Gestational diabetes mellitus (GDM) is associated with developing type 2 diabetes, but very few studies have examined its effect on developing cardiovascular disease. We conducted a retrospective cohort study utilizing a large primary care database in the United Kingdom. From 1 February 1990 to 15 May 2016, 9,118 women diagnosed with GDM were identified and randomly matched with 37,281 control women by age and timing of pregnancy (up to 3 months). Adjusted incidence rate ratios (IRRs) with 95% confidence intervals (CIs) were calculated for cardiovascular risk factors and cardiovascular disease. Women with GDM were more likely to develop type 2 diabetes (IRR = 21.96; 95% CI 18.31–26.34) and hypertension (IRR = 1.85; 95% CI 1.59–2.16) after adjusting for age, Townsend (deprivation) quintile, body mass index, and smoking. For ischemic heart disease (IHD), the IRR was 2.78 (95% CI 1.37–5.66), and for cerebrovascular disease 0.95 (95% CI 0.51–1.77; p-value = 0.87), after adjusting for the above covariates and lipid-lowering medication and hypertension at baseline. Follow-up screening for type 2 diabetes and cardiovascular risk factors was poor. Limitations include potential selective documentation of severe GDM for women in primary care, higher surveillance for outcomes in women diagnosed with GDM than control women, and a short median follow-up postpartum period, with a small number of outcomes for IHD and cerebrovascular disease. Women diagnosed with GDM were at very high risk of developing type 2 diabetes and had a significantly increased incidence of hypertension and IHD. Identifying this group of women in general practice and targeting cardiovascular risk factors could improve long-term outcomes.

Androgen excess is a defining feature of polycystic ovary syndrome (PCOS), which affects 10% of women and represents a lifelong metabolic disorder, with increased risk of type 2 diabetes, hypertension, and cardiovascular events. Previous studies have suggested an increased risk of nonalcoholic fatty liver disease (NAFLD) in individuals with PCOS and implicated androgen excess as a potential driver. We carried out a retrospective longitudinal cohort study utilizing a large primary care database in the United Kingdom, evaluating NAFLD rates in 63,120 women with PCOS and 121,064 age-, body mass index (BMI)-, and location-matched control women registered from January 2000 to May 2016. In 2 independent cohorts, we also determined the rate of NAFLD in women with a measurement of serum testosterone (n = 71,061) and sex hormone-binding globulin (SHBG; n = 49,625). We used multivariate Cox models to estimate the hazard ratio (HR) for NAFLD and found that women with PCOS had an increased rate of NAFLD (HR = 2.23, 95% CI 1.86–2.66, p < 0.001), also after adjusting for BMI or dysglycemia. Serum testosterone >3.0 nmol/L was associated with an increase in NAFLD (HR = 2.30, 95% CI 1.16–4.53, p = 0.017 for 3–3.49 nmol/L and HR = 2.40, 95% CI 1.24–4.66, p = 0.009 for >3.5 nmol/L). Mirroring this finding, SHBG <30 nmol/L was associated with increased NAFLD hazard (HR = 4.75, 95% CI 2.44–9.25, p < 0.001 for 20–29.99 nmol/L and HR = 4.98, 95% CI 2.45–10.11, p < 0.001 for <20 nmol/L). Limitations of this study include its retrospective nature, absence of detailed information on criteria used to diagnosis PCOS and NAFLD, and absence of data on laboratory assays used to measure serum androgens. We found that women with PCOS have an increased rate of NAFLD. In addition to increased BMI and dysglycemia, androgen excess contributes to the development of NAFLD in women with PCOS. In women with PCOS-related androgen excess, systematic NAFLD screening should be considered.

Idiopathic intracranial hypertension (IIH) is a condition of unknown origin characterized by elevated intracranial pressure typically manifesting as papilledema, with a consequent risk of visual loss and chronic disabling headache.^1,2 Incidence and economic burden of IIH are rising in line with global obesity figures.³ Diagnostic criteria include brain imaging to exclude mass lesion, hydrocephalus, and venous thrombosis as well as the presence of papilledema and a lumbar puncture pressure greater than 25 cm cerebrospinal fluid with normal constituents.⁴ Currently, management focuses on preserving vision and reducing headache morbidity.⁵

The use of primary care electronic health records for research is abundant. The benefits gained from utilising such records lies in their size, longitudinal data collection and data quality. However, the use of such data to undertake high quality epidemiological studies, can lead to significant challenges particularly in dealing with misclassification, variation in coding and the significant effort required to pre-process the data in a meaningful format for statistical analysis. In this paper, we describe a methodology to aid with the extraction and processing of such databases, delivered by a novel software programme; the “Data extraction for epidemiological research” (DExtER). The basis of DExtER relies on principles of extract, transform and load processes. The tool initially provides the ability for the healthcare dataset to be extracted, then transformed in a format whereby data is normalised, converted and reformatted. DExtER has a user interface designed to obtain data extracts specific to each research question and observational study design. There are facilities to input the requirements for; eligible study period, definition of exposed and unexposed groups, outcome measures and important baseline covariates. To date the tool has been utilised and validated in a multitude of settings. There have been over 35 peer-reviewed publications using the tool, and DExtER has been implemented as a validated public health surveillance tool for obtaining accurate statistics on epidemiology of key morbidities. Future direction of this work will be the application of the framework to linked as well as international datasets and the development of standardised methods for conducting electronic pre-processing and extraction from datasets for research purposes.

Context: Empagliflozin was found to decrease mortality in patients with type 2 diabetes mellitus (T2DM) and a prior cardiovascular disease (CVD) event. Objectives: To establish whether these benefits can be replicated in a real-world setting, should be expected with the use of dapagliflozin, and apply to T2DM patients at low risk of CVD. Design: General practice, population-based, retrospective cohort study (January 2013 to September 2015). Setting: The Health Improvement Network database. Participants: A total of 22,124 T2DM patients (4444 exposed to dapagliflozin; 17,680 unexposed T2DM patients) matched for age, sex, body mass index, T2DM duration, and smoking. Main Outcome Measures: The primary outcome was all-cause mortality (high and low risk for CVD) in the total study population, expressed as the adjusted incidence rate ratio (aIRR) with 95% confidence intervals (CIs). As a secondary analysis in the low-risk population, all-cause mortality and incident CVD were considered. Results: Patients with T2DM exposed to dapagliflozin were significantly less likely to die of any cause (aIRR: 0.50; 95% CI: 0.33 to 0.75; P = 0.001). Similarly, in low-risk patients, death from any cause was significantly lower in the cohort exposed to dapagliflozin (aIRR: 0.44; 95% CI: 0.25 to 0.78; P = 0.002). The difference in the risk of incident CVD did not reach statistical significance between groups in low-risk patients (aIRR: 0.89; 95% CI: 0.61 to 1.31; P = 0.546). Conclusions: Patients with T2DM who were exposed to dapagliflozin had a lower risk of death from any cause irrespective of baseline CVD status.