Data methods in optometry. Part 6: fitting a regression line to data

1. Fitting a linear regression to data provides much more information about the relationship between two variables than a simple correlation test. A goodness of fit test of the line should always be carried out. Hence, r squared estimates the strength of the relationship between Y and X, ANOVA whether a statistically significant line is present, and the ‘t’ test whether the slope of the line is significantly different from zero. 2. Always check whether the data collected fit the assumptions for regression analysis and, if not, whether a transformation of the Y and/or X variables is necessary. 3. If the regression line is to be used for prediction, it is important to determine whether the prediction involves an individual y value or a mean. Care should be taken if predictions are made close to the extremities of the data and are subject to considerable error if x falls beyond the range of the data. Multiple predictions require correction of the P values. 3. If several individual regression lines have been calculated from a number of similar sets of data, consider whether they should be combined to form a single regression line. 4. If the data exhibit a degree of curvature, then fitting a higher-order polynomial curve may provide a better fit than a straight line. In this case, a test of whether the data depart significantly from a linear regression should be carried out.

Adherence to antiepileptic medicines in children:a multiple-methods assessment involving dried blood spot sampling

Purpose - To evaluate adherence to prescribed antiepileptic drugs (AEDs) in children with epilepsy using a combination of adherence-assessment methods. Methods - A total of 100 children with epilepsy (≤17 years old) were recruited. Medication adherence was determined via parental and child self-reporting (≥9 years old), medication refill data from general practitioner (GP) prescribing records, and via AED concentrations in dried blood spot (DBS) samples obtained from children at the clinic and via self- or parental-led sampling in children's own homes. The latter were assessed using population pharmacokinetic modeling. Patients were deemed nonadherent if any of these measures were indicative of nonadherence with the prescribed treatment. In addition, beliefs about medicines, parental confidence in seizure management, and the presence of depressed mood in parents were evaluated to examine their association with nonadherence in the participating children. Key Findings - The overall rate of nonadherence in children with epilepsy was 33%. Logistic regression analysis indicated that children with generalized epilepsy (vs. focal epilepsy) were more likely (odds ratio [OR] 4.7, 95% confidence interval [CI] 1.37–15.81) to be classified as nonadherent as were children whose parents have depressed mood (OR 3.6, 95% CI 1.16–11.41). Significance - This is the first study to apply the novel methodology of determining adherence via AED concentrations in clinic and home DBS samples. The present findings show that the latter, with further development, could be a useful approach to adherence assessment when combined with other measures including parent and child self-reporting. Seizure type and parental depressed mood were strongly predictive of nonadherence.

Data Assimilation Technique For Flood Monitoring and Prediction

This paper focuses on the development of methods and cascade of models for flood monitoring and forecasting and its implementation in Grid environment. The processing of satellite data for flood extent mapping is done using neural networks. For flood forecasting we use cascade of models: regional numerical weather prediction (NWP) model, hydrological model and hydraulic model. Implementation of developed methods and models in the Grid infrastructure and related projects are discussed.

Serum Adiponectin and Ghrelin, Metabolic Syndrome and Diabetes Status in Cuban Americans

Purpose: Metabolic syndrome (MetS) is associated with the development of cardiovascular disease (CVD) and type 2 diabetes. Decreases in circulating adiponectin and ghrelin have been associated with MetS. Our primary aim was to evaluate the relationship of MetS with adiponectin and ghrelin for Cuban Americans with and without type 2 diabetes. Methods: Cross-sectional study of 367 adults, self identified as Cuban extraction and randomly recruited from a mailing list of Broward and Miami-Dade counties. Fasted whole blood for adiponectin (ADPN) was collected using K3EDTA tubes and measured by ELISA. Ghrelin was assayed with fasted blood plasma by Enzyme Immunometric Assay. MetS and 10-year risk for coronary heart disease (CHD) were determined using the ATP III criteria. Results: Adiponectin (F=51.8, R2 =0.21 p<0.001) and ghrelin (F=12.77, R 2 =0.06, p<0.001) differed by diabetes status (ANOVA) not age and gender. In stepwise linear regression models triglyceride levels ≥ 150 mg/dL negatively corresponded (coefficient = -0.23) with ghrelin levels for persons without diabetes (F=7.45, R2 =0.053, p=0.007); abdominal obesity and fasting plasma glucose predicted high sensitivity C-reactive protein (hs-CRP) for persons with and without diabetes (F=16.3, R2 = 0.144, p <0.001). Conclusion: Low ghrelin levels were associated with MetS regardless of diabetes status. High adiponectin levels were related to a low probability for those without diabetes only. There was a positive association of hs-CRP with BMI, MetS and number of MetS components.

ASSOCIATION OF SERUM VITAMIN D AND KEY CO-NUTRIENTS IN RELATION TO HYPERTENSION: A CROSS-SECTIONAL STUDY BASED ON NHANES DATA

Observational studies demonstrate strong associations between deficient serum vitamin D (25(OH)D) levels and cardiovascular disease. To further examine the association between vitamin D and hypertension (HTN), data from the 2003-2006 National Health and Nutrition Examination Survey were analyzed to assess whether the association between vitamin D and HTN varies by sufficiency of key co-nutrients necessary for metabolic vitamin D reactions to occur. Logistic regression results demonstrate independent effect modification by calcium, magnesium, and vitamin A on the association between vitamin D and HTN. Among non-pregnant adults with adequate renal function, those with low levels of calcium, magnesium, and vitamin D levels had 1.75 times the odds of HTN compared to those with sufficient vitamin D levels (p = <0.0001). Additionally, participants with low levels of calcium, magnesium, vitamin A, and vitamin D had 5.43 times the odds of HTN compared to those with vitamin D sufficiency (p = 0.0103).

Identifying health inequalities in individuals with major mental illness (MMI) using routine data

Abstract and Summary of Thesis: Background: Individuals with Major Mental Illness (such as schizophrenia and bipolar disorder) experience increased rates of physical health comorbidity compared to the general population. They also experience inequalities in access to certain aspects of healthcare. This ultimately leads to premature mortality. Studies detailing patterns of physical health comorbidity are limited by their definitions of comorbidity, single disease approach to comorbidity and by the study of heterogeneous groups. To date the investigation of possible sources of healthcare inequalities experienced by individuals with Major Mental Illness (MMI) is relatively limited. Moreover studies detailing the extent of premature mortality experienced by individuals with MMI vary both in terms of the measure of premature mortality reported and age of the cohort investigated, limiting their generalisability to the wider population. Therefore local and national data can be used to describe patterns of physical health comorbidity, investigate possible reasons for health inequalities and describe mortality rates. These findings will extend existing work in this area. Aims and Objectives: To review the relevant literature regarding: patterns of physical health comorbidity, evidence for inequalities in physical healthcare and evidence for premature mortality for individuals with MMI. To examine the rates of physical health comorbidity in a large primary care database and to assess for evidence for inequalities in access to healthcare using both routine primary care prescribing data and incentivised national Quality and Outcome Framework (QOF) data. Finally to examine the rates of premature mortality in a local context with a particular focus on cause of death across the lifespan and effect of International Classification of Disease Version 10 (ICD 10) diagnosis and socioeconomic status on rates and cause of death. Methods: A narrative review of the literature surrounding patterns of physical health comorbidity, the evidence for inequalities in physical healthcare and premature mortality in MMI was undertaken. Rates of physical health comorbidity and multimorbidity in schizophrenia and bipolar disorder were examined using a large primary care dataset (Scottish Programme for Improving Clinical Effectiveness in Primary Care (SPICE)). Possible inequalities in access to healthcare were investigated by comparing patterns of prescribing in individuals with MMI and comorbid physical health conditions with prescribing rates in individuals with physical health conditions without MMI using SPICE data. Potential inequalities in access to health promotion advice (in the form of smoking cessation) and prescribing of Nicotine Replacement Therapy (NRT) were also investigated using SPICE data. Possible inequalities in access to incentivised primary healthcare were investigated using National Quality and Outcome Framework (QOF) data. Finally a pre-existing case register (Glasgow Psychosis Clinical Information System (PsyCIS)) was linked to Scottish Mortality data (available from the Scottish Government Website) to investigate rates and primary cause of death in individuals with MMI. Rate and primary cause of death were compared to the local population and impact of age, socioeconomic status and ICD 10 diagnosis (schizophrenia vs. bipolar disorder) were investigated. Results: Analysis of the SPICE data found that sixteen out of the thirty two common physical comorbidities assessed, occurred significantly more frequently in individuals with schizophrenia. In individuals with bipolar disorder fourteen occurred more frequently. The most prevalent chronic physical health conditions in individuals with schizophrenia and bipolar disorder were: viral hepatitis (Odds Ratios (OR) 3.99 95% Confidence Interval (CI) 2.82-5.64 and OR 5.90 95% CI 3.16-11.03 respectively), constipation (OR 3.24 95% CI 3.01-3.49 and OR 2.84 95% CI 2.47-3.26 respectively) and Parkinson’s disease (OR 3.07 95% CI 2.43-3.89 and OR 2.52 95% CI 1.60-3.97 respectively). Both groups had significantly increased rates of multimorbidity compared to controls: in the schizophrenia group OR for two comorbidities was 1.37 95% CI 1.29-1.45 and in the bipolar disorder group OR was 1.34 95% CI 1.20-1.49. In the studies investigating inequalities in access to healthcare there was evidence of: under-recording of cardiovascular-related conditions for example in individuals with schizophrenia: OR for Atrial Fibrillation (AF) was 0.62 95% CI 0.52 - 0.73, for hypertension 0.71 95% CI 0.67 - 0.76, for Coronary Heart Disease (CHD) 0.76 95% CI 0.69 - 0.83 and for peripheral vascular disease (PVD) 0.83 95% CI 0.72 - 0.97. Similarly in individuals with bipolar disorder OR for AF was 0.56 95% CI 0.41-0.78, for hypertension 0.69 95% CI 0.62 - 0.77 and for CHD 0.77 95% CI 0.66 - 0.91. There was also evidence of less intensive prescribing for individuals with schizophrenia and bipolar disorder who had comorbid hypertension and CHD compared to individuals with hypertension and CHD who did not have schizophrenia or bipolar disorder. Rate of prescribing of statins for individuals with schizophrenia and CHD occurred significantly less frequently than in individuals with CHD without MMI (OR 0.67 95% CI 0.56-0.80). Rates of prescribing of 2 or more anti-hypertensives were lower in individuals with CHD and schizophrenia and CHD and bipolar disorder compared to individuals with CHD without MMI (OR 0.66 95% CI 0.56-0.78 and OR 0.55 95% CI 0.46-0.67, respectively). Smoking was more common in individuals with MMI compared to individuals without MMI (OR 2.53 95% CI 2.44-2.63) and was particularly increased in men (OR 2.83 95% CI 2.68-2.98). Rates of ex-smoking and non-smoking were lower in individuals with MMI (OR 0.79 95% CI 0.75-0.83 and OR 0.50 95% CI 0.48-0.52 respectively). However recorded rates of smoking cessation advice in smokers with MMI were significantly lower than the recorded rates of smoking cessation advice in smokers with diabetes (88.7% vs. 98.0%, p<0.001), smokers with CHD (88.9% vs. 98.7%, p<0.001) and smokers with hypertension (88.3% vs. 98.5%, p<0.001) without MMI. The odds ratio of NRT prescription was also significantly lower in smokers with MMI without diabetes compared to smokers with diabetes without MMI (OR 0.75 95% CI 0.69-0.81). Similar findings were found for smokers with MMI without CHD compared to smokers with CHD without MMI (OR 0.34 95% CI 0.31-0.38) and smokers with MMI without hypertension compared to smokers with hypertension without MMI (OR 0.71 95% CI 0.66-0.76). At a national level, payment and population achievement rates for the recording of body mass index (BMI) in MMI was significantly lower than the payment and population achievement rates for BMI recording in diabetes throughout the whole of the UK combined: payment rate 92.7% (Inter Quartile Range (IQR) 89.3-95.8 vs. 95.5% IQR 93.3-97.2, p<0.001 and population achievement rate 84.0% IQR 76.3-90.0 vs. 92.5% IQR 89.7-94.9, p<0.001 and for each country individually: for example in Scotland payment rate was 94.0% IQR 91.4-97.2 vs. 96.3% IQR 94.3-97.8, p<0.001. Exception rate was significantly higher for the recording of BMI in MMI than the exception rate for BMI recording in diabetes for the UK combined: 7.4% IQR 3.3-15.9 vs. 2.3% IQR 0.9-4.7, p<0.001 and for each country individually. For example in Scotland exception rate in MMI was 11.8% IQR 5.4-19.3 compared to 3.5% IQR 1.9-6.1 in diabetes. Similar findings were found for Blood Pressure (BP) recording: across the whole of the UK payment and population achievement rates for BP recording in MMI were also significantly reduced compared to payment and population achievement rates for the recording of BP in chronic kidney disease (CKD): payment rate: 94.1% IQR 90.9-97.1 vs.97.8% IQR 96.3-98.9 and p<0.001 and population achievement rate 87.0% IQR 81.3-91.7 vs. 97.1% IQR 95.5-98.4, p<0.001. Exception rates again were significantly higher for the recording of BP in MMI compared to CKD (6.4% IQR 3.0-13.1 vs. 0.3% IQR 0.0-1.0, p<0.001). There was also evidence of differences in rates of recording of BMI and BP in MMI across the UK. BMI and BP recording in MMI were significantly lower in Scotland compared to England (BMI:-1.5% 99% CI -2.7 to -0.3%, p<0.001 and BP: -1.8% 99% CI -2.7 to -0.9%, p<0.001). While rates of BMI and BP recording in diabetes and CKD were similar in Scotland compared to England (BMI: -0.5 99% CI -1.0 to 0.05, p=0.004 and BP: 0.02 99% CI -0.2 to 0.3, p=0.797). Data from the PsyCIS cohort showed an increase in Standardised Mortality Ratios (SMR) across the lifespan for individuals with MMI compared to the local Glasgow and wider Scottish populations (Glasgow SMR 1.8 95% CI 1.6-2.0 and Scotland SMR 2.7 95% CI 2.4-3.1). Increasing socioeconomic deprivation was associated with an increased overall rate of death in MMI (350.3 deaths/10,000 population/5 years in the least deprived quintile compared to 794.6 deaths/10,000 population/5 years in the most deprived quintile). No significant difference in rate of death for individuals with schizophrenia compared with bipolar disorder was reported (6.3% vs. 4.9%, p=0.086), but primary cause of death varied: with higher rates of suicide in individuals with bipolar disorder (22.4% vs. 11.7%, p=0.04). Discussion: Local and national datasets can be used for epidemiological study to inform local practice and complement existing national and international studies. While the strengths of this thesis include the large data sets used and therefore their likely representativeness to the wider population, some limitations largely associated with using secondary data sources are acknowledged. While this thesis has confirmed evidence of increased physical health comorbidity and multimorbidity in individuals with MMI, it is likely that these findings represent a significant under reporting and likely under recognition of physical health comorbidity in this population. This is likely due to a combination of patient, health professional and healthcare system factors and requires further investigation. Moreover, evidence of inequality in access to healthcare in terms of: physical health promotion (namely smoking cessation advice), recording of physical health indices (BMI and BP), prescribing of medications for the treatment of physical illness and prescribing of NRT has been found at a national level. While significant premature mortality in individuals with MMI within a Scottish setting has been confirmed, more work is required to further detail and investigate the impact of socioeconomic deprivation on cause and rate of death in this population. It is clear that further education and training is required for all healthcare staff to improve the recognition, diagnosis and treatment of physical health problems in this population with the aim of addressing the significant premature mortality that is seen. Conclusions: Future work lies in the challenge of designing strategies to reduce health inequalities and narrow the gap in premature mortality reported in individuals with MMI. Models of care that allow a much more integrated approach to diagnosing, monitoring and treating both the physical and mental health of individuals with MMI, particularly in areas of social and economic deprivation may be helpful. Strategies to engage this “hard to reach” population also need to be developed. While greater integration of psychiatric services with primary care and with specialist medical services is clearly vital the evidence on how best to achieve this is limited. While the National Health Service (NHS) is currently undergoing major reform, attention needs to be paid to designing better ways to improve the current disconnect between primary and secondary care. This should then help to improve physical, psychological and social outcomes for individuals with MMI.

A study of computational methods to analyze gene expression data

The recent advent of new technologies has led to huge amounts of genomic data. With these data come new opportunities to understand biological cellular processes underlying hidden regulation mechanisms and to identify disease related biomarkers for informative diagnostics. However, extracting biological insights from the immense amounts of genomic data is a challenging task. Therefore, effective and efficient computational techniques are needed to analyze and interpret genomic data. In this thesis, novel computational methods are proposed to address such challenges: a Bayesian mixture model, an extended Bayesian mixture model, and an Eigen-brain approach. The Bayesian mixture framework involves integration of the Bayesian network and the Gaussian mixture model. Based on the proposed framework and its conjunction with K-means clustering and principal component analysis (PCA), biological insights are derived such as context specific/dependent relationships and nested structures within microarray where biological replicates are encapsulated. The Bayesian mixture framework is then extended to explore posterior distributions of network space by incorporating a Markov chain Monte Carlo (MCMC) model. The extended Bayesian mixture model summarizes the sampled network structures by extracting biologically meaningful features. Finally, an Eigen-brain approach is proposed to analyze in situ hybridization data for the identification of the cell-type specific genes, which can be useful for informative blood diagnostics. Computational results with region-based clustering reveals the critical evidence for the consistency with brain anatomical structure.

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.

Estimation of whole body muscle, adipose/fat mass, validation in health and during weight loss. Development of prediction equations using MRI as reference method

Background: Body composition is affected by diseases, and affects responses to medical treatments, dosage of medicines, etc., while an abnormal body composition contributes to the causation of many chronic diseases. While we have reliable biochemical tests for certain nutritional parameters of body composition, such as iron or iodine status, and we have harnessed nuclear physics to estimate the body’s content of trace elements, the very basic quantification of body fat content and muscle mass remains highly problematic. Both body fat and muscle mass are vitally important, as they have opposing influences on chronic disease, but they have seldom been estimated as part of population health surveillance. Instead, most national surveys have merely reported BMI and waist, or sometimes the waist/hip ratio; these indices are convenient but do not have any specific biological meaning. Anthropometry offers a practical and inexpensive method for muscle and fat estimation in clinical and epidemiological settings; however, its use is imperfect due to many limitations, such as a shortage of reference data, misuse of terminology, unclear assumptions, and the absence of properly validated anthropometric equations. To date, anthropometric methods are not sensitive enough to detect muscle and fat loss. Aims: The aim of this thesis is to estimate Adipose/fat and muscle mass in health disease and during weight loss through; 1. evaluating and critiquing the literature, to identify the best-published prediction equations for adipose/fat and muscle mass estimation; 2. to derive and validate adipose tissue and muscle mass prediction equations; and 3.to evaluate the prediction equations along with anthropometric indices and the best equations retrieved from the literature in health, metabolic illness and during weight loss. Methods: a Systematic review using Cochrane Review method was used for reviewing muscle mass estimation papers that used MRI as the reference method. Fat mass estimation papers were critically reviewed. Mixed ethnic, age and body mass data that underwent whole body magnetic resonance imaging to quantify adipose tissue and muscle mass (dependent variable) and anthropometry (independent variable) were used in the derivation/validation analysis. Multiple regression and Bland-Altman plot were applied to evaluate the prediction equations. To determine how well the equations identify metabolic illness, English and Scottish health surveys were studied. Statistical analysis using multiple regression and binary logistic regression were applied to assess model fit and associations. Also, populations were divided into quintiles and relative risk was analysed. Finally, the prediction equations were evaluated by applying them to a pilot study of 10 subjects who underwent whole-body MRI, anthropometric measurements and muscle strength before and after weight loss to determine how well the equations identify adipose/fat mass and muscle mass change. Results: The estimation of fat mass has serious problems. Despite advances in technology and science, prediction equations for the estimation of fat mass depend on limited historical reference data and remain dependent upon assumptions that have not yet been properly validated for different population groups. Muscle mass does not have the same conceptual problems; however, its measurement is still problematic and reference data are scarce. The derivation and validation analysis in this thesis was satisfactory, compared to prediction equations in the literature they were similar or even better. Applying the prediction equations in metabolic illness and during weight loss presented an understanding on how well the equations identify metabolic illness showing significant associations with diabetes, hypertension, HbA1c and blood pressure. And moderate to high correlations with MRI-measured adipose tissue and muscle mass before and after weight loss. Conclusion: Adipose tissue mass and to an extent muscle mass can now be estimated for many purposes as population or groups means. However, these equations must not be used for assessing fatness and categorising individuals. Further exploration in different populations and health surveys would be valuable.

Studies of antihypertensive drug persistence and adherence in the Glasgow Blood Pressure Clinic

Hypertension (HTN) is a major risk factor for cardiovascular diseases including stroke, coronary heart disease (CHD), chronic renal failure, peripheral vascular disease, myocardial infarction, congestive heart failure and premature death. The prevalence of HTN in Scotland is very high and although a high proportion of the patients receive antihypertensive medications, blood pressure (BP) control is very low. Recommendations for starting a specific antihypertensive class have been debated between various guidelines over the years. Some guidelines and HTN studies have preferred to start with a combination of an antihypertensive class instead of using a single therapy, and they have found greater BP reductions with combination therapies than with monotherapy. However, it has been shown in several clinical trials that 20% to 35% of hypertensive patients could not achieve the target BP, even though they received more than three antihypertensive medications. Several factors were found to affect BP control. Adherence and persistence were considered as the factors contributing the most to uncontrolled hypertension. Other factors such as age, sex, body mass index (BMI), alcohol intake, baseline systolic BP (SBP), and the communication between physicians and patients have been shown to be associated with uncontrolled BP and resistant hypertension. Persistence, adherence and compliance are interchangeable terms and have been used in the literature to describe a patient’s behaviour with their antihypertensive drugs and prescriptions. The methods used to determine persistence and adherence, as well as the inclusion and exclusion criteria, vary between persistence and adherence studies. The prevalence of persistence and adherence have varied between these studies, and were determined to be high in some studies and low in others. The initiation of a specific antihypertensive class has frequently been associated with an increase or decrease in adherence and persistence. The tolerability and efficacy of the initial antihypertensive class have been the most common methods of explaining this association. There are also many factors that suggest a relationship with adherence and persistence. Some factors in previous studies, such as age, were frequently associated with adherence and persistence. On the other hand, relationships with certain factors have varied between the studies. The associations of age, sex, alcohol use, smoking, baseline systolic blood pressure (SBP) and diastolic BP (DBP), the presence of comorbidities, an increase in the number of pills and the relationship between patients and physicians with adherence and persistence have been the most commonly investigated factors. Most studies have defined persistence in terms of a patient still taking medication after a period of time. A medication possession ratio (MPR) ≥ 80 has been used to define compliance. Either of these terminologies, or both, have been used to estimate adherence. In this study, I used the same definition for persistence to identify patients who have continued with their initial treatment, and used persistence and MPR to define patients who adhered to their initial treatment. The aim of this study was to estimate the prevalence of persistence and adherence in Scotland. Also, factors that could have had an effect on persistence and adherence were studied. The number of antihypertensive drugs taken by patients during the study and factors that led to an increase in patients being on a combination therapy were also evaluated. The prevalence of resistance and BP control were determined by taking the BP after the last drug had been taken by persistent patients during five follow-up studies. The relationship of factors such as age, sex, BMI, alcohol use, smoking, estimated glomerular filtration rate (eGFR), and albumin levels with BP reductions for each antihypertensive class were determined. Information Services Division (ISD) data, which includes all antihypertensive drugs, were collected from pharmacies in Scotland and linked to the Glasgow Blood Pressure Clinic (GBPC) database. This database also includes demographic characteristics, BP readings and clinical results for all patients attending the GBPC. The case notes for patients who attended the GBPC were reviewed and all new antihypertensive drugs that were prescribed between visits, BP before and after taking drugs, and any changes in the hypertensive drugs were recorded. A total of 4,232 hypertensive patients were included in the first study. The first study showed that angiotensin converting enzyme inhibitor (ACEI) and beta-blockers (BB) were the most prescribed antihypertensive classes between 2004 and 2013. Calcium channel blockers (CCB), thiazide diuretics and angiotensin receptor blockers (ARB) followed ACEI and BB as the most prescribed drugs during the same period. The prescription trend of the antihypertensive class has changed over the years with an increase in prescriptions for ACEI and ARB and a decrease in prescriptions for BB and diuretics. I observed a difference in antihypertensive class prescriptions by age, sex, SBP and BMI. For example, CCB, thiazide diuretics and alpha-blockers were more likely to be prescribed to older patients, while ACEI, ARB or BB were more commonly prescribed for younger patients. In a second study, 4,232 and 3,149 hypertensive patients were included to investigate the prevalence of persistence in the Scottish population in 1- and 5-year studies, respectively. The prevalence of persistence in the 1-year study was 72.9%, while it was only 62.8% in the 5-year study. Those patients taking ARB and ACEI showed high rates of persistence and those taking diuretics and alpha blockers had low rates of persistence. The association of persistence with clinical characteristics was also investigated. Younger patients were more likely to totally stop their treatment before restarting their treatment with other antihypertensive drugs. Furthermore, patients who had high SBP tended to be non-persistent. In a third study, 3,085 and 1,979 patients who persisted with their treatment were included. In the first part of the study, MPR was calculated, and patients with an MPR ≥ 80 were considered as adherent. Adherence rates were 29.9% and 23.4% in the 1- and 5-year studies, respectively. Patients who initiated the study with ACEI were more likely to adhere to their treatments. However, patients who initiated the study with thiazide diuretics were less likely to adhere to their treatments. Sex, age and BMI were different between the adherence and non-adherence groups. Age was an independent factor affecting adherence rates during both the 1- and 5-year studies with older patients being more likely to be adherent. In the second part of the study, pharmacy databases were checked with patients' case notes to compare antihypertensive drugs that were collected from the pharmacy with the antihypertensive prescription given during the patient’s clinical visit. While 78.6% of the antihypertensive drugs were collected between clinical visits, 21.4% were not collected. Patients who had more days to see the doctor in the subsequent visit were more likely to not collect their prescriptions. In a fourth study, 3,085 and 1,979 persistent patients were included to calculate the number of antihypertensive classes that were added to the initial drug during the 1-year and 5-year studies, respectively. Patients who continued with treatment as a monotherapy and who needed a combination therapy were investigated during the 1- and 5-year studies. In all, 55.8% used antihypertensive drugs as a monotherapy and 44.2% used them as a combination therapy during the 1-year study. While 28.2% of patients continued with treatment without the required additional therapy, 71.8% of the patients needed additional therapy. In all, 20.8% and 46.5% of patients required three different antihypertensive classes or more during the 1-year and 5-year studies, respectively. Patients who started with ACEI, ARB and BB were more likely to continue as monotherapy and less likely to need two more antihypertensive drugs compared with those who started with alpha-blockers, non-thiazide diuretics and CCB. Older ages, high BMI levels, high SBP and high alcohol intake were independent factors that led to an increase in the probability of patients taking combination therapies. In the first part of the final study, BPs were recorded after the last drug had been taken during the 5 year study. There were 815 persistent patients who were assigned for this purpose. Of these, 39% had taken one, two or three antihypertensive classes and had controlled BP (controlled hypertension [HTN]), 29% of them took one or two antihypertensive classes and had uncontrolled BP (uncontrolled HTN), and 32% of the patients took three antihypertensive classes or more and had uncontrolled BP (resistant HTN). The initiation of an antihypertensive drug and the factors affecting BP pressure were compared between the resistant and controlled HTN groups. Patients who initiated the study with ACEI were less likely to be resistant compared with those who started with alpha blockers and non-thiazide diuretics. Older patients, and high BMI tended to result in resistant HTN. In the second part of study, BP responses for patients who initiated the study with ACEI, ARB, BB, CCB and thiazide diuretics were compared. After adjusting for risk factors, patients who initiated the study with ACEI and ARB were more respondent than those who took CCB and thiazide diuretics. In the last part of this study, the association between BP reductions and factors affecting BP were tested for each antihypertensive drug. Older patients responded better to alpha blockers. Younger patients responded better to ACEI and ARB. An increase in BMI led to a decreased reduction in patients on ACEI and diuretics (thiazide and non-thiazide). An increase in albumin levels and a decrease in eGFR led to decreases in BP reductions in patients on thiazide diuretics. An increase in eGFR decreased the BP response with ACEI. In conclusion, although a high percentage of hypertensive patients in Scotland persisted with their initial drug prescription, low adherence rates were found with these patients. Approximately half of these patients required three different antihypertensive classes during the 5 years, and 32% of them had resistant HTN. Although this study was observational in nature, the large sample size in this study represented a real HTN population, and the large pharmacy data represented a real antihypertensive population, which were collected through the support of prescription data from the GBPC database. My findings suggest that ACEI, ARB and BB are less likely to require additional therapy. However, ACEI and ARB were better tolerated than BB in that they were more likely to be persistent than BB. In addition, users of ACEI, and ARB have good BP response and low resistant HTN. Linkage patients who participated in these studies with their morbidity and mortality will provide valuable information concerning the effect of adherence on morbidity and mortality and the potential benefits of using ACEI or ARB over other drugs.

Molecular and serological detection of occult hepatitis B virus among healthy hepatitis B surface antigen-negative blood donors in Malaysia.

Background: Occult hepatitis B infections are becoming a major global threat, but the available data on its prevalence in various parts of the world are often divergent. Objective: This study aimed to detect occult hepatitis B virus in hepatitis B surface antigen-negative serum using anti-HBc as a marker of previous infection. Patient and Methods: A total of 1000 randomly selected hepatitis B surface antigen-negative sera from blood donors were tested for hepatitis B core antibody and hepatitis B surface antibody using an ELISA and nested polymerase chain reaction was done using primers specific to the surface gene (S-gene). Results: Of the 1000 samples 55 (5.5%) were found to be reactive, of which 87.3% (48/55) were positive for hepatitis B surface antibody, indicating immunity as a result of previous infection however, that does not exclude active infection with escaped mutant HBV. Nested PCR results showed the presence of hepatitis B viral DNA in all the 55 samples that were positive for core protein, which is in agreement with the hepatitis B surface antibody result. Conclusion: This study reveals the 5.5% prevalence of occult hepatitis B among Malaysian blood donors as well as the reliability of using hepatitis B core antibody in screening for occult hepatitis B infection in low endemic, low socioeconomic settings.

Postprandial serum endotoxin in healthy humans is modulated by dietary fat in a randomized, controlled, cross-over study

Background: High-fat diets may contribute to metabolic disease via postprandial changes in serum endotoxin and inflammation. It is unclear how dietary fat composition may alter these parameters. We hypothesized that a meal rich in n-3 (ω3) fatty acids would reduce endotoxemia and associated inflammation but a saturated or n-6 (ω6) fatty acid-rich meal would increase postprandial serum endotoxin concentrations and systemic inflammation in healthy adults. Methods: Healthy adults (n = 20; mean age 25 ± 3.2 S.D. years) were enrolled in this single-blind, randomized, cross-over study. Participants were randomized to treatment and reported to the laboratory, after an overnight fast, on four occasions separated by at least one week. Participants were blinded to treatment meal and consumed one of four isoenergetic meals that provided: 1) 20 % fat (control; olive oil) or 35 % fat provided from 2) n-3 (ω3) (DHA = 500 mg; fish oil); 3) n-6 (ω6) (7.4 g; grapeseed oil) or 4) saturated fat (16 g; coconut oil). Baseline and postprandial blood samples were collected. Primary outcome was defined as the effect of treatment meal on postprandial endotoxemia. Serum was analyzed for metabolites, inflammatory markers, and endotoxin. Data from all 20 participants were analyzed using repeated-measures ANCOVA. Results: Participant serum endotoxin concentration was increased during the postprandial period after the consumption of the saturated fat meal but decreased after the n-3 meal (p < 0.05). The n-6 meal did not effect a different outcome in participant postprandial serum endotoxin concentration from that of the control meal (p > 0.05). There was no treatment meal effect on participant postprandial serum biomarkers of inflammation. Postprandial serum triacylglycerols were significantly elevated following the n-6 meal compared to the n-3 meal. Non-esterified fatty acids were significantly increased after consumption of the saturated fat meal compared to other treatment meals. Conclusions: Meal fatty acid composition modulates postprandial serum endotoxin concentration in healthy adults. However, postprandial endotoxin was not associated with systemic inflammation in vivo. Trial registration: This study was retrospectively registered at clinicaltrials.gov as NCT02521779 on July 28, 2015.

Development of Novel Time-Domain Electromagnetic Methods for Offshore Groundwater Studies: A Data Application from Bat Yam, Israel

Recent marine long-offset transient electromagnetic (LOTEM) measurements yielded the offshore delineation of a fresh groundwater body beneath the seafloor in the region of Bat Yam, Israel. The LOTEM application was effective in detecting this freshwater body underneath the Mediterranean Sea and allowed an estimation of its seaward extent. However, the measured data set was insufficient to understand the hydrogeological configuration and mechanism controlling the occurrence of this fresh groundwater discovery. Especially the lateral geometry of the freshwater boundary, important for the hydrogeological modelling, could not be resolved. Without such an understanding, a rational management of this unexploited groundwater reservoir is not possible. Two new high-resolution marine time-domain electromagnetic methods are theoretically developed to derive the hydrogeological structure of the western aquifer boundary. The first is called Circular Electric Dipole (CED). It is the land-based analogous of the Vertical Electric Dipole (VED), which is commonly applied to detect resistive structures in the subsurface. Although the CED shows exceptional detectability characteristics in the step-off signal towards the sub-seafloor freshwater body, an actual application was not carried out in the extent of this study. It was found that the method suffers from an insufficient signal strength to adequately delineate the resistive aquifer under realistic noise conditions. Moreover, modelling studies demonstrated that severe signal distortions are caused by the slightest geometrical inaccuracies. As a result, a successful application of CED in Israel proved to be rather doubtful. A second method called Differential Electric Dipole (DED) is developed as an alternative to the intended CED method. Compared to the conventional marine time-domain electromagnetic system that commonly applies a horizontal electric dipole transmitter, the DED is composed of two horizontal electric dipoles in an in-line configuration that share a common central electrode. Theoretically, DED has similar detectability/resolution characteristics compared to the conventional LOTEM system. However, the superior lateral resolution towards multi-dimensional resistivity structures make an application desirable. Furthermore, the method is less susceptible towards geometrical errors making an application in Israel feasible. In the extent of this thesis, the novel marine DED method is substantiated using several one-dimensional (1D) and multi-dimensional (2D/3D) modelling studies. The main emphasis lies on the application in Israel. Preliminary resistivity models are derived from the previous marine LOTEM measurement and tested for a DED application. The DED method is effective in locating the two-dimensional resistivity structure at the western aquifer boundary. Moreover, a prediction regarding the hydrogeological boundary conditions are feasible, provided a brackish water zone exists at the head of the interface. A seafloor-based DED transmitter/receiver system is designed and built at the Institute of Geophysics and Meteorology at the University of Cologne. The first DED measurements were carried out in Israel in April 2016. The acquired data set is the first of its kind. The measured data is processed and subsequently interpreted using 1D inversion. The intended aim of interpreting both step-on and step-off signals failed, due to the insufficient data quality of the latter. Yet, the 1D inversion models of the DED step-on signals clearly detect the freshwater body for receivers located close to the Israeli coast. Additionally, a lateral resistivity contrast is observable in the 1D inversion models that allow to constrain the seaward extent of this freshwater body. A large-scale 2D modelling study followed the 1D interpretation. In total, 425 600 forward calculations are conducted to find a sub-seafloor resistivity distribution that adequately explains the measured data. The results indicate that the western aquifer boundary is located at 3600 m - 3700 m before the coast. Moreover, a brackish water zone of 3 Omega*m to 5 Omega*m with a lateral extent of less than 300 m is likely located at the head of the freshwater aquifer. Based on these results, it is predicted that the sub-seafloor freshwater body is indeed open to the sea and may be vulnerable to seawater intrusion.

Machine Learning methods for hepatocellular malignancies segmentation and MVI prediction

The aim of this thesis project is to automatically localize HCC tumors in the human liver and subsequently predict if the tumor will undergo microvascular infiltration (MVI), the initial stage of metastasis development. The input data for the work have been partially supplied by Sant'Orsola Hospital and partially downloaded from online medical databases. Two Unet models have been implemented for the automatic segmentation of the livers and the HCC malignancies within it. The segmentation models have been evaluated with the Intersection-over-Union and the Dice Coefficient metrics. The outcomes obtained for the liver automatic segmentation are quite good (IOU = 0.82; DC = 0.35); the outcomes obtained for the tumor automatic segmentation (IOU = 0.35; DC = 0.46) are, instead, affected by some limitations: it can be state that the algorithm is almost always able to detect the location of the tumor, but it tends to underestimate its dimensions. The purpose is to achieve the CT images of the HCC tumors, necessary for features extraction. The 14 Haralick features calculated from the 3D-GLCM, the 120 Radiomic features and the patients' clinical information are collected to build a dataset of 153 features. Now, the goal is to build a model able to discriminate, based on the features given, the tumors that will undergo MVI and those that will not. This task can be seen as a classification problem: each tumor needs to be classified either as “MVI positive” or “MVI negative”. Techniques for features selection are implemented to identify the most descriptive features for the problem at hand and then, a set of classification models are trained and compared. Among all, the models with the best performances (around 80-84% ± 8-15%) result to be the XGBoost Classifier, the SDG Classifier and the Logist Regression models (without penalization and with Lasso, Ridge or Elastic Net penalization).

Two Novel Mutations In The Thyroid Hormone Receptor β In Patients With Resistance To Thyroid Hormone (rth β): Clinical, Biochemical, And Molecular Data.

The syndrome of resistance to thyroid hormone (RTH β) is an inherited disorder characterized by variable tissue hyposensitivity to 3,5,30-l-triiodothyronine (T3), with persistent elevation of free-circulating T3 (FT3) and free thyroxine (FT4) levels in association with nonsuppressed serum thyrotropin (TSH). Clinical presentation is variable and the molecular analysis of THRB gene provides a short cut diagnosis. Here, we describe 2 cases in which RTH β was suspected on the basis of laboratory findings. The diagnosis was confirmed by direct THRB sequencing that revealed 2 novel mutations: the heterozygous p.Ala317Ser in subject 1 and the heterozygous p.Arg438Pro in subject 2. Both mutations were shown to be deleterious by SIFT, PolyPhen, and Align GV-GD predictive methods.