Heart failure in young adults

Heart failure (HF) is a major health concern affecting 15 million people in Europe and around 900 000 people in the U.K. HF predominantly affects the elderly, with the mean age of patients with a diagnosis of HF between 70 and 80 years. Most previous HF studies have accordingly focused on older patients. Although HF is less common in younger adults (<65 years), 15% to 20% of patients hospitalised with HF are younger than 60 years of age. Very few studies have described the characteristics of younger adults with HF and its outcome. The aims of this thesis are to describe the clinical characteristics of younger adults with HF, explore the epidemiology of HF in younger adults and determine their short- and long-term outcomes. This was made possible by access multiple databases consisting of large patient cohorts with HF. The first chapter is a systematic literature review of younger adults with HF. Gaps in the current literature were identified and the thesis focused on some of these. The CHARM study allows detail characterisations of younger adults with HF. It recorded characteristics of patients with HF, including symptoms and signs of HF, electrocardiographic changes, chest radiographic findings, and also left ventricular ejection fraction. HF hospitalisations and its precipitating factors were also recorded systematically. Younger adults were more likely to have a third heart sound and hepatomegaly, but less likely to have pulmonary crackles and peripheral oedema. Similarly, radiological findings in younger adults were less likely to show interstitial pulmonary oedema or pleural effusion. Interestingly, younger adults aged <40 years not only have similar HF hospitalisation rate to older patients, however during their presentation with decompensated HF, they were less likely to have clinical pulmonary oedema and radiological signs of HF. Physicians managing younger adults with HF need to be aware of this. Younger adults were also less compliant with medications and lifestyle restriction resulting in hospitalisation with decompensated HF. Fortunately, despite these challenges, mortality rates in younger adults with HF were lower compared to older patients. To further substantiate the findings from the CHARM study, the MAGGIC study, a meta-analysis consists of over 40 000 patients with HF from large observational studies and randomised controlled trials, was examined. In both databases, the commonest aetiology of HF in younger adults was dilated cardiomyopathy. The ejection fraction was the lowest in younger adults. Similar to the CHARM study, mortality rates in younger adults were lower compared to older patients. However, in the MAGGIC study, by stratifying mortality into patients with preserved ejection fraction and with reduced ejection fraction, younger patients with preserved ejection fraction have a much lower mortality rate compared to patients with reduced ejection fraction. Findings from clinical trials are not always reflective of the real life clinical practice. The U.K. Clinical Practice Research Datalink (CPRD), a large and well-validated primary care database with 654 practices contributing information into the database representing approximated 8% of the U.K. population, is a rich dataset offering a unique opportunity to examine the characteristics, treatments, and outcomes of younger adults with HF in the community. In contrast to the CHARM and MAGGIC studies, younger adults aged <40 years were stratified into 20-29 and 30-39 years in the CPRD analysis. This is possible due to the larger number of younger adults with HF. Further stratifying the younger age groups demonstrated heterogeneity among younger adults with HF. In contrast to previous data showing younger adults have lower co-morbidities, the proportions of depression, chronic kidney disease, asthma, and any connective tissue disease were high among patients aged 20-29 years in the analysis from the CPRD. Surprisingly, the treatment rates for angiotensin converting enzyme (ACE) inhibitor, and aldosterone antagonist were the lowest in patients aged 20-29 years. With the exception of patients aged ≥80 years, treatment rate with beta-blocker was also the lowest in patients aged 20-29 years. With over two decades of follow up, long-term mortality rates in younger adults with HF can be determined. The mortality rates continued to decline from 1988 to 2011. Physicians managing younger adults with HF can now use this contemporary data to provide prognostic information to patients and their family. A hospital administrative database is the logical next platform to explore younger adults with HF. The Alberta Ministry of Health database links an outpatient database to a hospitalisation database providing ample data to examine the relationship between outpatient clinic visits and hospital admissions in younger adults with HF. Following a diagnosis of HF in the outpatient setting, younger adults were admitted to the hospital with decompensated HF much sooner than older patients. Younger adults also presented to emergency department more frequently following their first hospitalisation for HF. In conclusion, this thesis presented the characteristics and outcomes of younger adults with HF, and helped to extend our current understanding on this important topic. I hope the data presented here will benefit not only physicians looking after younger adults with HF, but also patients and their family.

Exploring the potential role of allostatic load biomarkers in risk assessment of patients presenting with depressive symptoms

Background: Depression is a major health problem worldwide and the majority of patients presenting with depressive symptoms are managed in primary care. Current approaches for assessing depressive symptoms in primary care are not accurate in predicting future clinical outcomes, which may potentially lead to over or under treatment. The Allostatic Load (AL) theory suggests that by measuring multi-system biomarker levels as a proxy of measuring multi-system physiological dysregulation, it is possible to identify individuals at risk of having adverse health outcomes at a prodromal stage. Allostatic Index (AI) score, calculated by applying statistical formulations to different multi-system biomarkers, have been associated with depressive symptoms. Aims and Objectives: To test the hypothesis, that a combination of allostatic load (AL) biomarkers will form a predictive algorithm in defining clinically meaningful outcomes in a population of patients presenting with depressive symptoms. The key objectives were: 1. To explore the relationship between various allostatic load biomarkers and prevalence of depressive symptoms in patients, especially in patients diagnosed with three common cardiometabolic diseases (Coronary Heart Disease (CHD), Diabetes and Stroke). 2 To explore whether allostatic load biomarkers predict clinical outcomes in patients with depressive symptoms, especially in patients with three common cardiometabolic diseases (CHD, Diabetes and Stroke). 3 To develop a predictive tool to identify individuals with depressive symptoms at highest risk of adverse clinical outcomes. Methods: Datasets used: ‘DepChron’ was a dataset of 35,537 patients with existing cardiometabolic disease collected as a part of routine clinical practice. ‘Psobid’ was a research data source containing health related information from 666 participants recruited from the general population. The clinical outcomes for 3 both datasets were studied using electronic data linkage to hospital and mortality health records, undertaken by Information Services Division, Scotland. Cross-sectional associations between allostatic load biomarkers calculated at baseline, with clinical severity of depression assessed by a symptom score, were assessed using logistic and linear regression models in both datasets. Cox’s proportional hazards survival analysis models were used to assess the relationship of allostatic load biomarkers at baseline and the risk of adverse physical health outcomes at follow-up, in patients with depressive symptoms. The possibility of interaction between depressive symptoms and allostatic load biomarkers in risk prediction of adverse clinical outcomes was studied using the analysis of variance (ANOVA) test. Finally, the value of constructing a risk scoring scale using patient demographics and allostatic load biomarkers for predicting adverse outcomes in depressed patients was investigated using clinical risk prediction modelling and Area Under Curve (AUC) statistics. Key Results: Literature Review Findings. The literature review showed that twelve blood based peripheral biomarkers were statistically significant in predicting six different clinical outcomes in participants with depressive symptoms. Outcomes related to both mental health (depressive symptoms) and physical health were statistically associated with pre-treatment levels of peripheral biomarkers; however only two studies investigated outcomes related to physical health. Cross-sectional Analysis Findings: In DepChron, dysregulation of individual allostatic biomarkers (mainly cardiometabolic) were found to have a non-linear association with increased probability of co-morbid depressive symptoms (as assessed by Hospital Anxiety and Depression Score HADS-D≥8). A composite AI score constructed using five biomarkers did not lead to any improvement in the observed strength of the association. In Psobid, BMI was found to have a significant cross-sectional association with the probability of depressive symptoms (assessed by General Health Questionnaire GHQ-28≥5). BMI, triglycerides, highly sensitive C - reactive 4 protein (CRP) and High Density Lipoprotein-HDL cholesterol were found to have a significant cross-sectional relationship with the continuous measure of GHQ-28. A composite AI score constructed using 12 biomarkers did not show a significant association with depressive symptoms among Psobid participants. Longitudinal Analysis Findings: In DepChron, three clinical outcomes were studied over four years: all-cause death, all-cause hospital admissions and composite major adverse cardiovascular outcome-MACE (cardiovascular death or admission due to MI/stroke/HF). Presence of depressive symptoms and composite AI score calculated using mainly peripheral cardiometabolic biomarkers was found to have a significant association with all three clinical outcomes over the following four years in DepChron patients. There was no evidence of an interaction between AI score and presence of depressive symptoms in risk prediction of any of the three clinical outcomes. There was a statistically significant interaction noted between SBP and depressive symptoms in risk prediction of major adverse cardiovascular outcome, and also between HbA1c and depressive symptoms in risk prediction of all-cause mortality for patients with diabetes. In Psobid, depressive symptoms (assessed by GHQ-28≥5) did not have a statistically significant association with any of the four outcomes under study at seven years: all cause death, all cause hospital admission, MACE and incidence of new cancer. A composite AI score at baseline had a significant association with the risk of MACE at seven years, after adjusting for confounders. A continuous measure of IL-6 observed at baseline had a significant association with the risk of three clinical outcomes- all-cause mortality, all-cause hospital admissions and major adverse cardiovascular event. Raised total cholesterol at baseline was associated with lower risk of all-cause death at seven years while raised waist hip ratio- WHR at baseline was associated with higher risk of MACE at seven years among Psobid participants. There was no significant interaction between depressive symptoms and peripheral biomarkers (individual or combined) in risk prediction of any of the four clinical outcomes under consideration. Risk Scoring System Development: In the DepChron cohort, a scoring system was constructed based on eight baseline demographic and clinical variables to predict the risk of MACE over four years. The AUC value for the risk scoring system was modest at 56.7% (95% CI 55.6 to 57.5%). In Psobid, it was not possible to perform this analysis due to the low event rate observed for the clinical outcomes. Conclusion: Individual peripheral biomarkers were found to have a cross-sectional association with depressive symptoms both in patients with cardiometabolic disease and middle-aged participants recruited from the general population. AI score calculated with different statistical formulations was of no greater benefit in predicting concurrent depressive symptoms or clinical outcomes at follow-up, over and above its individual constituent biomarkers, in either patient cohort. SBP had a significant interaction with depressive symptoms in predicting cardiovascular events in patients with cardiometabolic disease; HbA1c had a significant interaction with depressive symptoms in predicting all-cause mortality in patients with diabetes. Peripheral biomarkers may have a role in predicting clinical outcomes in patients with depressive symptoms, especially for those with existing cardiometabolic disease, and this merits further investigation.

Administrative justice and the control of bureaucratic decision-making: A study investigating how decision-makers in local authority education departments respond to the work of redress mechanisms

This socio-legal thesis has explored the factors responsible for explaining whether and how redress mechanisms control bureaucratic decision-making. The research considered the three principal institutions of administrative justice: courts, tribunals, and ombudsman schemes. The field setting was the local authority education area and the thesis examined bureaucratic decision-making about admissions to school, home-to-school transport, and Special Educational Needs (SEN). The thesis adopted a qualitative approach, using interviews and documentary research, within a multiple embedded case study design. The intellectual foundations of the research were inter-disciplinary, cutting across law, socio-legal studies, public administration, organization studies, and social policy. The thesis drew on these scholarly fields to explore the nature of bureaucratic decision-making, the extent to which it can be controlled and the way that learning occurs in bureaucracies and, finally, the extent to which redress mechanisms might exercise control. The concept of control was studied across all its dimensions – in relation both to ex post control in specific cases and the more challenging notion of ex ante or structuring control. The aim of the thesis was not to measure the prevalence of bureaucratic control by redress mechanisms, but to understand the factors that might explain its presence or absence in a particular area. The findings of the research have allowed for a number of analytical refinements and extensions to be made to existing theoretical and empirical understandings. 14 factors, along with 87 supporting propositions, have been set out with the aim of making empirically derived suggestions which can be followed up in future research. In terms of the thesis’ contribution to existing knowledge, its comparative focus and its emphasis on the broad notion of control offered the potential for new insights to be developed. Overall, the thesis claims to have made three contributions to the conceptual framework for understanding the exercise of control by redress mechanisms: it emphasizes the importance of ‘feedback’ in relation to the nature of the cases referred to redress mechanisms; it calls attention to the structure of bureaucratic decision-making as well as its normative character; and it discusses how the operational modes of redress mechanisms relate to their control functions.