AimsIncreased visit‐to‐visit glycaemic variability is independently associated with adverse outcomes in Type 2 diabetes. Our aim was to identify the patient characteristics associated with raised visit‐to‐visit glycaemic variability in people with Type 2 diabetes.MethodsA case–control study was conducted to establish associations between HbA1c variability and clinical covariates in 10 130 people with Type 2 diabetes. Variability was calculated by two metrics [sd and coefficient of variation (CV)] from a minimum of four HbA1c readings obtained over a 4‐year period. High and low variability groups were defined as the top and bottom tertile of the sd or CV, and used in logistic regression analyses including a number of clinical and biochemical covariates. The analyses were stratified into low mean (< 53 mmol/mol; 7%) and high mean (≥ 53 mmol/mol; 7%) HbA1c groups.ResultsFindings were consistent across both HbA1c groups and variability metrics. Treatment, independent of other factors, was the most strongly associated covariate for the risk of high HbA1c variability. A six‐fold increased risk was observed in the low HbA1c group, between the most and least intense treatment regimens (P < 0.001). Similar findings were present in the high HbA1c group with a three‐fold increase in risk (P < 0.001). In addition, male gender, younger age, reduced HDL‐cholesterol and increased BMI were all found to be independently associated with raised visit‐to‐visit glycaemic variability.ConclusionsIntensive treatment resulting in low mean HbA1c was associated with marked increase in HbA1c variability. Irrespective of diabetes control, the greatest visit‐to‐visit variability was observed in young, insulin resistant men.

Gastrointestinal fistulation has been widely reported as an adverse effect of nicorandil therapy in Europe. People who have underlying diverticular disease are most at risk of this side effect. In Western countries, diverticular disease is highly prevalent and can be clinically silent. This study aimed to identify diverticular disease genetic risk scores (GRSs) associated with early nicorandil stoppage, a surrogate marker for drug intolerance. A case‐control study was carried out on 1,077 patients from the Genetics of Diabetes Audit and Research Tayside Scotland (GoDARTS) database. Cases were defined as having < 9 nicorandil prescriptions with no identifiable reason for stopping (n = 230). Controls had either ≥ 9 prescriptions, treatment continuation to death/study end or stoppage post‐myocardial infarction. Two diverticular GRSs were created and used in logistic regression models. Isosorbide mononitrate was used as a control analysis. Patients with a raised diverticular GRS, based on 23 replicable loci, had increased risk of stopping nicorandil therapy early (univariate (odds ratio (OR) 2.26; P = 0.04], multivariate (OR 3.96; P = 0.01)). Similar trends were noted when using the full 42 variant diverticular score but statistical significance was not reached. The isosorbide control analysis did not reach statistical significance. Our analysis demonstrates a novel positive association between a raised diverticular GRS and early stoppage of nicorandil therapy.

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Cardiovascular disease remains the leading global cause of death. Early intervention, with lifestyle advice alongside appropriate medical therapies, is fundamental to reduce patient mortality among high-risk individuals. For those who live with the daily challenges of cardiovascular disease, pharmacological management aims to relieve symptoms and prevent disease progression. Despite best efforts, prescription drugs are not without their adverse effects, which can cause significant patient morbidity and consequential economic burden for healthcare systems. Patients with cardiovascular diseases are often among the most vulnerable to adverse drug reactions due to multiple co-morbidities and advanced age. Examining a patient’s genome to assess for variants that may alter drug efficacy and susceptibility to adverse reactions underpins pharmacogenomics. This strategy is increasingly being implemented in clinical cardiology to tailor patient therapies. The identification of specific variants associated with adverse drug effects aims to predict those at greatest risk of harm, allowing alternative therapies to be given. This review will explore current guidance available for pharmacogenomic-based prescribing as well as exploring the potential implementation of genetic risk scores to tailor treatment. The benefits of large databases and electronic health records will be discussed to help facilitate the integration of pharmacogenomics into primary care, the heartland of prescribing.

with data from a previous audit conducted between 2016 and 2017. Methods 208 patients with DR were identified on EMIS between 2018 and 2019. They were then classified according to DR grade and time from last screening to most recent follow-up eye examination within 12 months, 3-6 months, 4 weeks, and 1 week. Moreover, data is shown for HbA1c value and type of diabetic treatment.