Automating incidence and prevalence analysis in open cohorts.

MOTIVATION: Data is increasingly used for improvement and research in public health, especially administrative data such as that collected in electronic health records. Patients enter and exit these typically open-cohort datasets non-uniformly; this can render simple questions about incidence and prevalence time-consuming and with unnecessary variation between analyses. We therefore developed methods to automate analysis of incidence and prevalence in open cohort datasets, to improve transparency, productivity and reproducibility of analyses. IMPLEMENTATION: We provide both a code-free set of rules for incidence and prevalence that can be applied to any open cohort, and a python Command Line Interface implementation of these rules requiring python 3.9 or later. GENERAL FEATURES: The Command Line Interface is used to calculate incidence and point prevalence time series from open cohort data. The ruleset can be used in developing other implementations or can be rearranged to form other analytical questions such as period prevalence. AVAILABILITY: The command line interface is freely available from https://github.com/THINKINGGroup/analogy_publication .

Associations between primary care recorded cannabis use and mental ill health in the UK: a population-based retrospective cohort study using UK primary care data.

BACKGROUND: Cannabis use is a global public health issue associated with increased risks of developing mental health disorders, especially in young people. We aimed to investigate the relationships between cannabis exposure and risks of receiving mental illness diagnoses or treatment as outcomes. METHODS: A population based, retrospective, open cohort study using patients recorded in 'IQVIA medical research data', a UK primary care database. Read codes were used to confirm patients with recorded exposure to cannabis use who were matched up to two unexposed patients. We examined the risk of developing three categories of mental ill health: depression, anxiety or serious mental illness (SMI). RESULTS: At study entry, the exposed cohort had an increased likelihood of having experienced mental ill health [odds ratio (OR) 4.13; 95% confidence interval (CI) 3.99-4.27] and mental ill health-related prescription (OR 2.95; 95% CI 2.86-3.05) compared to the unexposed group. During the study period we found that exposure to cannabis was associated with an increased risk of developing any mental disorder [adjusted hazard ratio (aHR) 2.73; 95% CI 2.59-2.88], also noted when examining by subtype of disorder: anxiety (aHR 2.46; 95% CI 2.29-2.64), depression (aHR 2.34; 95% CI 2.20-2.49) and SMI (aHR 6.41; 95% CI 5.42-7.57). These results remained robust in sensitivity analyses. CONCLUSION: These findings point to the potential need for a public health approach to the management of people misusing cannabis. However, there is a gross under-recording of cannabis use in GP records, as seen by the prevalence of recorded cannabis exposure substantially lower than self-reported survey records.

Sodium-glucose cotransporter-2 inhibitors and the risk of gout in patients with type 2 diabetes mellitus: A propensity-score-matched, new-user design study with an active comparator using the IQVIA Medical Research Data UK database.

AIM: To conduct a pharmacoepidemiological study to explore the association between sodium-glucose cotransporter-2 (SGLT2) inhibitors and gout in patients with type 2 diabetes mellitus (T2DM). MATERIALS AND METHODS: A retrospective open cohort study using the IQVIA Medical Research Data UK database was performed between November 1, 2012 and December 31, 2018, estimating the risk of gout in patients with T2DM who were new users of SGLT2 inhibitors, compared to propensity-score-matched new users of dipeptidyl peptidase-4 (DPP-4) inhibitors. RESULTS: A total of 85 incident cases of gout were recorded over 30 389 person-years of observation in 13 617 new users of SGLT2 inhibitors and 29 426 new users of DPP-4 inhibitors. Crude incidence rates (IRs) per 1000 person-years were 2.90 and 2.47 for new users of SGLT2 inhibitors and DPP-4 inhibitors, respectively. The unadjusted hazard ratio (HR) was 1.18 (95% confidence interval [CI] 0.76-1.83). The adjusted HR was 1.20 (95% CI 0.77-1.86). In the at-treatment analysis, crude IRs per 1000 person-years were found to be 2.68 and 2.53 for SGLT2 inhibitor and DPP-4 inhibitor users, respectively. In the adjusted model, the adjusted HR was 1.3 (95% CI 0.90-2.29). Sensitivity analyses did not change the findings. CONCLUSIONS: In this nationwide study, no difference in the incidence of gout was documented in patients treated with SGLT2 inhibitors compared to DPP-4 inhibitor users. This neutral finding remained consistent in sensitivity analyses.

Cardiometabolic screening and monitoring in patients prescribed antipsychotic drugs in primary care: A population-based cohort study.

BACKGROUND: This study aimed to investigate the level of guideline adherence for cardiometabolic health monitoring for patients prescribed antipsychotic medicines in UK primary care. METHODS: In this population-based retrospective open cohort study, we used dataset of patients from the IQVIA Medical Research Data (IMRD) database between 1st January 2003 to 31st December 2018. Clinical Read codes were used to identify a cohort of adult patients with a diagnosis of Schizophrenia and at least four prescriptions of an anti-psychotic medication within 12 months of diagnosis. We then extracted data in relation to monitoring of cardiometabolic parameters (body compositions, lipids, and glucose outcomes) at baseline, then at six weeks, 12 weeks, and then 12 months. The frequency of outcome monitoring was described using descriptive statistics. FINDINGS: A total of 11,435 patients were eligible and of them (n = 9707; 84·8%) were prescribed second-generation antipsychotics (SGAs). Only a small portion of the cohort (≈2·0%) received complete monitoring (at time points) for certain outcomes. Just over half the patients (n = 6599, 52%) had evidence of any cardiometabolic baseline testing for any of the study outcomes and the high majority had at least one abnormal lab value at baseline (n = 4627, 96·7%). INTERPRETATION: In UK primary care, cardiometabolic monitoring practices among patients prescribed antipsychotics remain suboptimal. There is a need to promote guideline adherence to prevent adverse outcomes in antipsychotic users.

Prevalence and demographic variation of cardiovascular, renal, metabolic, and mental health conditions in 12 million english primary care records.

BACKGROUND: Primary care electronic health records (EHR) are widely used to study long-term conditions in epidemiological and health services research. Therefore, it is important to understand how well the recorded prevalence of these conditions in EHRs, compares to other reliable sources overall, and varies by socio-demographic characteristics. We aimed to describe the prevalence and socio-demographic variation of cardiovascular, renal, and metabolic (CRM) and mental health (MH) conditions in a large, nationally representative, English primary care database and compare with prevalence estimates from other population-based studies. METHODS: This was a cross-sectional study using the Clinical Practice Research Datalink (CPRD) Aurum primary care database. We calculated prevalence of 18 conditions and used logistic regression to assess how this varied by age, sex, ethnicity, and socio-economic status. We searched the literature for population prevalence estimates from other sources for comparison with the prevalences in CPRD Aurum. RESULTS: Depression (16.0%, 95%CI 16.0-16.0%) and hypertension (15.3%, 95%CI 15.2-15.3%) were the most prevalent conditions among 12.4 million patients. Prevalence of most conditions increased with socio-economic deprivation and age. CRM conditions, schizophrenia and substance misuse were higher in men, whilst anxiety, depression, bipolar and eating disorders were more common in women. Cardiovascular risk factors (hypertension and diabetes) were more prevalent in black and Asian patients compared with white, but the trends in prevalence of cardiovascular diseases by ethnicity were more variable. The recorded prevalences of mental health conditions were typically twice as high in white patients compared with other ethnic groups. However, PTSD and schizophrenia were more prevalent in black patients. The prevalence of most conditions was similar or higher in the primary care database than diagnosed disease prevalence reported in national health surveys. However, screening studies typically reported higher prevalence estimates than primary care data, especially for PTSD, bipolar disorder and eating disorders. CONCLUSIONS: The prevalence of many clinically diagnosed conditions in primary care records closely matched that of other sources. However, we found important variations by sex and ethnicity, which may reflect true variation in prevalence or systematic differences in clinical presentation and practice. Primary care data may underrepresent the prevalence of undiagnosed conditions, particularly in mental health.

Risk of incident obstructive sleep apnoea in patients with type 1 diabetes: a population-based retrospective cohort study.

AIMS/HYPOTHESIS: People with type 2 diabetes are at increased risk of developing obstructive sleep apnoea. However, it is not known whether people with type 1 diabetes are also at an increased risk of obstructive sleep apnoea. This study aimed to examine whether people with type 1 diabetes are at increased risk of incident obstructive sleep apnoea compared with a matched cohort without type 1 diabetes. METHODS: We used a UK primary care database, The Health Improvement Network (THIN), to perform a retrospective cohort study between January 1995 and January 2018 comparing sleep apnoea incidence between patients with type 1 diabetes (exposed) and without type 1 diabetes (unexposed) (matched for age, sex, BMI and general practice). The outcome was incidence of obstructive sleep apnoea. Baseline covariates and characteristics were assessed at the start of the study based on the most recent value recorded prior to the index date. The Cox proportional hazards regression model was used to estimate unadjusted and adjusted hazard ratios, based on a complete-case analysis. RESULTS: In total, 34,147 exposed and 129,500 matched unexposed patients were included. The median follow-up time was 5.43 years ((IQR 2.19-10.11), and the mean BMI was 25.82 kg/m2 (SD 4.33). The adjusted HR for incident obstructive sleep apnoea in patients with type 1 diabetes vs those without type 1 diabetes was 1.53 (95% CI 1.25, 1.86; p<0.001). Predictors of incident obstructive sleep apnoea in patients with type 1 diabetes were older age, male sex, obesity, being prescribed antihypertensive or lipid-lowering drugs, atrial fibrillation and depression. CONCLUSIONS/INTERPRETATION: Individuals with type 1 diabetes are at increased risk of obstructive sleep apnoea compared with people without diabetes. Clinicians should suspect obstructive sleep apnoea in patients with type 1 diabetes if they are old, have obesity, are male, have atrial fibrillation or depression, or if they are taking lipid-lowering or antihypertensive drugs.

Obesity Without Metabolic Abnormality and Incident CKD: A Population-Based British Cohort Study.

RATIONALE & OBJECTIVE: Metabolically healthy obesity (obesity without any metabolic abnormality) is not considered to be associated with increased risk of morbidity and mortality. We examined and quantified the association between metabolically healthy overweight/obesity and the risk of incident chronic kidney disease (CKD) in a British primary care population. STUDY DESIGN: Retrospective population-based cohort study. SETTING & PARTICIPANTS: 4,447,955 of the 5,182,908 adults in The Health Improvement Network (THIN) database (United Kingdom, 1995-2015) with a recorded body mass index (BMI) at the time of registration date who were free of CKD and cardiovascular disease. EXPOSURE: 11 body size phenotypes were created, defined by BMI categories (underweight, normal weight, overweight, and obesity) and 3 metabolic abnormalities (diabetes, hypertension, and dyslipidemia). OUTCOME: Incident CKD defined as a recorded code for kidney replacement therapy, a recorded diagnosis of CKD, or by an estimated glomerular filtration rate of<60mL/min/1.73m2 for≥90 days, or a urinary albumin-creatinine ratio>3mg/mmol for≥90 days. RESULTS: Of the 4.5 million individuals, 1,040,921 (23.4%) and 588,909 (13.2%) had metabolically healthy overweight and metabolically healthy obesity, respectively. During a mean follow-up interval of 5.4±4.3 (SD) years, compared with individuals with a metabolically healthy normal weight (n=1,656,231), there was a higher risk of incident CKD among those who had metabolically healthy overweight (adjusted HR, 1.30 [95% CI, 1.28-1.33]) and metabolically healthy obesity (adjusted HR, 1.66 [95% CI, 1.62-1.70]). The association was stronger in those younger than 65 years of age. In all BMI categories, there was greater risk of incident CKD with a greater number of metabolic abnormalities in a graded manner. LIMITATIONS: Potential misclassification of metabolic status due to delayed diagnosis and residual confounding due to unmeasured factors. CONCLUSIONS: Overweight and obesity without metabolic abnormality are associated with a higher risk of incident CKD compared with those with normal body weight and no metabolic abnormality.

Angiotensin-converting enzyme inhibitors and risk of age-related macular degeneration in individuals with hypertension.

AIMS: Several observational studies have examined the potential protective effect of angiotensin-converting enzyme inhibitor (ACE-I) use on the risk of age-related macular degeneration (AMD) and have reported contradictory results owing to confounding and time-related biases. We aimed to assess the risk of AMD in a base cohort of patients aged 40 years and above with hypertension among new users of ACE-I compared to an active comparator cohort of new users of calcium channel blockers (CCB) using data obtained from IQVIA Medical Research Data, a primary care database in the UK. METHODS: In this study, 53 832 and 43 106 new users of ACE-I and CCB were included between 1995 and 2019, respectively. In an on-treatment analysis, patients were followed up from the time of index drug initiation to the date of AMD diagnosis, loss to follow-up, discontinuation or switch to the comparator drug. A comprehensive range of covariates were used to estimate propensity scores to weight and match new users of ACE-I and CCB. Standardized mortality ratio weighted Cox proportional hazards model was used to estimate hazard ratios of developing AMD. RESULTS: During a median follow-up of 2 years (interquartile range 1-5 years), the incidence rate of AMD was 2.4 (95% confidence interval 2.2-2.6) and 2.2 (2.0-2.4) per 1000 person-years among the weighted new users of ACE-I and CCB, respectively. There was no association of ACE-I use on the risk of AMD compared to CCB use in either the propensity score weighted or matched, on-treatment analysis (adjusted hazard ratio: 1.07 [95% confidence interval 0.90-1.27] and 0.87 [0.71-1.07], respectively). CONCLUSION: We found no evidence that the use of ACE-I is associated with risk of AMD in patients with hypertension.

Decreased renal function is associated with incident dementia: An IMRD-THIN retrospective cohort study in the UK.

INTRODUCTION: Decreased renal function is a potential risk factor for dementia. METHODS: This retrospective cohort study of 2.8 million adults aged ≥50 years used the IMRD-THIN database, representative of UK primary care, from January 1, 1995 to February 24, 2020. The associations between estimated glomerular filtration rate (eGFR) and urine albumin creatinine ratio (ACR) with incident all-cause dementia were analyzed using Cox regression. RESULTS: In the eGFR cohort (n = 2,797,384), worsening renal dysfunction was associated with increased hazard of all-cause dementia, with greatest hazard at eGFR 15-30 ml/min/1.73min2 (hazard ratio [HR] 1.26, 95% confidence interval [CI] 1.19-1.33). In the ACR cohort (n = 641,912), the hazard of dementia increased from ACR 3-30 mg/mmol (HR 1.13, 95% CI 1.10-1.15) to ACR > 30 mg/mmol (HR 1.25, 95% CI 1.18-1.33). DISCUSSION: Worsening eGFR and albuminuria have graded associations with the risk of dementia, which may have significant implications for the care of patients with kidney disease.

The risk of COVID-19 in survivors of domestic violence and abuse.

A 'shadow pandemic' of domestic violence and abuse (DVA) has emerged secondary to strict public health measures containing the spread of SARS-CoV-2. Many countries have implemented policies to allow the free movement of DVA survivors in attempts to minimise their exposure to abusive environments. Although these policies are well received, as a result there is a possibility of increased COVID-19 transmission within this vulnerable group who are not currently prioritised for vaccination. Therefore, we aimed to compare the risk of developing suspected or confirmed COVID-19 in women (aged over 16 years) exposed to DVA against age-sex-matched unexposed controls, following adjustment for known COVID-19 risk factors. A population-based retrospective open cohort study was undertaken between the 31 January 2020 and 28 February 2021 using 'The Health Improvement Network' database. We identified 10,462 eligible women exposed to DVA who were matched to 41,467 similarly aged unexposed women. Following adjustment for key covariates, women exposed to DVA were at an increased risk (aHR 1.57; 95% CI 1.29-1.90) of suspected/confirmed COVID-19 compared to unexposed women. These findings support previous calls for positive policy action improving DVA surveillance and prioritising survivors for COVID-19 vaccination.

Type 2 diabetes mellitus, glycaemic control, associated therapies and risk of rheumatoid arthritis: a retrospective cohort study.

OBJECTIVE: To compare the incident risk of RA in patients with type 2 diabetes mellitus (T2DM) and to explore the role of glycaemic control and associated therapeutic use in the onset of RA. METHODS: This study was a retrospective cohort study using patients derived from the IQVIA Medical Research Data (IMRD-UK) database between 1995 and 2019. A total of 224 551 newly diagnosed patients with T2DM were matched to 449 101 patients without T2DM and followed up to assess their risk of RA. Further analyses investigated the effect of glycaemic control, statin use and anti-diabetic drugs on the relationship between T2DM and RA using a time-dependent Cox regression model. RESULTS: During the study period, the incidence of RA was 8.1 and 10.6 per 10 000 person-years in the exposed and unexposed groups, respectively. The adjusted hazard ratio (aHR) was 0.73 (95% CI 0.67, 0.79). In patients who had not used statins in their lifetime, the aHR was 0.89 (95% CI 0.69, 1.14). When quantifying the effects of glycaemic control, anti-diabetic drugs and statins using time-varying analyses, there was no association with glycaemic control [aHR 1.00 (95% CI 0.99, 1.00)], use of metformin [aHR 1.00 (95% CI 0.82, 1.22)], dipeptidyl peptidase-4 inhibitors [DPP4is; aHR 0.94 (95% CI 0.71, 1.24)] and the development of RA. However, statins demonstrated a protective effect for progression of RA in those with T2DM [aHR 0.76 (95% CI 0.66, 0.88)], with evidence of a duration-response relationship. CONCLUSION: There is a reduced risk of RA in patients with T2DM that may be attributable to the use of statins.

Sodium-glucose co-transporter-2 inhibitors and susceptibility to COVID-19: A population-based retrospective cohort study.

Sodium-glucose co-transporter-2 (SGLT2) inhibitors are widely prescribed in people with type 2 diabetes. We aimed to investigate whether SGLT2 inhibitor prescription is associated with COVID-19, when compared with an active comparator. We performed a propensity-score-matched cohort study with active comparators and a negative control outcome in a large UK-based primary care dataset. Participants prescribed SGLT2 inhibitors (n = 9948) and a comparator group prescribed dipeptidyl peptidase-4 (DPP-4) inhibitors (n = 14 917) were followed up from January 30 to July 27, 2020. The primary outcome was confirmed or clinically suspected COVID-19. The incidence rate of COVID-19 was 19.7/1000 person-years among users of SGLT2 inhibitors and 24.7/1000 person-years among propensity-score-matched users of DPP-4 inhibitors. The adjusted hazard ratio was 0.92 (95% confidence interval 0.66 to 1.29), and there was no evidence of residual confounding in the negative control analysis. We did not observe an increased risk of COVID-19 in primary care amongst those prescribed SGLT2 inhibitors compared to DPP-4 inhibitors, suggesting that clinicians may safely use these agents in the everyday care of people with type 2 diabetes during the COVID-19 pandemic.

Renin-angiotensin system inhibitors and susceptibility to COVID-19 in patients with hypertension: a propensity score-matched cohort study in primary care.

INTRODUCTION: Renin-angiotensin system (RAS) inhibitors have been postulated to influence susceptibility to Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). This study investigated whether there is an association between their prescription and the incidence of COVID-19 and all-cause mortality. METHODS: We conducted a propensity-score matched cohort study comparing the incidence of COVID-19 among patients with hypertension prescribed angiotensin-converting enzyme I (ACE) inhibitors or angiotensin II type-1 receptor blockers (ARBs) to those treated with calcium channel blockers (CCBs) in a large UK-based primary care database (The Health Improvement Network). We estimated crude incidence rates for confirmed/suspected COVID-19 in each drug exposure group. We used Cox proportional hazards models to produce adjusted hazard ratios for COVID-19. We assessed all-cause mortality as a secondary outcome. RESULTS: The incidence rate of COVID-19 among users of ACE inhibitors and CCBs was 9.3 per 1000 person-years (83 of 18,895 users [0.44%]) and 9.5 per 1000 person-years (85 of 18,895 [0.45%]), respectively. The adjusted hazard ratio was 0.92 (95% CI 0.68 to 1.26). The incidence rate among users of ARBs was 15.8 per 1000 person-years (79 out of 10,623 users [0.74%]). The adjusted hazard ratio was 1.38 (95% CI 0.98 to 1.95). There were no significant associations between use of RAS inhibitors and all-cause mortality. CONCLUSION: Use of ACE inhibitors was not associated with the risk of COVID-19 whereas use of ARBs was associated with a statistically non-significant increase compared to the use of CCBs. However, no significant associations were observed between prescription of either ACE inhibitors or ARBs and all-cause mortality.

Data extraction for epidemiological research (DExtER): a novel tool for automated clinical epidemiology studies.

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.

Cardio-metabolic outcomes in South Asians compared to White Europeans in the United Kingdom: a matched controlled population-based cohort study.

BACKGROUND: There appears to be an inequality in the risk of cardio-metabolic disease between those from a South Asian (SA) background when compared to those of White Europeans (WE) descendance, however, this association has not been explored in a large European cohort. This population-based open retrospective cohort explores the incidence of cardio-metabolic disease in those without pre-existing cardiometabolic disease taken from a large UK primary care database from 1st January 2007 to 31st December 2017. METHODS: A retrospective open cohort matched population-based study using The Health Improvement Network (THIN) database. The outcomes of this study were the incidences of cardio-metabolic events (type 2 diabetes mellitus, hypertension, ischemic heart disease, stroke, heart failure, and atrial fibrillation). RESULTS: A total of 94,870 SA patients were matched with 189,740 WE patients. SA were at an increased risk of developing: T2DM (adjusted hazard ratio (aHR) 3.1; 95% CI 2.97-3.23); HTN (1.34; 95% CI: 1.29-1.39); ischaemic heart disease (IHD) (1.81; 95% CI: 1.68-1.93) and heart failure (HF) (1.11; 95% CI: 1.003-1.24). However, they were at a lower risk of atrial fibrillation (AF) (0.53; 95% CI: 0.48-0.59) when compared to WE. Of those of SA origin, the Bangladeshi community were at the greatest risk of T2DM, HTN, IHD and HF, but were at the lowest risk of AF in when compared to Indians and Pakistanis. CONCLUSION: Considering the high risk of cardio-metabolic diseases in the SA cohort, differential public health measures should be considered in these patients to reduce their risk of disease, which may be furthered tailored depending on their country of origin.

Epidemiology, morbidity and mortality in Behçet's disease: a cohort study using The Health Improvement Network (THIN).

OBJECTIVES: The epidemiology of Behçet's disease (BD) has not been well characterized in the UK. Evidence on the risk of cardiovascular disease, thromboembolic disease and mortality in patients with BD compared with the general population is scarce. METHODS: We used a large UK primary care database to investigate the epidemiology of BD. A retrospective matched cohort study was used to assess the following outcomes: risk of cardiovascular, thromboembolic disease and mortality. Controls were selected at a 1:4 ratio (age and gender matched). Cox proportional hazard models were used to derive adjusted hazard ratios (aHR). RESULTS: The prevalence of BD was 14.61 (95% CI 13.35-15.88) per 100 000 population in 2017. A total of 1281 patients with BD were compared with 5124 age- and gender-matched controls. There was significantly increased risk of ischaemic heart disease [aHR 3.09 (1.28-7.44)], venous thrombosis [aHR 4.80 (2.42-9.54)] and mortality [aHR 1.40 (1.07-1.84)] in patients with BD compared with corresponding controls. Patients with BD were at higher risk of pulmonary embolism compared with corresponding controls at baseline [adjusted odds ratio 4.64 (2.66-8.09), P < 0.0001]. The majority of patients with pulmonary embolism and a diagnosis of BD had pulmonary embolism preceding the diagnosis of BD, not after (87.5%; n = 28/32). CONCLUSION: BD has a higher prevalence than previously thought. Physicians should be aware of the increased risk of developing ischaemic heart disease, stroke/transient ischaemic attack and deep venous thrombosis in patients with BD at an earlier age compared with the general population. Risk of embolism in patients with BD might vary across the disease course.

Correction: Increased risk of ischemic heart disease, hypertension, and type 2 diabetes in women with previous gestational diabetes mellitus, a target group in general practice for preventive interventions: A population-based cohort study.

[This corrects the article DOI: 10.1371/journal.pmed.1002488.].

Polycystic ovary syndrome, androgen excess, and the risk of nonalcoholic fatty liver disease in women: A longitudinal study based on a United Kingdom primary care database.

BACKGROUND: 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. METHODS AND FINDINGS: 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. CONCLUSIONS: 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.

Increased risk of ischemic heart disease, hypertension, and type 2 diabetes in women with previous gestational diabetes mellitus, a target group in general practice for preventive interventions: A population-based cohort study.

BACKGROUND: Gestational diabetes mellitus (GDM) is associated with developing type 2 diabetes, but very few studies have examined its effect on developing cardiovascular disease. METHODS AND FINDINGS: 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. CONCLUSIONS: 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.

Males with prolactinoma are at increased risk of incident cardiovascular disease.

OBJECTIVE: To investigate whether the risk of incident cardiovascular disease (CVD) is increased in patients with prolactinoma. DESIGN: Population-based, retrospective, open-cohort study using The Health Improvement Network (THIN) database. PATIENTS: A total of 2233 patients with prolactinoma and 10 355 matched controls (1:5 ratio) from UK General Practices contributing to THIN were included. Sex, age, body mass index and smoking status were used as matching parameters. The primary outcome was any incident CVD, defined by Read codes suggesting myocardial infarction, angina pectoris, stroke, transient ischaemic attack or heart failure. Sex-specific-adjusted incidence rate ratios (aIRRs) were calculated with Poisson regression, using clinically relevant parameters as model covariates. Sensitivity analyses were performed to check whether a change in the initial assumptions could have an impact on the findings. RESULTS: During the 6-year observation period, the composite CVD outcome was recorded in 54 patients with prolactinoma and 180 "nonexposed" individuals. The incidence rate was 1.8 and 14.8 per 1000 person-years for the females and males with prolactinoma, respectively. The aIRRs for CVD were estimated at 0.99 [95% confidence interval (CI): 0.61-1.61, P = .968)] in female patients and 1.94 (95% CI: 1.29-2.91, P = .001) in male patients. These findings remained robust in sensitivity analyses restricting to patients with documented record of dopamine agonist treatment and those with newly diagnosed prolactinoma. CONCLUSIONS: In contrast to females, men with prolactinoma have increased risk for incident CVD; the aetiology of this gender-specific finding remains to be elucidated.