Diabetes in Patients With Idiopathic Parkinson's Disease

OBJECTIVE—Previous observational studies reported inconsistent results on the association between diabetes and Parkinson's disease, and data on the risk of developing incident diabetes in relation to Parkinson's disease are scarce. We aimed at comparing the diabetes prevalence between patients with or without Parkinson's disease and at exploring the risk of developing incident diabetes associated with Parkinson's disease

CODE-EHR best practice framework for the use of structured electronic healthcare records in clinical research

Big data is central to new developments in global clinical science aiming to improve the lives of patients. Technological advances have led to the routine use of structured electronic healthcare records with the potential to address key gaps in clinical evidence. The covid-19 pandemic has demonstrated the potential of big data and related analytics, but also important pitfalls. Verification, validation, and data privacy, as well as the social mandate to undertake research are key challenges. The European Society of Cardiology and the BigData@Heart consortium have brought together a range of international stakeholders, including patient representatives, clinicians, scientists, regulators, journal editors and industry. We propose the CODE-EHR Minimum Standards Framework as a means to improve the design of studies, enhance transparency and develop a roadmap towards more robust and effective utilisation of healthcare data for research purposes

Limited evidence on persistence with anticoagulants, and its effect on the risk of recurrence of venous thromboembolism: a systematic review of observational studies

Pareen Vora, Montse Soriano-Gabarró, Kiliana Suzart, Gunnar Persson Brobert Department of Epidemiology, Bayer Pharma AG, Berlin, Germany Purpose: The risk of venous thromboembolism (VTE) recurrence is high following an initial VTE event, and it persists over time. This recurrence risk decreases rapidly after starting with anticoagulation treatment and reduces by ~80%–90% with prolonged anticoagulation. Nonpersistence with anticoagulants could lead to increased risk of VTE recurrence. This systematic review aimed to estimate persistence at 3, 6, and 12 months with anticoagulants in patients with VTE, and to evaluate the risk of VTE recurrence in nonpersistent patients.Methods: PubMed and Embase® were searched up to May 3, 2014 and the search results updated to May 31, 2015. Studies involving patients with VTE aged ≥18 years, treatment with anticoagulants intended for at least 3 months or more, and reporting data for persistence were included. Proportions were transformed using Freeman–Tukey double arcsine transformation and pooled using the DerSimonian–Laird random-effects approach.Results: In total, 12 observational studies (7/12 conference abstracts) were included in the review. All 12 studies either reported or provided data for persistence. The total number of patients meta-analyzed to estimate persistence at 3, 6, and 12 months was 71,969 patients, 58,940 patients, and 68,235 patients, respectively. The estimated persistence for 3, 6, and 12 months of therapy was 83% (95% confidence interval [CI], 78–87; I2=99.3%), 62% (95% CI, 58–66; I2=98.1%), and 31% (95% CI, 22–40; I2=99.8%), respectively. Only two studies reported the risk of VTE recurrence based on nonpersistence – one at 3 months and the other at 12 months.Conclusion: Limited evidence showed that persistence was suboptimal with an estimated 17% patients being nonpersistent with anticoagulants in the crucial first 3 months. Persistence declined over 6 and 12 months. Observational data on persistence with anticoagulation treatment, especially direct oral anticoagulants, in patients with VTE and its effect on risk of VTE recurrence were scarce and further research is required. Keywords: meta-analysis, deep vein thrombosis, recurrence, vitamin K antagonists, direct oral anticoagulant

Characteristics, treatment patterns, and residual cardiovascular risk of patients with a first acute myocardial infarction: A nationwide population-based cohort study in Norway

There are few nationwide descriptive studies of longitudinal drug use and residual cardiovascular risk in patients with myocardial infarction (MI) in contemporary clinical practice. The objectives of this work were to describe characteristics and longitudinal cardiovascular drug use of patients with a first acute MI in Norway, and to quantify residual risks of cardiovascular events and death. Using nationwide health registries in Norway, we identified 43 750 adults with a first MI (2010 to 2015) and ≥1 prescription for antiplatelet medication. We described cardiovascular medication post-MI and calculated residual cardiovascular risks. Between 3 months and 13–15 months post MI, medication use dropped from 93.3% to 75.1% for low-dose aspirin, 78.1% to 11.0% for dual antiplatelet therapy, 91.6% to 78.7% for antihypertensives, and 88.0% to 70.7% for lipid-lowering therapy. Incidence rate ratios (IRRs) for recurrent MI were similar between subpopulations at 12 months and notably different at 12–36 months. IRRs (95% CIs) at 12–36 months were 1.52 (1.26–1.82) for 65–74 years, 2.26 (1.88–2.71) for 75–84 years, and 3.97 (3.29–4.79) for ≥85 years (vs. 18–49 years), 2.42 (2.18–2.69) for those with ischaemic heart disease (IHD), 2.26 (1.97–2.59) for peripheral artery disease (PAD), 2.17 (1.98–2.36) for hypertension, and 1.82 (1.65–2.01) for diabetes. In conclusion, secondary prevention medication use 13–15 months following a first MI is suboptimal among patients in Norway. The elderly and those with IHD, PAD, diabetes, or hypertension are at high-risk for recurrent MI/stroke/death and should be managed closely beyond the first year

Height and body mass index in young adulthood and risk of schizophrenia: a longitudinal study of 1 347 520 Swedish men

OBJECTIVE: Measures of body size reflect genetic and environmental influences on growth and energy balance. Associations between such measures and risk of schizophrenia have been inconsistent. METHOD: This is a population-based cohort study of 1 347 520 men born in Sweden from 1952 to 1982, with height and body mass index (BMI) data available from conscription records. The Swedish National Hospital Discharge Register was used to identify subjects diagnosed with schizophrenia from 1970 to 2000. RESULTS: Subjects with lower BMI and shorter height had an increased risk of developing schizophrenia. Underweight subjects had an approximately 30% increase in risk compared with normal BMI subjects (adjusted HR = 1.30, 95% CI: 1.20-1.42). Tall subjects had an approximately 15% reduction in risk compared with short subjects (adjusted HR = 0.85, 95% CI: 0.80-0.92). CONCLUSION: Both height and BMI in early adulthood are strongly and inversely associated with risk of schizophrenia. We discuss these findings in relation to possible genetic and nutritional causal mechanisms

Characteristics, treatment patterns, and residual cardiovascular risk of patients with a first acute myocardial infarction: A nationwide population-based cohort study in Norway

There are few nationwide descriptive studies of longitudinal drug use and residual cardiovascular risk in patients with myocardial infarction (MI) in contemporary clinical practice. The objectives of this work were to describe characteristics and longitudinal cardiovascular drug use of patients with a first acute MI in Norway, and to quantify residual risks of cardiovascular events and death. Using nationwide health registries in Norway, we identified 43 750 adults with a first MI (2010 to 2015) and ≥1 prescription for antiplatelet medication. We described cardiovascular medication post-MI and calculated residual cardiovascular risks. Between 3 months and 13–15 months post MI, medication use dropped from 93.3% to 75.1% for low-dose aspirin, 78.1% to 11.0% for dual antiplatelet therapy, 91.6% to 78.7% for antihypertensives, and 88.0% to 70.7% for lipid-lowering therapy. Incidence rate ratios (IRRs) for recurrent MI were similar between subpopulations at 12 months and notably different at 12–36 months. IRRs (95% CIs) at 12–36 months were 1.52 (1.26–1.82) for 65–74 years, 2.26 (1.88–2.71) for 75–84 years, and 3.97 (3.29–4.79) for ≥85 years (vs. 18–49 years), 2.42 (2.18–2.69) for those with ischaemic heart disease (IHD), 2.26 (1.97–2.59) for peripheral artery disease (PAD), 2.17 (1.98–2.36) for hypertension, and 1.82 (1.65–2.01) for diabetes. In conclusion, secondary prevention medication use 13–15 months following a first MI is suboptimal among patients in Norway. The elderly and those with IHD, PAD, diabetes, or hypertension are at high-risk for recurrent MI/stroke/death and should be managed closely beyond the first year

Migraine incidence, comorbidity and health resource utilization in the UK

Population-based data on migraine incidence and comorbidity are scarce. We therefore aimed to quantify incidence rates and comorbidity of diagnosed migraine and health resource utilization (HRU) in migraineurs in the UK primary care setting. We conducted a follow-up study with a nested case-control analysis on the General Practice Research Database. The study encompassed 51,688 patients with a first-time diagnosis of migraine between 1994 and 2001, and the same number of matched controls. The migraine incidence rate was 3.69 (95% confidence interval 3.66, 3.73) cases per 1000 person-years. It was around 2.5 times higher in women. Most chronic diseases were slightly more prevalent in migraineurs than in controls. Triptan users had higher health resource utilization than other migraineurs. This study shows that migraine is a common diagnosis in general practice and associated with a high prevalence of comorbidity. The increased HRU in triptan users suggests greater migraine severity

Structured assessment for prospective identification of safety signals in electronic medical records:evaluation in the health improvement network

BACKGROUND: Pharmacovigilance signal detection largely relies on individual case reports, but longitudinal health data are being explored as complementary information sources. Research to date has focused on the ability of epidemiological methods to distinguish established adverse drug reactions (ADRs) from unrelated adverse events. OBJECTIVE: The aim of this study was to evaluate a process for structured clinical and epidemiological assessment of temporally associated drugs and medical events in electronic medical records. METHODS: Pairs of drugs and medical events were selected for review on the basis of their temporal association according to a calibrated self-controlled cohort analysis in The Health Improvement Network. Six assessors trained in pharmacovigilance and/or epidemiology evaluated seven drugs each, with up to 20 medical events per drug. A pre-specified questionnaire considered aspects related to the nature of the temporal pattern, demographic features of the cohort, concomitant medicines, earlier signs and symptoms, and possible confounding by underlying disease. This informed a classification of drug–event pairs as known ADRs, meriting further evaluation, or dismissed. RESULTS: The number of temporally associated medical events per drug ranged from 11 to 307 (median 50) for the 42 selected drugs. Out of the 509 relevant drug–event combinations subjected to the assessment, 127 (25 %) were classified as known ADRs. Ninety-one (24 %) of the remaining pairs were classified as potential signals meriting further evaluation and 291 (76 %) were dismissed. Suggestive temporal patterns and lack of clear alternative explanations were the most common reasons that drug–event pairs were classified as meriting further evaluation. Earlier signs and symptoms and confounding by the underlying disease were the most common reasons that drug–event pairs were dismissed. CONCLUSIONS: Exploratory analysis of electronic medical records can detect important potential safety signals. However, effective signal detection requires that statistical signal detection be combined with clinical and epidemiological review to achieve an acceptable false positive rate

Big data from electronic health records for early and late translational cardiovascular research : challenges and potential

Aims: Cohorts of millions of people's health records, whole genome sequencing, imaging, sensor, societal and publicly available data present a rapidly expanding digital trace of health. We aimed to critically review, for the first time, the challenges and potential of big data across early and late stages of translational cardiovascular disease research. Methods and results: We sought exemplars based on literature reviews and expertise across the BigData@Heart Consortium. We identified formidable challenges including: data quality, knowing what data exist, the legal and ethical framework for their use, data sharing, building and maintaining public trust, developing standards for defining disease, developing tools for scalable, replicable science and equipping the clinical and scientific work force with new inter-disciplinary skills. Opportunities claimed for big health record data include: richer profiles of health and disease from birth to death and from the molecular to the societal scale; accelerated understanding of disease causation and progression, discovery of new mechanisms and treatment-relevant disease sub-phenotypes, understanding health and diseases in whole populations and whole health systems and returning actionable feedback loops to improve (and potentially disrupt) existing models of research and care, with greater efficiency. In early translational research we identified exemplars including: discovery of fundamental biological processes e.g. linking exome sequences to lifelong electronic health records (EHR) (e.g. human knockout experiments); drug development: genomic approaches to drug target validation; precision medicine: e.g. DNA integrated into hospital EHR for pre-emptive pharmacogenomics. In late translational research we identified exemplars including: learning health systems with outcome trials integrated into clinical care; citizen driven health with 24/7 multi-parameter patient monitoring to improve outcomes and population-based linkages of multiple EHR sources for higher resolution clinical epidemiology and public health. Conclusion: High volumes of inherently diverse ('big') EHR data are beginning to disrupt the nature of cardiovascular research and care. Such big data have the potential to improve our understanding of disease causation and classification relevant for early translation and to contribute actionable analytics to improve health and healthcare.Collaborator Big data from electronic health records for early and late translational cardiovascular research: challenges and potential.Bodil Svennblad, Stefan K James och Jonas Oldgren ingår i gruppen Innovative Medicines Initiative 2nd programme, Big Data for Better Outcomes,BigData@Heart Consortium of 20 academic and industry partners including ESC.</p