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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 簡國龍(Kuo-Liong Chien) | |
dc.contributor.advisor | 簡國龍(Kuo-Liong Chien | klchien@ntu.edu.tw | 0000-0003-4979-8351), | |
dc.contributor.author | Yun-Yu Chen | en |
dc.contributor.author | 陳韻伃 | zh_TW |
dc.date.accessioned | 2023-03-19T23:21:33Z | - |
dc.date.copyright | 2022-06-29 | |
dc.date.issued | 2022 | |
dc.date.submitted | 2022-06-23 | |
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Outcomes in patients with cardiac amyloidosis and implantable cardioverter-defibrillator. Europace. 2020;22:1216-23. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/85687 | - |
dc.description.abstract | 背景:心血管疾病是全球主要的死亡原因,造成心血管疾病患者死亡的主要因素為冠狀動脈疾病、心臟衰竭、和中風。探討風險因子與心血管疾病風險之間的關聯性很重要,透過風險評估可以改善治療策略,而世代研究可以衡量特定暴露在心血管結局的發生率和危險因子。 方法:我們使用世代研究來探討心血管疾病的危險因素和臨床結果。本博士論文包含三個研究:(1) 第一個研究利用金山社區心血管世代研究調查,探討一般民眾心因性猝死的危險因子 (針對年紀大於35歲、沒有冠心病、和左心室收縮功能< 35%者)。研究重點放在12導程心電圖、標準心臟超音波、和頸動脈超音波等篩檢工具的異常,利用佛萊明風險分數方法來發展預測十年內心因性猝死的評分系統,並使用自助抽樣法驗證。(2) 第二個研究針對心房顫動患者,我們使用臺灣全民健康保險研究資料庫的醫療資料,來發展預測一年內中風評分系統,並進行內部驗證。(3) 第三個研究基於全國大型世代資料,探討臺灣地區罕見疾病類澱粉性沉積症患者的發生率,以及評估長期心室頻脈和心因性死亡的風險。 結果:(1) 嶄新心因性猝死預測分數系統 (CCCC-SCD-Score) 具有良好的十年內心因性猝死預測能力 (高風險切點: > 5; 一致性指數 [C指數]: 0.881, 95 % 信賴區間: 0.805-0.958; Hosmer-Lemeshow 適合度檢定: P值 = 0.82),分數依年齡組別 (最高4分)、左心室肥大 (1分)、高血壓 (1分)、左心室射出分量 < 40% (1分)、主動脈瓣流速 > 190 cm/s (1分)、以及頸動脈斑塊分數 ≥ 5 (1分) 計算。(2) 透過評估電燒狀態新發展的心房顫動預測中風評分系統 (AF-CA-Stroke: 高風險切點: > 5; 一致性指數 [C指標]: 0.658, 95 % 信賴區間: 0.644-0.675; Hosmer-Lemeshow 適合度檢定: P值 = 0.81),在預測一年內中風風險方面比傳統評分系統 (CHADS2,一致性指數 [C指數]: 0.577, 95 % 信賴區間: 0.570-0.584) 具有更好的辨別能力 (DeLong測試: P值 < 0.001),分數依年齡組別 (最高5分)、未接受心房顫動電燒手術 (1分)、過去中風史 (1分)、慢性腎臟病 (1分)、其他過去心臟 (冠心症) 或周邊血管疾病 (1分) 計算。(3) 類澱粉性沉積症患者在臺灣的發生率為每十萬人年6.54人,心臟型類澱粉性沉積症患者在臺灣的發生率為每十萬人年0.61人。罹患有類澱粉性沉積症的患者未來發生心室頻脈的風險 (調整後風險函數比: 7.90, 95% 信賴區間: 4.49-13.9) 和心血管死亡風險 (調整後風險函數比: 5.09, 95 % 信賴區間: 4.23-6.12) 都較沒有罹患類澱粉性沉積症的患者高。 結論:瞭解各種心血管疾病患者的危險因子很重要,可以針對具有心血管事件高風險的患者,進行長期追蹤,以助於提供初級預防處置和治療的策略。 | zh_TW |
dc.description.abstract | Background: Cardiovascular diseases (CVDs) are among the leading causes of death worldwide. The main causes of death in CVD patients are coronary artery disease (CAD), heart failure, and stroke. Cohort studies are used to measure incidence rates for cardiovascular (CV) outcomes based on a specific exposure, as well as to examine the risk factors and clinical outcomes associated with CVDs. By assessing risk, the treatment strategies can be improved for patients with CVDs. Methods: We investigated several factors and outcomes of CVDs in the cohort studies. The doctoral dissertation included three projects: (1) The objective of the first project was to investigate risk factors for sudden cardiac death (SCD) in a general population aged ≤ 35 years without a prior history of CAD or left ventricular ejection fraction < 35 based on the Chin Shan Community Cardiovascular Cohort, focusing on the screening tools of 12-lead electrogram, standard echocardiography, and carotid artery duplex sonography. By using the Framingham risk score methods, we developed a novel CCCC-SCD-Score to predict incident 10-year SCD. The CCCC-SCD-Score was internally validated using bootstrapping method. (2) The objective of the second project was to develop a novel model-based point scoring system for 1-year stroke prediction in patients with atrial fibrillation (AF) using Taiwan's National Health Insurance Research Database. An internal validation study was performed. (3) The objective of the third project was to investigate the risks of new-onset ventricular tachycardia and CV outcomes in patients with amyloidosis after a long-term follow-up based on a representative national cohort. Results: (1) A CCCC-SCD-Score score is calculated using age groups (maximum points = 4), left ventricular hypertrophy, hypertension, left ventricular ejection fraction < 40%, aortic flow rate > 190 cm/s, and carotid plaque scores ≥ 5 (point = 1 for each risk factor). In predicting 10-year SCD risk, the CCCC-SCD-Score had good prediction performance (cut-off point: > 5; C-index: 0.881, 95% confidence interval [CI]: 0.805-0.958; Hosmer-Lemeshow test: P-value = 0.82). (2) The AF-CA-Stroke scoring system includes important clinical risk factors: age (maximum points = 5), the status of not having undergone AF ablation (point = 1), prior stroke history (point = 1), chronic kidney disease (point = 1), and prior CAD or vascular disease (point = 1). The novel AF-CA-Stroke scoring system using the status of AF ablation (cut-off point: > 5; C-index: 0.658, 95% CI: 0.644-675; Hosmer-Lemeshow test: P-value = 0.81) predicted incident 1-year stroke risk more accurately than conventional CHADS2 scoring system (C-index: 0.577, 95% CI: 0.570-584) (P-value = 0.001, using the DeLong test). (3) The incidence rates of amyloidosis and cardiac amyloidosis were 6.54 and 0.61 per 100000 person-years, respectively. Amyloidosis was associated with higher rates of ventricular tachycardia (adjusted HR: 7.90, 95% CI: 4.49-13.9) and CV deaths (adjusted HR: 5.09, 95% CI: 4.23-6.12). Conclusions: Knowledge of risk factors in patients with various CVDs is essential, and long-term follow-up of patients at high risk for cardiovascular events can aid in primary prevention and guide treatment strategies. | en |
dc.description.provenance | Made available in DSpace on 2023-03-19T23:21:33Z (GMT). No. of bitstreams: 1 U0001-2106202216135100.pdf: 11395500 bytes, checksum: 4e7398d29909205d0d51e4d208d62f24 (MD5) Previous issue date: 2022 | en |
dc.description.tableofcontents | 致謝 1 中文摘要 2 English Abstract 3 Abbreviations 5 Chapter 1:Introduction 10 1.1 Overview of Cardiovascular Diseases 10 1.2 Risk Assessment on Clinical Outcomes based on Cohort Studies 11 1.3 Study Projects 12 Project 1: Risk Assessment of Sudden Cardiac Death 12 Applying the Chin-Shan Community Cardiovascular Cohort Study to Explore the Risk Factors of Sudden Cardiac Death: A Novel Point-Based Prediction Model for General Population 12 Project 2: Risk Assessment of Stroke in Patients with Atrial Fibrillation 12 Novel Model-Based Point Scoring System for Predicting Stroke Risk in Atrial Fibrillation Patients: Results from a Nationwide Cohort Study with Validation 12 Project 3: Clinical Outcomes in Patients with Amyloidosis 12 Risks of Ventricular Tachyarrhythmia and Deaths in Patients with Amyloidosis– A Long-term Cohort Study 12 1.4 Project 1: Risk Assessment of Sudden Cardiac Death 13 1.4.1 Definition and Importance of Sudden Cardiac Death 13 1.4.2 Examination of the Risk Factors of Cardiovascular Diseases 14 1.4.3 Study Gaps, Study Hypotheses, and Study Aims – Project 1 18 1.5 Project 2: Risk Assessment of Stroke in Patients with Atrial Fibrillation 20 1.5.1 Stroke Risk and Various Managements in Atrial Fibrillation Patients 20 1.5.2 Managing for Atrial Fibrillation Patients 20 1.5.3 Risk Assessment of Stroke for Atrial Fibrillation 21 1.5.4 Study Gaps, Study Hypotheses, and Study Aims – Project 2 24 1.6 Project 3: Clinical Outcomes in Patients with Amyloidosis 25 1.6.1 Amyloidosis and Cardiac Amyloidosis 25 1.6.2 Incidence of Amyloidosis and Cardiac Amyloidosis 26 1.6.3 Amyloidosis and Risk of Cardiac Arrhythmia 26 1.6.4 Study Gaps, Study Hypotheses, and Study Aims – Project 3 27 Chapter 2:Methods 28 2.1 Project 1: Risk Assessment of Sudden Cardiac Death 28 2.1.1 Study Design and Study Population 28 2.1.2 Ascertainment of Baseline Data 28 2.1.3 Follow-up Strategy and Outcome Confirmation 32 2.1.4 Framingham Risk Score 33 2.1.5 Statistical Analyses 34 2.1.6 Sample Size and Power 37 2.2 Project 2: Risk Assessment of Stroke in Patients with Atrial Fibrillation 38 2.2.1 Study Design and Study Population 38 2.2.2 Training Cohort and Internal Validation Cohort 38 2.2.3 Ascertainment of Baseline Data 39 2.2.4 Follow-up Strategy and Outcome Confirmation 41 2.2.5 Statistical Analyses 41 2.2.6 Sample Size and Power 43 2.3 Project 3: Clinical Outcomes in Patients with Amyloidosis 44 2.3.1 Databases 44 2.3.2 Study Design and Participants 44 2.3.3 Study Endpoints During the Follow-up 46 2.3.4 Statistical Analyses 46 2.3.5 Sample Size and Power 48 Chapter 3:Results 49 3.1 Project 1: Risk Assessment of Sudden Cardiac Death 49 3.1.1 Baseline Characteristics of the Cohort 49 3.1.2 Clinical History, ECG Patterns, and Sudden Cardiac Deaths 49 3.1.3 Associations between Ultrasonographic Findings and Sudden Cardiac Death 50 3.1.4 CCCC-SCD-Score Construction Using the Training Dataset 50 3.1.5 Bootstrapping Validation 53 3.2 Project 2: Risk Assessment of Stroke in Patients with Atrial Fibrillation 54 3.2.1 Training Dataset and Selection of Clinical Risk Factors 54 3.2.2 Validation Dataset 56 3.2.3 Distributions among Various Scoring Systems and Incident Stroke Risks in the Training Dataset 57 3.3 Project 3: Clinical Outcomes in Patients with Amyloidosis 59 3.3.1 Patient Characteristics 59 3.3.2 Incidence of Cardiovascular Events 59 3.3.3 Cardiovascular Outcomes 60 3.3.4 Cardiovascular Risk Factors within Amyloidosis Patients 61 Chapter 4:Discussions 62 4.1 Project 1: Risk Assessment of Sudden Cardiac Death 62 4.1.1 Main Findings 62 4.1.2 Applying Electrogram and Echocardiography to Detect SCD Risk 62 4.1.3 Evidence of Carotid Plaque and SCD Risk 65 4.1.4 Model-based Risk Prediction Score and Traditional Risk Factors 66 4.1.5 Clinical Implications 67 4.1.6 Study Limitations 68 4.1.7 Conclusions 69 4.1.8 Acknowledgements 70 4.1.9 Conflict of Interests 70 4.2 Project 2: Risk Assessment of Stroke in Patients with Atrial Fibrillation 71 4.2.1 Main Findings 71 4.2.2 Effects of Various Age Groups and Comorbidities on Stroke Risks 71 4.2.3 Managing Stroke Risks in Patients with AF and the Impact of Catheter Ablation 72 4.2.4 Hypertension and Diabetes Mellitus 74 4.2.5 Gender 74 4.2.6 Renal Function as a Stroke Risk in Managing Patients with Atrial Fibrillation 75 4.2.7 Study Limitations 75 4.2.8 Conclusions 76 4.2.9 Acknowledgements 77 4.2.10 Conflict of Interests 77 4.3 Project 3: Clinical Outcomes in Patients with Amyloidosis 78 4.3.1 Main Findings 78 4.3.2 Incidence of Amyloidosis and Cardiac Amyloidosis 78 4.3.3 New-onset VT and CV Events in Patients with Amyloidosis and Cardiac Amyloidosis 79 4.3.4 Predictors of Ventricular Tachycardia in Amyloidosis 80 4.3.5 Clinical Implications 81 4.3.6 Study Limitations 82 4.3.7 Conclusions 83 4.3.8 Acknowledgements 84 4.3.9 Conflict of Interests 84 References 85 Figures 94 Tables 106 Appendices 141 Programming 145 Coding 1-1: Calculating Person-years 145 Coding 1-2: Regression Models 146 Coding 1-3: Bootstrapping 148 Coding 1-4: ROC Comparisons 149 Coding 1-5: Sample Size & Power for Study 1 150 Coding 2-1: ROC & Category-free NRI 154 Coding 2-2: Sample Size & Power for Study 2 157 Coding 3-1: Propensity-score Matching Technique 158 Coding 3-2: Conditional Cox Proportional Hazards Model 179 Coding 3-3: Sample Size & Power for Study 3 180 Publications 181 | |
dc.language.iso | en | |
dc.title | 利用世代研究探討心血管疾病患者在不同治療方針與各項風險因子之預後 | zh_TW |
dc.title | Applying the Cohort Studies to Explore the Outcomes in Patients with Cardiovascular Diseases under Various Treatment Strategies and Risk Factors | en |
dc.type | Thesis | |
dc.date.schoolyear | 110-2 | |
dc.description.degree | 博士 | |
dc.contributor.author-orcid | 0000-0001-7009-7838 | |
dc.contributor.advisor-orcid | 簡國龍(0000-0003-4979-8351) | |
dc.contributor.oralexamcommittee | 李文宗(Wen-Chung Lee),張慶國(Chin-Kuo Chang),林先和(Hsien-Ho Lin),方啟泰(Chi-Tai Fang),林彥璋(Yenn-Jiang Lin),葉宏一(Hung-I Yeh) | |
dc.contributor.oralexamcommittee-orcid | 李文宗(0000-0003-3171-7672),張慶國(0000-0002-8338-7196),林先和(0000-0002-7481-6016),方啟泰(0000-0002-7380-1699),林彥璋(0000-0001-8395-1052) | |
dc.subject.keyword | 類澱粉性沉積症,心房纖維顫動,心血管疾病,風險評估,心因性猝死,中風, | zh_TW |
dc.subject.keyword | amyloidosis,atrial fibrillation,cardiovascular diseases,risk assessment,sudden cardiac death,stroke, | en |
dc.relation.page | 204 | |
dc.identifier.doi | 10.6342/NTU202201040 | |
dc.rights.note | 同意授權(全球公開) | |
dc.date.accepted | 2022-06-23 | |
dc.contributor.author-college | 公共衛生學院 | zh_TW |
dc.contributor.author-dept | 流行病學與預防醫學研究所 | zh_TW |
dc.date.embargo-lift | 2022-06-29 | - |
顯示於系所單位: | 流行病學與預防醫學研究所 |
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