臺灣博碩士論文加值系統

中央升主動脈收縮壓(SBP-C)和脈搏壓(PP-C)是評估人類心血管疾病的總死亡率最重要的兩個判斷指標，因此、現今有許多已經商業化的測量裝置可用來非侵入式的取得中心動脈收縮壓及脈搏壓，這些裝置大部分必須使用昂貴的高傳導壓張計及經驗豐富的操作者用以獲得手腕壓力波形，經過不同的數學運算取得中央升主動脈收縮壓及脈搏壓，就像是SphygmoCor及HEM-9000AI。而總轉換函式(generalized transfer function, GTF)對於預測SBP-C則具有相當好的準確度，但是因為上述所提到的限制，以至於其普遍性不高。本研究提出一個方法可以使用一般電子血壓計即能簡單取得的脈搏體積記錄波形(pulse volume recording, PVR)，用其代替不易取得的血壓波形，以創造出一個具有方便性及低價位的電子血壓計，用以測量中央升主動脈收縮壓及脈搏壓的非侵入式裝置。而此測量結果則會與其它SBP-C預測函式作比較，如脈搏波形分析法(pulse wave analysis, PWA)及N點移動平均法(N-point moving average, NPMA)。
本篇論文提出以PVR波形用以取代侵入式肱動脈波形，而此PVR波形則是利用一般商業用的電子血壓計，將壓脈袋內壓力固定於特定壓力下而取得。此所得的PVR訊號經過GTF、PWA或NPMA分別之預測函數，則可以求得中央升主動脈收縮壓或脈搏壓。本篇論文將實驗分為兩個組別，一組為控制組，用以建立此三種預測函數各別所需之參數，且使用的電子血壓計為WatchBP Office, Microlife。參與此組別的研究人數為40人，平均年齡為64.1 ± 14.0歲。另一組別為測試組，不重複的100人加入此組別，平均年齡為61.9 ± 13.2歲，用以驗證所建立的三種中央升主動脈收縮壓之預測函數的能力及準確性，使用的電子血壓計為VP-2000, Colin。所有侵入式測量到的中央升主動脈壓力波形、肱動脈壓力波形及非侵入式測量的PVR波形皆為同步測量及記錄，實驗的地點為台北榮民總醫院導管室。
本論文證明了由兩種不同電子血壓計測量到的非侵入式PVR波形，且使用電子血壓計測量的收縮壓及舒張壓所校正，是適合且可用於GTF之SBP-C預測函數。在測試組裡，使用PVR波形與GTF預測函數預測中央升主動脈收縮壓的準確度為-2.1 ± 7.7 mmHg，此結果是與其它為比較標準的SBP-C之預測函數相似。PWA預測函數準確度為1.7 ± 7.9 mmHg及NPMA預測函數準確度為-0.6 ± 7.7 mmHg，此結果皆為與侵入式測量之中央升主動脈收縮壓作比較。
雖然以脈壓袋為基礎的PVR訊號比侵入式肱動脈壓力訊號缺少了較高頻的訊號，但PVR是足夠使用在GTF、PWA及NPMA上，且不論此三種預測函數是使用侵入式中央主動脈波形及肱動脈波形，或侵入式中央主動脈波形及非侵入式PVR所產生的結果，都可用以預測中央升主動脈收縮壓。本篇論文成功的應用由兩台不同電子血壓計所取得的PVR波形於三種不同的中央升主動脈收縮壓預測函數，且同時證明及比較與侵入式測量所得的中央升主動脈收縮壓的準確性。

Central ascending aortic systolic (SBP-C) and pulse (PP-C) blood pressure are the most important indexes for cardiovascular mortality in humankind. Currently commercial devices for assessing SBP-C and PP-C non-invasively are almost dependent on an expensively high-fidelity tonometer and an experienced operator for obtaining a wrist pressure waveform, such as SphygmoCor and HEM-9000AI. Then, the wrist pressure waveform was calculated by several different mathematic model for yielding SBP-C and PP-C. The accuracy of gener-alized transfer function (GTF) for predicting SBP-C was quite good. However, according to limitations mentioned above, it was still not popular. This study brought a hypothesis that a pulse volume recording (PVR) waveform obtained easily from a common non-invasive blood pressure monitor could replaced the peripheral pressure waveform to estimate SBP-C non-invasively and with a convenient methodology and at lower cost. The result of this hy-pothesis was compared with other SBP-C prediction models, such as pulse wave analysis (PWA) and N-point moving average (NIBP).
The PVR waveform was presented as a surrogate for invasive brachial pressure waveform in this study. This waveform is easily obtained from a commercial noninvasive blood pressure monitor when the cuff pressure is fixed at a constant pressure. Then, the predicted SBP-C was yielded from the obtained PVR waveform using GTF, PWA and NPMA prediction model. Two study groups were used in the present study. The control group was used to create the parameters of these three prediction models by using WatchBP Office, Microlife. Forty subjects were joined in this group, and the average age was 64.1 ± 14.0 years. Another one hundred subjects were joined the other testing group, and the average age was 61.9 ± 13.2 years. This testing group was used to assess the accuracy of three prediction models to esti-mate SBP-C noninvasively that was using VP-2000, Colin. All the invasive aortic pressure waveform, invasive brachial pressure waveform and non-invasive PVR waveform were rec-orded simultaneously in the catheterization laboratory at Taipei Veterans General Hospital.
This study demonstrated that PVR waveform which calibrated to oscillometric base SBP and DBP from two different noninvasive blood pressure monitors was suited to predict SBP-C by using GTF prediction model. The accuracy of PVR waveform with GTF prediction model was -2.1 ± 7.7 mmHg, the result was similar to other benchmark of SBP-C prediction model. PWA prediction model was 1.7 ± 7.9 mmHg and with NPMA prediction model was -0.6 ± 7.7 mmHg in the testing group. These results were all compared with invasively measured SBP-C.
Although a brachial cuff-based PVR waveform was lack of sufficient high-frequency signals in comparison in a brachial waveform, it is good enough to estimate SBP-C using GTF. And it is accurate as well as PWA and NPMA with either an aortic-to-brachial or aor-tic-to-PVR transfer functions. This study successfully applied PVR waveform from two non-invasive blood pressure monitors in three kinds of SBP-C prediction models, and proved the accuracy compared with the standard invasively measured SBP-C.

摘要 ........................................................... I
ABSTRACT .................................................... III
謝誌 ........................................................... V
CONTEXT ...................................................... VI
FIGURE ....................................................... IX
TABLE ........................................................ XV
CHAPTER 1 INTRODUCTION ........................................ 1
CHAPTER 2 REVIEW .............................................. 6
2‐1 GENERATION OF BLOOD PRESSURE WAVEFORM ..................... 6
2‐2 MEASUREMENT OF BLOOD PRESSURE ............................. 10
2‐2.1 Direct Measurement ...................................... 10
2‐2.2 Indirect Measurement .................................... 11
2‐3 VALIDATION OF OSCILLOMETRIC METHOD ........................ 14
2‐3.1 Derive the Central Aortic Systolic Blood Pressure ....... 14
2‐3.2 Generalized Transfer Function ........................... 18
2‐3.3 Autoregressive‐Exogenous Model .......................... 24
2‐3.4 Pulse Wave Analysis ..................................... 26
2‐3.5 N‐Point Moving Average .................................. 28
2‐4 SUMMARY ................................................... 31
CHAPTER 3 METHODS AND MATERIALS .............................. 32
3‐1 STUDY PROCEDURE ........................................... 32
3‐2 GENERALIZED TRANSFER FUNCTION ............................. 33
3‐3 PULSE WAVE ANALYSIS ....................................... 35
3‐4 N‐POINT MOVING AVERAGE .................................... 36
3‐5 STUDY POPULATION .......................................... 37
3‐6 DATA ACQUISITION .......................................... 39
3‐7 DATA ANALYSIS ............................................. 41
3‐8 STATISTICAL ANALYSES ...................................... 41
3‐9 SUMMARY ................................................... 42
CHAPTER 4 RESULTS ............................................ 43
4‐1 QUANTIFICATION OF THE CALIBRATION ERROR IN THE GENERALIZED TRANSFER FUNCTION .............................................................. 43
4‐2 RESULTS IN GENERALIZED TRANSFER FUNCTION .................. 52
4‐2.1 Comparison of averaged and continuous pressure waveform for the GTF ............................................................... 52
4‐2.2 Constructs of the generalized transfer functtions......... 57
4‐2.3 Generation of SBP‐C using A2BGTF and A2PGTF .............. 58
4‐3 RESULTS IN PULSE WAVE ANALYSIS ............................. 64
4‐3.1 Constructs of the pulse wave analysis model .............. 64
4‐3.2 Generation of SBP‐C using A2BPWA and A2PPWA .............. 65
4‐4 RESULTS IN N‐POINT MOVING AVERAGE .......................... 67
4‐4.1 Constructs of the N‐point moving average parameters ...... 67
4‐4.2 Generation of SBP‐C using A2BNPMA and A2PNPMA ............ 68
4‐5 DEFINITION OF THE TOLERANCE OF EACH SBP‐C ESTIMATION METHODS IN CALIBRATION ERROR .......................................................... 71
CHAPTER 5 DISCUSSION .......................................... 73
5‐1 ACCURACY OF NON‐INVASIVE BLOOD PRESSURE MONITOR ............ 73
5‐2 THE EFFECT OF NON‐INVASIVE CALIBRATION ..................... 74
5‐3 PVR WITH GENERALIZED TRANSFER FUNCTION ..................... 76
5‐4 PVR WITH PULSE WAVE ANALYSIS ............................... 79
5‐5 PVR WITH N‐POINT MOVING AVERAGE ............................ 80
5‐6 COMPARING GTF WITH PWA AND NPMA PREDICTION MODEL ... ....... 83
5‐7 LIMITATION OF THE PRESENT STUDY ............................ 84
5‐8 SUMMARY .................................................... 88
CHAPTER 6 CONCLUSION ........................................... 89
REFERENCE ...................................................... 90

Figure 1-1 Illustration of pressure parameters in measured aortic pressure waveform: SBP: systolic blood pressure, DBP: diastolic blood pressure. 1
Figure 1-2 Hazard ratios of the individual blood pressure variables per 10 mmHg increment for all-cause (right panel) and cardiovascular (left panel)............ 3
Figure 2-1 Diagrammatic section of the heart............ 7
Figure 2-2 Conducting system of the heart............ 8
Figure 2-3 Divisions of the cardiac cycle: (a) systole; (b) diastole............ 9
Figure 2-4 Summary of events in the left atrium, left ventricle, and aorta during the cardiac cycle............ 10
Figure 2-5 The auscultatory technique for the determination of brachial blood pressure2............ 12
Figure 2-6 The oscillometric method............ 13
Figure 2-7 The prototype of automatically NIBP............ 13
Figure 2-8 The contribution of reflected wave, backward pressure wave, in the branch of artery............ 15
Figure 2-9 Blood pressure waveform at different sites in human body............ 16
Figure 2-10 Blood pressure waveforms of different sites with ages............ 16
Figure 2-11 Description of the contribution of reflected wave in a young (left) and an old (right) subject............ 17
Figure 2-12 Generalized transfer functions between the ascending aorta and brachial (above) and radial artery (below)............ 19
Figure 2-13 The ensemble-averaged TF with mean (solid line) and 95% confidence intervals (dashed line)............ 20
Figure 2-14 Description of the GTF is little variability in the lower frequencies but significant variability in the higher frequencies............ 21
Figure 2-15 Illustration for an artificial neural network to reconstruct an aortic pressure waveform............ 22
Figure 2-16 (a) Characteristic modulus amplifications and phase shifts of pressure wave harmonics between aortic root and brachial artery used for the ARCSolver-generalized transfer function and data published by Karamanoglu et al. (b) Principles to derive aSBP and AIx............ 22
Figure 2-17 The Bland-Altman analysis of differences between predicted aSBPs using ARCSolver and SphygmoCor............ 22
Figure 2-18 “Transferred errors” to derived aortic (a) systolic and (b) diastolic pressure due to standard isolated errors in brachial systolic (SBP) and diastolic (DBP) blood pressure used for calibration............ 23
Figure 2-19 The GTF of ARX method in steady-state and hemodynamic transient condition............ 25
Figure 2-20 Reconstructed pressure contour of GTF of ARX method. A, measured aortic pressure contour (doted lines) and radial pressure contour (solid lines). B, reconstructed pressure contour with GTF. C, reconstructed pressure contour with ITF............ 25
Figure 2-21 Parameters identified from (a) the brachial pulse and (b) the pulse volume recording (PVR)............ 27
Figure 2-22 Bland–Altman analyses in the generation group (n=50). Data combine baseline and after sublingual nitroglycerin administration measurements.(a) agreement between invasive brachial systolic blood pressure (SBP) and measured aortic SBP; (b) agreement between invasive brachial pressure value of SBP2 and measured aortic SBP; (c) agreement between measured and predicted aortic SBP by the invasive brachial pressure wave prediction model; Dashed lines indicate the boundaries of two s.d. of the differences. Solid line indicates mean of the differences. CI, confidence interval3 27
Figure 2-23 Bland–Altman analyses in the validation group (n=50). Data combine baseline and after sublingual nitroglycerin administration measurements.(a) agreement between invasive brachial systolic blood pressure (SBP) and measured aortic SBP; (b) agreement between invasive brachial pressure value of SBP2 and measured aortic SBP; (c) agreement between measured and predicted aortic SBP by the invasive brachial pressure wave prediction model; Dashed lines indicate the boundaries of two s.d. of the differences. Solid line indicates mean of the differences. CI, confidence interval............ 28
Figure 2-24 (A) Illustration of the application of an n-point moving average with a denominator of n/4 (n = 128 Hz) to a radial artery pressure waveform. (B) Derivation of SBP-C from arterial pressure waveform............ 29
Figure 2-25 (A) Linear regression of central aortic systolic pressure measured invasively and non-invasively estimated central SBP. (B) Bland-Altman analysis of central aortic systolic pressure measured invasively and non-invasively. Mean difference was -0.4 mmHg with 2.5 mmHg standard difference............ 30
Figure 3-1 Illustration of an individual transfer function obtained from aligned and measured aortic, brachial and PVR waveforms using fast Fourier transform............. 35
Figure 3-2 Illustration of pulse wave analysis to predict central aortic systolic blood pressure by using a linear regression function............. 36
Figure 3-3 Illustration of NPMA-derived waveforms obtained from different denominators; red, measured aortic pressure waveform; blue, measured brachial or PVR waveforms............. 37
Figure 3-4 Block diagram depicts the protocol for recording invasive aortic and brachial pressure waveforms and non-invasive PVR waveform in the control group............. 39
Figure 3-5 Block diagram depicts the protocol for recording invasive aortic pressure waveforms and non-invasive PVR waveform in the testing group. 40
Figure 4-1 illustrations of the potential sources of error in the non-invasive estimation of central aortic blood pressure using the generalized transfer function (GTF) technique. DBP, diastolic blood pressure; SBP, systolic blood pressure............. 44
Figure 4-2 Relationship between input and output errors in the estimation of central aortic blood pressure. (a) Central systolic blood pressure (SBP-C); (b) central pulse pressure (PP-C). PP-B, invasive brachial pulse pressure; PP-O, oscillometric brachial pulse pressure; SBP-B, invasive brachial systolic blood pressure; SBP-O, oscillometric brachial systolic blood pressure. Dotted lines are lines of identity. Solid lines are lines of linear regression............. 46
Figure 4-3 Comparisons between the brachial pressure and the PVR waveforms. (A) Time domain analysis. Upper panel, the brachial and PVR waveforms are ensemble averaged from 40 individual waveforms resampled to 512 points, respectively, in the control group. Lower panel, the brachial and PVR waveforms reconstructed from low-frequency components (< 4Hz) of the respective ensemble averaged waveforms. (B) Frequency domain analysis. Amplitude, mean amplitude of harmonic waves with error of 1 s.d. at each frequencies; difference, mean difference of brachial amplitude or phase minus aortic amplitude or phase with error bars of 1 s.d.; PVR, pulse volume recording; ratio, mean ratio of brachial amplitude over aortic amplitude with error bars of 1 s.d............. 50
Figure 4-4 PVR waveforms obtained at different cuff pressure and calibrated with non-invasive cuff SBP and DBP in the same subject............ 51
Figure 4-5 The Fourier analysis of continuous aortic (right), brachial (middle) and PVR (left) pressure waveform............ 52
Figure 4-6 The individual transfer function between the central aortic and brachial artery using simultaneously continuous pressure recordings............ 53
Figure 4-7 The Fourier analysis of single averaged aortic (right), brachial (middle) and PVR (left) pressure waveform............ 54
Figure 4-8 Comparison of individual transfer function using single averaged (solid line) and continuous (dotted line) waveform............ 54
Figure 4-9 Validation of the effect of individual transfer functions in brachial (upper) or PVR (bottom). Resampled 512-points pressure waveforms (right), individual transfer functions between aorta and periphery (middle) and reconstructed (solid line) and real (dotted line) aortic pressure waveform (left)............ 56
Figure 4-10 (A) Spectral plots of the aortic-to-brachial (A2BGTF) generalized transfer function generated from the 40 steady-state recordings in the control group. The spectra of the A2BGTF previously reported by Karamanoglu et al. are also shown as dashed lines and empty circles.35 The relatively flat phase spectrum of our A2BGTF results from the alignment of the central aortic and brachial pressure waveforms to identical start-systolic points. (B) Spectral plots of the aortic-to-invasively calibrated PVR (A2PGTF). The spectra of the A2BGTF are also shown as the solid lines and circles. PVR, pulse volume recording. Error bars indicate 1 s.d............. 59
Figure 4-11 Bland-Altman analysis in the control group. (A) SBP-C estimated using a high-frequency components (≦9 Hz) brachial waveform and an A2BGTF; (B) SBP-C estimated using a low-frequency components (<4 Hz) brachial waveform and an A2BGTF............ 60
Figure 4-12 Bland-Altman analysis in the control group. (A) SBP-C estimated using a high-frequency components (≦9 Hz) non-invasively calibrated PVR waveform and an A2BGTF; (B) SBP-C estimated using a high-frequency components (≦9 Hz) non-invasively calibrated PVR waveform and an A2PGTF............ 60
Figure 4-13 Bland-Altman analysis in the control group. (A) SBP-C estimated using a low-frequency components (<4 Hz) non-invasively calibrated PVR waveform and an A2BGTF; (B) SBP-C estimated using a low-frequency components (<4 Hz) non-invasively calibrated PVR waveform and an A2PGTF............ 61
Figure 4-14 Bland-Altman analysis in the testing group. (A) SBP-C estimated using a high-frequency components (≦9 Hz) non-invasively calibrated PVR waveform and an A2BGTF; (B) SBP-C estimated using a high-frequency components (≦9 Hz) non-invasively calibrated PVR waveform and an A2PGTF............ 61
Figure 4-15 Bland-Altman analysis in the testing group. (A) SBP-C estimated using a low-frequency components (<4 Hz) non-invasively calibrated PVR waveform and an A2BGTF; (B) SBP-C estimated using a low-frequency components (<4 Hz) non-invasively calibrated PVR waveform and an A2PGTF............ 62
Figure 4-16 Bland-Altman analysis in the control group. SBP-C estimated using a brachial waveform and an A2BPWA............ 65
Figure 4-17 Bland-Altman analysis in the control group. SBP-C estimated using a non-invasively calibrated PVR waveform and (A) an A2BPWA, and (B) A2PGTF............ 65
Figure 4-18 Bland-Altman analysis in the testing group. SBP-C estimated using a non-invasively calibrated PVR waveform and (A) an A2BPWA, and (B) A2PPWA............ 65
Figure 4-19 Histogram of individual best denominator with brachial pressure waveforms in the control group............ 67
Figure 4-20 Bland-Altman analysis in the control group. SBP-C estimated using a brachial waveform and an A2BNPMA............ 69
Figure 4-21 Bland-Altman analysis in the (A) control group and (B) testing group. SBP-C estimated using a non-invasively calibrated PVR waveform and an A2BPWA............ 69
Figure 5-1 Illustration for denominator (N) effect using N-point moving average. Different denominator of NPMA method effect the brachial pressure waveform in time domain (upper panel). Magnitude of aortic and brachial pressure waveform (left-bottom panel). Magnitude of aortic and smoothed waveform of N=6 (middle-bottom). Magnitude of aortic and smoothed waveform of N=4 (right-bottom)............. 81
Figure 5-2 An example shows the calibration of a pulse volume recording (PVR) waveform to cuff mean blood pressure (MBP-O) and diastolic blood pressure (DBP-O) may produce a huge error, whereas calibration to cuff systolic blood pressure (SBP-O) and DBP-O produces an acceptable error. (A) A PVR waveform is calibrated to SBP-O (which slightly underestimates the invasive brachial SBP, 131.9 mmHg) and DBP-O (which substantially overestimates the invasive DBP, 59.1 mmHg). MBP-O also substantially underestimates the invasive brachial MBP (87.9 mmHg). (B) In comparison to the PVR waveform calibrated to SBP-O and DBP-O, the PVR waveform calibrated to MBP-O and DBP-O is markedly compressed and its peak (88.1 mmHg) severely underestimates the invasive brachial SBP. Horizontal dashed lines indicate the level of MBP-O............. 85

Table 1 Subjects characteristics............ 38
Table 2 Differences between central aortic and brachial blood pressures (n=40)............ 47
Table 3 Accuracy of the non-invasive blood pressure monitor (n=40)............ 47
Table 4 Transfer function errors............ 48
Table 5 Calibration output errors............ 48
Table 6 Parameters of the A2BGTF............ 59
Table 7 Mean difference and correlations between the measured and the generalized transfer function derived central aortic systolic blood pressures............ 62
Table 8 Estimation of the best Denominator for NPMA compared with measured aortic systolic blood pressure in the control group............ 68
Table 9 Mean difference and correlations between the measured and the pulse wave analysis and N-point moving average derived central aortic systolic blood pressures............ 68
Table 10 Errors of method for estimating central aortic systolic pressure (n=40)............ 71
Table 11 Calibration output errors of method for estimating central aortic systolic pressure (n=40)............ 71
Table 12 Mean difference and correlations between the measured and the generalized transfer function derived central aortic systolic blood pressures: different calibration methods............ 86

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