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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 潘文涵(Wen-Harn Pan) | |
dc.contributor.author | Jiunn-Horng Chen | en |
dc.contributor.author | 陳俊宏 | zh_TW |
dc.date.accessioned | 2021-06-15T00:17:25Z | - |
dc.date.available | 2010-09-16 | |
dc.date.copyright | 2009-09-16 | |
dc.date.issued | 2009 | |
dc.date.submitted | 2009-05-18 | |
dc.identifier.citation | 1. Bieber JD, Terkeltaub RA. Gout: on the brink of novel therapeutic options for an ancient disease. Arthritis Rheum. 2004;50(8):2400-2414.
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/41372 | - |
dc.description.abstract | 研究目的:尿酸與痛風發生頻率的相關性,已有確切的流行病學文獻支持。同時也有研究進一步報告指出具有痛風的病史,較有冠心病更易於導致心血管疾病的死亡。所以學者乃由尿酸與痛風之間的強烈相關性,進而揣測尿酸與心血管疾病之間的可能相關性。雖然目前這種相關性在高危險族群中,已較為確立,但是尿酸在一般人群中是否是一個心血管疾病的危險因子,仍具爭議。
此外雖然目前教科書上對於高尿酸血症與痛風的診斷,已使用明確的血尿酸濃度切點,但是有關尿酸濃度與痛風發作的關係的診斷學數據,卻尚未有大型人群調查資料可資佐證。 所以本研究(1)旨在決定不同血尿酸濃度預估痛風發作危險的可行性,期望能更適切的定義痛風疾病診斷的尿酸篩檢濃度,並建立未來痛風疾病的預防與治療目標指引。(2)評估一般民眾的血尿酸濃度、高尿酸血症(血尿酸濃度大於7 mg/dl),與全死亡率以及各種不同心血管疾病死亡的因果時序相關性。 研究方法:這是一個前瞻性的世代研究,使用台灣美兆健診中心的資料(1)研究十八歲以上體檢病人,尿酸與痛風之間的相關性。(2)研究三十五歲以上體檢病人中,尿酸與心血管疾病的相關性。前者(1)的追蹤結果是根據台灣的健保資料檔,並定義痛風為(甲)至少兩次的一般科醫師或風濕科專科醫師的診斷登記為屬於痛風的ICD或A碼。(乙)同時候的醫師處方也開立有秋水仙與降尿酸的藥物。以此針對血尿酸濃度的增加來評估痛風發作的相關危險性。後者(2)的追蹤結果是根據台灣的國家死亡登記檔,比較血尿酸濃度的增加對於全死亡率、及各種心血管死亡率的相關危險性。本研究分別得到中央研究院與中國醫藥大學的人體試驗委員會同意,並使用COX比例危害迴歸模型,以及統計軟體SAS 9.01版 (SAS Institute, Cary, NC)作為分析工具。 研究結果:本研究從1994年到96年的原始美兆健診中心的資料檔案共取得146,900筆(男性67,954筆,女性 78,946筆) 的資料,經過排除不適當的資料,得到研究(1)共有132,556筆大於十八歲的參加者資料(男性60,181筆,女性 72,375筆)進入分析,平均追蹤時間為7.31年,其間共有1,606 筆(男性1,341筆,女性265筆) 的痛風診斷。經估計痛風的標準年發生率為每千人有1.69 人年。經採用接受操作特徵曲線(ROC curve)方式推測得血尿酸濃度對於痛風預測最高敏感度與特定度的極限值估計,男性為7.5 mg/dl,女性為6.0 mg/dl。並採用人口可歸因危險百分比分析,顯示血尿酸濃度在6 mg/dl 以上可以解釋85.4%的男性痛風,與血尿酸濃度在4.5 mg/dl以上可以解釋85.2%的女性痛風。 研究(2)則有90,393筆大於三十五歲參加者(男性67,954筆,女性 78,946筆)的資料進入分析,平均追蹤時間為8.2年,共有5,427個死亡,其中包括心血管疾病死亡1,151人(21.2%)。藉由比例危害迴歸模型以及進一步校正相關干擾因子如:年齡、性別、身體質量比、高膽固醇症、高三酸甘油酯症、糖尿病、高血壓、抽菸與喝酒等,來估計血尿酸對心血管疾病的危險風險比。結果發現高尿酸血症與全死亡率、心血管疾病、與缺血性腦中風死亡率的危險風險比分別是1.16 (p <0.001)、1.39 (p <0.001)、與1.35 (p =0.02)。這種相關危險性不僅出現在高血壓(1.44, p <0.001)或糖尿病(1.64, p <0.001)等高危險群中,即連低風險的族群中,尿酸對全死亡率、及心血管死亡率的危險風險比也分別是1.24 (p =0.02)與1.48 (p =0.16)。 研究結論:我們在此前瞻性人群調查研究中發現,在不同性別的血尿酸濃度,對於痛風的發作預測,可能有不同的篩檢與預防極限值。並且在本研究中我們也發現高尿酸血症不僅在台灣的一般民眾中是全死亡率、以及心血管疾病、缺血性中風死亡率的一個獨立危險因子,這同時也獨立影響及於高危險族群,與潛在的低風險的族群。這個發現在臨床上應用的可行價值仍須待進一步的探討與研究。 | zh_TW |
dc.description.abstract | Objective. The association between the serum uric acid (sUA) level and the frequency of gout attack has been documented in epidemiologic reports. Gout was reported as a predisposing factor for cardiovascular disease (CVD) mortality. A relationship between sUA and CVD was thus speculated due to a strong association between sUA and gout. Although this association in high-risk groups has been documented, in general population it was yet undetermined. Besides, while we understand a definition of sUA level on hyperuricemia and gout diagnosis has been documented in the textbook, the prospective research to report a risk threshold of sUA for the occurrence of gout is still limited. Therefore the objectives of this study were aimed (1) to determine the risk of gout in relation to sUA levels and to find an optimal control level for gout prevention, and (2) to assess the temporal association between sUA level, hyperuricemia (sUA level >7 mg/dl), and mortality of all-cause and CVD in the general population.
Methods. A prospective cohort study of the association between sUA and gout on >18 years old participants, and of the association between sUA and mortality on >35 years old subjects, was conducted using data from the MJ Health Screening Centers in Taiwan. The formal sub-study used outcome follow-up data from the National Health Insurance and the latter from the National Mortality Registry in Taiwan. In the formal, criteria for gout diagnosis consisted of (1) A-code or ICD-code of gout assigned during at least two visits to physicians or rheumatologists, and (2) simultaneous prescription of colchicine and urate-lowering drugs. Likewise, the risk of gout was estimated with respect to sUA levels. In the latter sub-study, mortality from all causes, total and respective CVD were compared according to increasing sUA levels. Cox proportional hazard model was used for analysis in both sub-studies which were approved either by the Institutional Review Board of Academia Sinica, Taipei, Taiwan, or by the Institutional Review Board of the China Medical University Hospital. The statistical software SAS version 9.01 (SAS Institute, Cary, NC) was used for analysis. Results. Data from 146,900 participants (67,954 men and 78,946 women) of MJ Health Screening Center from 1994 to 1996 were retrieved for analysis. In the formal sub-study on gout, there were a total of 132,556 individuals (60,181 men and 72,375 women) included in the analysis, with a mean follow-up of 7.31 years. Among them, 1,606 (1,341 men and 265 women) were diagnosed with gout. The standardized overall annual incidence of gout was 1.69 cases per 1,000 person-years. Using the receiver operating characteristic plot method to maximize sensitivity and specificity for predicting gout, the most appropriate sUA thresholds were 7.5 mg/dl for men and 6.0 mg/dl for women. Population-attributable risk analysis revealed that 85.4% of male and 85.2% of female incident gout were attributable to sUA levels | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T00:17:25Z (GMT). No. of bitstreams: 1 ntu-98-D91842001-1.pdf: 938561 bytes, checksum: b38552e5120aedd6ca29563e81619d8f (MD5) Previous issue date: 2009 | en |
dc.description.tableofcontents | Table of Contents
口試委員會審定書…………………………………………II 誌謝…………………………………………………………III 中文摘要……………………………………………………IV 英文摘要……………………………………………………VII Chapter 1、BACKGROUND AND SIGNIFICANCE…………….……..1 1-1. Hyperuricemia………………..…….……….………….………….....1 1-2. Gout……....................................................................….…….3 1-3. Inter-relations among Hyperuricemia, Gout, Metabolic Syndrome and Cardiovascular Diseases……...............................................….…7 1-4. Cohort Studies…………………………………………………..…….16 1-5. Unresolved Questions...................................................................................19 Chapter 2、 OBJECTIVES..………………………………………………….......26 Chapter 3、PATIENTS AND METHODS……………………………………….. 27 3-1.Study design…………………………………………………………….27 3-2.Data collection and variables of interest………………………28 3-3. Follow-up and end-points…………………………………………29 3-4. Statistical analysis…………………………………………….30 Chapter 4、RESULTS……………..……………………………………………….33 Part I Study of Association between Serum Uric Acid and Gouty arthritis…………………………………………………………………..33 4-1-1. Baseline characteristics and comorbidities.……..………….…..33 4-1-2. Age, gender, serum uric acid and incident gout.……..…………34 4-1-3. Diagnostic characteristics of serum uric acid level in predicting incident gout. ……………………………………………………….…35 4-1-4. Population-attributable risk of incident gout at various levels of serum uric acid.………..……………………………………………….36 Part II Study of Association between Serum Uric Acid and Cardiovascular Mortality………………..……………………….…….37 4-2-1 Participant characteristics…………………..…………..…….…...37 4-2-2. Effect of hyperuricemia in all patients……………………….….37 4-2-3. Effect of hyperuricemia in high-risk (patients with hypertension and diabetes) and low-risk subgroups…………….………..…….….38 4-2-4 Sex Effect.…………………………………………………….39 Chapter 5、DISCUSSION…………...…………………………………..………….41 Part I. Study of Association between Serum Uric Acid and Gouty Arthritis………………………………..………….………………..……41 Part II Study of Association between Serum Uric Acid and Cardiovascular Mortality…..……..…….……………………………..46 Chapter 6、CONCLUSIONS……………………………………………..…..……50 Tables、 Table 1、Causes of hyperuricemia…………………………………………22 Table 2、 Summary of most recent prospective cohort studies examining the association between serum uric acid and cardiovascular outcomes among high-risk patients.…..........….…23 Table 3、 Summary of most recent prospective cohort studies that showed no association between sUA and cardiovascular outcomes in the general population...........................................................…24 Table 4、Summary of most recent prospective cohort studies that showed a positive association between serum uric acid and cardiovascular outcomes in the general population...................…25 Table 5. Baseline characteristics of the participants in the MJ Health Screening Center, stratified by gender (N=132,556)……………......…..52 Table 6. Baseline characteristics of MJ participants who developed gout versus those who did not……………………………………………...………...53 Table 7. Relative risks of each metabolic risk factor on the occurrence of gouty arthritis, stratified by genders……………………………………...……..54 Table 8. Baseline characteristics of the participants in the MJ Health Screening Center, stratified by gender.............................................................55 Table 9. Risk of hyperuricemia or per unit increase in SUA on mortality of all-cause, and various types of cardiovascular diseases. (n = 89,469)…..............................................................................................................56 Figure、 Figure 1, Relationship between incidence (per 1,000 person-years) of gout and serum uric acid levels by gender and by age. Incidence estimates and 95% confidence intervals are provided…………….…..57 Figure 2, Hazard ratios of gout attack comparing higher serum uric acid quartiles to the lowest quartile, stratified by gender. There are 1,606 (1,341 men and 265 women) gout events occurred in 132,556 participants (60,181 men and 72,375 women). ……………....………..58 Figure 3, Sensitivity, specificity, predictive values, and population- attributable risk by various levels of baseline serum uric acid Abbreviation: SEN: sensitivity; SPE: specificity; PPV: positive predictive value; NPV: negative predictive value; PAR: population attributable risk……………………………………………………...…………..59 Figure 4. Survivorship from total cardiovascular disease (CVD) mortality, stratified by increasing serum uric acid levels from a mean (SD) of 8.2 (1.3) years follow-up of the MJ health examinees….....................................................................................................…60 Figure 5. Hazard ratios (HRs) of hyperuricemia (serum uric acid >7 mg/dl) on mortality from (A), cardiovascular disease (1,151 events) and (B), all-causes (5,427 events), for all examinees (n = 90,393) and for patients with hypertension (n = 29,421) and diabetes (n = 7,899)…................................................................................................................61 Figure 6. Respective cardiovascular disease (CVD) mortality rates (A and B) and hazard ratios (C and D) according to serum uric acid (sUA) level quartiles (A and C) and ordered sUA categories (B and D) in both sexes..............................................................................................................62 REFERENCES…………..…………………………………...……………63 | |
dc.language.iso | en | |
dc.title | 高尿酸血症與痛風關節炎及心血管疾病死亡關係
之前瞻性風險研究 | zh_TW |
dc.title | A Prospective Study of Hyperuricemia on
Gouty Arthritis and Mortality of Cardiovascular Disease | en |
dc.type | Thesis | |
dc.date.schoolyear | 97-2 | |
dc.description.degree | 博士 | |
dc.contributor.coadvisor | 李文宗(Wen-Chung Lee) | |
dc.contributor.oralexamcommittee | 周昌德(Cheng-Teh Chou),余家利(Chia-Li Yu),周碧瑟(Pesus Chou),簡國龍(Kuo-Liong Chien),孫建安(Chien-An Sun) | |
dc.subject.keyword | 尿酸,高尿酸血症,死亡率,心血管疾病,痛風,比例危害迴歸模型., | zh_TW |
dc.subject.keyword | serum uric acid,hyperuricemia,mortality,cardiovascular disease,gout., | en |
dc.relation.page | 72 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2009-05-19 | |
dc.contributor.author-college | 公共衛生學院 | zh_TW |
dc.contributor.author-dept | 流行病學研究所 | zh_TW |
顯示於系所單位: | 流行病學與預防醫學研究所 |
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