exercise arms consisted of 30 min of walking at 70% of estimated max heart rate every other day. Glucose levels were measured with continuous glucose monitors and activity measured by wrist-worn monitors. Food-intake was recorded by 4-day food diaries during baseline, first and last 2 weeks of each exercise arm. There was no difference in exercise intensity, total caloric intake or total physical activity between morning and evening arms. As primary outcomes, acute (24 h) glucose area under the curve (AUC), was lower (P = 0.02) after acute morning exercise (180.6 ± 68.4 mmol/l) compared to baseline (210.3 ± 76.7 mmol/l); and there were no differences identified for glucose (mmol/l) between baseline, morning and evening exercise at any specific time point when data were analysed with two-way ANOVA. As secondary outcomes, acute glucose AUC was significantly lower (P = 0.01) in participants taking metformin before breakfast (152.5 ± 29.95 mmol/l) compared with participants taking metformin after breakfast (227.2 ± 61.51 mmol/l) only during the morning exercise arm; and during weeks 5-6 of the exercise protocol, glucose AUC was significantly lower (P = 0.04) for participants taking metformin before breakfast (168.8 ± 15.8 mmol/l), rather than after breakfast (224.5 ± 52.0 mmol/l), only during morning exercise. Our data reveal morning moderate exercise acutely lowers glucose levels in people with type 2 diabetes being prescribed metformin. This difference appears to be driven by individuals that consumed metformin prior to breakfast rather than after breakfast. This beneficial effect upon glucose levels of combined morning exercise and pre-breakfast metformin persisted through the final 2 weeks of the trial. Our findings suggest that morning moderate intensity exercise combined with pre-breakfast metformin intake may benefit the management of glycaemia in people with type 2 diabetes. KEY POINTS: Morning moderate exercise acutely lowers glucose levels in people with type 2 diabetes being prescribed metformin. This difference appears to be driven by individuals that consumed metformin prior to breakfast rather than after breakfast. Morning exercise combined with pre-breakfast metformin persistently reduced glucose compared to morning exercise combined with post-breakfast metformin through the final week (week 6) of the intervention. Our study suggests it may be possible to make simple changes to the time that people with type 2 diabetes take metformin and perform exercise to improve their blood glucose.

Ongoing burden and recent trends in severe hospitalised hypoglycaemia events in people with type 1 and type 2 diabetes in Scotland: A nationwide cohort study 2016-2022.

AIMS: We examined severe hospitalised hypoglycaemia (SHH) rates in people with type 1 and type 2 diabetes in Scotland during 2016-2022, stratifying by sociodemographics. METHODS: Using the Scottish National diabetes register (SCI-Diabetes), we identified people with type 1 and type 2 diabetes alive anytime during 2016-2022. SHH events were determined through linkage to hospital admission and death registry data. We calculated annual SHH rates overall and by age, sex, and socioeconomic status. Summary estimates of time and stratum effects were obtained by fitting adjusted generalised additive models using R package mgcv. RESULTS: Rates for those under 20 with type 1 diabetes reached their minimum at the 2020-2021 transition, 30% below the study period average. A gradual decline over time also occurred among 20-49-year-olds with type 1 diabetes. Overall, females had 15% higher rates than males with type 2 diabetes (rate ratio 1.15, 95% CI 1.08-1.22). People in the most versus least deprived quintile experienced 2.58 times higher rates (95% CI 2.27-2.93) in type 1 diabetes and 2.33 times higher (95% CI 2.08-2.62) in type 2 diabetes. CONCLUSIONS: Despite advances in care, SHH remains a significant problem in diabetes. Future efforts must address the large socioeconomic disparities in SHH risks.