Dissertations / Theses on the topic 'HEART DISEASE PREDICTION'

Introduction There has been much discussion on personalised medicine; however use of genotype in risk prediction for coronary heart disease (CHD) has not resulted in appreciable improvements over non-genetic risk factors. The primary aim was to determine whether candidate single nucleotide polymorphisms (SNPs) identified from genome-wide association studies improved prediction of CHD over conventional risk factors (CRF). The secondary aim was to determine whether the use of apolipoproteins or lipoprotein(a) improved risk prediction of CHD. Methods Analyses used the Edinburgh Heart Disease Prevention Study (EHDPS), with 1592 men aged 30-59 and follow-up after 20 years; and the Edinburgh Artery Study (EAS), with 1592 men and women aged 54-75 and 15 years of follow-up. Candidate SNPs were identified by systematic literature reviews. CHD status was evaluated as severe (myocardial infarction or coronary revascularisation), and any (severe CHD, angina or non-specified ischaemic heart disease). Cox proportional hazards models were used to evaluate addition of candidate SNPs or lipids to models containing CRF. Results A group of genome-wide significant SNPs resulted in a non-significant improvement in C-index for severe CHD (0.038, p=0.082), and a significant improvement in C-index for any CHD (0.042, p=0.016); the associated net reclassification improvements (NRI) were 20.5% and 18.7%, respectively. Regression trees identified SNPs that were predictive of the remaining variance after adjusting for CRF; this resulted in a significant improvement in C-index for any CHD (0.031, p=0.008). The NRI were 11.0% and 9.6% for severe and any CHD, respectively. When compared with HDL cholesterol/total cholesterol, apolipoprotein AI/total cholesterol yielded a NRI of 3.3% for severe CHD. Lipoprotein(a) improved prediction of severe CHD, with a non-significant improvement in C-index (0.020, p=0.087), and NRI of 11.8%. Conclusion The results of this study indicate that a well selected group of candidate SNPs can improve risk prediction for CHD over-and-above CRF. The inclusion of lipoprotein(a), along with CRF, appeared to improve prediction of severe CHD, but not any CHD.

Thesis (MCur)--Stellenbosch University, 2015.
ENGLISH ABSTRACT: Background: Coronary artery disease is a form of cardiovascular disease (CVD) which manifests itself in three ways: angina pectoris, acute coronary syndrome and cardiac death. Thirty-three people die daily of a myocardial infarction (cardiac death) and 7.5 million deaths annually are caused by CVD (51% from strokes and 45% from coronary artery disease) worldwide. Globally, the CVD death rate is a mere 4% compared to South Africa which has a 42% death rate. It is predicted that by the year 2030 there will be 25 million deaths annually from CVD, mainly in the form of strokes and heart disease. The WHO compared the death rates of high-income countries to those of low- and middle-income countries, like South Africa, and the results show that CVD deaths are declining in high-income countries but rapidly increasing in low- and middle-income countries. Although there are several risk prediction tools in use worldwide, to predict ischemic risk, South Africa does not use any of these tools. Current practice in South Africa to diagnose acute coronary syndrome is the use of a physical examination, ECG changes and positive serum cardiac maker levels. Internationally the same practice is used to diagnose acute coronary syndrome but risk assessment tools are used additionally to this practise because of limitations of the ECG and serum cardiac markers when it comes to NSTE-ACS. Objective: The aim of this study was to systematically appraise evidence on the accuracy of acute coronary syndrome risk prediction tools in adults. Methods: An extensive literature search of studies published in English was undertaken. Electronic databases searched were Cochrane Library, MEDLINE, Embase and CINAHL. Other sources were also searched, and cross-sectional studies, cohort studies and randomised controlled trials were reviewed. All articles were screened for methodological quality by two reviewers independently with the QUADAS-2 tool which is a standardised instrument. Data was extracted using an adapted Cochrane data extraction tool. Data was entered in Review Manager 5.2 software for analysis. Sensitivity and specificity was calculated for each risk score and an SROC curve was created. This curve was used to evaluate and compare the prediction accuracy of each test. Results: A total of five studies met the inclusion criteria of this review. Two HEART studies and three GRACE studies were included. In all, 9 092 patients participated in the selected studies. Estimates of sensitivity for the HEART risks score (two studies, 3268 participants) were 0,51 (95% CI 0,46 to 0,56) and 0,68 (95% CI 0,60 to 0,75); specificity for the HEART risks score was 0,90 (95% CI 0,88 to 0,91) and 0,92 (95% CI 0,90 to 0,94). Estimates of sensitivity for the GRACE risk score (three studies, 5824 participants) were 0,03 (95% CI0,01 to 0,05); 0,20 (95% CI 0,14 to 0,29) and 0,79 (95% CI 0,58 to 0,93). The specificity was 1,00 (95% CI 0,99 to 1,00); 0,97 (95% CI 0,95 to 0,98) and 0,78 (95% CI 0,73 to 0,82). On the SROC curve analysis, there was a trend for the GRACE risk score to perform better than the HEART risk score in predicting acute coronary syndrome in adults. Conclusion: Both risk scores showed that they had value in accurately predicting the presence of acute coronary syndrome in adults. The GRACE showed a positive trend towards better prediction ability than the HEART risk score.
AFRIKAANSE OPSOMMING: Agtergrond: Koronêre bloedvatsiekte is ‘n vorm van kardiovaskulêre siekte. Koronêre hartsiekte manifesteer in drie maniere: angina pectoris, akute koronêre sindroom en hartdood. Drie-en-dertig mense sterf daagliks aan ‘n miokardiale infarksie (hartdood). Daar is 7,5 miljoen sterftes jaarliks as gevolg van kardiovaskulêre siektes (51% deur beroertes en 45% as gevolg van koronêre hartsiektes) wêreldwyd. Globaal is die sterfte syfer as gevolg van koronêre vaskulêre siekte net 4% in vergelyking met Suid Afrika, wat ‘n 42% sterfte syfer het. Dit word voorspel dat teen die jaar 2030 daar 25 miljoen sterfgevalle jaarliks sal wees, meestal toegeskryf aan kardiovaskulêre siektes. Die hoof oorsaak van sterfgevalle sal toegeskryf word aan beroertes en hart siektes. Die WHO het die sterf gevalle van hoeinkoms lande vergelyk met die van lae- en middel-inkoms lande, soos Suid Afrika, en die resultate het bewys dat sterf gevalle as gevolg van kardiovaskulêre siekte is besig om te daal in hoe-inkoms lande maar dit is besig om skerp te styg in lae- en middel-inkoms lande. Daar is verskeie risiko-voorspelling instrumente wat wêreldwyd gebruik word om isgemiese risiko te voorspel, maar Suid Afrika gebruik geen van die risiko-voorspelling instrumente nie. Huidiglik word akute koronêre sindroom gediagnoseer met die gebruik van n fisiese ondersoek, EKG verandering en positiewe serum kardiale merkers. Internationaal word die selfde gebruik maar risiko-voorspelling instrumente word aditioneel by gebruik omdat daar limitasies is met EKG en serum kardiale merkers as dit by NSTE-ACS kom. Doelwit: Die doel van hierdie sisematiese literatuuroorsig was om stelselmatig die bewyse te evalueer oor die akkuraatheid van akute koronêre sindroom risiko-voorspelling instrumente vir volwassenes. Metodes: 'n Uitgebreide literatuursoektog van studies wat in Engels gepubliseer is was onderneem. Cochrane biblioteek, MEDLINE, Embase en CINAHL databases was deursoek. Ander bronne is ook deursoek. Die tiepe studies ingesluit was deurnsee-studies, kohortstudies en verewekansigde gekontroleerde studies. Alle artikels is onafhanklik vir die metodologiese kwaliteit gekeur deur twee beoordeelaars met die gebruik van die QUADAS-2 instrument, ‘n gestandaardiseerde instrument. ‘n Aangepaste Cochrane data instrument is gebruik om data te onttrek. Data is opgeneem in Review Manager 5.2 sagteware vir ontleding. Sensitiwiteit en spesifisiteit is bereken vir elke risiko instrument en ‘n SROC kurwe is geskep. Die SROC kurwe is gebruik om die akkuraatheid van voorspelling van elke instrument te evalueer en te toets. Resultate: Twee HEART studies en drie GRACE studies is ingesluit. In total was daar 9 092 patiente wat deelgeneeem het in die gekose studies. Skattings van sensitiwiteit vir die HEART risiko instrument (twee studies, 3268 deelnemers) was 0,51 (95% CI 0,47 to 0,56) en 0,68 (95% CI 0,60 to 0,75) spesifisiteit vir die HEART risiko instrument was 0,89 (95% CI 0,88 to 0,91) en 0,92 (95% CI 0,90 to 0,94). Skattings van sensitiwiteit vir die GRACE risiko instrument (drie studies, 5824 deelnemers) was 0,28 (95% CI 0,13 to 0,53); 0,20 (95% CI 0,14 to 0,29) en 0,79 (95% CI 0,58 to 0,93). Die spesifisiteit vir die GRACE risiko instrument was 0,97 (95% CI 0,95 to 0,99); 0,97 (95% CI 0,95 to 0,98) en 0,78 (95% CI 0,73 to 0,82). Met die SROC kurwe ontleding was daar ‘n tendens vir die GRACE risiko instrument om beter te vaar as die HEART risiko instrument in die voorspelling van akute koronêre sindroom in volwassenes. Gevolgtrekking: Altwee risiko instrumente toon aan dat albei instrumente van waarde is. Albei het die vermoë om die teenwoordigheid van akute koronêre sindroom in volwassenes te voorspel. Die GRACE toon ‘n positiewe tendens teenoor beter voorspelling vermoë as die HEART risiko instrument.

È importante individuare strategie e meccanismi per sfruttare le opportunità offerte dalla digitalizzazione in ambito sanitario delle attività e dalla gestione dei Big Data per migliorare efficienza, monitoraggio, prevenzione e cura delle patologie. possibilità di applicazione della medicina di precisione, refertazione in anatomia patologica e automazione della raccolta dati. Il lavoro di tesi è incentrato sulle problematiche legate alle malattie cardio-cerebrovascolari e la loro correlazione con il territorio con cui i soggetti interagiscono. È stato realizzato un nuovo sistema di monitoraggio del territorio che possa individuare possibili legami tra la composizione del territorio, in termini di opere pubbliche e private, e lo stato di salute delle persone. Un apposito insieme di dati viene fornito al modello di modello di machine learning, basato sulle reti neurali e provvederà ad operare nell'estrazione di possibili correlazioni tra la tipologia di edifici e la percentuale di soggetti a rischio cardiovascolare.

In this study, the prediction model based on the Stacking principle is called the Stacking fusion model. Little evidence demonstrates that the Stacking fusion model possesses better prediction performance in the field of heart disease diagnosis than other classification models. Since this model belongs to the family of ensemble learning models, which has a bad interpretability, it should be used with caution in medical diagnoses. The purpose of this study is to verify whether the Stacking fusion model has better prediction performance than stand-alone machine learning models and other ensemble classifiers in the field of heart disease diagnosis, and to find ways to explain this model. This study uses experiment and quantitative analysis to evaluate the prediction performance of eight models in terms of prediction ability, algorithmic stability, false negative rate and run-time. It is proved that the Stacking fusion model with Naive Bayes classifier, XGBoost and Random forest as the first-level learners is superior to other classifiers in prediction ability. The false negative rate of this model is also outstanding. Furthermore, the Stacking fusion model is explained from the working principle of the model and the SHAP framework. The SHAP framework explains this model’s judgement of the important factors that influence heart disease and the relationship between the value of these factors and the probability of disease. Overall, two research problems in this study help reveal the prediction performance and reliability of the cardiac disease prediction model based on the Stacking principle. This study provides practical and theoretical support for hospitals to use the Stacking principle in the diagnosis of heart disease.

The American College of Sports Medicine has published formulae that are widely used to predict functional aerobic capacity for any treadmill speed and grade combination. However, it has been demonstrated that these formulae overpredict oxygen consumption (V̇O₂) for patients with coronary artery disease as well as for apparently healthy individuals. To study this, we measured V̇O₂, ventilation (V̇_E), and respiratory exchange ratio (R) responses in 21 apparently healthy subjects (AH) and 16 coronary artery diseased subjects (CAD) during a modified Balke protocol. Modification of the protocol consisted of extending the stage time from two minutes to three minutes at the higher intensities to allow a greater time for a physiological steady-state to occur. The attainment of a steady-state may lead to the reduction of or the elimination of prediction errors. No differences were observed between two and three minute VO₂ responses at maximal and submaximal exercise for either group. At peak exercise, the AH group was significantly (P≤.05) different from the CAD group when compared for heart rate (164±2.6 vs 140±4.8 bts•min⁻¹ ), V̇O₂ (33.3±1.1 vs 26.7±2.3 ml•kg⁻¹•min⁻¹), and total treadmill time (9.9±.33 vs 8.1±.54 min). At submaximal exercise, V̇O₂ responses were also significantly (p≤.05) greater for the AH group when compared to the CAD group (26.6±.95 vs 21.9±1.8 ml•kg⁻¹•min⁻¹). No significant differences were observed for RPE and blood lactate at peak exercise and V̇_E and R responses at submaximal or peak exercise between the two groups. Predicted values for peak V̇O₂ were significantly (p≤.05) higher than measured values (33.3±1.1 vs 38.8±1.1 ml•kg⁻¹•min⁻¹) and (26.7±2.3 vs 34.1±1.7 ml•kg⁻¹•min⁻¹) for the AH and CAD groups, respectively. However, no significant differences were noted between predicted and measured V̇O₂ responses at submaximal exercise for either group. Individuals classified as Type A were not significantly different from classified Type B individuals when compared for the cardio-respiratory variables measured. These data demonstrate that the ACSM prediction formulae significantly overpredict V̇O₂ for both AH and CAD subjects at maximal treadmill intensities. However, at submaximal intensities, these prediction formulae are acceptable for both groups of subjects. Furthermore, these data suggest that two minutes per stage allows sufficient time for physiological steady-state to occur at clearly submaximal intensities. Although at the higher intensities, extending the stage time beyond two minutes may be indicated.
M.S.

The purpose of this thesis was to assess the prevalence and management of established cardiovascular (CV) risk factors and the prevalence and influence of self-reported markers (number of teeth and frequency of gum bleeding) of periodontal disease (PD), a less explored CV risk factor, in patients with stable chronic coronary heart disease (CHD). We studied patients from the global STabilization of Atherosclerotic plaque By Initiation of darapLadIb TherapY (STABILITY) trial (n=15,828), in which patients with stable chronic CHD were randomized to either darapladib or placebo. Our studies were performed using descriptive statistics and multivariable linear, logistic and Cox regression models. The use of secondary preventive medications was generally high across the whole study population. Despite this, CV risk factors were highly prevalent, including obesity, hypertension and hypercholesterolemia. Achievement of guideline-recommended treatment targets was lacking and little improvement was seen throughout the study duration. Approximately 40% of patients reported having <15 remaining teeth and 25% reported gum bleeding. More tooth loss was associated with a greater CV risk factor burden after adjustment, while the associations for gum bleeding were less evident. After multivariable adjustment for CV risk factors and socioeconomic status, more tooth loss was associated with an increased risk of major adverse CV events (a composite of CV death, myocardial infarction and stroke), CV mortality, all-cause mortality and fatal or non-fatal stroke. We found associations between a higher degree of tooth loss and elevated levels of several prognostic biomarkers known to reflect various pathophysiological mechanisms involved in CV morbidity and mortality. Most biomarkers had little attenuating effect on the relationship between tooth loss and outcomes in a multivariable model. In conclusion, we found an inadequate CV risk factor control despite a high use of evidence-based pharmacological therapies, likely to explain some of the excess risk in CHD patients. Further, we demonstrated a high prevalence of PD markers, tooth loss in particular, that were associated with a wide range of established CV risk factors, prognostic biomarkers and outcomes. Collectively, these findings indicate that tooth loss may be a significant risk factor among patients with stable chronic CHD.

Introduction. Computational modelling has been used widely in biological and clinical applications, but relatively less in surgical design and optimization. Magnetic resonance image (MRI)-based right ventricle (RV) models were introduced for patients with repaired Tetralogy of Fallot (rTOF) to assess ventricle cardiac function, and to identify morphological and mechanical parameters which can be used to predict and optimize post-surgery cardiac outcome. Tetralogy of Fallot is a common congenital heart defect which includes a ventricular septal defect and severe right ventricular outflow obstruction, account for the majority of cases with late onset RV failure. The current surgical approach for the patients with repaired ToF including pulmonary valve replacement/insertion (PVR) has yielded mixed results. It is of great interest to identify parameters which may be used to predict surgical cardiac function outcome after PVR. Data, Model, and Methods. Cardiac Magnetic Resonance (CMR) data from 20 healthy volunteers (11 males, mean year : 22.8) and 56 TOF patients (37 males, mean year : 25.3) were provided by Children's Hospital - Boston, Harvard Medical School from our NIH-funded project (R01 HL089269). RV wall thickness (WT), circumferential and longitudinal curvature (C-cur and L-cur), surface area (SA) and surface to volume ratio (SVR) were obtained based on CMR data for morphological analysis. 6 healthy volunteers and 16 TOF patients were chosen to construct 3D computational models for mechanical analysis. The 3D CMR-based RV/LV/Patch combination models included a) isotropic and anisotropic material properties, b) myocardial fiber orientation, c) active contraction with two zero-load geometries, and d) fluid-structure interactions. The models were used to obtain the assessment for RV mechanical conditions, which might be helpful for PVR surgical outcome prediction. All the computational models were built and solved in a commercial finite element software ADINA. Statistical methods including Linear Mixed- effort Method and Logistical regression were used in the morphological and mechanical analysis to find out potential indicators for predicting PVR outcome from the morphological and mechanical parameters. Results. In morphological analysis, statistically significant differences were found in RV SA and SVR between better-outcome patient group (BPG) and worse-outcome patient group (WPG). At begin of ejection, mean RV SA of BPG was 13.6% lower than that from WPG (241.1 cm2 v.s. 279.0 cm2, p =0.0161). Mean RV SVR of BPG was 13.1% lower than that from WPG (1.26 cm2/ml v.s. 1.45 cm2/ml, p =0.0271). Similar results were also found in RV SA and SVR at begin of filling. Furthermore, RV EF change from pre- to post-PVR were found negatively correlated with RV SA and SVR. In mechanical analysis, 22 structure-only models with one zero-load geometry (1G) were constructed to obtain stress/strain distributions. Stress-P1 from BPG was found to be closer to that from HG, compared to Stress- P1 of WPG. At the beginning of ejection, mean Stress-P1 of BPG was only 6.8% higher than that from healthy group (p =0.6889), while average Stress-P1 of WPG was 84.1% higher than that of healthy group (p =0.0418). Similar results were also found at begin of filling. The results suggested that comparing patients' RV stress values with healthy RV stress values may help identify patients with possible better outcome. The models with two zero-load geometries (2G models) and FSI models were also constructed. Their numerical results indicated that 2G models can provide end-ejection and end-filling results which were not available in 1G models, and FSI models can provide flow velocity, pressure and shear stress information which lacked in structure-only models (1G and 2G models). Conclusion. In vivo image-based 3D patient- specific computational models could lead to considerable potential gain not only in surgical design and outcome prediction, but also in understanding the mechanisms of RV failure for patients with repaired TOF.

У кваліфікаційній роботі бакалавра спроектовано комп’ютерну систему прогнозування ризиків появи серцевих захворювань. До її складу входять дві основні компоненти: підсистема збору даних життєвих показників людини та інтелектуальний модуль прогнозування ризиків появи серцевих захворювань. Підсистему збору життєвих показників людини реалізовано за допомогою мобільних сенсорів, які кріпляться до організму людини, однокристального міні-комп’ютера Raspberry PI, як центрального вузла, що виконує функції контролера при передачі даних та хмарного сховища – для зберігання та аналізу зібраної інформації. В якості сенсорів, які кріпляться до тіла людини використано: пульсометр, давач температури тіла та вимірювач артеріального тиску. Окрім цього, для врахування параметрів навколишнього середовища, у якому перебуває людина, застосовано сенсори аналізу параметрів повітря: температури, вологості, наявності шкідливих речовин та інтенсивності світла. Інтелектуальний модуль прогнозування ризиків появи серцевих захворювань реалізовано за допомогою мови програмування Python та із застосування відкритих бібліотек машинного навчання. При моделюванні використано і досліджено характеристики шести моделей бінарної класифікації, у результаті якого встановлено, що найбільш ефективною є модель на основі випадкові лісів (Random Forest), що забезпечує точність прогнозування на рівні 97,5%.
The computer system for predicting the risk of heart disease has been designed in the bachelor's thesis. It consists of two main components: a subsystem for collecting data on human vital signs and an intelligent module for predicting the risk of heart disease. The human vital signs collection subsystem is implemented using mobile sensors attached to the human body, a single-chip Raspberry PI mini-computer, as a central node that acts as a controller for data transmission and cloud storage - to store and analyze the collected information. The following sensors attached to the human body: a heart rate monitor, a body temperature sensor and a blood pressure monitor. In addition, sensors for analyzing air parameters: temperature, humidity, the presence of harmful substances and light intensity were using to take into account the parameters of the environment in which a person is. The intelligent module for predicting the risk of heart disease is implemented using the Python programming language and the use of open machine learning libraries. The simulation used and investigated the characteristics of six models of binary classification, as a result of which it was found that the most effective model is based on random forests (Random Forest), which provides forecasting accuracy of 97.5%.
ПЕРЕЛІК ОСНОВНИХ УМОВНИХ ПОЗНАЧЕНЬ, СИМВОЛІВ І СКОРОЧЕНЬ 7 ВСТУП 8 РОЗДІЛ 1 АНАЛІЗ ВИМОГ ТА ОСОБЛИВОСТЕЙ ПРОЕКТУВАННЯ КОМП’ЮТЕРНИХ СИСТЕМ МЕДИЧНОГО ПРИЗНАЧЕННЯ 9 1.1 Аналіз технічного завдання на проектування комп’ютерної системи прогнозування ризиків появи серцевих захворювань 9 1.2 Обґрунтування доцільності та особливості проектування комп’ютерної системи 17 РОЗДІЛ 2 МОДЕЛЬ ТА СТРУКТУРА КОМП’ЮТЕРНОЇ СИСТЕМИ ПРОГНОЗУВАННЯ РИЗИКІВ ПОЯВИ СЕРЦЕВИХ ЗАХВОРЮВАНЬ 22 2.1 Моделі та архітектури комп’ютерних систем у сфері охорони здоров’я 22 2.2 Фактори впливу навколишнього середовища на стан організму людини та комп’ютерна система автоматизованого їх аналізу 25 2.3 Різновиди та розвиток IoT у медичній галузі 29 2.4 Проектування архітектури комп’ютерної системи прогнозування ризиків появи серцевих захворювань 34 РОЗДІЛ 3 ПРОГРАМНА МОДЕЛЬ ІНТЕЛЕКТУАЛЬНОГО МОДУЛЯ ПРОГНОЗУВАННЯ РИЗИКІВ ВИНИКНЕННЯ СЕРЦЕВИХ ЗАХВОРЮВАНЬ 42 3.1 Аналіз відкритих джерел даних для побудови моделі прогнозування щодо виникнення серцевих захворювань 42 3.2 Препроцесинг даних 44 3.3 Виявлення залежностей між ознаками вхідного набору даних 51 3.4 Виявлення значимих ознак набору даних 56 3.5 Реалізація моделей прогнозування розвитку серцевих захворювань 59 РОЗДІЛ 4 БЕЗПЕКА ЖИТТЄДІЯЛЬНОСТІ, ОСНОВИ ОХОРОНИ ПРАЦІ 67 ВИСНОВКИ 68 СПИСОК ВИКОРИСТАНИХ ДЖЕРЕЛ 69 Додаток A. Технічне завдання

We illustrate the development of a 20-year prediction model of first major coronary or ischemic stroke event in a Northern Italian population of men and women aged 35 to 69 years at baseline. The model included age, blood lipids, systolic blood pressure, anti-hypertensive treatment, smoking habits and diabetes. The discrimination ability of the model was high as 0.736 in men and 0.801 in women. The model has been internally and externally validated using a different cohort study of subjects enrolled in Latina. Based on the external validation analysis, the risk score seems to be appropriate for long-term risk prediction in Italy and, more generally, in low-incidence populations. The clinical utility of the risk score in stratifying subjects in risk categories has been evaluated considering two strategies for the identification of “high-risk” subjects with contrasting public health goals, either to decrease the fraction of missed events or to decrease un-necessary treatment. These can be implemented by choosing threshold values for the predicted risk driven by either sensitivity or by specificity, respectively. The risk stratification based on 20-year absolute predicted risk had a higher clinical utility than any stratification based on the number of risk factors. Finally, we discussed from the statistical perspective the concept of “improvement” in risk prediction through the paradigmatic analysis of two indicators of disease heritability and social status, i.e. family history of coronary heart disease and educational level, added to the initial model. A new SAS package, Risk Estimation in Survival Analysis using SAS 9.2 [reSAS], detailed in the appendix, has been specifically developed from the author.

Includes bibliographical references
Pulmonary hypertension (PH) is defined as a rise in the pressure in the pulmonary arteries resulting from a variety of diseases including chronic infectious diseases, lung diseases and left heart diseases (LHD). It is a global health problem and accounts for a substantial portion of cardiovascular disease. PH due to LHD (PH-LHD) is credited to be the most common form of PH worldwide and is associated with adverse outcomes. Considering the suggestions of high prevalence and potential adverse outcomes of PH in sub-Saharan Africa (SSA), the investigation of the etiologies, clinical profile, correlates, and outcomes of PH-LHD in this region is a medical priority. Methods: Through a systematic review, we assessed existing evidence on the predictors of PH-LHD outcomes. Then, through two prospective multinational cohort registries, we investigated 1) the spectrum of PH in SSA; 2) the clinical profile and 6 months outcome of PH-LHD; 3) the role of electrocardiogram for diagnosing PH and 4) its prognostic role in heart failure (HF). PH was diagnosed by echocardiography in the context of clinical suspicion. Results: In high income countries, PH-LHD is almost invariably associated with increased mortality risk, but the effects on hospitalization are yet to be fully characterized. All groups of PH are found in SSA with LHD being the major cause. PH-LHD affects young people and is predominantly due to HF and rheumatic valvular heart disease. In these patients, left atrium size and tricuspid annular plan excursion are predictors of pulmonary pressures, and PH-LHD predicts short term hospitalization but not mortality. A normal electrocardiogram is very rare in patients with PH, but electrocardiogram criteria of right ventricular strain are rather rare and non-specific. Similarly, electrocardiogram abnormalities are frequent among Africans with HF, some have prognostic value for mortality risk. Conclusion: PH-LHD is the most common form of PH in SSA, with affected patients presenting with advanced disease, and it is associated with adverse outcomes. ECG abnormalities are prevalent in both PH and HF, but few of these abnormalities have prognostic value for mortality risk. Evaluating the efficacy and safety of low-cost and available drugs in reducing HF hospitalizations in PH-LHD is a key future priority. Improving early diagnosis of PH should also be encouraged.

L'objectif est de tester les associations de marqueurs inflammatoires et lipidiques avec la survenue de cardiopathies ischémiques chez la personne âgée non institutionnalisée. Les analyses sont menées dans une étude cas cohorte dans le cadre de l'étude des 3 Cités. Elle inclut 199 sujets ayant développé un premier évènement coronaire sur 4 ans de suivi et 1086 sujets sans antécédents cardiovasculaires (sous cohorte). Un premier travail suggère que la protéine C-réactive (CRP-US) est un marqueur de risque indépendant des évènements coronaires (risque relatif standardisé du log de la CRP-US=1,27 ; IC95%=1,08-1,64) mais n'améliore pas la prédiction du risque coronaire. Le second travail démontre une hétérogénéité dans l'association des lipides classiques et des apolipoprotéines avec les évènements coronaires selon la prise et la nature du traitement hypolipémiant à l'inclusion. Le troisième travail indique que les apolipoprotéines AI et B100 mais pas le non-HDL cholestérol améliorent significativement la prédiction du risque coronaire sur la base d'indice de reclassification.

The main expansion of the discovery of genetic variants associated with complex diseases has occurred during the last decade. This expansion has been accompanied, and in some sense motivated, by the desire to use this information to improve the predictive capacity of many diseases with an unidentified familial component, including coronary heart disease (CHD), with the aim of translating this genetic knowledge into clinical practice. This doctoral thesis is structured in two lines of investigation that address distinct aspects of this issue, first to evaluate the possible role of genetic variation in a candidate gene in modulating CHD risk, and second to evaluate whether genetic information can be used to improve risk assessment tools used in clinical practice. In the first research line (described in Part I), we investigate the contribution of genetic variation in one of the most widely-studied genes in cardiovascular genetics, ESR1, which encodes the Oestrogen receptor α protein. We provide a solid meta-analysis of evidence regarding the most widely-studied variant in this gene and we further explore the role of a broad range of common and uncommon variants in this gene in CHD risk. Using these approaches, we find no evidence of association between the genetic variants studied and CHD risk. However, although we can confidently accept that common genetic polymorphisms are not associated with cardiovascular disease, we cannot discard the possibility that other types of variation in this gene (for instance epigenetic variation) could modify susceptibility to cardiovascular disease, or that other elements of this pathway are associated with an increased risk of CHD. In this research I have provided a reliable answer to this long running unanswered question in cardiovascular genetics, allowing research to re-focus on other elements of this system or other pathways. In the second line, we explored the possible utility of genetic information obtained from genome-wide association studies (GWAS) in prediction of 10-year risk of CHD events by adding this information to cardiovascular risk functions. We have followed the recommendations proposed by the American Heart Association for evaluating the utility of novel biomarkers in clinical practice, and have demonstrated that although the magnitudes of the effects of these genetic variants on CHD risk are modest, there is a tendency towards improvement in the capacity of the risk functions to predict future CHD events. The translation of genetic information into clinical practice was one of the main motivations for the investment in genome-wide association studies, and my research represents one of the first efforts to explore this possibility.
L’expansió principal pel que fa al descobriment de variants genètiques associades amb malalties complexes s’ha dut a terme durant la última dècada. Aquesta expansió ha estat acompanyada, i d’alguna forma motivada, pel desig d’usar aquesta informació per millorar la capacitat de predicció d’aquelles malalties on hi és present un cert component familiar però en les que no es coneixien les variants que conferien un major risc de patir la malaltia, entre elles la cardiopatia isquèmica (CI). La present tesis doctoral està estructurada en dues línies d’investigació que avaluen el possible rol d’un gen candidat en la susceptibilitat de la CI i també avalua la millora en la capacitat de predicció d’un esdeveniment coronari de les eines usades habitualment en la pràctica clínica mitjançant la inclusió d’informació genètica. Més concretament, la primera línea d’investigació es centra en la contribució de la variació genètica en un dels gens més estudiats en relació amb CI: el gen que codifica pel receptor d’estrogens alfa (ESR1). En aquesta línea hem proveït un sòlid meta-anàlisis entre la variant més àmpliament estudiada d’aquest gen i risc coronari i també hem explorat el paper de la majoria de les variants comunes descrites en aquest gen i risc de CI. Mitjançant cap dels anàlisis hem trobat evidència d’associació entre les variants genètiques en aquest gen i el risc de CI. No obstant això, i encara que podem acceptar que les variants genètiques comunes d’aquest gen no estan associades amb esdeveniments coronaris, no podem descartar que altres tipus de variació en aquest gen (com per exemple variació epigenètica) pugui estar modificant la susceptibilitat a patir un esdeveniment coronari, ni tampoc que altres elements de la mateixa cadena de senyalització estiguin associats amb la malaltia. En la segona línea d’investigació, hem explorat el possible paper de les variants genètiques, obtingudes mitjançant estudis d’associació global del genoma (GWAS), en la millora de la capacitat de predicció a 10 anys dels esdeveniments coronaris, mitjançant la seva addició en les funcions de risc cardiovascular clàssiques. Hem seguit les recomanacions proposades per la American Heart Association per l’avaluació en la pràctica clínica de nous biomarcadors, i hem demostrat que, tot i que la magnitud de l’associació d’aquestes variants és modesta, hi ha una tendència cap a la millora de la capacitat de predicció de les funcions de risc.

The worldwide increasing number of persons affected by largely preventable diseases like diabetes demands better prevention and treatment. Insulin is required for effective utilisation of circulating nutrients. Impaired responsiveness to insulin (insulin resistance, IR) is a hallmark of type 2 diabetes and independently raises the risk of heart attack and stroke. The pathophysiology of IR is incompletely understood. High-throughput measurement of large numbers of circulating biomarkers may provide new insights beyond established risk factors. The aims of this thesis were to (i) use proteomics, metabolomics and genomics methods in large community samples to identify biomarkers of IR; (ii) assess biomarkers for risk prediction and insights into aetiology and consequences of IR; and (iii) use Mendelian randomisation analysis to assess causality. In Study I, analysis of 80 circulating proteins in 70-to-77-year-old Swedes identified cathepsin D as a biomarker for IR and highlighted a tentative causal effect of IR on raised plasma tissue plasminogen activator levels. In Study II, nontargeted fasting plasma metabolomics was used to discover 52 metabolites associated with glycaemic traits in non-diabetic 70-year-old men. Replication in independent samples of several thousand persons provided evidence for a causal effect of IR on reduced plasma oleic acid and palmitoleic acid levels. In Study III, nontargeted metabolomics in plasma samples obtained at three time points during an oral glucose challenge in 70-year-old men identified associations between a physiologic measure of IR and concentration changes in medium-chain acylcarnitines, monounsaturated fatty acids, bile acids and lysophosphatidylethanolamines. Study IV provided evidence in two large longitudinal cohorts for causal effects of type 2 diabetes and impaired insulin secretion on raised coronary artery disease risk. In conclusion, the Studies in this thesis provide new insights into the pathophysiology and adverse health consequences of IR and illustrate the value of combining traditional epidemiologic designs with recent molecular techniques and bioinformatics methods. The results provide limited evidence for the role of circulating proteins and small molecules in IR and require replication in separate studies and validation in experimental designs.

Depression is common in people with coronary heart disease (CHD) and is associated with worse physical outcomes. The nature of the causal association between CHD and depression, and the mechanism underpinning the association of depression with worse physical outcomes, remains unclear. Perseverative negative thinking may contribute to the development of depression in people with CHD. The aim of this thesis was to investigate the prospective association of perseverative negative thinking with depression, anxiety and worse physical outcomes in people with CHD, and to explore factors that may mediate this association. First, a systematic review identified 30 studies, of which the majority found an association between measures of perseverative negative thinking and subsequent depression, anxiety or emotional distress in people with long term conditions. Studies that controlled for covariates showed more mixed results, though the majority (15 / 25) still supported a significant association, with effects being small in magnitude. Findings were limited mainly to the association of rumination and/or catastrophizing with subsequent depression, and study quality was limited. Next, in an observational prospective cohort study 169 inpatients and outpatients with recent acute coronary syndrome (ACS) completed self-report assessments of rumination (Ruminative Responses Scale brooding subscale), worry (Penn State Worry Questionnaire), depression (Patient Health Questionnaire-8), anxiety (Beck Anxiety Inventory), and health-related quality of life (EuroQol-5D health-related quality of life, Seattle Angina Questionnaire) after hospitalisation, and at 2 month and 6 month follow-up. Additionally, assessments of potential mechanistic factors (social support, problem solving, instrumental behaviours and negative cognitive biases) were made. Baseline brooding was a significant independent predictor of depression at 6 months after controlling for the effects of important confounding variables, accounting for 2% of the variance. Findings suggested that the association of brooding with depression may be explained by deficits in problem solving ability. Rumination and problem solving may provide useful targets for the development of evidence-based interventions to improve depression among people with CHD, although the findings presented here fall short of proving a causal relationship. Future trials could be used to investigate the causal nature of the association of rumination and problem solving with depression in people with ACS.

INTRODUCCIÓ El pronòstic vital dels pacients amb cardiopaties congènites (CC) ha millorat significativament en els darrers anys, fet que ha focalitzat als professionals en la morbiditat associada. Estudis de neuroimatge han demostrat que els nens amb CC tenen una incidència incrementada de lesions cerebrals i retràs maduratiu que podrien originar-se durant la vida intra-uterina. Per altra banda, es coneix que fins a un 50% dels nens amb una cardiopatia congènita presentaran al llarg de la infància dèficits en alguna de les àrees del desenvolupament neurològic. Existeix evidència que relaciona l’origen de l’afectació materna i fetal en la preeclàmpsia amb l’alteració de la invasió trofoblàstica i la posterior hipòxia tissular placentària. En aquest context augmenten els factors antiangiogènics com sFlt i disminueixen els proangiogènics com PlGF. Diversos estudis relacionen les cardiopaties congènites amb complicacions pròpies de l’embaràs en un entorn d’insuficiència placentària. Es coneix que els fetus amb CC tenen una incidència de baix pes al néixer corregit per gènere i setmanes de gestació superior als fetus sans. OBJECTIUS L’objectiu d’aquesta tesis doctoral és establir la presència d’alteracions neurològiques prenatals mitjançant tècniques d’imatge i determinar la implicació de la funció placentària en el desenvolupament neurològic en nens amb diferents tipus de CC. MÈTODES Es tracta d’un estudi prospectiu multicèntric. Les dades obtingudes es van comparar entre nens sans i afectes de CC així com entre grups de cardiopatia. Per a la classificació dels subgrups es va decidir classificar els tipus de cardiopatia segons els sis diagnòstics més freqüents del tipus moderat-sever: Transposició de Grans Vasos (TGV), Tetralogia de Fallot, Hipoplasia de Cavitats Esquerres (HCE), Defectes septals (DS), Obstruccions aòrtiques (OA) i un últim grup de cardiopaties diverses (Altres). Es van separar també els casos segons una classificació funcional utilitzada prèviament en estudis del nostre grup: cardiopaties valvulars, conotruncals i obstrucció del tracte de sortida esquerre. Al grup cas, 179 mares embarassades de fetus amb CC moderades o severes. Paral·lelament es van reclutar 138 gestants control portadores de fetus sans. RESULTATS Es va registrar un augment significatiu de les complicacions de l’embaràs d’origen placentari en el conjunt de casos amb CC comparats amb els controls. Els resultats de l’estudi de les mesures cefàliques i cerebrals entre cardiopaties i controls a través de RM eren congruents amb la literatura en que la mida cefàlica dels nascuts amb CC és inferior a la dels nens sans en el conjunt de CC10. El grup de HCE tenia les biometries més petites. En sang materna, es van trobar nivells de PlGF inferiors en el grup de CC. Entre ells, els afectats per Fallot presentava el nivell més baix, en canvi, el ràtio de factors angiogènics sFlt-1/PlGF era significativament superior als casos que als controls i el grup Fallot presentava de nou el ràtio més alt. En l’estudi de correlacions, el valor de sFlt-1 i del ràtio sFlt-1/PlGF en sang materna era inversament proporcional al pes al néixer i al perímetre cefàlic. Els resultats del nostre estudi mostren que el desenvolupament neuroconductual dels nens amb CC valorat als dos anys de vida mitjançant l’escala de Bayley-III és similar a la mitjana poblacional. No hi ha diferències entre grups de cardiopaties. CONCLUSIONS Existeixen diferències en les proves d’imatge prenatals en CC comparades amb controls així com en l’embaràs amb CC s’observa un augment dels factors antiangiogènics en sang materna i una disminució dels proangiogènics. En la nostra cohort, no podem relacionar aquests canvis amb un pitjor neurodesenvolupament postnatal.
INTRODUCCIÓN El pronóstico vital de los pacientes con cardiopatía congénita (CC) ha mejorado significativamente en los últimos años, lo que ha centrado a los profesionales su morbilidad asociada. Los estudios de neuroimagen han demostrado que los niños con CC tienen una mayor incidencia de lesiones cerebrales y retraso de maduración que podrían originarse durante la vida intrauterina. Por otro lado, se sabe que hasta el 50% de los niños con cardiopatía congénita presentarán déficits a lo largo la infancia en alguna de las áreas del neurodesarrollo. Hay evidencia que relaciona el orígen de la afectación materna y fetal en la preeclampsia con una alteración de la invasión trofoblástica y una posterior hipoxia del tejido placentario. En ese contexto, aumentan los factores antiangiogénicos como el sFlt y disminuyen factores proangiogénicos como el PlGF. Otros estudios relacionan la enfermedad cardíaca congénita con complicaciones típicas del embarazo en un ambiente de insuficiencia placentaria. Como ejemplo, se sabe que los fetos con CC tienen incidencia aumentada de bajo peso al nacer, corregido por sexo y semanas de gestación, comparados con los niños sanos. OBJETIVOS El objetivo de esta tesis doctoral es establecer la presencia de alteraciones neurológicas prenatales utilizando técnicas de diagnóstico por imagen y determinar la implicación de la función placentaria en el desarrollo neurológico de los niños con CC. MÉTODOS Se trata de un estudio prospectivo multicéntrico. Los datos obtenidos se compararon entre niños sanos y afectados por CC así como entre grupos de enfermedades cardíacas. Para la clasificación en subgrupos se decidió dividir según los seis diagnósticos más frecuentes del tipo moderado-severo: Transposición de Grandes Vasos (TGV), Tetralogía Fallot, Hipoplasia de Cavidades Izquierdas (HCE), Defecto Septales (DS), Obstrucción Aórtica (OA) y un último grupo con cardiopatías diversas (Otras). Los casos también se separaron de acuerdo con una clasificación funcional utilizada previamente en estudios de nuestro grupo: cardiopatías valvulares, conotruncales y obstrucción del tracto de salida izquierdo. En el grupo caso 179 madres embarazadas de fetos con CC moderada o grave. Al mismo tiempo se reclutaron 138 gestantes portadores de fetos sanos. RESULTADOS Se registró un aumento significativo de las complicaciones del embarazo de origen placentario en el grupo caso en comparación con los controles. Los resultados del estudio de las medidas cefálicas y cerebrales entre las cardiopatías y los controles a través de la RMN fueron congruentes con la literatura mostrando que el tamaño cefálico de los nacidos con CC es menor que el de los niños sanos en el conjunto de CC. El grupo de HCE tenía las biometrías más pequeñas. En sangre materna, se encontraron niveles más bajos de PlGF en el grupo de CC. Entre ellos, los afectados por Fallot tuvieron el nivel más bajo. El valor del ratio de factores angiogénicos sFlt-1/PlGF fue significativamente mayor que en los casos en que en los controles y el grupo Fallot de nuevo tenía el ratio más elevado. En el estudio de correlaciones, el valor de sFlt-1 y la relación sFlt-1/PlGF en la sangre materna fueron inversamente proporcionales al peso al nacer y al perímetro cefálico. Los resultados de nuestro estudio muestran que el desarrollo neuroconductual de los niños con CC evaluado a los dos años de vida mediante la escala Bayley-III es similar al promedio de la población. No hay diferencias entre los grupos de enfermedades cardíacas. CONCLUSIONES Existen diferencias en las pruebas de diagnóstico por imágen prenatales en CC comparadas con fetos sanos, así como en el embarazo con CC hay un aumento de los factores antiangiogénicos en sangre materna y una disminución de la proangiogenicos. En nuestra cohorte, no podemos relacionar estos cambios.
INTRODUCTION Survival prognosis of patients affected by congenital heart disease (CHD) has significantly improved these last years and has turned focus on associated morbidity. Neuroimaging studies have shown children with CHD have an increased incidence of brain injury and maturing delay that could have its origin during prenatal life. On the other hand, it is known that up to 50% of children with congenital heart disease will present some type of neurological deficit throughout childhood. Evidence suggests an alteration of trophoblastic invasion and subsequent placental tissue hypoxia as the origin of maternal and fetal symptoms in preeclampsia. In this environenent, an increase of antiangiogenic factors such as sFlt and decrease proangiogenic factors such as PlGF is often found. Other studies have related CHD pregnancy to complications typical of pregnancy in an environment of placental failure. It is known that fetuses with CHD have a low incidence at birth corrected by gender and weeks of gestation higher than healthy fetuses. OBJECTIVES The aims of this PhD studies are to establish the presence of prenatal neurological alterations using imaging techniques and to assess the implication of placental function in neurological development in children with different types of CHD. METHODS This is a multicenter prospective study. The data obtained were compared between healthy children and CHD fetuses, as well as among groups of cardiac malformations. We decided to classify the types of heart disease according to the six most frequent diagnoses of the moderate-severe type: Transposition of Great Vessels (TGV), Tetralogy of Fallot, Hypoplastic Left Heart Syndrome (HLHS), Septal Defects (SD), Aortic Obstruction (AO) and a group with other heart diseases (Others). Cases were also separated according to a functional classification previously used in studies of our group: valvular heart disease, conotruncal malformations and left exit ventricular outflow track obstruction (LVOTO). Case group consisted in 179 pregnant women carrying fetuses with a moderate or severe CHD. 138 patients pregnant with a healthy fetus were recruited for control group. RESULTS A significant increase in placenta-related pregnancy complications was recorded in patients with CHD compared to controls. Cephalic and cerebral measures between heart disease and controls through MRI were consistent with previous literature: cephalic size of those born with CHD is lower than that of healthy children. HLHS group had the smallest biometrics once compared with others. In maternal blood, lower PlGF levels were found in the CHD group. Among them, those affected by Fallot had the lowest level. The ratio of angiogenic factors sFlt-1/PlGF was significantly higher in case group compared to controls and this time again, Fallot group had the highest ratio. Levels of sFlt-1 and sFlt-1/PlGF ratio in maternal blood were inversely proportional to the weight at birth and the cephalic perimeter. The results of our study show that the neuroconductive development in children with CHD rated at two years of life using Bayley-III test is no different to the average population. We also did not find any differences between CHD groups. CONCLUSIONS There are differences in prenatal imaging tests in CHD compared to controls as well as in an increase of antiangiogenic factors in maternal blood and a decrease in proangiogenics factors can be found in CHD pregnancies. In our study, we could not relate these changes to a worse neuro development at two years of age.
Universitat Autònoma de Barcelona. Programa de Doctorat en Pediatria, Obstetrícia i Ginecologia

BACKGROUND Cardiac surgery patients have some of the highest reported incidence and prevalence of pressure injuries (PI). A growing subset of cardiac surgery include patients with end-stage heart failure who undergo ventricular assist device (VAD) or total artificial heart (TAH) surgery. The risk of PI and their natural history of development in this population are unknown and the specific risk factors for PI development remain unexplored. OBJECTIVES To perform a systematic review of the literature to identify the incidence and risk factors of PI development in patients undergoing VAD-TAH surgery and thereby inform study design and variables in an eight-year retrospective study of all patients undergoing VAD-TAH surgery at a large academic university medical center. METHODS The preferred reporting items for systematic reviews and meta-analyses or PRISMA statement guided this systematic review. Quality of evidence was determined using the Johns Hopkins Nursing Evidence-Based Practice Rating Scale. Two reviewers independently appraised manuscripts matching the eligibility criteria for study inclusion. Four databases including PubMed, CINAHL, Web of Science, Google Scholar, and hand searches of journals based on reference lists from included studies were utilized. Initial results of this primary search revealed zero studies that met inclusion and this search methodology was confirmed by medical librarian consultation. Therefore, a follow up retrospective study was necessary to identify incidence of PI in the VAD-TAH population. However, a secondary search, dropping keywords of VAD-TAH and instead focusing on studies of on-pump cardiac surgery and mixed surgical studies where cardiac surgery patients were included, was conducted to establish variables to guide a retrospective study of all VAD-TAH surgeries between 2010-2018. The retrospective study evaluated the incidence of pressure ulcers by case, patient and incidence density for each of the respective 1000 patient days during the study period. Univariate statistics are reported by four different VAD-TAH devices. Variables significant in bivariate analysis were entered in a stepwise logistic regression model. RESULTS In the systematic review, 312 articles were identified from the databases with eight additional articles from hand searches. Following abstract review, 208 were excluded for not meeting inclusion criteria or study quality metrics. 77 articles were read in full, with 61 excluded, leaving 16 articles for inclusion. 31 risk factors were identified for PI development in on-pump cardiac surgery patients with 11 risk factors which were identified as significant in multivariate analysis for inclusion in the retrospective study.

O objetivo desta tese foi identificar e caracterizar áreas com altas taxas de mortalidade por doenças do aparelho circulatório (DAC) e seus dois principais subgrupos de causas: as doenças isquêmicas do coração (DIC) e as doenças cerebrovasculares (DCV), entre os anos de 2008 e 2012 na área de influência do complexo petroquímico do estado do Rio de Janeiro COMPERJ, por meio de métodos estatísticos e sistemas de informações geográficas (SIG). Os resultados da investigação são apresentados na forma de dois manuscritos. O primeiro objetivou descrever o perfil da distribuição espacial da mortalidade por (DAC), caracterizar e predizer territórios com maior risco de morte por esta causa, com base em classificação das unidades espaciais por indicador de qualidade urbana (IQUmod). A análise multivariada foi realizada por meio do método conhecido como árvore de decisão e regressão, baseado em algoritmo CART para a obtenção do modelo preditivo para UVLs com diferentes riscos de mortalidade por DAC. O modelo desenvolvido foi capaz de discriminar sete conjuntos de UVLs, com diferentes taxas médias de mortalidades. O subconjunto que apresenta a maior taxa média (1037/100 mil hab.) apresenta 3 UVLs com mais de 75% de seus domicílios com abastecimento de água inadequado e valor de IQUmod acima de 0.6. Conclui-se que na área de influência do COMPERJ existem áreas onde a mortalidade por DAC se apresenta com maior magnitude e que a identificação dessas áreas pode auxiliar na elaboração, diagnóstico, prevenção e planejamento de ações de saúde direcionadas aos grupos mais susceptíveis. O segundo manuscrito teve por objetivo descrever o perfil da distribuição espacial da mortalidade por DIC e DCV em relação ao contexto socioambiental segundo áreas geográficas. O modelo de regressão linear de Poisson com parâmetro de estimação via quasi-verossimilhança foi usado para verificar associação entre as variáveis. Foram identificados como fatores de risco para mortalidade por DIC e DCV a variável relativa a melhor renda e maior distância entre domicílios e unidades de saúde; a proporção de domicílios em ruas pavimentadas aparece como fator de proteção. A distribuição espacial e as associações encontradas entre os desfechos e preditores sugerem que as populações residentes em localidades mais afastadas dos centros urbanos apresentam maiores taxas de mortalidade por DIC e DCV e que isto pode estar relacionado a contextos rurais de localização das residências e a distância geográfica destas populações aos serviços de saúde. Aponta-se para a necessidade de desenvolvimento de ações que propiciem maior amplitude no atendimento em saúde, no intuito da redução de eventos cardiovasculares mórbidos incidentes naquelas populações.

A doença cardiovascular (DCV) é uma condição clínica comum entre pacientes (pcts) portadores de doença renal crônica (DRC) e é causa de eventos fatais observados peri transplante renal (TX). A melhor estratégia de avaliação cardiovascular em candidatos a transplante (CTR) ainda é controversa.Ignora-se se todos os pacientes devem ser submetidos a testes não-invasivos/invasivos ou se estes devem ser reservados aqueles com determinadas características clínicas, como população geral. O objetivo deste estudo foi comparar a estratificação de risco baseada em método nãoinvasivo de detecção de doença coronária com dois métodos de estratificação clínica de risco cardiovascular preconizados pela American Society of Transplantation (AST) e European Renal Association (ERA). A AST subdivide os pcts em : alto risco (idade maior ou igual a 50 anos e/ou diabete e/ou DCV clínica) e baixo risco (os demais). A ERA subdivide em: alto risco (DCV clínica), risco intermediário (diabéticos e/ou idade maior ou igual a 50 anos) e baixo risco (os demais). Nós estudamos 386 pcts com DRC em diálise enviados ao nosso serviço para avaliação cardiovascular antes da inclusão na lista de espera de TX. Foram estratificados quanto ao risco de eventos de acordo com os dois algoritmos acima e alterações na cintilografia de perfusão miocárdica (SPECT-MIBI) com dipiridamol e acompanhados até a morte, TX ou ocorrência de eventos. A estratificação clínica (RR:1,8 [IC95% 1,3 2,6- P<0,0001] e o SPECT-MIBI (RR:1,5 [IC95% 1,2-1,9-P=0,002] identificaram os pcts de maior risco de eventos cardiovasculares . Apenas os pcts ASTalto risco (RR1,4 [IC95%1,1-1,8-P=0,002] e ERA médio risco com SPECTMIBI alterado (RR:1,7 [IC95% 1,2-2,3-P=0,003] tiveram maior incidência de eventos. Os pcts de baixo risco pelos dois algorítmos de estratificação clínica (P=0,50) e do sistema ERA alto risco (RR:1,1 [IC95% 0,8-1,5-P=0,41], não se beneficiaram dos resultados do estudo não-invasivo. Concluímos que os estudos não-invasivos não devem ser utilizados em todos os CTR mas devem ser reservados aos pcts previamente identificados pela estratificação clínica de risco. Esses resultados permitem uma abordagem mais racional da avaliação pré- TX com melhor uso dos recursos econômicos escassos.
Cardiovascular (CV) disease is a common condition in chronic kidney disease (CKD) patients and is the leading cause of fatal events during and after renal transplantation. The best strategy for CV evaluation and coronary risk stratification in renal transplant candidates remains controversial. Moreover, there is no consensus regarding the best strategy for detection of coronary artery disease (CAD). We still do not know if all patients should be evaluated by noninvasive testing or if this approach should be restricted to individuals with clinical evidence of CAD, as in the general population. The objective of this study was to compare CV risk stratification based on nonivasive testing for CAD with two clinical stratification methods as advanced by The American Society of Transplantation (AST) and by The European Renal Association (ERA), respectively. The AST divides patients in high risk (age50 years and/or diabetes and/or CV disease) and low risk (all others).The ERA divides : high risk (CV disease), intermediate risk (age 50 years and/or diabetes), and low risk (as above). We studied 386 CKD patients treated by hemodyalisis, to CV evaluation before being admitted to the renal transplant waiting list. All patients were stratified for the risk of future major cardiovascular events (MACE) using the clinical algorithms and also by myocardial scintigraphy (SPECT-MIBI) with dipyridamol and followedup until death, transplant or MACE. Clinical algorithms (RR:1,8 [IC95% 1,3 2,6-P<0,0001] and SPECT-MIBI(RR:1,5 [IC95% 1,2-1,9-P=0,002] identified patients at increased risk of events. The combined use of clinical stratification followed by SPECT showed that the only patients that would benefit from SPECT risk stratification were those belonging the AST-high risk (RR1,4 [IC95%1,1-1,8-P=0,002] and ERA-intermediate risk groups (RR:1,7 [IC95% 1,2-2,3-P=0,003]. In all other groups :ERA-high-risk (RR:1,1[IC95% 0,8-1,5- P=0,41] and ERA and AST-low-risk (P=0,50) SPECT did not add to the probability of events defined by clinical stratification alone. We conclude that SPECT should not be applied to all renal transplant candidates but should be restricted to those considered at a category of risk as defined by clinical algorithms. These results delineate a more rational approach to risk stratification in renal transplant candidates with a better utilization of economical resources.

Introduction: Achieving optimal times of reperfusion in STEMI patients transferred for primary percutaneos coronary intervention (PCI) remains a challenge, particularly in geographically disperse regions. Our goal was to create a prediction model of STEMI diagnosis - wire crossing time and perform an internal validation. Methods: Prospective cohort study of patients admitted to the critical care unit (2007-2018) diagnosed with STEMI who required to be transferred to PCI center. An analysis was carried out to identify the predictive variables leading to a delay in STEMI diagnosis -wire crossing times. Afterwards, a prediction model was created and an internal validation of this model was performed. Results: A total of 1.049 patients were included during the study period. The delaying predictive factors were: severe Killip on admission (Killip ≥3) (OR 1,100 IC 95% (1,048-1,155) p=0,0001), coronary artery bypass grafting (OR 1,241 IC 95% (1,119-1,377) p <0,001), out-of-hospital cardiac arrests (OR 1,150 IC 95% (1,078-1,228) p <0,001), lateral ischemia (OR 1,065 IC 95% (1,030-1,102) p=0,0002), first medical contact in a non-PCI center (OR 1,225 IC 95% (1,174-1,279) p<0,001), primary healthcare center (OR 1,183 IC 95% (1,131-1,238) p<0,001), home care (OR 1,077 IC 95% (1,026-1,131) p=0,003) and distance (Km) from PCI center; < 40 Km (OR 1,034 IC 95% (1,026-1,043) p<0,001) and >40 Km (OR 1.079 IC 95% (1,066-1,092) . Internal validation showed a square R of 0.355 and a correlation of 0.6. The area under the curve to predict time >120 minutes was 0.785. Conclusions: STEMI diagnosis-wire crossing time predictor variables were identified and included in a prediction model. Internal validation was success. This tool could be useful in clinical practice when taking relevant decisions in STEMI patients
Introducció: És difícil aconseguir temps òptims d´angioplàstia primària (AP) en un percentatge de pacients amb IAMEST procedents del medi extra-hospitalari o d'hospitals sense programa d'AP. Disposar d'una eina de predicció del temps d'AP desde el diagnòstic podria ser útil. El nostre objectiu va ser crear un model de predicció del temps d'ECG diagnòstic-pas de guia i realitzar una validació d'aquest model. Mètode Estudi de cohorts prospectiu de pacients ingressats a la unitat de cures crítiques cardiològiques (2007-2018) amb IAMEST, tractats amb AP i que van requerir ser traslladats a un centre amb disponibilitat d'hemodinàmica. Es va realitzar un anàlisi per identificar les variables predictores de demora de l'ECG diagnòstic- pas de guia, es va crear un model de predicció d'aquest temps i una validació interna del model. Resultats Es van incloure un total de 1.049 pacients en l'estudi. Les variables incloses en el model de predicció van ser la insuficiència cardíaca greu a l'ingrés (Killip ≥3) (OR 1,100 IC 95% (1,048-1,155) p = 0,0001), la cirurgia cardíaca prèvia de bypass (OR 1,241 IC 95% (1,119-1,377) p <0,001), la mort sobtada extrahospitalària (OR 1,150 IC 95% (1,078-1,228) p <0,001), la localització lateral de l'IAM (OR 1,065 IC 95% (1,030-1,102) p = 0, 0002), el primer contacte amb hospital sense disponibilitat d'hemodinàmica (OR 1,225 IC 95% (1,174-1,279) p <0,001), centre d'atenció primària (OR 1,183 IC 95% (1,131-1,238) p <0,001), domicili ( OR 1,077 IC 95% (1,026-1,131) p = 0,003) i finalment la distància al centre amb hemodinàmica; <40 Km (OR 1,034 IC 95% (1,026-1,043) p <0,001) i> 40 km (OR 1.079 IC 95% (1,066-1,092) p <0,001). La validació interna va mostrar un R quadrat de 0,355 i una correlació de 0,6. L'àrea sota la corba per a temps superiors a 120 minuts va ser de 0,785. Conclusions Identificades les variables predictores del temps ECG diagnòstic-pas de guia es va crear un model de predicció, amb una validació interna satisfactòria, que pot ser útil en la presa de decisions clíniques en el IAMEST

碩士
國立高雄應用科技大學
電子工程系
106
Ventricular septal defect (VSD) is the most common congenital heart disease in newborns. It has become an important topic for researchers and doctors to study through early detection and diagnosis for the treatment. In this thesis, 140 clinical reports of cardiac ultrasound are collected and adopted from the hospital. Through professional interpretation, the doctors filtered and selected 29 valid samples related to VSD with the VSD disease presented by the heart sound signal. The VSD feature is generated and compared the characteristics of the VSD signal with a normal physiological signal and using a supervised learning algorithm for classification and prediction. Firstly, the processing of the heart sound signal extracts and divides the periodic signal through the standardized R-R interval. Secondly, the process uses the Fast Fourier Transform (FFT) to obtain the frequency domain of the heart sound signal. Finally, the heart sound signal is performed the cross-correlation quality verification procedure. The automatically diagnosed the disease for this thesis can provide and assist doctors reducing the time and accuracy of congenital heart disease diagnosis. The related algorithms for this thesis are compared with Support Vector Machine (SVM), Bayes (NB), Decision Tree (DT) and k-Nearest Neighbor (kNN), etc. The resulted data are shown SVM, it can be to provide a good weapon to diagnose heart disease accuracy 96.43% and F1 score 0.964, respectively.

碩士
國立臺北護理健康大學
運動保健研究所
102
The purpose of the study was to understand the prevalence of heart failure and related factors of heart failure among patients with chronic obstructive pulmonary disease. Based on retrospective review of the medical records for patients who diagnosed chronic obstructive pulmonary disease were enrolled in this study. There were 258 patients of COPD as the sample of this study (mean age 75.96±11.18 years old) and divided into heart failure group (n=128) and the health group (n=130). First, the blood levels of CRP and other risk factors (gender, age and smoking) were analyzed. Second, the subjects were divided by age into 4 groups including the below 65 y/o, 66-75 y/o, 76-85 y/o and above 85 y/o to compare the difference with the other risk factors. The results showed that：(1) It was found that CRP, smoking, and age is the top three risk factors for heart failure. (2) The 76-85 y/o of heart failure group had risk factors were significantly different than other age groups. (3) CRP, smoking, age, and gender were found to be predictors for heart failure. This study suggested patient of COPD should quit smoke to reduce the morbidity of heart failure.

This thesis examines the hypothesis that coronary artery motion analysis is predictive of the location of clinical coronary artery events. It includes a preamble that describes a clinical scenario highlighting this unmet clinical need and describes in detail the components of this thesis. The thesis includes an overarching statement and a series of published and unpublished manuscripts. The published manuscripts describe in detail the findings that: 1. Qualitative coronary artery motion analysis predicts the location of culprit lesions responsible for ST segment elevation myocardial infarctions (published prior to commencement of this doctoral degree). 2. The pattern of qualitative coronary artery motion in patients with subsequent ST segment elevation myocardial infarction is not different to the pattern in angiographically normal coronary arteries. 3. Two-dimensional quantitative coronary artery motion analysis predicts the location of future non-ST segment elevation myocardial infarctions. 4. Quantitative coronary artery motion analysis using multislice computed tomography correlates with the location of coronary artery disease. The unpublished manuscripts describe in detail (that): 5. Two-dimensional quantitative coronary artery motion analysis predicts the location of future ST segment elevation myocardial infarctions. 6. A four-dimensional quantitative method for coronary artery motion analysis and its relationship to both the location of a. stenotic disease, and b. lesion location in ST segment elevation myocardial infarctions. An important conclusion of this thesis is that coronary artery motion analysis has utility for the prediction of clinical coronary artery events, although further development and refinement of analysis methodology is required prior to its clinical application.

no
Dear Editor In undertaking studies of palliative care in heart failure and chronic obstructive pulmonary disease (COPD) in the UK, we identified procedural, conceptual and ethical challenges that may arise from one feature of The End of Life Care Strategy for England.1 The strategy presents the question, ‘Would I be surprised if the person in front of me was to die in the next six months or one year?’ as a prompt to initiate discussion of endof-life care needs and preferences (paragraph 3.23). We believe this question is inappropriate in heart failure and COPD and its use will inhibit the initiation of a palliative care approach with these patients.

Thesis submitted to the Faculty of Arts, University of the Witwatersrand, for the degree of Doctor of Philosophy Johannesburg 1995
The large percentage of deaths attributed to recurrent Coronary Heart Disease (CHD) has generated a search for behavioural and psychological factors which mitigate the consequences of CHD. An aim of the present thesis is to extend this search by identifying factors which predict prognosis fer recovery from CHD. Two key factors seen to influence prognosis are aerobic exercise and Type A behaviour. Extant research into the role of exercise has been hindered by methodological weaknesses. As a consequence, the precise means by which exercise influences CHD patients' psychological and physiological strain remains unclear. Similarly, the Type A literature has been flawed by the inaccurate conceptualisation and measurement of Type A behaviour as a global, and 110t a multidimensional, construct. Research which has examined the multidimensional nature of Type A behaviour has been restricted to low risk samples. Thus, a further aim. of the present research is to examine ; prognostic role of exercise and Type A components within the context of cardiac rehabilitation. In achieving this aim, three studies are conducted. [Abbreviated Abstract. Open document to view full version]
MT2017

Thesis (Ph.D.)--York University, 2005. Graduate Programme in Psychology.
Typescript. Includes bibliographical references (leaves 202-245). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:NR11594

Submitted in fulfillment of the requirements for the Degree of Masters in Technology: Cardiology, Durban University of Technology, 2012.
Cardiomyopathies and their resultant heart failure (HF) remain a major cause of cardiovascular morbidity and mortality (Wood and Picard, 2004). Idiopathic dilated cardiomyopathy (IDCMO) is a primary myocardial disease of unknown cause, characterized by left ventricular (LV) or biventricular dilatation and impaired myocardial contractility. Dilated cardiomyopathy (DCMO), along with rheumatic heart disease and hypertension (HPT), is one of the leading causes of HF in Africa. In fact, in an epidemiology study of 884 patients in Soweto, IDCMO was the second major cause of HF. Thirty five percent of patients in the study, with HF, had IDCMO (Sliwa, Damasceno, Mayosi, 2005). Methodology: Patients referred to the cardiomyopathy (CMO) clinic at Chris Hani Baragwanath hospital, situated in the echocardiographic lab, were recruited, provided they satisfied the exclusion and inclusion criteria and were enrolled after obtaining voluntary informed consent. From May 2009 to September 2010, 70 patients with IDCMO were recruited for this trial. Patients with DCMO were identified by means of echocardiographic criteria which included a left ventricular ejection fraction (LVEF) of less than 45% and an end diastolic dimension (EDD) of greater than of 52 mm (2D in long parasternal axis). Results: In the present study the prevalence of left ventricular (LV) thrombus in patients with IDCMO was 18.6%. When using Univariate logistic regression, the only independent predictors of LV thrombus formation was LVEF and age. However, when multivariate logistic regression analysis was applied to the data, the only predictor with a significant association was age. The reason for this is not clear. It is postulated that perhaps younger patients have differences in the pathophysiology of their disease such as a greater smoldering inflammatory component which may therefore predispose them to thrombus formation. For example the presence of IL-6 may be important in the formation of LV clot in cases of LV dysfunction (Sosin, Bhatia, Davis, Lip, 2003). The association between LVEF and LV thrombus was borderline significant. Conclusion: The prevalence of LV thrombus formation in this cohort of patients with IDCMO was 18.6%. Echocardiographic parameters alone cannot predict which patients are more likely to develop thrombus formation.
National Research Foundation

碩士
慈濟大學
醫學研究所
93
During the past 30 years, there has been a shift in the spectrum of leading causes of deaths from infectious disease to chronic disease, which resulted from the economic, culture and life style changes in Taiwan. Many of the chronic diseases are closely related to atherosclerosis. Cardiac death, most of that related to coronary atherosclerosis, was still the third of the ten leading causes of death in Taiwan in 2003. Therefore, atherosclerotic prevention is important in public health. Reviewed literatures revealed that the role of uric acid in coronary artery disease (CAD) was unclear. Framingham study reported that uric acid was not a significant factor to concern the formation and prognosis of CAD. British and Japanese teams also supported these results between 1997 and 2001. National Health and Nutrition Examination Survey (NHANES) study, however, found the uric acid significantly correlated with CAD in women, but not in men. Moreover, Germany and Italian teams had sequentially concluded that there was a significant correlation in men. They also started to study these relations in a specific age and race. In Taiwan, the cohort study for CAD has been conducted in 4 townships: Jin-Shan, San-Zhi, Zhu-Dong and Pu-Zi. They focused on the primary prevention using lipid profile, obesity, insulin level, diabetes mellitus and family history as the risk factors. Moreover, the follow-up years were shorter than those of overseas studies. As we know, a longitudinal study on CAD patients was not found in Taiwan yet. In this study, we used survival analysis to predict if uric acid as a factor to affect the survival time of CAD patients. We reviewed the clinical data of 1308 CAD patients, who were followed up by “Coronary artery disease, A secondary prevention program”, in Tzu-Chi medical center between January 1997 and December 2003. The clinical characters, medical records, blood chemistry data and dead time were collected. Kaplan-Meier survival curve analysis was used to analyze the relations between survival time and different level of uric acid. The relative risk (RR) of uric acid on cardiac death and total were evaluated by Cox regression analysis. We also discussed if uric acid is an independent predictor of mortality for CAD patients. A total of 254 patients were excluded. The data of 1054 patients (80.6%) were analyzed. There were 195 patients died (127 cardiac deaths) during the follow-up with annular cardiac death rate of 3.80%. A positive relation between cardiac death rate and uric acid level was found in this study. This result suggests that uric acid level correlate with the survival time of CAD patients significantly. Multivariate Cox regression analysis revealed that the relative risk of cardiac death rise 9% with an increase 1mg/dl of uric acid (RR 1.09, 95%CI 1.01 to 1.18, p<0.05). When the level of uric acid was classified into four quartiles, it appeared that patients in the fourth quartile had a higher cardiac death rate than those in the first quartile with a RR of 2.05 (95%CI 1.18 to 3.57, p<0.05). The influence of uric acid on the prediction of cardiac death was not affected by sex and age, although annular cardiac death was different between male and female (2.91 vs 6.85%). Univariate Cox regression analysis revealed that uric acid significantly affected the cardiac death rate in low risk groups, except for hypertension and diabetes mellitus. Moreover, uric acid may increase platelet agglutination, stimulate vascular smooth muscle cell proliferation and induce inflammation, resulted in hypertension and renal disease. These effects may influence the incidence and prognosis of CAD. Thus, the results of this study support uric acid is an independent predictor of mortality on CAD patients and suggest that uric acid should be considered as one of controllable factors for CAD.

碩士
國立雲林科技大學
工業工程與管理系
104
Chronic diseases have the highest mortality rate in the world, in which the main cause of death is heart disease. The number of patients died of heart disease increases year by year, and here is a trend of younger age prevalence. Electrocardiogram (ECG) is often used to determine whether a patient has heart disease or myocardial infarction. It is the most commonly used diagnostic technique for the diagnosis of heart disease. However some patients can’t use the device in static state. Therefore, the exercise ECG is the best way to detect heart disease. Exercise ECG is the amount of oxygen consumed per minute of the body during exercise. It uses the maximum oxygen uptake (VO2 max) to interpret the situation of heart and lung function, but not every patient is suitable for the use of exercise test to detect heart disease. We need a method that can accurately determine the risk of heart disease without exercise. The purpose of this study is to establish a prediction model to pre-examine patients suffering from heart disease. The National Health and Nutrition Examination Survey was adopted in this study. From 2003 to 2004, a total of 2638 was used as the participants. Through the genetic algorithm combining with Naïve Bayes Classifier and Logistic Regression, we established a model to predict the maximum oxygen uptaking in patients to determine whether a patient is likely to have a heart disease. According Genetic Algorithm combine with data mining, the impact factors of affecting heart disease were age, heart rate, standing height, weight, waist circumference, BMI and blood urea nitrogen. The results of this study can advance the possibility of heart disease in patients and provide patients with risk factors for disease to prevent and reduce the risk of disease.

The United States health-care system is considered to be unsustainable due to its unbearably high cost. Many of the resources are spent on acute conditions rather than aiming at preventing them. Preventive medicine methods, therefore, are viewed as a potential remedy since they can help reduce the occurrence of acute health episodes. The work in this dissertation tackles two distinct problems related to the prevention of acute disease. Specifically, we consider: (1) early detection of incorrect or abnormal postures of the human body and (2) the prediction of hospitalization due to heart related diseases. The solution to the former problem could be used to prevent people from unexpected injuries or alert caregivers in the event of a fall. The latter study could possibly help improve health outcomes and save considerable costs due to preventable hospitalizations. For body posture detection, we place wireless sensor nodes on different parts of the human body and use the pairwise measurements of signal strength corresponding to all sensor transmitter/receiver pairs to estimate body posture. We develop a composite hypothesis testing approach which uses a Generalized Likelihood Test (GLT) as the decision rule. The GLT distinguishes between a set of probability density function (pdf) families constructed using a custom pdf interpolation technique. The GLT is compared with the simple Likelihood Test and Multiple Support Vector Machines. The measurements from the wireless sensor nodes are highly variable and these methods have different degrees of adaptability to this variability. Besides, these methods also handle multiple observations differently. Our analysis and experimental results suggest that GLT is more accurate and suitable for the problem. For hospitalization prediction, our objective is to explore the possibility of effectively predicting heart-related hospitalizations based on the available medical history of the patients. We extensively explored the ways of extracting information from patients' Electronic Health Records (EHRs) and organizing the information in a uniform way across all patients. We applied various machine learning algorithms including Support Vector Machines, AdaBoost with Trees, and Logistic Regression adapted to the problem at hand. We also developed a new classifier based on a variant of the likelihood ratio test. The new classifier has a classification performance competitive with those more complex alternatives, but has the additional advantage of producing results that are more interpretable. Following this direction of increasing interpretability, which is important in the medical setting, we designed a new method that discovers hidden clusters and, at the same time, makes decisions. This new method introduces an alternating clustering and classification approach with guaranteed convergence and explicit performance bounds. Experimental results with actual EHRs from the Boston Medical Center demonstrate prediction rate of 82% under 30% false alarm rate, which could lead to considerable savings when used in practice.

Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence
Cardiovascular diseases are the main cause of the number of deaths in the world, being the heart disease the most killing one affecting more than 75% of individuals living in countries of low and middle earnings. Considering all the consequences, firstly for the individual’s health, but also for the health system and the cost of healthcare (for instance, treatments and medication), specifically for cardiovascular diseases treatment, it has become extremely important the provision of quality services by making use of preventive medicine, whose focus is identifying the disease risk, and then, applying the right action in case of early signs. Therefore, by resorting to DM (Data Mining) and its techniques, there is the ability to uncover patterns and relationships amongst the objects in healthcare data, giving the potential to use it more efficiently, and to produce business intelligence and extract knowledge that will be crucial for future answers about possible diseases and treatments on patients. Nowadays, the concept of DM is already applied in medical information systems for clinical purposes such as diagnosis and treatments, that by making use of predictive models can diagnose some group of diseases, in this case, heart attacks. The focus of this project consists on applying machine learning techniques to develop a predictive model based on a real dataset, in order to detect through the analysis of patient’s data whether a person can have a heart attack or not. At the end, the best model is found by comparing the different algorithms used and assessing its results, and then, selecting the one with the best measures. The correct identification of early cardiovascular problems signs through the analysis of patient data can lead to the possible prevention of heart attacks, to the consequent reduction of complications and secondary effects that the disease may bring, and most importantly, to the decrease on the number of deaths in the future. Making use of Data Mining and analytics in healthcare will allow the analysis of high volumes of data, the development of new predictive models, and the understanding of the factors and variables that have the most influence and contribution for this disease, which people should pay attention. Hence, this practical approach is an example of how predictive analytics can have an important impact in the healthcare sector: through the collection of patient’s data, models learn from it so that in the future they can predict new unknown cases of heart attacks with better accuracies. In this way, it contributes to the creation of new models, to the tracking of patient’s health data, to the improvement of medical decisions, to efficient and faster responses, and to the wellbeing of the population that can be improved if diseases like this can be predicted and avoided. To conclude, this project aims to present and show how Data Mining techniques are applied in healthcare and medicine, and how they contribute for the better knowledge of cardiovascular diseases and for the support of important decisions that will influence the patient’s quality of life.

Submitted in fulfilment for the Degree of Masters in Technology: Clinical Technology, Durban University of Technology, 2010.
Cardiovascular disease (CVD) is one of the major causes of premature deaths worldwide. In South Africa, approximately 195 people die from cardiovascular diseases each day. The earlier coronary artery disease (CAD) is detected, the better the prognosis. NT- pro- brain natriuretic peptide (NT-proBNP) is a cardiac neurohormone that is secreted in the cardiac ventricles in response to excessive stretching of heart muscle cells. Brain natriuretic peptide (BNP) is currently being used as a marker of left ventricular dysfunction but limitations are evident in patients with sepsis, volume overload, stroke and acute mitral regurgitation. OBJECTIVES: The main objective of this study was to identify a possible value of NT- proBNP level which indicates CAD. It also aimed to compare NT- proBNP levels with the number of diseased vessels; to assess the association between proBNP levels and patients’ age and gender; to determine the percentage of false positive proBNP levels; to determine the probability of false positive exercise stress testing and to correlate NT- proBNP levels with LVEDP. METHODS: Sixty patients were recruited from the Cardiology Department at St Anne’s hospital to participate in this trial. They were divided into two groups; Group A, the control group, consisted of thirty patients with a positive EST and Group B, the experimental group, consisted of thirty patients with an inconclusive EST. After the EST, all patients from both groups were required to have a NT- proBNP blood test, a left and right coronary angiogram and a left ventriculogram. iii RESULTS: Results of the study showed that post EST NT- proBNP levels, in both groups, increased in the presence of CAD (p<0.001). For the positive EST group, the area under the ROC curve was 0.975 which was highly statistically significantly different from the null hypothesis value of 0.5 (p<0.001) and a cut- off value of 120 pg/ml was identified with the highest sensitivity (95.7%) and specificity (100%). For patients in the inconclusive EST group, the area under the ROC curve was 0.912 which was highly statistically significantly different from the null hypothesis value of 0.5 (p<0.001) and a cut-off value of 85 pg/ml was identified with the highest sensitivity (87.5%) and specificity (86.4%). There was a statistically significant difference between the median NT- proBNP values of males and females in the group of patients with positive EST (p=0.048). The values were higher in males. However, there was no significant difference between the genders in the group with an inconclusive EST. A strong and significant correlation (p<0.001) between left ventricular end diastolic pressures (LVEDP) and number of disease vessels was demonstrated. The probability of a false positive result for EST was 24.1%. and the probability of a false negative result was 25.8%. CONCLUSION: Results of the study showed that post EST NT- proBNP levels, in both groups, increased in the presence of CAD and could accurately predict the presence of CAD. Cut- off values of 120 pg/ml for the positive EST group and 85 pg/ml for the inconclusive EST group were identified with the highest sensitivity and specificity. In the positive EST group, a trend of increasing NT-proBNP with age was and NT-proBNP values were higher in males. The positive EST was relatively accurate at predicting CAD; however, 75.9% of patients with an inconclusive EST did not have CAD.Exercise stress testing in this regard, is therefore relatively inaccurate at predicting CAD in patients with inconclusive ESTs, and the need for an additional tool, such as NT-proBNP measurements post inconclusive EST is warranted in the determination of the presence of CAD.

碩士
中臺科技大學
醫學影像暨放射科學系暨研究所
105
Coronary artery stenosis readings were predicted in this study on the basis of clinical data for patients with coronary heart diseases using the inverse problem algorithm. Five factors, including age, BSA (body surface area), MAP (mean artery pressure), sugar AC (ante cibum), and LDL-C (low-density Lipoprotein-Cholesterol) were incorporated into a nonlinear first-order regression fit analysis to develop a prediction equation with sixteen terms derived via a revised inverse problem algorithm implemented through the STATISTICA 7.0 default regression fit. The clinical data acquired from ninety-three coronary heart disease patients were first normalized to the same domain range of [-1 to +1], and then processed by the above algorithm to find the compromised solution of predicted coronary artery stenosis reading. The actual reading was obtained by weighting the stenosis of three major cardiac artery branches, namely, the left anterior descending artery (LAD) (wi 0.3), left circumflex artery (LCA) (wi 0.3), and right coronary artery (RCA) (wi 0.4). The derived regression fit possessed the final loss function value Φ=3.589 and correlation coefficient r2 =0.892 with variance of 79.55%. Accordingly, forty-five patients with similar syndromes were analyzed to verify the prediction, which exhibited a high coincidence. The LDL-C factor was dominant for the prediction of the largest coefficient in the derived equation, whereas the age factor exhibited a minor contribution to the regression fit. The attempts to reduce the number of influence factors to 4, 3 or 2 for the model simplification yielded the results, whose low linearity and high loss function values reflected their inappropriate setting.

碩士
國立臺灣大學
臨床醫學研究所
98
Background The most common underlying reason for patients to die suddenly from cardiac arrest is coronary heart disease (CHD). Although a large number of risk factors for Sudden Cardiac Death have been identified, translating these findings into a comprehensive risk stratification strategy is challenging. T wave morphology descriptors on standard twelve-lead electrocardiogram (ECG) have shown to predict arrhythmic events in patients with previous myocardial infarction or congestive heart failure. However, these descriptors have not been considered to determine the risk stratification in CHD patients with Implantable Cardioverter Defibrillator (ICD). This study was conducted to examine T wave morphology descriptors prognostic importance in CHD patients with ICD, comparison CHD patients without ICD. Methods 41 CHD patients with ICD were compared with 55 CHD patients without ICD and 55 healthy patients using a case-control design. T wave morphology descriptors including (lead dispersion, T wave morphology dispersion, percentage of the loop area, percentage of the outer area, and the total cosine between QRS and T wave [TCRT] were studied in these patients Results A total of 41 CHD with ICD patients with a mean age of 65 ± 10 years were enrolled and followed-up for 3.1 ± 2.1 years. In the ICD group, the occurrence rate of HTN and DM were 73% and 50%. The mean left ventricular ejection fraction (LVEF) was 47% ± 14%. The total mortality rate in ICD group was 21.9%, shock within 1 year rate was 27% and shock rate was 32%. QRS duration and T wave morphology descriptors like TCRT, TMD were statistically significantly different in CHD patients and CHD patients with ICD patients.(P&lt;0.001,&lt;0.001 and &lt;0.001 respectively). A stepwise backward Cox regression analysis showed that first shock rate was significantly associated with TMD(P = 0.05). On the basis of PL&lt;0.64, PO>0.298 and TMD>74.1 as cutoff points, a significant difference in long-term survival were observed from a Kaplan-Meier survival curve (P &lt; 0.022, P&lt;0.032 and P&lt;0.038 respectively). The Cox regression analysis showed that total mortality was significantly associated with LVEF (p=0.037), No. of diseased vessel(p=0.028) ,HTN(p=0.024), DM(p=0.033), Creatine (p=0.019), QRS duration (p=0.027), PO(p=0.032) and PL(p=0.032) (Table 5) and first shock was significantly associated with b-blocker use(p=0.046), sex(p=0.047), hypertension (p=0.027)and TMD (P = 0.031). Conclusion In conclusion, TCRT ,TMD and QRS duration may provide further risk stratification for CHD patients, and TMD,PO and PL may impact on the long term survival of CHD patients with ICD. Moreover, TMD may be a good predictor for shock rate in CHD patients with ICD.

Tese de mestrado integrado em Engenharia Biomédica e Biofísica, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2017
De acordo com os dados de 2017 da Organização Mundial da Saúde, as doenças cardiovasculares são a principal causa de morte a nível mundial. Se estes tipos de doenças não forem diagnosticadas e tratadas atempadamente, podem levar a insuficiências cardíacas ou outras complicações irreversíveis. As duas doenças cardiovasculares congénitas estudadas neste trabalho são a coarctação aórtica (CoA), caracterizada por uma estenose, habitualmente, na zona do arco da artéria aorta, e a doença da válvula aórtica (AvD), uma malformação ao nível da válvula aórtica. Estas doenças são responsáveis por cerca de 50,000 intervenções por ano. Deste modo, a melhoria métodos de diagnóstico e de intervenção adequados e eficientes é uma prioridade e pode levar ao decréscimo no número das intervenções, bem como reduzir a morbilidade e a mortalidade. A área de imagiologia médica de diagnóstico tem tido uma evolução significativa ao longo dos anos e é de extrema importância nas tentativas de substituição de métodos de diagnóstico invasivos. As imagens médicas são adquiridas e posteriormente processadas e analisadas, com recurso a programas adequados. Atualmente, é possível obter os valores de gradientes de pressão relativa a partir de Ecocardiografia Doppler e Ressonância Magnética. Contudo, os gradientes de pressão medidos no cateterismo cardíaco, o método gold standard para o diagnóstico de CoA e AvD, são gradientes de pressão absoluta. Nesta dissertação desenvolveu-se um método de diagnóstico de CoA e AvD, a partir dos mapas de pressão relativa no estreitamento da aorta e na válvula aórtica, respectivamente. O método matemático desenvolvido tem por base as equações de Poisson, resolvida com a condição de fronteira de Neumann utilizando os métodos de elementos finitos, e a de Navier Stokes para a conservação do momento. O método desenvolvido também tem em conta a informação proveniente da função de Windkessel da artéria aorta, uma artéria distensível. Esta função dá-nos o comportamento da propagação do pulso de pressão com uma velocidade de pulso de propagação. Deste modo, é observado um desfasamento temporal entre as curvas de fluxo da pressão e da velocidade, entre as duas regiões de interesse escolhidas. Deste modo, o método, denominado de Time-shift Corrected Pressure Maps (TCPM, sigla em inglês), permite obter os mapas de pressão absoluta, isto é, mapas de pressão que têm em conta o intervalo de tempo entre os picos de pressão na aorta descendente e ascendente, no caso do primeiro estudo, e antes e depois da válvula aórtica, no caso do segundo estudo. Os pacientes de ambos os estudos tinham indicação clínica para cateterismo cardíaco e foram submetidos a ressonância magnética cardiovascular de contraste de fase em tempo real (4D PC MRI, em inglês), para recolher as imagens ao nível da aorta e da válvula aórtica e os respectivos campos de velocidade da corrente sanguínea. O primeiro estudo tem como objetivo a aplicação do método TCPM a 27 pacientes de CoA (n=16 masculinos, n=11 femininos, faixa etária de 4 a 52 anos, idade média de 20±15 anos). Após aquisição das imagens, estas foram processadas usando programas específicos. Em primeiro lugar foi necessário segmentar a aorta, seguiu-se a seleção das regiões de interesse e, finalmente, a obtenção dos campos de velocidade e dos mapas de pressão relativa entre as duas regiões de interesse selecionadas. Após aplicação do método TCPM, foram aplicados testes estatísticos (correlação, teste t e Bland-Altman) para comparar os valores obtidos a partir de TCPM com os valores obtidos no cateterismo cardíaco. Após processamento das imagens dos 27 pacientes, 6 pacientes foram retirados do estudo. N=3 pacientes foram retirados porque a percentagem de fluxo que passa pelo estreitamento é insuficiente para calcular o gradiente de pressão a partir de TCPM e N=3 pacientes foram retirados porque a aorta não estava inserida por completo no FOV. As medições obtidas a partir de TPCM e cateterismo cardíaco têm uma correlação linear significante (R²=0,90; p<0,001). A partir dos gráficos Bland-Altman é possível verificar uma boa concordância entre as medições de ambos os métodos, com bias de -2,69 mmHg e os limites de concordância de ±4,74 mmHg. O teste de equivalência mostrou uma relação significante entre os métodos (p=0,007). O segundo estudo tem como objetivo a aplicação do método TPCM e o método da Área de Gorlin a 4 pacientes de AvD (n=4 masculinos, faixa etária 17 a 36 anos, idade média 27±7 anos). O método da Área de Gorlin permite obter o gradiente de pressão absoluta a partir da área geométrica da válvula e do fluxo total que passa nessa área. Após a aquisição das imagens, foi feito o processamento das mesmas. Numa primeira fase, as imagens foram segmentadas na região da válvula aórtica. Depois, as imagens segmentadas foram analisadas em dois programas distintos. O primeiro foi utilizado de forma a obter os campos de velocidade e os mapas de pressão relativa entre dois pontos antes e depois da válvula aórtica. O segundo permitiu definir a região da válvula como região de interesse e exportar os valores de velocidade, área, pressão relativa e fluxo absoluto nessa região. Os resultados mostram uma correlação linear significativa entre os valores de cateterismo cardíaco e de TCPM (R²=0,99; p<0,001). Os gráficos de Bland-Altman mostram uma boa concordância entre os valores de TCPM (24,75±22,50 mmHg) e de cateterismo (20,88±19,51 mmHg), com um bias de -3,87 mmHg e limites de concordância de ±3,64 mmHg. Os resultados também sugeriram uma ligeira subestimação dos valores do cateterismo cardíaco a partir do método da Área de Gorlin (14,47±13,00 mmHg), com um bias de 6,41 mmHg e limites de concordância de ±7,15 mmHg. Este estudo foi feito com uma amostra diminuta de 4 pacientes, o que não é suficiente para retirar conclusões com significância. Contudo, foi uma primeira abordagem positiva, que mostra a potencialidade que este método pode vir a apresentar. O método TCPM proposto neste projeto permite a medição não invasiva de gradientes de pressão absoluta a partir de mapas de pressão relativa em pacientes de CoA e AvD. Vários aspectos têm que ser tidos em conta de forma a garantir a eficácia deste método. Por exemplo, as regiões de interesse escolhidas têm que se cuidadosamente selecionadas de forma a serem perpendicular à direção do fluxo naquele local. Só desta maneira é possível obter o fluxo, os campos de velocidade e as pressões relativas corretas. Também, se o raio da estenose for menor que 2 voxéis, a relação sinal-ruído aumenta substancialmente, e a resolução especial da aquisição é insuficiente. Contudo, a aplicação do método TPCM a casos de grande estreitamento não é necessária visto que estes casos já são tipicamente identificados em imagens anatómicas de ressonância magnética e que o paciente segue automaticamente para intervenção quando a área do estreitamente representa cerca de 50% do valor de área típico da aorta. O método não invasivo TCPM apresenta uma boa concordância com o cateterismo cardíaco em termos da medição dos gradientes de pressão em CoA e AvD. Os bias e os limites de concordância entre cateterismo e TCPM foram substancialmente mais pequenos que os bias e os limites de concordância entre cateterismo e ecocardiografia Doppler e entre o cateterismo e o método da Área de Gorlin. Com os resultados apresentados já é possível ver o potencial desta técnica no processo de diagnóstico e decisão de intervenção em casos de CoA e AvD. Contudo, estudos com populações maiores será extremamente benéfico para validar clinicamente este método.
This dissertation aims to validate MRI-based time-shift corrected pressure mapping (TCPM) against cardiac catheterization in CoA and AvD patients. Also, in AvD patients, catheterization will be compared against Gorlin Area method. This project is divided in two independent studies: the first one for CoA patients and the second one for AvD patients, all with clinical indication for cardiac catheterization. In both CoA and AvD, clinical guidelines recommend treatment in the presence of a relevant pressure gradient. While reliable non-invasive measurement approaches would be crucial, the accuracy of currently available methods has been limited. In both studies, 4D PC-MRI was performed to compute relative pressure maps via Pressure-Poisson equation. To consider the patient-specific peak pressure time-shift from the ascending to the descending aorta and before and after the aortic valve, relative pressure gradient maps were corrected by the inertial term. Comparison between TCPM and invasive peak-to-peak measurements was performed using correlation, Bland-Altman plots and mean-equivalence t-test. In the first study, with a cohort of 21 patients with CoA, TCPM and catheter measurements showed significant linear correlation (R²=0.90; p<0.001). Bland-Altman plots demonstrated good agreement between TCPM and catheter derived pressure gradients with mean differences of -2.69 mmHg and 95% limits of agreement between -6.38 and 1.00 mmHg between methods. The mean-equivalence test was significant (p=0.007). In the second study, with a cohort of 4 patients with AvD, the catheterization measurements were compared against TPCM measurements. The results showed significant linear correlation (R²=0.99; p<0.001). Bland Altman plots showed a good agreement between TCPM (24.75±22.50 mmHg) and catheter derived peak-to-peak pressure gradients (20.88±19.51 mmHg), and suggested slight underestimation of the pressure gradients by the Gorlin Area method (14.47±13.00 mmHg). Non-invasive TCPM showed equivalence to pressure gradients from invasive heart catheterization in patients with CoA and AvD. However, in the AvD study, they were obtained for a very small cohort of patients and do not have sufficient statistical significance to validate the method for AvD patients.

This dissertation investigated the psychometric properties and clinical applications of the Psychosocial Inventory for Cardiovascular Illness (PICI). The PICI is an inventory developed to measure the psychosocial risk factors for heart disease including anxiety, depression, stress, social isolation, and anger. The inventory was developed to measure the ways that each psychosocial risk factor contributes to the coronary artery disease process through the lifestyle behaviors and pathophysiological mechanisms with which they are associated. The primary purpose of the study was to examine predictive validity for the PICI. With support for predictive validity, the inventory may aid in early identification of individuals at increased risk for coronary artery disease (CAD) so that behavioral, psychosocial, and medical interventions can be implemented. Both healthy and cardiac samples were used in the inventory development and validation process. The PICI was administered in conjunction with similar inventories and physiological markers of CAD were collected including percent of coronary artery blockage and history of heart attacks. Item analysis and factor analysis were used to yield a 20-item PICI comprised of three subscales to include Negative Affect, Social Isolation, and Anger. It was hypothesized that the PICI subscales would predict group membership; whether or not a participant carried a diagnosis of CAD, and would be have a strong relationship to the physiological markers of CAD that were measured. Analysis revealed that the PICI was unable to predict diagnostic status and did not have a strong relationship with the physiological markers of CAD. Results suggest that the PICI has acceptable reliability and construct validity as demonstrated in the current sample, yet further investigation must be conducted to gain support for the instrument’s predictive abilities.
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The agriculture sectors in Canada are highly vulnerable to a wide range of inter-related weather risks linked to seasonal climate variability (e.g., El Ni ̃no Southern Oscillation(ENSO)), short-term extreme weather events (e.g., heatwaves), and emergent disease(e.g., grape powdery mildew). All of these weather-related risks can cause severe crop losses to agricultural crop yield and crop quality as Canada grows a wide range of farm products, and the changing weather conditions mainly drive farming practices. This dissertation presents three machine learning-based statistical models to assess the weather risks on the Canadian agriculture regions and to provide reliable risk forecasting to improve the decision-making of Canadian agricultural producers in farming practices. The first study presents a multi-scale, cluster-based Principal Component Analysis(PCA) approach to assess the potential seasonal impacts of ENSO to spring wheat and barley on agricultural census regions across the Canada prairies areas. Model prediction skills for annual wheat and barley yield have examined in multi-scale from spatial cluster approaches. The ’best’ spatial models were used to define spatial patterns of ENSO forcing on wheat and barley yields. The model comparison of our spatial model to non-spatial models shows spatial clustering and ENSO forcing have increase model performance of prediction skills in forecasting future cereal crop production. The second study presents a copula-Bayesian network approach to assess the impact of extreme high-temperature events (heatwave events) on the developments of regional crops across the Canada agricultural regions at the eco-district-scale. Relevantweather variables and heatwave variables during heatwave periods have identified and used as input variables for model learning. Both a copula-Bayesian network and Gaussian-based network modeling approach is evaluated and inter-compared. The copula approach based on ’vine copulas’ generated the most accurate predictions of heatwave occurrence as a driver of crop heat stress. The last study presents a stochastic, hybrid-Bayesian machine-learning approach to explore the complex causal relationships between weather, pathogen, and host for grape powdery mildew in an experimental farm in Quebec, Canada. This study explores a high-performance network model for daily disease risk forecast by using estimated development factors of pathogen and host from recorded daily weather variables. A fungicide strategy for disease control has presented by using the model outputs and forecasted future weather variability. The dissertation findings are beneficial to Canada’s agricultural sector. The inter-related weather risks explored by the three separate studies in multi-scales provide a better understanding of the interactions between changing weather conditions, extreme weather, and crop production. The research showcases new insights, methods, and tools for minimizing risk in agricultural decision-making
Graduate
2021-08-19