臺灣博碩士論文加值系統

背景：對於第一型糖尿病患（Type 1 Diabetes Mellitus, T1DM）而言，嚴重低血糖事件為主要的併發症之一，而過去研究已發現嚴重低血糖事件對於心血管疾病的風險有負面的影響，但大多研究對於第一型糖尿病的嚴重低血糖事件皆以有發生以及無發生來定義，僅有少數的研究針對嚴重低血糖事件的累積發生次數進行分組分析。本研究欲使用軌跡分析（Group-Based Trajectory Modeling, GBTM），合併嚴重低血糖事件的發生時機點以及發生次數多寡來探討其對於心血管疾病（Cardiovascular Disease, CVD）及全因死亡風險之相關性。
目的：本研究利用軌跡分析繪第一型糖尿病患者之嚴重低血糖發生軌跡，並分析不同嚴重低血糖事件軌跡型態病人之特性，以及不同軌跡第一型糖尿病患者發生心血管疾病與全死因之風險。
方法：本研究使用台灣全民健康保險申報資料，擷取1998年至2003年間出現第一型糖尿病診斷的患者作為研究世代，接著從期間內第一次第一型糖尿病診斷的日期開始觀察4年，以每一年為區間，計算4個區間內嚴重低血糖事件發生次數，並據此進行軌跡分析。嚴重低血糖事件追蹤結束後，接著觀察其心血管疾病的發生至研究結束（2013年12月31日）。本研究採用群組化軌跡模式來描繪嚴重低血糖事件的軌跡，並利用Cox proportional hazard model，在控制人口學與共病後分析不同嚴重低血糖事件的軌跡對於心血管疾病與全因死亡的調整風險對比值（adjusted hazard ratio, aHR）及其95%信賴區間（confidence interval, CI）；也使用邏輯斯迴歸（Logistic regression）模式分析不同軌跡樣本之相關特性。
結果：本研究發現在四年之間的嚴重低血糖事件發生頻率大約可以分為三種軌跡型態，分別有：GROUP1早期低血糖高風險組（n=60）、GROUP2晚期低血糖高風險組（n=39）、以及GROUP3低血糖中等程度風險組（n=132）。於四年觀察期間未發生任何嚴重低血糖的樣本則被歸類為對照組CONTROL GROUP（n=8,919）。年齡較輕。以多元邏輯斯迴歸分析不同軌跡的樣本特性後發現∶相較於GROUP3，GROUP2的樣本顯著較輕（adjusted odds ratio（aOR）=0.927, P value=0.0006），CONTROL GROUP樣本年齡則是顯著較高（aOR=1.015, P value=0.0211）此外，相較於GROUP3，盛行個案被歸類為GROUP2的勝算則是顯著較低（aOR=0.048, P value〈0.0001）。Cox複迴歸分析發現，相對於CONTROL GROUP，GROUP1有較高的心血管疾病危害對比值（aHR=1.138, P=0.608），但GROUP2（aHR=0.153, P=0.061）與GROUP3（aHR=0.772, P=0.191）則是有較低的風險對比值，但前述風險對比值均未達統計顯著意義。在全死因風險差異的探討部分，本研究發現∶GROUP1（aHR=1.298，P value=0.272）及GROUP3（aHR=1.038，P value=0.822）較CONTROL GROUP有較高的死亡風險，而GROUP2（aHR=0.412，P value=0.126）則是有較低的死亡風險，但也皆未達到統計上的顯著意義。
結論：本研究利用軌跡分析將第一型糖尿病患的嚴重低血糖事件分成三組不同的軌跡，相較於未發生嚴重低血糖事件的控制組比較，三組不同軌跡樣本之心血管疾病或全因死亡有顯著的相關性。。由於本研究在觀察嚴重低血糖事件發生的四年期間將該期間內發生心血管疾病以及死亡樣本予以排除，因此可能會造成潛在的存活效應與選樣偏差問題，且能夠接受完整四年嚴重低血糖事件數觀察的人數並不多，導致部分軌跡組別的樣本數過少，而沒有足夠的統計檢力來探討不同軌跡樣本後續之心血管疾病與死亡風險。

Severe hypoglycemia is one of the major complications of Type 1 Diabetes Mellitus (T1DM), but little information has been available concerning frequency or trajectory of severe hypoglycemia events with T1DM. This study used Group-Based Trajectory Modeling technique to simultaneously consider timing and frequency of severe hypoglycemia events, which was used to associate with cardiovascular disease (CVD) risk and all-cause mortality. Data were retrieved from National Health Insurance Research Database. Patients with a diagnosis of T1DM between 1998 and 2003 were selected as the study subjects. The 4-year period following date of the first T1DM diagnosis was used to determine types of trajectory. All study subjects were then followed to December 31, 2013. Early high risk group (GROUP1), late high risk group (GROUP2) and moderate risk group (GROUP3) were identified. Patients who didn’t experience any severe hypoglycemia were defined as the CONTROL GROUP. Cox regression model showed that compared to CONTROL GROUP, GROUP1 was associated with an elevated adjusted hazard ratio (aHR) at 1.138 (P=0.608). However, GROUP2 and GROUP3 were associated with reduced CVD risk (aHR=0.153, P=0.061; aHR=0.772, P=0.191, respectively). Additionally, compared to CONTROL GROUP, GROUP1 and GROUP3 had higher risk of all-cause mortality, with aHR of 1.298 (P=0.272) and 1.038 (P=0.823), while GROUP2 was associated with a lower risk of all-cause mortality (aHR=0.412, P=0.126). We concluded compared with the CONTROL GROUP, the three types of trajectory were all not significantly associated with CVD risk or all-cause-mortality.

目錄
摘要 I
目錄 VII
表目錄 X
圖目錄 XI
第一章 前言 1
1.1 前言 1
1.2 研究目的 3
第二章 文獻回顧 4
2.1 第一型糖尿病介紹 4
2.2 第一型糖尿病的併發症 4
2.3 第一型糖尿病患發生嚴重低血糖後導致心血管疾病的文獻回顧 7
表2.1 第一型糖尿病患發生嚴重低血糖事件後導致心血管疾病之文獻回顧 9
2.4 軌跡分析 12
第三章 研究方法 14
3.1 資料來源 14
3.2 研究設計及樣本納入排除標準 14
3.2.1 研究設計 14
3.2.2 排除條件 14
3.3 研究對象定義與選取 15
3.3.1 第一型糖尿病患世代定義及選取 15
3.3.2 嚴重低血糖事件定義及選取 15
3.3.3 排除個案 15
3.3.4 新發生心血管疾病的定義及選取 16
3.3.5 控制變項之定義及選取 16
表3.1 各變項之診斷代碼 17
3.4 資料分析 19
3.4.1 嚴重低血糖事件軌跡分組 19
3.4.2 不同嚴重低血糖軌跡組別的樣本特性比較 19
3.4.3 不同軌跡與控制組樣本之心血管疾病風險差異 19
3.4.4 不同軌跡樣本之間的心血管疾病風險差異 20
3.4.5 不同軌跡與控制組樣本之全因死亡風險差異 20
3.4.6不同軌跡樣本之間的全因死亡風險差異 21
第四章 研究結果 23
4.1 研究樣本 23
4.2 嚴重低血糖事件之軌跡分析 23
4.3 不同軌跡樣本特性之多變量多元邏輯斯迴歸分析 24
4.4 不同軌跡與控制組樣本之心血管疾病風險差異 25
4.5 不同軌跡樣本之間的心血管疾病風險差異 26
4.6不同軌跡與控制組樣本之全因死亡風險差異 26
4.7 不同軌跡樣本之間的全因死亡風險差異 27
第五章 討論 28
5.1 研究主要發現 28
5.2 研究結果的比較與闡釋 28
5.3 研究優勢與研究限制 31
5.3.1 研究優勢 31
5.3.2 研究限制 32
第六章 結論 34
表4.1 各軌跡組別數的配適指標 35
表4.2 各組別之特性分佈 36
表4.3 不同軌跡樣本特性之多變量多元邏輯斯迴歸分析（以GROUP3為參考組） 39
表4.4 不同嚴重低血糖軌跡及對照組與心血管疾病發生風險相關性之迴歸分析 41
表4.5 各樣本組別於追蹤期間出現之心血管疾病及全因死亡人數 42
表4.6 不同嚴重低血糖軌跡及對照組與心血管疾病發生風險相關性之迴歸分析（競爭死因分析） 43
表4.7 三組嚴重低血糖軌跡樣本之心血管疾病風險相關性之迴歸分析 44
表4.8 三組嚴重低血糖軌跡樣本之心血管疾病風險相關性之迴歸分析（競爭死因分析） 45
表4.9 三組嚴重低血糖軌跡與控制組樣本之全因死亡風險迴歸分析 46
表4.10 三組嚴重低血糖軌跡樣本之全因死亡風險相關性之迴歸分析 47
參考文獻 50
附錄一、糖尿病共病嚴重度指標分類 55
附錄2.1 軌跡分析之不同軌跡組數型態及樣本數－兩組 58
附錄2.2 軌跡分析之不同軌跡組數型態及樣本數－四組 59
附錄2.3 軌跡分析之不同軌跡組數型態及樣本數－五組 60
附錄3 嚴重低血糖事件（有/無）與心血管疾病發生風險相關性之迴歸分析 61
附錄4 嚴重低血糖事件（累積次數分組）與心血管疾病發生風險相關性之迴歸分析 62
表目錄
表2.1 第一型糖尿病患發生嚴重低血糖事件後導致心血管疾病之文獻回顧 9
表3.1 各變項之診斷代碼 17
表4.1 各軌跡組別數的配適指標 35
表4.2 各組別之特性分佈 36
表4.3 不同軌跡樣本特性之多變量多元邏輯斯迴歸分析（以GROUP3為參考組） 39
表4.4 不同嚴重低血糖軌跡及對照組與心血管疾病發生風險相關性之迴歸分析 41
表4.5 各樣本組別於追蹤期間出現之心血管疾病及全因死亡人數 42
表4.6 不同嚴重低血糖軌跡及對照組與心血管疾病發生風險相關性之迴歸分析（競爭死因分析） 43
表4.7 三組嚴重低血糖軌跡樣本之心血管疾病風險相關性之迴歸分析 44
表4.8 三組嚴重低血糖軌跡樣本之心血管疾病風險相關性之迴歸分析（競爭死因分析） 45
表4.9 三組嚴重低血糖軌跡與控制組樣本之全因死亡風險迴歸分析 46
表4.10 三組嚴重低血糖軌跡樣本之全因死亡風險相關性之迴歸分析 47
附錄一、糖尿病共病嚴重度指標分類 55
附錄2.1 軌跡分析之不同軌跡組數型態及樣本數－兩組 58
附錄2.2 軌跡分析之不同軌跡組數型態及樣本數－四組 59
附錄2.3 軌跡分析之不同軌跡組數型態及樣本數－五組 60
附錄3 嚴重低血糖事件（有/無）與心血管疾病發生風險相關性之迴歸分析 61
附錄4 嚴重低血糖事件（累積次數分組）與心血管疾病發生風險相關性之迴歸分析 62
圖目錄
圖3-1 研究架構 22
圖4.1 研究樣本數流程圖 48
圖4.2 嚴重低血糖事件之軌跡圖 49

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