The association between adverse childhood experiences and adult cardiac function in the UK Biobank.

Aims: The importance of early life factors in determining health in later adulthood is increasingly recognized. This study evaluated the association of adverse childhood experiences (ACEs) with cardiovascular magnetic resonance (CMR) phenotypes.

Methods And Results: UK Biobank participants who had completed CMR and the self-reported questionnaire on traumatic childhood experiences were included.

Neuroticism personality traits are linked to adverse cardiovascular phenotypes in the UK Biobank.

Aims: To evaluate the relationship between neuroticism personality traits and cardiovascular magnetic resonance (CMR) measures of cardiac morphology and function, considering potential differential associations in men and women.

Methods And Results: The analysis includes 36 309 UK Biobank participants (average age = 63.9 ± 7.

Machine-learning versus traditional approaches for atherosclerotic cardiovascular risk prognostication in primary prevention cohorts: a systematic review and meta-analysis.

Background: Cardiovascular disease (CVD) risk prediction is important for guiding the intensity of therapy in CVD prevention. Whilst current risk prediction algorithms use traditional statistical approaches, machine learning (ML) presents an alternative method that may improve risk prediction accuracy. This systematic review and meta-analysis aimed to investigate whether ML algorithms demonstrate greater performance compared with traditional risk scores in CVD risk prognostication.

Trends and Outcomes for Percutaneous Coronary Intervention and Coronary Artery Bypass Graft Surgery in New South Wales from 2008 to 2019.

Risk profiles are changing for patients who undergo percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG). In Australia, little is known of the nature of these changes in contemporary practice and of the impact on patient outcomes. We identified all CABG (n = 40,805) and PCI (n = 142,399) procedures in patients aged ≥18 years in New South Wales, Australia, during 2008 to 2019.

Assessing the effectiveness of empirical calibration under different bias scenarios.

Background: Estimations of causal effects from observational data are subject to various sources of bias. One method for adjusting for the residual biases in the estimation of treatment effects is through the use of negative control outcomes, which are outcomes not believed to be affected by the treatment of interest. The empirical calibration procedure is a technique that uses negative control outcomes to calibrate p-values.

Causal inference for observational longitudinal studies using deep survival models.

Objective: Causal inference for observational longitudinal studies often requires the accurate estimation of treatment effects on time-to-event outcomes in the presence of time-dependent patient history and time-dependent covariates.

Materials And Methods: To tackle this longitudinal treatment effect estimation problem, we have developed a time-variant causal survival (TCS) model that uses the potential outcomes framework with an ensemble of recurrent subnetworks to estimate the difference in survival probabilities and its confidence interval over time as a function of time-dependent covariates and treatments.

Results: Using simulated survival datasets, the TCS model showed good causal effect estimation performance across scenarios of varying sample dimensions, event rates, confounding and overlapping.

Demographic and health profiles of people with severe mental illness in general practice in Australia: a cross-sectional study.

Background: People with severe mental illness have a higher rate of premature death than the general population, largely due to primary care preventable diseases. There has been little research on the health profile of this population attending Australian general practices.

Methods: In this nationwide cross-sectional study, MedicineInsight data for adult patients regularly attending general practices in 2018 were analysed to estimate the prevalence of schizophrenia or bipolar disorders (SBD) and investigate the health profile of people with SBD compared with other patients.

Predictive performance and impact of algorithms in remote monitoring of chronic conditions: A systematic review and meta-analysis.

Background: The use of telehealth interventions, such as the remote monitoring of patient clinical data (e.g. blood pressure, blood glucose, heart rate, medication use), has been proposed as a strategy to better manage chronic conditions and to reduce the impact on patients and healthcare systems.

Exploring variation in the performance of planned birth: A mixed method study.

Objective: Variation in practice in relation to indications and timing for both induction of labour (IOL) and planned caesarean section (CS) clearly exists. However, the extent of this variation, and how this variation is explained by clinicians remains unclear. The aim of this study was to map the variation in IOL and planned CS at eight Australian hospitals, and understand why variation occurs from the perspective of clinicians at these hospitals.

Medications used disproportionately during pregnancy: Priorities for research on the risks and benefits of medications when used during pregnancy.

Purpose: To identify medications used disproportionately more or less among pregnant women relative to women of childbearing age.

Methods: Medication use among pregnant women in New South Wales, Australia was identified using linked perinatal and pharmaceutical dispensing data from 2006 to 2012. Medication use in women of childbearing age (including pregnant women) was identified using pharmaceutical dispensing data for a 10% random sample of the Australian population.

Targeted estimation of heterogeneous treatment effect in observational survival analysis.

The aim of clinical effectiveness research using repositories of electronic health records is to identify what health interventions 'work best' in real-world settings. Since there are several reasons why the net benefit of intervention may differ across patients, current comparative effectiveness literature focuses on investigating heterogeneous treatment effect and predicting whether an individual might benefit from an intervention. The majority of this literature has concentrated on the estimation of the effect of treatment on binary outcomes.

Utilisation of teratogenic medicines before and during pregnancy in Australian women.

Background: Given the potential hazards of teratogenic medicines, to a fetus exposed in utero, monitoring their use around pregnancy is imperative.

Aim: To measure utilisation of teratogenic medicines (Therapeutic Goods Administration's category D or X) in women who gave birth in New South Wales, Australia, during pregnancy and the 24 months prior.

Materials And Methods: We used linked population-based datasets including dispensing and perinatal data for all deliveries in NSW between 2005 and 2012.

Identifying patients using antidepressants for the treatment of depression: A predictive algorithm for use in pharmaceutical and medical claims data.

Purpose: Records of antidepressant dispensings are often used as a surrogate measure of depression. However, as antidepressants are frequently prescribed for indications other than depression, this is likely to result in misclassification. This study aimed to develop a predictive algorithm that identifies patients using antidepressants for the treatment of depression.

Algorithm for resolving discrepancies between claims for smoking cessation pharmacotherapies during pregnancy and smoking status in delivery records: The impact on estimates of utilisation.

Background: The linkage of routine data collections are valuable for population-based evaluation of smoking cessation pharmacotherapy in pregnancy where little is known about the utilisation or safety of these pharmacotherapies antenatally. The use of routine data collections to study smoking cessation pharmacotherapy is limited by disparities among data sources. This study developed an algorithm to resolve disparity between the evidence of pharmacotherapy utilisation for smoking cessation and the recording of smoking in pregnancy, examined its face validity and assessed the implications on estimates of smoking cessation pharmacotherapy utilisation.

The Australian Pharmaceutical Benefits Scheme data collection: a practical guide for researchers.

Background: The Pharmaceutical Benefits Scheme (PBS) is Australia's national drug subsidy program. This paper provides a practical guide to researchers using PBS data to examine prescribed medicine use.

Findings: Excerpts of the PBS data collection are available in a variety of formats.