本研究的研究對象為腎病末期接受血液透析患者，且參與數量僅有
72 位，難以將研究結論據此外推至所有接受血液透析或者其他種類透析 的患者。若後續能將各類透析患者包含在內，並增加研究對象的數量，
對於 baPWV 的預測角色或許能更明確顯現，這是值得繼續努力的一個 方向。對於一般民眾，雖有探討 baPWV 與性別、年齡以及具冠心病危 險因子者之間的相關性，但針對無症狀的民眾，其 baPWV 與心律不整 之間的關聯，仍未能有系統及前瞻性的研究。
以醫療政策制定者而言，若能發展低成本的篩檢工具，早期自一般 民眾中診斷出高危險群，給予預防性的治療，可以降低罹病率及死亡 率，減少醫療資源的耗用，因此值得吾人繼續研究探討。
參考文獻
英文文獻：
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The 36th Annual Conference of the Japanese Association for Cerebro-cardiovascular Disease Control, japanese Association of Cardiovascular Disease Prevention Satellite Symposium: 2001
中文文獻：
林世崇. 高階心肺急救學. 立大圖書有限公司. 民 90.
林杰. 透析治療學. 合記圖書出版社. 民 89.
蔡安津，<接受血液透析之慢性腎衰竭患者之心律變異性分析>，台北醫學大學醫學 資訊研究所，碩士論文，民 91.7。
劉醇忠，<血液透析前後血鈣與血磷變化的研究>，美國西太平洋大學企管研究所，
碩士論文，民 93. 6。
2005 年台灣腎臟醫學會年會報告：2003 年度透析統計資料
行政院衛生署 (2004) 全民健康保險醫療費用支付標準，血液透析之編號 58001C 修 訂事宜：93 年 5 月 31 日衛署健保字第 0930020746 號函
附錄
表一、血液透析支付標準調整方案
透析人次 累進遞減點數 累進調整後點數 500 人次以下 0
以 4100 點計算 501--1000 人次 50
超過 500 人次以 4050 點計算 1001--1500 人次 100
超過 1000 人次以 4000 點計算 1501--2000 人次 150
超過 1500 人次以 3950 點計算 2001--2500 人次 200
超過 2000 人次以 3900 點計算 2501--3000 人次 250
超過 2500 人次以 3850 點計算 3001 人次以上 300
超過 3000 人次以 3800 點計算
表二、操作型定義
表三、Grading system of 24-hour Holter ECG
more in succession ) of three or more VPBs Class 5 : Early VPBs ( R on T )表五、非連續變項與心室心律不整之描述性分析
表七、連續變項與心室心律不整之間的 t 檢定結果
變項名稱 t 值 p
baPWV -7.01 <0.0001
年齡 -1.84 0.0702
透析年資 0.36 0.7182
鎂離子 1.11 0.2694
鉀離子 1.79 0.0778
鈣離子 0.43 0.6661
磷離子 1.57 0.1223
尿素氮 0.65 0.519
肌酸酐 0.13 0.8937
表八、baPWV 不設虛擬變項控制自變項羅吉斯回歸
變項名稱 Odd's ratio 95%信賴區間 卡方值 p
性別 33.336 1.846--602.042 5.6413 0.0175
年齡 1.035 0.936--1.146 0.4515 0.5016
透析年資 1.382 0.997--1.915 3.7798 0.0519
baPWV 0.992 0.987--0.996 11.8789 0.0006
鎂離子 4.26 0.205--88.675 0.8757 0.3494
鉀離子 2.158 0.672--6.930 1.671 0.1961
磷離子 1.408 0.767--2.586 1.2169 0.27
表九、baPWV 設虛擬變項控制自變項羅吉斯回歸
變項名稱 Odd's ratio 95%信賴區間 卡方值 P
性別 0.025 0.001--0.570 5.3511 0.0207
R1 <0.001 <0.001-->999.999 0.005 0.9437
R2 <0.001 <0.001--0.060 9.643 0.0019
R3 0.012 <0.001--0.265 7.8237 0.0052
年齡 0.938 0.844--1.042 1.4359 0.2308
透析年資 0.688 0.48--0.987 4.1212 0.0423
糖尿病 0.635 0.033--12.077 0.0913 0.7625
慢性腎病 1.627 0.153--17.321 0.1627 0.6867 高血脂症 50.099 0.334-->999.999 2.3428 0.1259
高血壓 0.033 <0.001--1.150 3.5442 0.0598 baPWV 0.00424 29.7160 <0.0001 18.9019 <0.0001 1.004 1.002--1.006
係數 -8.2743 18.9110 <0.0001
依此分析結果的最佳預測模型：
Y = (-8.2743) + 0.00424(baPWV) Y：心室心律不整的發生
表十一、baPWV 設虛擬變項控制自變項反向羅吉斯回歸
Summary of Backward Elimination Step Effect
Removed
DF Number In
Wald Chi-Square
Pr > ChiSq
1 R1 1 15 0.0052 0.9425
表十二、baPWV 設虛擬變項控制自變項反向羅吉斯回歸
預測值 Wald 卡方值 p Odd's Ratio 95%信賴區間 係數 -1.8326 11.5805 0.0007
R2 2.0333 8.4023 0.0037 7.639 1.932--30.206 R3 3.7297 20.6594 <0.0001 41.667 8.343--208.093 依此分析結果可以得到最佳預測模型：
Y = (-1.8326) + 20.333R2 + 3.7297R3 Y：心室心律不整的發生
R2：1800< baPWV ≦2200
R3：2200< baPWV
baPWV：臨床測量值
圖 1 PWV 計算依據動脈脈波傳遞的 距離除以時間差 ( Colin Co.Ltd, Komaki, Japan )
圖 2 baPWV 的計算公式 ( Colin Co.Ltd,
Komaki, Japan )
0 500 1000 1500 2000 2500 3000 3500
1 11 21 31 41 51 61 71
baPWV 線性 (baPWV)
●心室心律不整
圖 3 baPWV 與心室心律不整回歸分析趨勢圖形
連續變項與心室心律不整之間的 t 檢定結果
SAS T-test and Logistic Regression Analysis and Stepwise Logistic Regression Analysis Result and
Summary
T-Tests
Variable Method Variances DF t Value Pr > |t|
baPWV Pooled Equal 70 -7.01 <.0001 baPWV Satterthwaite Unequal 69.1 -7.00 <.0001
年齡 Pooled Equal 70 -1.84 0.0702
年齡 Satterthwaite Unequal 69.2 -1.84 0.0706
透析年資 Pooled Equal 70 0.36 0.7182
透析年資 Satterthwaite Unequal 65.9 0.37 0.7160
Mg Pooled Equal 70 1.10 0.2736
Mg Satterthwaite Unequal 64.8 1.11 0.2694
K Pooled Equal 70 1.79 0.0778
K Satterthwaite Unequal 69.6 1.80 0.0767
Na Pooled Equal 70 1.31 0.1942
Na Satterthwaite Unequal 56 1.29 0.2009
Ca Pooled Equal 70 0.43 0.6661
Ca Satterthwaite Unequal 69.9 0.43 0.6653
P Pooled Equal 70 1.58 0.1179
T-Tests
Variable Method Variances DF t Value Pr > |t|
P Satterthwaite Unequal 60.1 1.57 0.1223
BUN Pooled Equal 70 0.66 0.5136
BUN Satterthwaite Unequal 57.3 0.65 0.5190
Cr Pooled Equal 70 0.13 0.8937
Cr Satterthwaite Unequal 63.1 0.13 0.8946 Equality of Variances
Variable Method Num DF Den DF F Value Pr > F
baPWV Folded F 34 36 1.13 0.7230
年齡 Folded F 34 36 1.10 0.7715
透析年資 Folded F 36 34 1.88 0.0684
Mg Folded F 36 34 2.01 0.0433
K Folded F 36 34 1.30 0.4425
Na Folded F 34 36 2.63 0.0051
Ca Folded F 36 34 1.22 0.5649
P Folded F 34 36 2.09 0.0317
BUN Folded F 34 36 2.44 0.0096
Cr Folded F 34 36 1.76 0.0970
baPWV 不設虛擬變項控制自變項羅吉斯回歸
The SAS System
The LOGISTIC Procedure
Model Information
Data Set WORK.WORKNEW1
Response Variable Y Number of Response Levels 2 Number of Observations 72
Model binary logit
Optimization Technique Fisher's scoring
Probability modeled is Y=0.
Model Convergence Status
Convergence criterion (GCONV=1E-8) satisfied.
Model Fit Statistics
Criterion
AIC 101.758 73.064
SC 104.034 107.214
-2 Log L 99.758 43.064
Testing Global Null Hypothesis: BETA=0 Test Chi-Square DF Pr > ChiSq Likelihood Ratio 56.6936 14 <.0001
Score 37.8975 14 0.0005
Wald 14.4238 14 0.4186
Analysis of Maximum Likelihood Estimates
Parameter DF Estimate
Standard Error
Wald
Chi-Square Pr > ChiSq Intercept 1 1.0677 7.6907 0.0193 0.8896
性別 1 3.5066 1.4764 5.6413 0.0175
年齡 1 0.0347 0.0517 0.4515 0.5016
透析年資 1 0.3234 0.1664 3.7798 0.0519
baPWV 1 -0.00839 0.00243 11.8789 0.0006
鎂離子 1 1.4494 1.5488 0.8757 0.3494
鉀離子 1 0.7694 0.5952 1.6710 0.1961
磷離子 1 0.3422 0.3102 1.2169 0.2700
Analysis of Maximum Likelihood Estimates
Parameter DF Estimate
Standard Error
Wald
Chi-Square Pr > ChiSq
鈣離子 1 -0.0935 0.4042 0.0535 0.8171
Odds Ratio Estimates
Effect Point Estimate
95% Wald Confidence Limits
性別 33.336 1.846 602.042
年齡 1.035 0.936 1.146
透析年資 1.382 0.997 1.915
baPWV 0.992 0.987 0.996
鎂離子 4.260 0.205 88.675
鉀離子 2.158 0.672 6.930
磷離子 1.408 0.767 2.586
鈣離子 0.911 0.412 2.011
左心室肥厚 2.107 0.265 16.783
Odds Ratio Estimates
Effect Point Estimate
95% Wald Confidence Limits
糖尿病 1.945 0.099 38.226
慢性腎病 0.279 0.015 5.107
高血脂症 0.025 <0.001 2.403
高血壓 38.574 1.425 >999.999
冠心病 0.070 0.006 0.831
Association of Predicted Probabilities and Observed Responses
Percent Concordant 93.9 Somers' D 0.879 Percent Discordant 6.0 Gamma 0.879 Percent Tied 0.1 Tau-a 0.445
Pairs 1295 C 0.939
baPWV 設虛擬變項控制自變項羅吉斯回歸
The SAS System
The LOGISTIC Procedure
Model Information
Data Set WORK.WORKNEW1
Response Variable Y Number of Response Levels 2 Number of Observations 72
Model binary logit
Optimization Technique Fisher's scoring
Probability modeled is Y=0.
Model Convergence Status
Quasi-complete separation of data points detected.
Model Fit Statistics
Criterion
AIC 101.758 76.342
SC 104.034 115.046
-2 Log L 99.758 42.342
Testing Global Null Hypothesis: BETA=0 Test Chi-Square DF Pr > ChiSq Likelihood Ratio 57.4153 16 <.0001
Score 37.9765 16 0.0015
Wald 11.6572 16 0.7672
Analysis of Maximum Likelihood Estimates
Parameter DF Estimate
Standard Error
Wald
Chi-Square Pr > ChiSq Intercept 1 24.7221 10.3525 5.7027 0.0169
性別 1 -3.6822 1.5918 5.3511 0.0207
Analysis of Maximum Likelihood Estimates
Parameter DF Estimate
Standard Error
Wald
Chi-Square Pr > ChiSq
慢性腎病 1 0.4867 1.2068 0.1627 0.6867
Odds Ratio Estimates
Effect Point Estimate
95% Wald Confidence Limits
sex 0.025 0.001 0.570
R1 <0.001 <0.001 >999.999
R2 <0.001 <0.001 0.060
R3 0.012 <0.001 0.265
年齡 0.938 0.844 1.042
透析年資 0.688 0.480 0.987
糖尿病 0.635 0.033 12.077
Odds Ratio Estimates
Effect Point Estimate
95% Wald Confidence Limits
慢性腎病 1.627 0.153 17.321
高血脂症 50.099 0.334 >999.999
高血壓 0.033 <0.001 1.150
冠心病 25.744 1.443 459.178
Mg 0.213 0.010 4.540
K 0.313 0.083 1.180
Ca 1.097 0.481 2.504
P 0.625 0.322 1.215
左心室肥厚 0.403 0.040 4.053
Association of Predicted Probabilities and Observed Responses
Percent Concordant 94.3 Somers' D 0.886 Percent Discordant 5.7 Gamma 0.886 Percent Tied 0.0 Tau-a 0.449
Pairs 1295 c 0.943
baPWV 不設虛擬變項控制自變項羅吉斯逐步回歸
The SAS System
The LOGISTIC Procedure
Model Information
Data Set WORK.WORKNEW1
Response Variable Y Number of Response Levels 2 Number of Observations 72
Model binary logit
Optimization Technique Fisher's scoring
Probability modeled is Y=0.
Stepwise Selection Procedure Step 0. Intercept entered:
Model Convergence Status
Convergence criterion (GCONV=1E-8) satisfied.
Residual Chi-Square Test
Chi-Square DF Pr > ChiSq 37.8975 14 0.0005
Step 1. Effect baPWV entered:
Model Convergence Status
Convergence criterion (GCONV=1E-8) satisfied.
Model Fit Statistics
Criterion
AIC 101.758 67.189
SC 104.034 71.742
-2 Log L 99.758 63.189
Testing Global Null Hypothesis: BETA=0 Test Chi-Square DF Pr > ChiSq Likelihood Ratio 36.5688 1 <.0001
Score 29.7160 1 <.0001
Wald 18.9019 1 <.0001
Residual Chi-Square Test Chi-Square DF Pr > ChiSq
13.8965 13 0.3812
Summary of Stepwise Selection Effect
Step Entered Removed DF
Number In
Score Chi-Square
Wald
Chi-Square Pr > ChiSq
1 baPWV 1 1 29.7160 <.0001
Analysis of Maximum Likelihood Estimates
Parameter DF Estimate
Standard Error
Wald
Chi-Square Pr > ChiSq Intercept 1 -8.2743 1.9027 18.9110 <.0001 baPWV 1 0.00424 0.000976 18.9019 <.0001
Odds Ratio Estimates
Effect Point Estimate
95% Wald Confidence Limits
baPWV 1.004 1.002 1.006
Association of Predicted Probabilities and Observed Responses
Percent Concordant 88.1 Somers' D 0.762 Percent Discordant 11.9 Gamma 0.762 Percent Tied 0.0 Tau-a 0.386
Pairs 1295 c 0.881
baPWV 設虛擬變項控制自變項反向羅吉斯回歸
The SAS System
The LOGISTIC Procedure
Model Information
Data Set WORK.WORKNEW1
Response Variable Y Number of Response Levels 2 Number of Observations 72
Model binary logit
Optimization Technique Fisher's scoring
Probability modeled is Y=0.
Backward Elimination Procedure Step 0. The following effects were entered:
Intercept sex R1 R2 R3 VAR5 VAR6 var10new var11new var12new var13new var14new Mg K Ca P LVHnew
Model Convergence Status
Quasi-complete separation of data points detected.
Model Fit Statistics
AIC 101.758 76.342
SC 104.034 115.046
-2 Log L 99.758 42.342
Testing Global Null Hypothesis: BETA=0 Test Chi-Square DF Pr > ChiSq Likelihood Ratio 57.4152 16 <.0001
Score 37.9765 16 0.0015
Wald 11.6593 16 0.7671
Step 1. Effect R1 is removed:
Model Convergence Status
Convergence criterion (GCONV=1E-8) satisfied.
Model Fit Statistics
Criterion
AIC 101.758 79.918
SC 104.034 116.344
Model Fit Statistics -2 Log L 99.758 47.918
Testing Global Null Hypothesis: BETA=0 Test Chi-Square DF Pr > ChiSq Likelihood Ratio 51.8400 15 <.0001
Score 36.3455 15 0.0016
Wald 14.2150 15 0.5093
Residual Chi-Square Test Chi-Square DF Pr > ChiSq
3.9513 1 0.0468
Step 2. Effect Ca is removed:
Model Convergence Status
Convergence criterion (GCONV=1E-8) satisfied.
Model Fit Statistics
Criterion
Model Fit Statistics
SC 104.034 112.182
-2 Log L 99.758 48.032
Testing Global Null Hypothesis: BETA=0 Test Chi-Square DF Pr > ChiSq Likelihood Ratio 51.7260 14 <.0001
Score 36.2746 14 0.0009
Wald 14.4443 14 0.4172
Residual Chi-Square Test Chi-Square DF Pr > ChiSq
4.0765 2 0.1303
Step 3. Effect
慢性腎病is removed:
Model Convergence Status
Convergence criterion (GCONV=1E-8) satisfied.
Model Fit Statistics
Criterion
Model Fit Statistics
AIC 101.758 76.221
SC 104.034 108.094
-2 Log L 99.758 48.221
Testing Global Null Hypothesis: BETA=0 Test Chi-Square DF Pr > ChiSq Likelihood Ratio 51.5366 13 <.0001
Score 36.2216 13 0.0005
Wald 14.7184 13 0.3253
Residual Chi-Square Test Chi-Square DF Pr > ChiSq
4.1566 3 0.2450
Step 4. Effect
年齡is removed:
Model Convergence Status
Convergence criterion (GCONV=1E-8) satisfied.
Model Fit Statistics
AIC 101.758 74.531
SC 104.034 104.128
-2 Log L 99.758 48.531
Testing Global Null Hypothesis: BETA=0 Test Chi-Square DF Pr > ChiSq Likelihood Ratio 51.2264 12 <.0001
Score 36.1382 12 0.0003
Wald 14.7296 12 0.2566
Residual Chi-Square Test Chi-Square DF Pr > ChiSq
4.5690 4 0.3344
Step 5. Effect
糖尿病is removed:
Model Convergence Status
Convergence criterion (GCONV=1E-8) satisfied.
Model Fit Statistics
AIC 101.758 73.284
SC 104.034 100.604
-2 Log L 99.758 49.284
Testing Global Null Hypothesis: BETA=0 Test Chi-Square DF Pr > ChiSq Likelihood Ratio 50.4731 11 <.0001
Score 35.7976 11 0.0002
Wald 14.5808 11 0.2025
Residual Chi-Square Test Chi-Square DF Pr > ChiSq
5.2780 5 0.3829
Step 6. Effect Mg is removed:
Model Convergence Status
Convergence criterion (GCONV=1E-8) satisfied.
Model Fit Statistics
AIC 101.758 72.094
SC 104.034 97.137
-2 Log L 99.758 50.094
Testing Global Null Hypothesis: BETA=0 Test Chi-Square DF Pr > ChiSq Likelihood Ratio 49.6640 10 <.0001
Score 35.7536 10 <.0001
Wald 15.8649 10 0.1036
Residual Chi-Square Test Chi-Square DF Pr > ChiSq
5.9891 6 0.4244
Step 7. Effect
左心室肥厚is removed:
Model Convergence Status
Convergence criterion (GCONV=1E-8) satisfied.
Model Fit Statistics
AIC 101.758 71.337
SC 104.034 94.104
-2 Log L 99.758 51.337
Testing Global Null Hypothesis: BETA=0 Test Chi-Square DF Pr > ChiSq Likelihood Ratio 48.4206 9 <.0001
Score 35.2643 9 <.0001
Wald 15.8925 9 0.0692
Residual Chi-Square Test Chi-Square DF Pr > ChiSq
7.1087 7 0.4177
Step 8. Effect P is removed:
Model Convergence Status
Convergence criterion (GCONV=1E-8) satisfied.
Model Fit Statistics
AIC 101.758 70.466
SC 104.034 90.956
-2 Log L 99.758 52.466
Testing Global Null Hypothesis: BETA=0 Test Chi-Square DF Pr > ChiSq Likelihood Ratio 47.2918 8 <.0001
Score 35.0556 8 <.0001
Score 35.0556 8 <.0001