Atrial fibrillation and frailty: An observational cohort study using electronic healthcare records

Atrial fibrillation is common in older people, and is associated with increased mortality and stroke. Patients with atrial fibrillation/flutter (AF) also commonly have frailty, which is associated with increased risk of a range of further adverse clinical outcomes. However, there is a lack of evidence on the burden and management of AF in people with frailty. A study using the primary care electronic health records of 536,955 patients aged ≥65 years was conducted to investigate the burden of frailty and AF amongst older people, and their associations with clinical outcomes. A systematic review and meta-analysis was completed to establish the current knowledge base, and to inform the quantitative analyses. Baseline characteristics were described and compared between those with and without AF as well as by frailty category according to the electronic frailty index. Rates of all-cause mortality, stroke, bleeding (intracranial and gastrointestinal), transient ischaemic attack (TIA), and falls were calculated per 1000 person-years, and compared with the non-AF patient population. Cox proportional hazards modelling was used to determine unadjusted and adjusted risk for each clinical outcome and mortality, and presented as hazard ratios (HR) alongside 95% confidence intervals. The association between oral anticoagulation (OAC) prescription stratified by frailty category with clinical outcomes was investigated using Cox proportional hazards modelling. At baseline, 61,177 (11.4%) patients had AF. People with AF had a higher burden of frailty than those without (89.5% vs. 55.3%) and had higher rates of mortality, stroke, TIA and bleeding. Of patients with AF and eligible for OAC, it was prescribed in 53.1% (41.7% in robust, mild frailty 53.2%, moderate 55.6%, severe 53.4%). OAC was associated with a 19% reduction in all-cause mortality (HR 0.81, 95%CI 0.77-0.85) and 22% reduction in stroke (HR 0.78, 0.67-0.92). There was no statistically significant difference in rates of bleeding between those prescribed and not prescribed OAC. For the first time in a large representative cohort of older people, this study quantified the burden of AF and frailty, and their association with a range of clinical outcomes. This study found no evidence that OAC should be withheld on the basis of concomitant frailty

Contributions of Higher Resolution Observational Evidence from Electronic Health Records to Understand the Causal Relevance of Blood Lipids to Heart Failure and Atrial Fibrillation

Heart failure (HF) and atrial fibrillation (AF) are increasingly prevalent due to aging populations, and both diseases have a big economic and healthcare burden globally. To date, there is no primary prevention specific to healthy populations. Blood lipids (i.e., LDL-C, HDL-C, and TG), which are involved with pathophysiological mechanisms of HF and AF, might play a role in the origin of both diseases. Therefore, the potential causal relevance of blood lipids to HF and AF should be investigated. Linkage electronic health records (EHRs) provide an opportunity to investigate the association between blood lipids and the incidence of HF and AF, as these records contain large sample sizes (e.g., n>1 million) with a wide range of diseases and biomarkers routinely recorded in clinical practice. Challenges include structuring the data into a research-ready format, accurately defining outcomes, and handling missing data. The data used in this thesis is from the CALIBER platform, which links routinely collected EHRs from general practices, hospital admission, and the death registries of 3 million patients in England from 1997 to 2016. In this thesis, I (1) constructed cohorts from EHRs and ensured the validity of the cohorts and (2) examined the association between blood lipids and the incidence of HF and AF using the EHR population-based cohort design. The observed findings were then compared to the results from meta-regression of trials on lipid-lowering drugs and those from a Mendelian randomisation approach, and then I (3) assessed the predictive value of adding blood lipids in the risk prediction of incident HF and AF. Additionally, I developed the model for the prediction of 10-year risk of newly occurring HF and AF. Taken together, these findings have a valuable implementation. For future research, my findings can be a basis for developing a new drug to fight against HF and AF. For clinical application, my findings can inform clinicians whether blood lipids should be targeted and what levels are needed to protect people from HF and AF. Besides, my results can inform clinicians to monitor their patients for the developing of HF and AF

Evaluation of strategies for reducing the burden of COPD in the UK using Bayesian methods

Chronic obstructive pulmonary disease (COPD) is responsible for 5.3% of all deaths and 1.7% of all hospital admissions in the UK. This thesis focuses on strategies to reduce COPD burden by targeting three aspects across the public healthcare system: prevention, emergency treatment, and long-term management. Analyses were performed in a Bayesian framework to exploit its flexibility in modelling uncertainty and the incorporation of prior knowledge. First, I assessed whether communication of personalised disease risk in primary care is an effective smoking cessation intervention, using cost-effectiveness and value of information analyses based on various data sources across the literature. The odds ratio for the effectiveness of communication of personalised disease risk was 1.48 (95%CrI:0.91-2.26). While I found a probability of cost-effectiveness of about 90%, further research up to a maximum of £27 million is justified to reduce the uncertainty around this estimate. Secondly, I assessed whether case ascertainment affects the detection of poorly performing hospital trusts in the treatment of acute exacerbation of COPD (AECOPD) in secondary care, using data from the National Asthma and COPD Audit Programme. Case ascertainment was associated with 30-day mortality (OR:1.74; 1.25-2.41) and adjusting for it impacted the findings, with 5 trusts becoming outliers and 2 trusts no longer classified as outliers. Finally, using general practice data from Clinical Practice Research Datalink, I assessed whether new guidelines suggesting triple therapy (long-acting beta-2 agonists, LABA + long-acting muscarinic antagonists, LAMA + inhaled corticosteroids, ICS) for the treatment of those with poorly-controlled COPD on LABA+LAMA dual therapy improves disease outcomes. Triple therapy was not associated with severe AECOPD (IRR:1.00; 0.93-1.07) or mortality (IRR:0.95; 0.86-1.06), but was associated with increased risk of pneumonia (IRR:1.19; 1.05-1.35). This thesis applied sophisticated Bayesian methods to increase understanding of how COPD burden could be reduced in different areas of the public healthcare system.Open Acces

A systematic review of natural language processing applied to radiology reports

NLP has a significant role in advancing healthcare and has been found to be key in extracting structured information from radiology reports. Understanding recent developments in NLP application to radiology is of significance but recent reviews on this are limited. This study systematically assesses recent literature in NLP applied to radiology reports. Our automated literature search yields 4,799 results using automated filtering, metadata enriching steps and citation search combined with manual review. Our analysis is based on 21 variables including radiology characteristics, NLP methodology, performance, study, and clinical application characteristics. We present a comprehensive analysis of the 164 publications retrieved with each categorised into one of 6 clinical application categories. Deep learning use increases but conventional machine learning approaches are still prevalent. Deep learning remains challenged when data is scarce and there is little evidence of adoption into clinical practice. Despite 17% of studies reporting greater than 0.85 F1 scores, it is hard to comparatively evaluate these approaches given that most of them use different datasets. Only 14 studies made their data and 15 their code available with 10 externally validating results. Automated understanding of clinical narratives of the radiology reports has the potential to enhance the healthcare process but reproducibility and explainability of models are important if the domain is to move applications into clinical use. More could be done to share code enabling validation of methods on different institutional data and to reduce heterogeneity in reporting of study properties allowing inter-study comparisons. Our results have significance for researchers providing a systematic synthesis of existing work to build on, identify gaps, opportunities for collaboration and avoid duplication