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研究生:許維志
研究生(外文):Wei-Chih Hsu
論文名稱:糖尿病周邊神經與自律神經病變盛行率、發生率與存活分析的社區研究
論文名稱(外文):Prevalence、Incidence and Survival Analysis of Somatic andAutonomic Diabetic Neuropathy in Community-Based Studies
指導教授:陳秀熙陳秀熙引用關係
指導教授(外文):Tony Hsiu-Hsi Chen
學位類別:博士
校院名稱:國立臺灣大學
系所名稱:預防醫學研究所
學門:醫藥衛生學門
學類:醫學學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:英文
論文頁數:131
中文關鍵詞:糖尿病併發症自律神經周邊神經流行病學
外文關鍵詞:Diabetic complicationautonomic neuropathyperipheral neuropathyepidemiology
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背景:
由於糖尿病盛行率日增,糖尿病併發症導致病患個人、家庭與社會的重大負擔。因此,進行社區型態的早期糖尿病神經病變流行病學研究,及早確認糖尿病神經病變個體以及神經病變相關因子,以及估算未來糖尿病神經病變對醫療和經濟的可能衝擊,有助於照護計畫擬定與政策參考。

目的:
進行社區型態的糖尿病神經病變流行病學研究,目的為早期確認周邊神經病變與自律神經病變陽性個案,調查社區糖尿病神經病變發生率與盛行率,相關因子,與存活分析等研究。

方法:
本研究利用基隆、馬祖兩個社區篩檢資料進行分析。基隆世代為一大型社區,因此研究設計採用兩階段篩檢模式。兩階段模式中,第一階段先採用18題神經症狀評量問卷詢問,其結果異常者在第二階段以神經傳導測量工具進行檢測。為測量問卷效度,首先隨機邀請121名糖尿病患者同時接受問卷及神經傳導檢查,隨後再以587名個案進行主要研究。與糖尿病神經病變相關危險因子研究包括:飯前血糖、糖化血色素、體重質量比、視網膜病變有無、年齡、性別、罹患糖尿病年數、總膽固醇及三酸甘油脂等。

馬祖世代為小型社區,因此針對所有糖尿病患者利用周邊神經病變與自律神經病變研究。周邊神經病變以神經傳導儀器進行,自律神經病變研究則以五分鐘心電圖紀錄進行心律變異性的測量。

研究主題包含:(1)在盛行率調查方面,以馬祖世代進行不同類型糖尿病神經病變(周邊神經與自律神經病變);此外利用基隆世代建立於2001年的兩階段研究,應用貝氏方法分別以驗證資料和文獻資料作為prior,校正main study的盛行率。(2)糖尿病神經病變發生率研究是利用基隆世代篩檢神經病變結果為陰性的對象,連結至2004年12月31日止的門診就醫資料,藉以得到神經病變發生與否與發生時間,並依據研究世代的總人年數,計算基隆地區糖尿病神經病變的發生率。(3)存活分析研究對象分為兩部分,第一是針對參加糖尿病照護網的708名病患,連結至2006年12月31日的全民健保死亡檔,調查死亡人數和死亡原因;第二部份是針對326位參加神經傳導測試檢查的病患,同樣調查死亡人數和死亡原因。在全因死因和糖尿病相關死亡的存活分析研究中,以神經病變存在與否分層分析,藉以探討糖尿病神經病變對於存活狀態的影響。(4)分別就糖尿病周邊神經與自律神經病變出現與否、以及兩組存活分析研究的對象,進行相關因子的調查。(5)利用上述流行病學調查的參數,包含盛行率、發生率、糖尿病相關與非糖尿病相關死亡率等,利用蒙地卡羅模擬與馬可夫氏鏈方法,模擬1000位糖尿病病患十年後的流行病學資料,藉以預測將來社會和醫療的負擔。

結果:
(1)盛行率調查部份,在馬祖地區143位血糖異常個案中,有133位民眾完成神經傳導檢查。其中12位(9.0%)為神經病變確診個案、27位(20.3%)為神經病變可能個案、94位(70.7%)為正常個案。在自律神經部份,對應的數據分別為17(14.4%)、64(54.2%)、 37(31.4%)。貝氏方法進行的盛行率研究,以驗證資料作為prior,神經病變盛行率為29.7%;以文獻資料作為prior,神經病變盛行率為25.5%。(2)糖尿病神經病變發生率方面,共有326位病患在2001年的篩檢中接受神經傳導檢查,218位檢查結果正常。連結2004年12月31日為止的全民健保門診檔,有 28名出現周邊神經病變診斷碼,三名死亡、160名正常,另外有27名在篩檢活動前已有周邊神經病變診斷碼。糖尿病神經病變發生率為4.8每百人年,調整篩檢前已有診斷碼的病人後,發生率為5.5每百人年。由盛行率和發生率,可計算出糖尿病神經病變停留期間為9.0-10.3年。(3)同時進行的兩種周邊神經與自律神經病變的相關因子不同。在多因子分析中,收縮壓與飯前血糖值和周邊神經病變有關,而自律神經病變則無統計顯著的相關因子。(4)
基隆地區708位參加糖尿病神經病變篩檢的民眾中,至2004年12月31日為止,共有93位民眾死亡,年齡(HR=1.06),男性(HR=0.38),身體質量指數(HR=0.90),尿素氮(HR=0.92),肌酸酐(HR=6.92),心血管和腦血管疾病病史(HR=2.25)為多因子分析的顯著相關變項。至於糖尿病相關死亡率,年齡(HR=1.06),肌酸酐(HR=7.97),心血管和腦血管疾病病史(HR=2.99)為顯著相關變項。
針對326位接受神經傳導檢查的糖尿病病患分析,糖尿病神經病變是全因死亡率中最強的因子,也是糖尿病相關死亡率次強的因子。在選擇模式中,糖尿病神經病變(HR=4.38), 飯前血糖值(HR=1.01) 、肌酸酐(HR=13.23)和膽固醇(HR=0.99)為全因死亡率的顯著因子;糖尿病神經病變(HR=5.69), 飯前血糖值(HR=1.01), 血色素(HR=0.70), 尿素氮(HR=0.84)和肌酸酐(HR=26.99)為糖尿病相關死亡率的顯著的因子。就追蹤5年死亡率而言,糖尿病神經病變存在與否對全因死亡和糖尿病相關死亡在Kaplan-Meier 曲線都呈現統計顯著差異。(5)利用蒙地卡羅模擬與馬可夫氏鏈方法,模擬1000位糖尿病病患十年後的流行病學資料,發現糖尿病神經病變盛行率由32.4%增加至59.7%。合併周邊神經病變患者,在糖尿病相關死亡(14.7% v.s 3.0%)和非糖尿病相關(9.2% v.s 3.0%)預估死亡率,均高於沒有周邊神經病變的病患。

結論:
本論文利用社區篩檢研究,糖尿病神經病變的盛行率、發生率、存活分析、相關因子與電腦模擬未進行針對研究。第二型糖尿病周邊神經病變盛行率在基隆與馬祖兩地區約為30%,自律神經病變盛行率高達兩倍。兩種類型的神經病變的相關因子不同,因此可以分別針對危險因子進行介入。合併糖尿病神經病變的患者,在全因死亡與糖尿病相關死亡的研究中,校正其他危險因子後,仍然是顯著的預測死亡因子。蒙地卡羅模擬十年後,神經病變的盛行率增加將近兩倍,將造成重大的醫療和社會負擔。因此,對於糖尿病併發症,尤其是神經病變的防治,需仰賴於早期偵測、嚴格血糖監控與治療、以及生活模式改正。對於糖尿病神經病變的篩檢效益,包括成本效益和成本利益分析,需要進一步進行以探討。
Background:
Because the prevalence of diabetes is increasing, the diabetes-related complications, including macrovascular and microvascular complications, lead to significant medical and economic burdens to patients, their families and whole society. Therefore, early detection and identification of complications among diabetic patients in community and intervention for modification of risk factors are important. Regarding to microvascular complications, the epidemiological studies of neuropathy have been rarely addressed in the literature.

Purpose:
This thesis aimed to conduct a series of community- based epidemiological studies for diabetic neuropathies, including somatic sensorimotor and autonomic neuropathy. These studies encompassed prevalence rate, incidence rate, important correlates affecting the occurrence of neuropathies and the sequel to mortality, survival analysis and computer simulation of diabetic neuropathies in the community setting.

Materials and Methods:
Patients enrolled in this thesis were from two community-based integrated screening programs in Keelung and Matsu. The Keelung cohort included a large numbers of participants, so a two-stage design was performed for identifying subjects with diabetic neuropathy. The first step in the two-stage study design used the Neurological Symptom Score (NSS) questionnaire to identify positive cases. These positive cases were further confirmed by nerve conduction tests in the second stage. A validation study was conducted for detecting the sensitivity, specificity of questionnaire. Another 587 diabetics were selected for main study. Subjects who screened positive in the first stage were referred to nerve conduction test for confirmation. Potential risk factors were assessed, including fasting plasma glucose, HbA1c, body mass index, retinopathy, age, sex, diabetic duration, total cholesterol, triglyceride, hemoglobin and life styles.

The second cohort, Matsu, is a small community. Therefore, all potential subjects with somatic sensorimotor and autonomic neuropathy were investigated. The somatic neuropathy was diagnosed by nerve conduction tests and the autonomic neuropathy was confirmed by 5-min resting electrocardiograph for heart rate variability.

This thesis consists of :(1)investigating prevalence of somatic and autonomic neuropathy at Matsu cohort; besides, Bayesian analysis, using validation data and publications data as prior, was employed to estimate the prevalence rate; (2)incidence rate of diabetic neuropathy was estimated from those who were found to be free of diabetic neuropathy at screening programs in 2001. Information about the time and diagnosis of peripheral nerve disorders at outpatient clinics after screen activity was obtained till the end of 2004 from National Health Insurance;(3)correlates of somatic and autonomic neuropathy were investigated;(4)survival analysis was performed on 708 diabetic patients and 326 diabetic patients who accepted nerve conduction study in 2001. Those patients were linked to National Health Insurance till the end of 2006, information of date and cause of death can be gathered for deceased. Kaplan-Meier test was done by the presence of somatic neuropathy or not. Important correlates and life styles for predicting all-cause and diabetes-related mortality were also studied;(5)Monte-Carlo simulation was used to predict the disease burden. The disease course of the 1000 patients in 10 years was randomly assigned.

Results:
(1)A number of 143 persons was found to have high fasting plasma glucose (>110 mg/dl) or with past history of type 2 diabetes in Matsu cohort. For 133 subjects who accepted NCS, 12 subjects (12/133=9.0%) were categorized into definite somatic neuropathy, 27 subjects 27/133=20.3%) were probable somatic neuropathy and 94 subjects (94/133=70.7%) were classified as no somatic neuropathy. Among 118 subjects who completed validated heart rate variability test, results of SDNN consist of : 17(17/118=14.4%)diabetics was categorized into low SDNN level, 64 (54.2%) patients were middle SDNN and 37(31.4%)patients were high SDNN level. (2) Among of the 326 diabetic patients who accepted nerve conduction study, 218 patients were classified as no somatic neuropathy in 2001. After linking to outpatient clinics dataset of National Health Insurance, 28 subjects were diagnosed as having peripheral nerve disorders till the end of 2004. Three of these 218 patients died, and 160 patients remained asymptomatic for peripheral neuropathy. Besides, a number of 27 had diagnosis of peripheral nerve lesion already before the screening date. The incidence rate of diabetic neuropathy was 4.8 per hundred person years. After adjusted for the 27 already existed cases before screening among 218 cases, the incidence rate was 5.5 per hundred person years. Because prevalence rate of diabetic neuropathy was 28.46~36.30%, the duration of developing symptomatic diabetic neuropathy was 7.2-10.3 years.(3)Correlates associated with somatic sensorimotor and autonomic neuropathies in pre-diabetic and diabetic subjects are different. In multivariate analysis, systolic blood pressure (OR=1.07 ; 95% CI=1.00-1.14) and fasting blood glucose (OR=1.07; 95% CI=1.03-1.11) accounted for somatic sensorimotor neuropathies where as no significant factors were found in autonomic neuropathy group. A total of 93 subjects died among 708 diabetic patients after 5-year follow up. Among these 708 diabetic patients, 326 patients who accepted nerve conduction study for screening somatic neuropathy, a total of 44 patients died. The statistically significant correlates for all-cause mortality in 93 deceased were: age(HR=1.06),male sex(HR=0.38),BMI(HR=0.90),BUN (HR=0.92),creatinine(HR=6.92),prior cardio-and cerebrovascular diseases(HR=2.25)in multivariate analysis. For diabetes-related death, the statistically significant correlates were: age(HR=1.06),creatinine level(HR=7.97),prior cardio- and cerebrovascular diseases (HR=2.99). Targeting the 326 subjects with nerve conduction tests, diabetic neuropathy is the strongest predictor for all cause mortality and the second strongest predictor for diabetes-related mortality, next to prior cardio-/cerebrovascular disease in univariate analysis. In selected model, presence of diabetic neuropathy (HR=4.38), fasting glucose(HR=1.01) and creatinine level (HR=13.23)and serum cholesterol(HR=0.99) remained statistically significant for all-cause mortality. For disease-related mortality, presence of neuropathy(HR=5.69), fasting glucose(HR=1.01), hemoglobin(HR=0.70), serum BUN (HR=0.84)and creatinine(HR=26.99) levels are statistically significant. (4)Kaplan-Meier curves during the 5 years of follow up showed that diabetic neuropathy was a statistically significant factor for all-cause (p<0.001)and diabetes-related mortality(p<0.001)by log-rank test. (5)By simulated cohort, 59.7% of diabetic patients will progress to somatic neuropathy after 10-year follow up. For patients with somatic neuropathy, 14.7% of diabetic patient will die of diabetes-related causes and 9.2% of these will die of non-diabetes related causes. For patients without somatic neuropathy, 3% of these will die of diabetes-related causes and also 3% will die of non-diabetes related causes.
.
Conclusion:
The present thesis provided an insight into estimating the prevalence rates, incidence rate, survival analysis, important correlates and medical burdens of diabetic neuropathy, including both types of somatic sensorimotor and autonomic neuropathies, by using a population-based screening program. We finds that the prevalence rates of somatic neuropathy in type 2 diabetes were approximate 30% in Keeling and Matsu community and autonomic neuropathy even doubled this figure. The incidence rate of developing diabetic neuropathy was 4.8-5.5 per hundred-person years. Correlates of both types of neuropathy and for predicting mortality were different. Somatic neuropathy is an independent risk factor for all-cause and diabetes-related mortality. After 10-years’ time in simulation study, prevalence rate of somatic neuropathy will be doubled among diabetic patients. The high prevalence rate will cause great medical and economic burdens on patient, family and whole society. Prevention of diabetic complications, and diabetic neuropathy in particular, were dependent on early detection, monitor and control blood sugar strictly and modification of life style in these vulnerable subjects. Screening programs for diabetic neuropathy, including cost-effective and cost-benefit analysis, should be carried out in the future for identifying the benefits in public health.
Abstract IV
中文摘要 XI
I. Introduction 1
II. Literature Review 4
1. Diabetic Neuropathy 4
2. Consensus of Investigation Methods for Diabetic Neuropathy 6
3. Utilization of Diagnostic Methods for Diabetic Neuropathy 8
4. Diabetic Autonomic Neuropathy 11
5. Epidemiological Studies 16
6. Comments 20
III. Material and Methods 22
1. Study Population 22
2. Two-Stage Screening Model 25
3. Diagnostic Equipments 27
4. Prevalence Rate of Diabetic Neuropathy 30
4-1. Prevalence rate of Somatic and Autonomic Neuropathy in Pre-diabetic and Diabetic Patients 30
4-2. Bayesian Approach to Estimating Prevalence Rate using Two-Stage screening program 32
5. Incidence Rate of Diabetic Neuropathy 41
6. Correlates of somatic neuropathy and autonomic neuropathy 42
7. Survival Analysis of Somatic Diabetic Polyneuropathy 43
8. Projection of Medical Burden of Diabetic Neuropathy 45
IV. Result 48
1.Prevalence Rate of Diabetic Neuropathy 48
1.1 Prevalence of Somatic and Autonomic Neuropathy 48
1.2 Bayesian Approach to Estimating Prevalence Rate using Two-Stage screening program 50
2. Incidence Rate of Somatic Sensorimotor Polyneuropathy 53
3. Correlates of Somatic Sensorimotor Polyneuropathy and Autonomic Neuropathy 55
4. Survival Analysis of Diabetic Patients and Patients with Screening for Diabetic Neuropathy by Nerve Conduction Studies 56
5. Projection of Medical Burden of Diabetic Neuropathy 59
V. Discussion 60
1. Prevalence Survey with two-stage Method 60
2.Prevalence of Somatic and Autonomic Neuropathy with one-shot Screening Method 63
3. Incidence of Diabetic Neuropathy 69
4. Correlates of Diabetic Neuropathy 70
5. Survival analysis and Somatic Neuropathy as a Significant Predictor for Mortality 71
4. Projection of Medical Burden of Diabetic Neuropathy 75
VI. Conclusion 77
VII. Reference 79
VIII. Figures 92
Figure 1(a) Flow chart of the two-stage screening model 92
Figure 1(b) Flowchart of prevalence, incidence, and survival of diabetic neuropathy 93
Figure 2 The acyclic graphic model for the prevalence of somatic neuropathy among diabetic patients 94
Figure 3 The Markov model for the four-stage course of diabetic neuropathy in simulation study 95
Figure 4 The decision tree for the simulation study 96
Figure 5(a) Little confidence on prior of sensitivity. 97
Figure 5(b) Heavy confidence on prior of sensitivity. 98
Figure 6(a) 5-year All-cause Mortality 99
Figure 6(b) 5-year Disease-specific Mortality 100
Figure 6(c) Comparison of identifying cases at screen and at NIH database for 5-year All-cause Mortality 101
Figure 7 Mortality of Monte Carlo Distributions 102
IX. Tables 107
Table 1 Literature Reviews for Prevalence Rate of Diabetic Neuropathy as Publication Prior 107
Table 2 Data from the main and validation study 110
Table 3 ICD-9 for Peripheral Neuropathy 111
Table 4 Parameters used in the simulation study 112
Table 5 Prevalence of somatic and autonomic neuropathy 113
Table 6 Estimates by Different Priors 114
Table 7 Estimates of Sensitivity、Specificity and Prevalence from Different Viewpoints 115
Table 8 Estimated results from main data 116
Table 9 Comparison of correlates related to somatic sensorimotor and autonomic neuropathy 117
Table 10 Multivariate analysis of somatic sensorimotor and autonomic neuropathy 119
Table 11 Number and Cause of Death among 708 Diabetic Patients 120
Table 12 Number and Cause of Death among 326 Diabetic Patients with Nerve Conduction Test 123
Table 13 Cox’s Regression Model for All-cause and Diabetes-related Mortality in 708 type 2 Diabetic Patients 125
Table 14 Cox’s Regression Model for All-cause and Diabetic-related Mortality in 326 type 2 Diabetic Patients with Nerve Conduction Test for Diabetic Polyneuropathy 128
X. Appendix 131
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