Devices and technology
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The SOMNOtouch device as a novel method for measuring short-term blood pressure variability: a comparison with the Finometer Lisa S. Manning, Thompson G. Robinson and Ronney B. Panerai Background Current noninvasive techniques to capture short-term blood pressure variability (BPV) have methodological and practical limitations. This study assessed the ability of a novel device, the SOMNOtouch, which derives continuous blood pressure (BP) measures from pulse transit time, to estimate BPV, compared with the widely used Finometer.
Conclusions The poor agreement observed in BPV estimates between the devices may reflect the inability of the current pulse transit time method to sensitively detect changes in BP. Further investigation is needed before such methods can be reliably used to measure short-term BPV. Blood Press Monit 20:361–368 Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.
Methods BP monitoring was performed simultaneously on the SOMNOtouch and Finometer devices in 16 healthy volunteers. Systolic and diastolic BPVs, defined as SD and coefficient of variation, were derived from measurements from each device for three predefined periods: 0–3, 7–10, and 0–10 min.
Blood Pressure Monitoring 2015, 20:361–368
Results Agreement in BPV indices from the two devices was assessed using the Bland–Altman technique. For all BPV parameters, over all measurement periods, broad scatter was observed on Bland–Altman plots. Bias (limits of agreement) for minutes 0–10: SD of systolic BP, − 3.03 mmHg (− 10.88 to + 4.55), SD of diastolic BP − 1.65 mmHg (− 4.41 to + 1.11).
Introduction Blood pressure (BP) is characterized by marked fluctuations over both the short and the long term [1]. This variability in an individual’s BP over a period of time is known as blood pressure variability (BPV). Several large studies have shown BPV to be an important prognostic factor for incident and recurrent cardiovascular events, independent of the mean BP [2–8]. To further investigate the prognostic significance and potential therapeutic modification of BPV, it is essential that we use precise, yet practical, measurement techniques for its estimation. This is a particular challenge when considering short-term BP variations – that is, fluctuations over 1 min or from one heart beat to the next.
Keywords: blood pressure measurement, blood pressure variability, cardiovascular disease, Finometer, pulse transit time University of Leicester, Department of Cardiovascular Sciences and NIHR Biomedical Research Unit in Cardiovascular Disease, Leicester, UK Correspondence to Lisa Manning, MBChB, Room 228, Robert Kilpatrick Clinical Sciences Building, University of Leicester, P.O. Box 65, Leicester LE2 7LX, UK Tel: + 44 0116 252 3182; fax: + 44 0116 252 5847; e-mail: [email protected] Received 17 December 2014Received 17 March 2015 Accepted 31 March 2015
together with the physiocal criteria of Wesseling, to provide reliable BP estimates [11,12]. These devices have previously been validated with regard to their accuracy and precision in measuring absolute BP and BPV [13–15].
Assessment of fast and short-lasting changes in BP requires continuous BP recording. As invasive BP monitoring is rarely considered appropriate in clinical practice or research settings, noninvasive beat-to-beat BP measurement is currently the optimal technique to capture short-term BPV [9,10]. The most commonly used commercially available noninvasive monitoring device, the Finapres, now succeeded by the Finometer, utilizes the finger-cuff or volume clamp method developed by Penaz,
Volume clamp methods, however, have several potential methodological and practical limitations: the participant must be nonambulatory throughout the recording, automated calibration (physiocal) must be used at least periodically to ensure reliability [11], the technique may not be appropriate for those with certain conditions – for example, for those with poor peripheral circulation [16], the cuff can only remain inflated for up to 2 h, thus limiting duration of measurement [17], cuff inflation may disturb the patient and lead to alterations in BP and inadequate cuff size or position can affect accuracy. The development of devices capable of measuring beat-to-beat BP noninvasively, without restriction and for longer, uninterrupted durations of time could lead to important progress in BPV research. In this study we investigate the ability of a novel BP monitoring device that derives continuous BP measures from pulse transit time (PTT) to capture short-term BPV: the SOMNOtouch (SOMNOmedics, Randersacker, Germany).
Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's website (www.bpmonitoring.com).
PTT, defined as the time taken for the pulse wave to travel between two arterial sites within the same cardiac cycle, can be measured noninvasively, and it has been
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DOI: 10.1097/MBP.0000000000000128
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found to be correlated with BP [18,19]. Several observational studies have tested the validity and practicability of using the PTT method for continuous BP monitoring, with partly conflicting results [20–24]. Gesche et al. [17] created a function between pulse wave velocity and systolic BP (SBP) and tested its reliability in the determination of BP from PTT measures using a nonlinear algorithm and a one-point calibration. This function forms the basis for the SOMNOmedics-patented PTT method. The SOMNOtouch, a compact device, around the size of a credit card, can be used for continuous BP monitoring for up to 24 h. It is capable of continuous ECG recording and finger plethysmography, measuring PTT as the period between the R spike of the ECG and the peripheral pulse wave in the finger. BP, SpO2 and an ECG trace are displayed on the small touch screen in real time; they can later be uploaded or transferred through Bluetooth to a data analysis system [25]. The SOMNOtouch has several potential advantages over finger-cuff measures: it is compact, lightweight and does not require connection to a data analysis unit during measurement; there is no cuff inflation; it can provide uninterrupted BP measures for up to 24 h with a single calibration. To our knowledge, the SOMNOtouch has not been previously assessed for its ability to estimate BPV. The aim of this study was to determine the accuracy of the SOMNOtouch device in measuring short-term BPV in healthy volunteers, through assessing agreement with BPV measures simultaneously obtained with the commonly used Finometer device.
Methods Participants and measurements
The study included 16 healthy, normotensive volunteers who were employees of the University of Leicester. Study measurements were performed in a dedicated research laboratory. Throughout the procedure, the participants were in the supine position. BP was recorded continuously with the Finometer MIDI device (Finapres Medical Systems, Amsterdam, The Netherlands) on the right hand. The finger cuff was attached to the middle finger of the right hand, and the physiocal was switched on, and then switched off just before the start of recording. The BP parameters were recorded onto a designated computer software system. The SOMNOtouch device was attached to the left wrist, the finger probe was attached to the left middle finger, the ECG electrodes were attached to the chest and the leads were connected to the device as per the manufacturer’s recommendations. Participant age, weight and height were input into the device. Casual cuff BP was measured in the right arm using a British Hypertension Society approved OMRON 705-IT cuff BP monitor (OMRON Healthcare UK Ltd, Milton Keynes, UK) twice at the beginning and twice at the end of the study. Casual BP was also measured once
in the left arm to detect any significant difference in BP between the two arms (>5 mmHg). The second of the two casual BP measurements in the right arm was used to calibrate the SOMNOtouch device, to ensure only a minimal delay between the cuff BP measurement and the start of the SOMNOtouch recording. The Finometer recording was commenced first, and the SOMNOtouch was then calibrated, and recording was commenced as soon as possible thereafter. When both the devices had been recording for at least 1 min, the marker button on the SOMNOtouch and a metronome device were pressed simultaneously to mark the start of study recordings. Data acquisition and editing
Analogue outputs from the Finometer were recorded onto a data acquisition system on a dedicated personal computer for subsequent offline analysis (PHYSIDAS, Department of Medical Physics, University Hospitals of Leicester NHS Trust). BP from the Finometer was sampled at 200 samples/ s. Data acquired by the SOMNOtouch device were uploaded onto a dedicated personal computer using software provided by SOMNOmedics and saved in the ASCII format, with separate files for SBP, diastolic BP (DBP), heart rate (HR) and the marker. Data editing for both devices was completed using in-house software. BP measurements from the Finometer were calibrated using the second of the two readings in the right arm (the same calibration BP used for the SOMNOtouch). Specifically written software adjusted the sampling frequency of the SOMNOtouch device from 64 to 200 samples/s to produce signals with a uniform time base. Data from both devices were inspected visually to identify artefact. Using the electrical output from the metronome on the Finometer recording and the marker start time from the SOMNOtouch files, data from the two devices were time synchronized. Data were then merged by the specifically written software to produce a single file with both Finometer and SOMNOtouch data in a standardized format. Statistical analysis
Further analysis was carried out on in-house programs to obtain mean values and variability parameters for each participant, from each device, for SBP, DBP and HR measurements. We used SD and coefficient of variation (CV) as our BPV parameters, as they are easily calculated, and commonly used. Data are presented as mean (SD) if normally distributed, and as median (interquartile range) if not normally distributed. The mean and variability parameters were calculated for three discreet time periods: the first 3 min, the final 3 min and the first 10 min of recording. This approach was chosen to assess agreement at the beginning and the end of the measurement period, as well as throughout recording, and thus to identify whether agreement between devices differed further from the calibration BP. Files were exported to SPSS (IBM SPSS version 20; SPSS Inc., Chicago, Illinois, USA) for further analysis. We also calculated the mean absolute
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A novel method for measuring short-term BPV Manning et al. 363
and variability parameters for BP and HR from the four casual cuff BPs. The average SBP, DBP and HR parameters from the two devices were compared for significant differences using independent t-tests. Statistical significance was set at P less than 0.05. In-house software was used to determine peak coherence function and the frequency for SBP, DBP and HR for each participant, as well as to obtain the cross-correlation peaks and time delay of measurements from the SOMNOtouch and Finometer (data not shown). There are no direct recommendations for the validation of a continuous non-intra-arterial device in terms of absolute BP measurement, or indeed BPV. Current validation protocols for new devices use measures from a standard mercury sphygmomanometer as the reference, and do not comment on the measurement of BPV, nor apply to continuous BP monitoring; thus, they cannot be directly applied or modified for the purposes of this study, which is primarily concerned with the measurement of short-term BPV using beat-to-beat BP measurements. The European Society of Hypertension international protocol for the validation of BP measuring devices and the British Hypertension Society guidelines use a grading criteria based on the cumulative percentage of readings falling within 5, 10 and 15 mmHg of the mercury standard, and the Association for the Advancement of Medical Instrumentation guidelines state that the test device must not differ from the mercury standard by a mean difference greater than 5 mmHg or an SD greater than 8 mmHg [26,27]. We used Bland–Altman plots to assess agreement between the average absolute BP measures and withinindividual BPV parameters for each participant, derived from the Finometer and SOMNOtouch devices [28]. The Bland–Altman technique allows for the degree of agreement between the two devices to be calculated, to ensure that the measurements from the new device are within a clinically acceptable range compared with the older device. A graph of the differences between two simultaneous measurements (y axis) against their mean values (x axis) was plotted. The 95% limit of agreement was then calculated from the mean difference (bias) and the SD of the differences (limit of agreement = mean difference ± 2 SD). In cases in which visual inspection of the Bland–Altman plots led to a suspicion of proportional bias, the relationship was formally assessed by linear regression analysis of the differences and mean values. If a significant slope on the regression line (P < 0.05) was identified, then regression-based 95% limits of agreement were calculated [28].
Results Data were collected from 16 healthy volunteers. After visual inspection, data from two participants were excluded from further analysis, one because of loss of BP signal from the Finometer recording and one because of a lack of a marker file from the SOMNOtouch recording,
leaving a total of 14 participants for the final analysis. The mean age was 37.7 years (SD 14.8), and four participants (28%) were male. Absolute blood pressure and heart rate
Over minutes 0–10, the group mean SBP from the SOMNOtouch BP measures was 119.3 mmHg (3.9) and that from the Finometer was 125.7 mmHg (6.6; P = 0.01); the mean DBP from the SOMNOtouch was 75.8 mmHg (1.7) and from the Finometer was 74.1 mmHg (3.4; P = 0.43). Within each of the three predefined measurement periods, statistically significant differences were observed in the mean SBP values obtained from the SOMNOtouch and Finometer devices (Supplementary Table 1, Supplemental digital content 1, http://links.lww.com/BPMJ/A8). No statistically significant differences were observed in the mean DBP or HR values, except for DBP during 0–3 min (Supplementary Table 1, Supplemental digital content 1, http://links.lww.com/BPMJ/A8). Individual correlation coefficients (r) for SBP ranged from 0.35 to 0.71 and for DBP from 0.22 to 0.54 for the whole 10-min measurement period, implying a weak to moderate positive correlation between SOMNOtouch and Finometer BP measures. A greater agreement in the average SBP measures and a narrower scatter on Bland–Altman plots were observed during minutes 0–3 compared with minutes 7–10: minutes 0–3, bias − 3.43 mmHg (limits of agreement, − 14.40 to + 7.32); minutes 7–10, − 7.54 mmHg (− 20.97 to + 15.40). Supplementary Figure 1 (Supplemental digital content 2, http://links.lww.com/BPMJ/A9) shows a Bland–Altman plot for the mean SBP from the SOMNOtouch and Finometer devices over the whole 10-min period. Limits of agreement for the mean DBP were narrower during minutes 0–3 than during minutes 7–10: minutes 0–3, bias 1.97 mmHg (− 9.59 to + 13.57); minutes 7–10, 1.40 mmHg (− 16.11 to 16.10). Limits of agreement for the mean HR (in beats/min) were narrow: minutes 0–10, bias − 0.86 bpm (limits of agreement, − 4.50 to + 2.81). Blood pressure and heart rate variability parameters Systolic blood pressure variability parameters
The averaged systolic BPV parameters for the whole group (SD and CV) obtained from the SOMNOtouch and Finometer devices are given in Table 1. Statistically significant differences in systolic BPV parameters derived from the two devices were observed in the 0–10 and 7–10 min periods, although not in the 0–3 min period (Table 1). Limits of agreement for SD and CV SBP were wide for all three measurement periods (Table 2), with broad scatter seen on Bland–Altman plots (Figs 1–3). Visual inspection of the plots for minutes 0–10 (Fig. 1) and minutes 0–3 (Fig. 2) revealed potential proportional bias. However, linear regression analysis of the differences in SD SBP against the mean SD SBP values revealed no statistically significant slopes on the regression lines.
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Table 1 Mean systolic and diastolic blood pressure variability and heart rate variability parameters derived from SOMNOtouch, Finometer, and casual cuff blood pressure measurements Time period 0–10 min
0–3 min
7–10 min
Parameter
SOMNOtouch value
Finometer value
P-value*
Casual cuff valuea
SD SBP (mmHg) CV SBP (%) SD DBP (mmHg) CV DBP (%) SD HR (bpm) CV HR (%) SD SBP (mmHg) CV SBP (%) SD DBP (mmHg) CV DBP (%) SD HR (bpm) CV HR (%) SD SBP (mmHg) CV SBP (%) SD DBP (mmHg) CV DBP (%) SD HR (bpm) CV HR (%)
3.59 3.01 1.71 2.23 4.83 6.51 10.64 9.05 6.85 8.94 7.57 10.23 1.17 2.49 1.16 1.66 4.33 5.93
6.65 5.14 3.36 4.58 4.85 6.50 11.24 9.27 6.97 9.94 7.73 10.31 2.67 3.78 2.66 3.66 4.52 6.13
0.01 0.01 0.01 0.01 0.92 0.92 0.20 0.16 0.86 0.86 0.42 0.70 0.01 0.01 0.01 0.01 0.01 0.01
11.70 9.64 7.79 10.51 5.25 5.75 – – – – – – – – – – – –
bpm, beats per minute; CV, coefficient of variation; DBP, diastolic blood pressure; HR, heart rate; SBP, systolic blood pressure. Calculated from four casual cuff BP measurements (two at the start and two at the end of the 10-min measurement period). *P-value for the difference between SOMNOtouch and Finometer parameters. a
Bias and limits of agreement for systolic and diastolic blood pressure variability parameters derived from the SOMNOtouch and Finometer devices over the three defined measurement periods
Table 2
Time period 0–10 min
0–3 min
7–10 min
Parameter
Bias
SD of difference
Limits of agreementa
SD SBP (mmHg) CV SBP (%) SD DBP (mmHg) CV DBP (%) SD SBP (mmHg) CV SBP (%) SD DBP (mmHg) CV DBP (%) SD SBP (mmHg) CV SBP (%) SD DBP (mmHg) CV DBP (%)
− 3.03 − 2.12 − 1.65 − 2.25 − 1.58 − 0.24 − 0.12 − 1.72 − 1.98 0.96 − 1.49 − 2.02
3.79 2.56 1.38 1.57 1.37 2.99 2.58 1.58 1.68 1.24 1.18 1.59
− 10.88 to + 4.55 − 7.24 to + 3.00 − 4.41 to + 1.11 − 5.42 to + 0.89 − 4.32 to + 1.37 − 6.21 to + 5.74 − 5.64 to + 5.06 − 4.87 to + 1.44 − 4.34 to + 1.38 − 1.22 to + 3.44 − 3.85 to + 0.87 − 5.20 to + 1.17
bpm, beats per minute; CV, coefficient of variation; DBP, diastolic blood pressure; HR, heart rate; SBP, systolic blood pressure. a Limits of agreement determined by bias ± (2 SD). *P-value for difference between SOMNOtouch and Finometer parameters.
Diastolic blood pressure variability parameters
Over the first 3 min period, no statistically significant differences were observed in the mean DBP variability indices derived from the two devices (Table 1). However, significant differences were observed for minutes 0–10 and 7–10 (Table 1). Limits of agreement for SD and CV DBP were wide (Table 2), with broad scatter seen on Bland–Altman plots across all three measurement periods (Fig. 4).
Heart rate variability parameters
No significant differences were observed in either CV or SD HR over minutes 0–3 and 0–10 (Table 1). Good agreement was found between HR variability parameters (CV and SD) derived from the SOMNOtouch and Finometer devices, with narrow scatter observed on Bland–Altman plots and narrow limits of agreement reported over all three
measurement periods: minutes 0–10 SD HR, bias − 0.01 bpm (limits of agreement − 0.90 to + 0.09).
Discussion To the best of our knowledge, this is the first study to assess the feasibility of using PTT-derived BP measurements to derive BPV. Estimates of short-term systolic and diastolic BPV derived from the SOMNOtouch and Finometer BP measurements varied considerably, with significant underestimation of BPV on using the SOMNOtouch measures, or alternatively, overestimation of BPV on using Finometer measures. Limits of agreement for all BPV parameters were wider than acceptable in the research setting, with Bland–Altman plots showing wide scatter, over all three measurement periods. As such, we would not currently recommend the SOMNOtouch device as an acceptable alternative to the Finometer for the estimate of short-term BPV. Limits of agreement for absolute
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A novel method for measuring short-term BPV Manning et al. 365
Fig. 3
15.00 10.00 5.00 0.00 −5.00 −10.00 −15.00 8.00 2.00 4.00 6.00 SD SBP mean (SOMNOtouch and Finometer) (mmHg)
Difference (SOMNOtouch SD SBP − Finometer SD SBP) (mmHg)
Difference in SD SBP (SOMNOtouch − Finometer) (mmHg)
Fig. 1
5.00
2.50
0.00 −2.50 −5.50 6.00 1.00 2.00 3.00 4.00 5.00 SD SBP mean (SOMNOtouch and Finometer) (mmHg)
Bland–Altman plot of SD of systolic blood pressure derived from SOMNOtouch and Finometer measurements for minutes 7–10. The horizontal dotted line indicates limits of agreement (bias ± 2 SD). The horizontal thick black line indicates bias. SBP, systolic blood pressure.
Fig. 2
Fig. 4
5.00
Difference in SD DBP (SOMNOtouch − Finometer) (mmHg)
Difference in SD SBP (SOMNOtouch − Finometer) (mmHg)
Bland–Altman plot of SD of systolic blood pressure derived from SOMNOtouch and Finometer measurements for minutes 0–10. The horizontal dotted line indicates limits of agreement (bias ± 2 SD). The horizontal thick black line indicates bias. SBP, systolic blood pressure.
4.00 3.00 2.00 1.00 0.00 −1.00 −2.00 −3.00 −4.00 −5.00 8.00 10.00 12.00 14.00 16.00 18.00 SD SBP mean (SOMNOtouch and Finometer) (mmHg)
Bland–Altman plot of SD of systolic blood pressure derived from SOMNOtouch and Finometer measurements for minutes 0–3. The horizontal dotted line indicates limits of agreement (bias ± 2 SD). The horizontal thick black line indicates bias. SBP, systolic blood pressure.
5.00 4.00 3.00 2.00 1.00 0.00 −1.00 −2.00 −3.00 −4.00 −5.00 5.00 1.00 2.00 3.00 4.00 SD DBP mean (SOMNOtouch and Finometer) (mmHg)
Bland–Altman plot of SD of diastolic blood pressure derived from SOMNOtouch and Finometer measurements for minutes 0–10. The horizontal dotted line indicates limits of agreement (bias ± 2 SD). The horizontal thick black line indicates bias. DBP, diastolic blood pressure.
assumptions as to which device this applies to or indeed whether it applies to both. BP measures from the two devices were wider than acceptable according to Association for the Advancement of Medical Instrumentation standards, although this study was not aimed at validating the SOMNOtouch device for absolute BP measurements, and such guidelines are not applicable to finger BP monitors. For absolute BP, agreement was greater during the first 3-min measurement period. One potential explanation for this is that BP measures from the SOMNOtouch diminish in accuracy as the time from the calibration cuff BP increases. However, one cannot make
Good agreement was seen in HR and HR variability parameters derived from the two devices. This suggests not only that the two devices agree in terms of HR measurement, but also that our method of time synchronizing data from the two devices was robust. This assumption is further supported by individual correlation coefficients and crosscorrelation peaks for HR parameters (data not shown), and by visual inspection of output data from both devices. There was a trend towards the SOMNOtouch reporting lower absolute SBP and higher DBP values, whereas the averaged
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variability parameters for SBP and DBP derived from the SOMNOtouch measures were lower than those derived from the Finometer measures. Although there are no previous studies on BPV estimation using PTT-derived BP measures, our findings do concur with those of studies that have assessed the technique’s ability to measure and track changes in absolute BP values. Two studies reported a good correlation between PTT-derived and cuff-based absolute BP measures [17,24], but found wide limits of agreement (− 19.8 to +19.8) [17] and reported that the PTT method lacked sensitivity in tracking BP changes; several studies comparing the PTT method with intra-arterial BP measurement have reported wide limits of agreement for absolute SBP [21,23,29] in cohorts of healthy volunteers [21] and individuals with cardiac disease [23], with wider limits of agreement among those with hypotension [23, 24]. Perhaps the PTT method is less precise at lower BP levels, which could be relevant in our study of healthy volunteers with mostly lower than average resting BP values. Other studies have reported more promising findings on the precision of PTT-derived absolute BP measures, although none report BPV estimation [20,21]. Overall interpretation of the findings from the available studies is complicated by heterogeneity in participants, methodology and reference BP measures, as well as by considerable differences in statistical designs. In addition, a lack of consensus on the acceptable level of agreement required for any new continuous noninvasive BP monitoring technique compared with currently accepted devices, particularly in terms of estimating BPV, means that we have no clearly defined benchmark for the minimum acceptable standard of precision. This said, on the basis of our findings as well as other available studies, one could postulate that the current PTTbased BP measurement techniques lack sufficient sensitivity to accurately track BP changes and are thus unlikely to be able to accurately capture BPV. Further possible explanations for the lack of agreement in BPV parameters between the Finometer and SOMNOtouch devices may be related to the ability of R-wave-gated photoplethysmography (RWPP) to detect changes in PTT. One literature review and several studies have reported that RWPP is not accurate at determining PTT [30,31], BP changes are not consistently associated with changes in PTT [30] and the correlation between PTT and BP measures from the Portapres device (portable version of the Finapres) in healthy adults is poor [32]. The applicability of the Moens–Korteweg equation, from which calibration functions are derived for PTT-based BP measures, has also been questioned. The equation assumes that there are insignificant variations in vessel radius and section, which may not be true in younger healthy individuals with compliant vessels. Thus, BP changes may simply not be accompanied by detectable changes in PTT on using the RWPP technique.
Studies using techniques other than RWPP have also found that BP changes are not always accompanied by the expected changes in PTT [29,31,33]. However, studies in sleep medicine have shown RWPP to be accurate in indicating BP arousals in the setting of obstructive sleep apnoea [19,34]. Perhaps in our study of healthy volunteers, fluctuations in BP were of too small in magnitude to be accompanied by detectable changes in PTT, because of the current PTT method lacking sensitivity to track BP changes. Determination of BP from PTT has methodological limitations that may have influenced our results: measurements are influenced by the quality of the ECG and finger plethysmography, and the measured PTT depends on the pre-ejection period, as well as the transition time of the arterial pulse pressure wave. The pre-ejection period may be affected by many factors including sympathetic activity and medication, and its contribution towards measured PTT varies considerably between individuals. The pre-ejection period and the transition time of the pulse wave are expected to contribute differently to SBP and DBP, and this may be relevant when considering the tendency for overestimation of SBP and underestimation of DBP by PTT methods, as compared with invasive and cuff BP measures, in our study and in others: the transition time of the pulse wave is correlated most to SBP, and both the pre-ejection period and the transition time of the pulse wave are correlated with DBP [21]. Inaccuracies in BP measurement and detection of BP changes by the Finometer device are also possible. Although validation studies suggest that the Finapres serves as a reliable alternative to intra-arterial BP measures in terms of absolute BP and BPV [14,15], validation data specific to the Finometer are limited, and neither device is as precise in BPV estimation as intra-arterial measurement. Furthermore, the volume clamp method has potential operational shortcomings, as discussed earlier. In our study, the risk of operational errors was minimized, as measurements were made by an experienced researcher in a dedicated, temperature-controlled research room; output files were visually inspected to detect artefact and potential finger-cuff application issues; and output signals were calibrated with a brachial cuff BP measurement. Limitations of this study include the following: limited precision of the estimates because of the small sample size and the lack of comparison with BPV from intra-arterial BP measures; BP fluctuations were only physiological, and we cannot comment on the ability of the SOMNOtouch to detect larger fluctuations in BP; potential inaccuracy in calibration, as casual cuff measurements were performed on the right arm but the SOMNOtouch was applied onto the left hand, and there was a slight, unavoidable time delay between casual BP measurement and the commencement of BP recordings. These potential sources of error were minimized by the measurement of BP in both arms before the monitoring period and exclusion of those with a greater than 5 mmHg difference, and by ensuring a minimal (few
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A novel method for measuring short-term BPV Manning et al. 367
seconds) delay between calibration and study commencement. The different sampling rates of the SOMNOtouch (64 samples/s) and Finometer (200 samples/s) devices also made comparing the two systems more complex. Whereas the Finometer outputs a continuous recording of BP, the SOMNOtouch provides either systolic or diastolic values that are averaged for a few heart cycles and then presented to the output as a ‘sample and hold’ value. Although downsampling the Finometer signal to 64 samples/s would be an option, the alternative of extending the SOMNOtouch output to 200 samples/s was preferred to provide good visualization of the BP changes during the cardiac cycle and help detect any potential artefact. As the final analysis was based on data resampled for each cardiac cycle, the change in the sampling rate for SOMNOtouch did not have any influence on the BPV metrics presented above. Our study demonstrated poor agreement between the SOMNOtouch device and the Finometer device in the assessment of BPV, which may in part reflect an inability of the PTT method to sensitively detect BP fluctuations. Furthermore, poor correlation and wide limits of agreement were seen between absolute BP readings from the two devices. For HR and HR variability, good agreement was observed. We would not currently recommend using the SOMNOtouch device to estimate short-term BPV. The ability of PTT-derived BP measurements to measure BPV and track BP changes, outside of the sleep medicine setting, warrants further investigation before such techniques can be relied upon to provide accurate estimates of BPV.
Acknowledgements L.M. is supported by a programme grant from the British Heart Foundation and United Kingdom Stroke Association (TSA BHF 2012/01). The authors thank SOMNOmedics for the loan of the SOMNOtouch device.
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Conflicts of interest
There are no conflicts of interest.
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Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; 1:307–310. 29 Young CC, Mark JB, White W, DeBree A, Vender JS, Fleming A. Clinical evaluation of continuous noninvasive blood pressure monitoring: accuracy and tracking capabilities. J Clin Monit 1995; 11:245–252. 30 Naschitz JE, Bezobchuk S, Mussafia-Priselac R, Sundick S, Dreyfuss D, Khorshidi I, et al. Pulse transit time by R-wave-gated infrared photoplethysmography: review of the literature and personal experience. J Clin Monit Comput 2004; 18:333–342. 31 Wipperman C, Schranz D, Huth R. Evaluation of pulse wave arrival time as a marker for blood pressure changes in critically ill infants and children. J Clin Monit, 11:328.
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The SOMNOtouch device as a novel method for measuring short-term blood pressure variability: a comparison with the Finometer Lisa S. Manning, Thompson G. Robinson and Ronney B. Panerai Background Current noninvasive techniques to capture short-term blood pressure variability (BPV) have methodological and practical limitations. This study assessed the ability of a novel device, the SOMNOtouch, which derives continuous blood pressure (BP) measures from pulse transit time, to estimate BPV, compared with the widely used Finometer.
Conclusions The poor agreement observed in BPV estimates between the devices may reflect the inability of the current pulse transit time method to sensitively detect changes in BP. Further investigation is needed before such methods can be reliably used to measure short-term BPV. Blood Press Monit 20:361–368 Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.
Methods BP monitoring was performed simultaneously on the SOMNOtouch and Finometer devices in 16 healthy volunteers. Systolic and diastolic BPVs, defined as SD and coefficient of variation, were derived from measurements from each device for three predefined periods: 0–3, 7–10, and 0–10 min.
Blood Pressure Monitoring 2015, 20:361–368
Results Agreement in BPV indices from the two devices was assessed using the Bland–Altman technique. For all BPV parameters, over all measurement periods, broad scatter was observed on Bland–Altman plots. Bias (limits of agreement) for minutes 0–10: SD of systolic BP, − 3.03 mmHg (− 10.88 to + 4.55), SD of diastolic BP − 1.65 mmHg (− 4.41 to + 1.11).
Introduction Blood pressure (BP) is characterized by marked fluctuations over both the short and the long term [1]. This variability in an individual’s BP over a period of time is known as blood pressure variability (BPV). Several large studies have shown BPV to be an important prognostic factor for incident and recurrent cardiovascular events, independent of the mean BP [2–8]. To further investigate the prognostic significance and potential therapeutic modification of BPV, it is essential that we use precise, yet practical, measurement techniques for its estimation. This is a particular challenge when considering short-term BP variations – that is, fluctuations over 1 min or from one heart beat to the next.
Keywords: blood pressure measurement, blood pressure variability, cardiovascular disease, Finometer, pulse transit time University of Leicester, Department of Cardiovascular Sciences and NIHR Biomedical Research Unit in Cardiovascular Disease, Leicester, UK Correspondence to Lisa Manning, MBChB, Room 228, Robert Kilpatrick Clinical Sciences Building, University of Leicester, P.O. Box 65, Leicester LE2 7LX, UK Tel: + 44 0116 252 3182; fax: + 44 0116 252 5847; e-mail: [email protected] Received 17 December 2014Received 17 March 2015 Accepted 31 March 2015
together with the physiocal criteria of Wesseling, to provide reliable BP estimates [11,12]. These devices have previously been validated with regard to their accuracy and precision in measuring absolute BP and BPV [13–15].
Assessment of fast and short-lasting changes in BP requires continuous BP recording. As invasive BP monitoring is rarely considered appropriate in clinical practice or research settings, noninvasive beat-to-beat BP measurement is currently the optimal technique to capture short-term BPV [9,10]. The most commonly used commercially available noninvasive monitoring device, the Finapres, now succeeded by the Finometer, utilizes the finger-cuff or volume clamp method developed by Penaz,
Volume clamp methods, however, have several potential methodological and practical limitations: the participant must be nonambulatory throughout the recording, automated calibration (physiocal) must be used at least periodically to ensure reliability [11], the technique may not be appropriate for those with certain conditions – for example, for those with poor peripheral circulation [16], the cuff can only remain inflated for up to 2 h, thus limiting duration of measurement [17], cuff inflation may disturb the patient and lead to alterations in BP and inadequate cuff size or position can affect accuracy. The development of devices capable of measuring beat-to-beat BP noninvasively, without restriction and for longer, uninterrupted durations of time could lead to important progress in BPV research. In this study we investigate the ability of a novel BP monitoring device that derives continuous BP measures from pulse transit time (PTT) to capture short-term BPV: the SOMNOtouch (SOMNOmedics, Randersacker, Germany).
Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's website (www.bpmonitoring.com).
PTT, defined as the time taken for the pulse wave to travel between two arterial sites within the same cardiac cycle, can be measured noninvasively, and it has been
1359-5237 Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.
DOI: 10.1097/MBP.0000000000000128
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found to be correlated with BP [18,19]. Several observational studies have tested the validity and practicability of using the PTT method for continuous BP monitoring, with partly conflicting results [20–24]. Gesche et al. [17] created a function between pulse wave velocity and systolic BP (SBP) and tested its reliability in the determination of BP from PTT measures using a nonlinear algorithm and a one-point calibration. This function forms the basis for the SOMNOmedics-patented PTT method. The SOMNOtouch, a compact device, around the size of a credit card, can be used for continuous BP monitoring for up to 24 h. It is capable of continuous ECG recording and finger plethysmography, measuring PTT as the period between the R spike of the ECG and the peripheral pulse wave in the finger. BP, SpO2 and an ECG trace are displayed on the small touch screen in real time; they can later be uploaded or transferred through Bluetooth to a data analysis system [25]. The SOMNOtouch has several potential advantages over finger-cuff measures: it is compact, lightweight and does not require connection to a data analysis unit during measurement; there is no cuff inflation; it can provide uninterrupted BP measures for up to 24 h with a single calibration. To our knowledge, the SOMNOtouch has not been previously assessed for its ability to estimate BPV. The aim of this study was to determine the accuracy of the SOMNOtouch device in measuring short-term BPV in healthy volunteers, through assessing agreement with BPV measures simultaneously obtained with the commonly used Finometer device.
Methods Participants and measurements
The study included 16 healthy, normotensive volunteers who were employees of the University of Leicester. Study measurements were performed in a dedicated research laboratory. Throughout the procedure, the participants were in the supine position. BP was recorded continuously with the Finometer MIDI device (Finapres Medical Systems, Amsterdam, The Netherlands) on the right hand. The finger cuff was attached to the middle finger of the right hand, and the physiocal was switched on, and then switched off just before the start of recording. The BP parameters were recorded onto a designated computer software system. The SOMNOtouch device was attached to the left wrist, the finger probe was attached to the left middle finger, the ECG electrodes were attached to the chest and the leads were connected to the device as per the manufacturer’s recommendations. Participant age, weight and height were input into the device. Casual cuff BP was measured in the right arm using a British Hypertension Society approved OMRON 705-IT cuff BP monitor (OMRON Healthcare UK Ltd, Milton Keynes, UK) twice at the beginning and twice at the end of the study. Casual BP was also measured once
in the left arm to detect any significant difference in BP between the two arms (>5 mmHg). The second of the two casual BP measurements in the right arm was used to calibrate the SOMNOtouch device, to ensure only a minimal delay between the cuff BP measurement and the start of the SOMNOtouch recording. The Finometer recording was commenced first, and the SOMNOtouch was then calibrated, and recording was commenced as soon as possible thereafter. When both the devices had been recording for at least 1 min, the marker button on the SOMNOtouch and a metronome device were pressed simultaneously to mark the start of study recordings. Data acquisition and editing
Analogue outputs from the Finometer were recorded onto a data acquisition system on a dedicated personal computer for subsequent offline analysis (PHYSIDAS, Department of Medical Physics, University Hospitals of Leicester NHS Trust). BP from the Finometer was sampled at 200 samples/ s. Data acquired by the SOMNOtouch device were uploaded onto a dedicated personal computer using software provided by SOMNOmedics and saved in the ASCII format, with separate files for SBP, diastolic BP (DBP), heart rate (HR) and the marker. Data editing for both devices was completed using in-house software. BP measurements from the Finometer were calibrated using the second of the two readings in the right arm (the same calibration BP used for the SOMNOtouch). Specifically written software adjusted the sampling frequency of the SOMNOtouch device from 64 to 200 samples/s to produce signals with a uniform time base. Data from both devices were inspected visually to identify artefact. Using the electrical output from the metronome on the Finometer recording and the marker start time from the SOMNOtouch files, data from the two devices were time synchronized. Data were then merged by the specifically written software to produce a single file with both Finometer and SOMNOtouch data in a standardized format. Statistical analysis
Further analysis was carried out on in-house programs to obtain mean values and variability parameters for each participant, from each device, for SBP, DBP and HR measurements. We used SD and coefficient of variation (CV) as our BPV parameters, as they are easily calculated, and commonly used. Data are presented as mean (SD) if normally distributed, and as median (interquartile range) if not normally distributed. The mean and variability parameters were calculated for three discreet time periods: the first 3 min, the final 3 min and the first 10 min of recording. This approach was chosen to assess agreement at the beginning and the end of the measurement period, as well as throughout recording, and thus to identify whether agreement between devices differed further from the calibration BP. Files were exported to SPSS (IBM SPSS version 20; SPSS Inc., Chicago, Illinois, USA) for further analysis. We also calculated the mean absolute
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A novel method for measuring short-term BPV Manning et al. 363
and variability parameters for BP and HR from the four casual cuff BPs. The average SBP, DBP and HR parameters from the two devices were compared for significant differences using independent t-tests. Statistical significance was set at P less than 0.05. In-house software was used to determine peak coherence function and the frequency for SBP, DBP and HR for each participant, as well as to obtain the cross-correlation peaks and time delay of measurements from the SOMNOtouch and Finometer (data not shown). There are no direct recommendations for the validation of a continuous non-intra-arterial device in terms of absolute BP measurement, or indeed BPV. Current validation protocols for new devices use measures from a standard mercury sphygmomanometer as the reference, and do not comment on the measurement of BPV, nor apply to continuous BP monitoring; thus, they cannot be directly applied or modified for the purposes of this study, which is primarily concerned with the measurement of short-term BPV using beat-to-beat BP measurements. The European Society of Hypertension international protocol for the validation of BP measuring devices and the British Hypertension Society guidelines use a grading criteria based on the cumulative percentage of readings falling within 5, 10 and 15 mmHg of the mercury standard, and the Association for the Advancement of Medical Instrumentation guidelines state that the test device must not differ from the mercury standard by a mean difference greater than 5 mmHg or an SD greater than 8 mmHg [26,27]. We used Bland–Altman plots to assess agreement between the average absolute BP measures and withinindividual BPV parameters for each participant, derived from the Finometer and SOMNOtouch devices [28]. The Bland–Altman technique allows for the degree of agreement between the two devices to be calculated, to ensure that the measurements from the new device are within a clinically acceptable range compared with the older device. A graph of the differences between two simultaneous measurements (y axis) against their mean values (x axis) was plotted. The 95% limit of agreement was then calculated from the mean difference (bias) and the SD of the differences (limit of agreement = mean difference ± 2 SD). In cases in which visual inspection of the Bland–Altman plots led to a suspicion of proportional bias, the relationship was formally assessed by linear regression analysis of the differences and mean values. If a significant slope on the regression line (P < 0.05) was identified, then regression-based 95% limits of agreement were calculated [28].
Results Data were collected from 16 healthy volunteers. After visual inspection, data from two participants were excluded from further analysis, one because of loss of BP signal from the Finometer recording and one because of a lack of a marker file from the SOMNOtouch recording,
leaving a total of 14 participants for the final analysis. The mean age was 37.7 years (SD 14.8), and four participants (28%) were male. Absolute blood pressure and heart rate
Over minutes 0–10, the group mean SBP from the SOMNOtouch BP measures was 119.3 mmHg (3.9) and that from the Finometer was 125.7 mmHg (6.6; P = 0.01); the mean DBP from the SOMNOtouch was 75.8 mmHg (1.7) and from the Finometer was 74.1 mmHg (3.4; P = 0.43). Within each of the three predefined measurement periods, statistically significant differences were observed in the mean SBP values obtained from the SOMNOtouch and Finometer devices (Supplementary Table 1, Supplemental digital content 1, http://links.lww.com/BPMJ/A8). No statistically significant differences were observed in the mean DBP or HR values, except for DBP during 0–3 min (Supplementary Table 1, Supplemental digital content 1, http://links.lww.com/BPMJ/A8). Individual correlation coefficients (r) for SBP ranged from 0.35 to 0.71 and for DBP from 0.22 to 0.54 for the whole 10-min measurement period, implying a weak to moderate positive correlation between SOMNOtouch and Finometer BP measures. A greater agreement in the average SBP measures and a narrower scatter on Bland–Altman plots were observed during minutes 0–3 compared with minutes 7–10: minutes 0–3, bias − 3.43 mmHg (limits of agreement, − 14.40 to + 7.32); minutes 7–10, − 7.54 mmHg (− 20.97 to + 15.40). Supplementary Figure 1 (Supplemental digital content 2, http://links.lww.com/BPMJ/A9) shows a Bland–Altman plot for the mean SBP from the SOMNOtouch and Finometer devices over the whole 10-min period. Limits of agreement for the mean DBP were narrower during minutes 0–3 than during minutes 7–10: minutes 0–3, bias 1.97 mmHg (− 9.59 to + 13.57); minutes 7–10, 1.40 mmHg (− 16.11 to 16.10). Limits of agreement for the mean HR (in beats/min) were narrow: minutes 0–10, bias − 0.86 bpm (limits of agreement, − 4.50 to + 2.81). Blood pressure and heart rate variability parameters Systolic blood pressure variability parameters
The averaged systolic BPV parameters for the whole group (SD and CV) obtained from the SOMNOtouch and Finometer devices are given in Table 1. Statistically significant differences in systolic BPV parameters derived from the two devices were observed in the 0–10 and 7–10 min periods, although not in the 0–3 min period (Table 1). Limits of agreement for SD and CV SBP were wide for all three measurement periods (Table 2), with broad scatter seen on Bland–Altman plots (Figs 1–3). Visual inspection of the plots for minutes 0–10 (Fig. 1) and minutes 0–3 (Fig. 2) revealed potential proportional bias. However, linear regression analysis of the differences in SD SBP against the mean SD SBP values revealed no statistically significant slopes on the regression lines.
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Table 1 Mean systolic and diastolic blood pressure variability and heart rate variability parameters derived from SOMNOtouch, Finometer, and casual cuff blood pressure measurements Time period 0–10 min
0–3 min
7–10 min
Parameter
SOMNOtouch value
Finometer value
P-value*
Casual cuff valuea
SD SBP (mmHg) CV SBP (%) SD DBP (mmHg) CV DBP (%) SD HR (bpm) CV HR (%) SD SBP (mmHg) CV SBP (%) SD DBP (mmHg) CV DBP (%) SD HR (bpm) CV HR (%) SD SBP (mmHg) CV SBP (%) SD DBP (mmHg) CV DBP (%) SD HR (bpm) CV HR (%)
3.59 3.01 1.71 2.23 4.83 6.51 10.64 9.05 6.85 8.94 7.57 10.23 1.17 2.49 1.16 1.66 4.33 5.93
6.65 5.14 3.36 4.58 4.85 6.50 11.24 9.27 6.97 9.94 7.73 10.31 2.67 3.78 2.66 3.66 4.52 6.13
0.01 0.01 0.01 0.01 0.92 0.92 0.20 0.16 0.86 0.86 0.42 0.70 0.01 0.01 0.01 0.01 0.01 0.01
11.70 9.64 7.79 10.51 5.25 5.75 – – – – – – – – – – – –
bpm, beats per minute; CV, coefficient of variation; DBP, diastolic blood pressure; HR, heart rate; SBP, systolic blood pressure. Calculated from four casual cuff BP measurements (two at the start and two at the end of the 10-min measurement period). *P-value for the difference between SOMNOtouch and Finometer parameters. a
Bias and limits of agreement for systolic and diastolic blood pressure variability parameters derived from the SOMNOtouch and Finometer devices over the three defined measurement periods
Table 2
Time period 0–10 min
0–3 min
7–10 min
Parameter
Bias
SD of difference
Limits of agreementa
SD SBP (mmHg) CV SBP (%) SD DBP (mmHg) CV DBP (%) SD SBP (mmHg) CV SBP (%) SD DBP (mmHg) CV DBP (%) SD SBP (mmHg) CV SBP (%) SD DBP (mmHg) CV DBP (%)
− 3.03 − 2.12 − 1.65 − 2.25 − 1.58 − 0.24 − 0.12 − 1.72 − 1.98 0.96 − 1.49 − 2.02
3.79 2.56 1.38 1.57 1.37 2.99 2.58 1.58 1.68 1.24 1.18 1.59
− 10.88 to + 4.55 − 7.24 to + 3.00 − 4.41 to + 1.11 − 5.42 to + 0.89 − 4.32 to + 1.37 − 6.21 to + 5.74 − 5.64 to + 5.06 − 4.87 to + 1.44 − 4.34 to + 1.38 − 1.22 to + 3.44 − 3.85 to + 0.87 − 5.20 to + 1.17
bpm, beats per minute; CV, coefficient of variation; DBP, diastolic blood pressure; HR, heart rate; SBP, systolic blood pressure. a Limits of agreement determined by bias ± (2 SD). *P-value for difference between SOMNOtouch and Finometer parameters.
Diastolic blood pressure variability parameters
Over the first 3 min period, no statistically significant differences were observed in the mean DBP variability indices derived from the two devices (Table 1). However, significant differences were observed for minutes 0–10 and 7–10 (Table 1). Limits of agreement for SD and CV DBP were wide (Table 2), with broad scatter seen on Bland–Altman plots across all three measurement periods (Fig. 4).
Heart rate variability parameters
No significant differences were observed in either CV or SD HR over minutes 0–3 and 0–10 (Table 1). Good agreement was found between HR variability parameters (CV and SD) derived from the SOMNOtouch and Finometer devices, with narrow scatter observed on Bland–Altman plots and narrow limits of agreement reported over all three
measurement periods: minutes 0–10 SD HR, bias − 0.01 bpm (limits of agreement − 0.90 to + 0.09).
Discussion To the best of our knowledge, this is the first study to assess the feasibility of using PTT-derived BP measurements to derive BPV. Estimates of short-term systolic and diastolic BPV derived from the SOMNOtouch and Finometer BP measurements varied considerably, with significant underestimation of BPV on using the SOMNOtouch measures, or alternatively, overestimation of BPV on using Finometer measures. Limits of agreement for all BPV parameters were wider than acceptable in the research setting, with Bland–Altman plots showing wide scatter, over all three measurement periods. As such, we would not currently recommend the SOMNOtouch device as an acceptable alternative to the Finometer for the estimate of short-term BPV. Limits of agreement for absolute
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A novel method for measuring short-term BPV Manning et al. 365
Fig. 3
15.00 10.00 5.00 0.00 −5.00 −10.00 −15.00 8.00 2.00 4.00 6.00 SD SBP mean (SOMNOtouch and Finometer) (mmHg)
Difference (SOMNOtouch SD SBP − Finometer SD SBP) (mmHg)
Difference in SD SBP (SOMNOtouch − Finometer) (mmHg)
Fig. 1
5.00
2.50
0.00 −2.50 −5.50 6.00 1.00 2.00 3.00 4.00 5.00 SD SBP mean (SOMNOtouch and Finometer) (mmHg)
Bland–Altman plot of SD of systolic blood pressure derived from SOMNOtouch and Finometer measurements for minutes 7–10. The horizontal dotted line indicates limits of agreement (bias ± 2 SD). The horizontal thick black line indicates bias. SBP, systolic blood pressure.
Fig. 2
Fig. 4
5.00
Difference in SD DBP (SOMNOtouch − Finometer) (mmHg)
Difference in SD SBP (SOMNOtouch − Finometer) (mmHg)
Bland–Altman plot of SD of systolic blood pressure derived from SOMNOtouch and Finometer measurements for minutes 0–10. The horizontal dotted line indicates limits of agreement (bias ± 2 SD). The horizontal thick black line indicates bias. SBP, systolic blood pressure.
4.00 3.00 2.00 1.00 0.00 −1.00 −2.00 −3.00 −4.00 −5.00 8.00 10.00 12.00 14.00 16.00 18.00 SD SBP mean (SOMNOtouch and Finometer) (mmHg)
Bland–Altman plot of SD of systolic blood pressure derived from SOMNOtouch and Finometer measurements for minutes 0–3. The horizontal dotted line indicates limits of agreement (bias ± 2 SD). The horizontal thick black line indicates bias. SBP, systolic blood pressure.
5.00 4.00 3.00 2.00 1.00 0.00 −1.00 −2.00 −3.00 −4.00 −5.00 5.00 1.00 2.00 3.00 4.00 SD DBP mean (SOMNOtouch and Finometer) (mmHg)
Bland–Altman plot of SD of diastolic blood pressure derived from SOMNOtouch and Finometer measurements for minutes 0–10. The horizontal dotted line indicates limits of agreement (bias ± 2 SD). The horizontal thick black line indicates bias. DBP, diastolic blood pressure.
assumptions as to which device this applies to or indeed whether it applies to both. BP measures from the two devices were wider than acceptable according to Association for the Advancement of Medical Instrumentation standards, although this study was not aimed at validating the SOMNOtouch device for absolute BP measurements, and such guidelines are not applicable to finger BP monitors. For absolute BP, agreement was greater during the first 3-min measurement period. One potential explanation for this is that BP measures from the SOMNOtouch diminish in accuracy as the time from the calibration cuff BP increases. However, one cannot make
Good agreement was seen in HR and HR variability parameters derived from the two devices. This suggests not only that the two devices agree in terms of HR measurement, but also that our method of time synchronizing data from the two devices was robust. This assumption is further supported by individual correlation coefficients and crosscorrelation peaks for HR parameters (data not shown), and by visual inspection of output data from both devices. There was a trend towards the SOMNOtouch reporting lower absolute SBP and higher DBP values, whereas the averaged
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variability parameters for SBP and DBP derived from the SOMNOtouch measures were lower than those derived from the Finometer measures. Although there are no previous studies on BPV estimation using PTT-derived BP measures, our findings do concur with those of studies that have assessed the technique’s ability to measure and track changes in absolute BP values. Two studies reported a good correlation between PTT-derived and cuff-based absolute BP measures [17,24], but found wide limits of agreement (− 19.8 to +19.8) [17] and reported that the PTT method lacked sensitivity in tracking BP changes; several studies comparing the PTT method with intra-arterial BP measurement have reported wide limits of agreement for absolute SBP [21,23,29] in cohorts of healthy volunteers [21] and individuals with cardiac disease [23], with wider limits of agreement among those with hypotension [23, 24]. Perhaps the PTT method is less precise at lower BP levels, which could be relevant in our study of healthy volunteers with mostly lower than average resting BP values. Other studies have reported more promising findings on the precision of PTT-derived absolute BP measures, although none report BPV estimation [20,21]. Overall interpretation of the findings from the available studies is complicated by heterogeneity in participants, methodology and reference BP measures, as well as by considerable differences in statistical designs. In addition, a lack of consensus on the acceptable level of agreement required for any new continuous noninvasive BP monitoring technique compared with currently accepted devices, particularly in terms of estimating BPV, means that we have no clearly defined benchmark for the minimum acceptable standard of precision. This said, on the basis of our findings as well as other available studies, one could postulate that the current PTTbased BP measurement techniques lack sufficient sensitivity to accurately track BP changes and are thus unlikely to be able to accurately capture BPV. Further possible explanations for the lack of agreement in BPV parameters between the Finometer and SOMNOtouch devices may be related to the ability of R-wave-gated photoplethysmography (RWPP) to detect changes in PTT. One literature review and several studies have reported that RWPP is not accurate at determining PTT [30,31], BP changes are not consistently associated with changes in PTT [30] and the correlation between PTT and BP measures from the Portapres device (portable version of the Finapres) in healthy adults is poor [32]. The applicability of the Moens–Korteweg equation, from which calibration functions are derived for PTT-based BP measures, has also been questioned. The equation assumes that there are insignificant variations in vessel radius and section, which may not be true in younger healthy individuals with compliant vessels. Thus, BP changes may simply not be accompanied by detectable changes in PTT on using the RWPP technique.
Studies using techniques other than RWPP have also found that BP changes are not always accompanied by the expected changes in PTT [29,31,33]. However, studies in sleep medicine have shown RWPP to be accurate in indicating BP arousals in the setting of obstructive sleep apnoea [19,34]. Perhaps in our study of healthy volunteers, fluctuations in BP were of too small in magnitude to be accompanied by detectable changes in PTT, because of the current PTT method lacking sensitivity to track BP changes. Determination of BP from PTT has methodological limitations that may have influenced our results: measurements are influenced by the quality of the ECG and finger plethysmography, and the measured PTT depends on the pre-ejection period, as well as the transition time of the arterial pulse pressure wave. The pre-ejection period may be affected by many factors including sympathetic activity and medication, and its contribution towards measured PTT varies considerably between individuals. The pre-ejection period and the transition time of the pulse wave are expected to contribute differently to SBP and DBP, and this may be relevant when considering the tendency for overestimation of SBP and underestimation of DBP by PTT methods, as compared with invasive and cuff BP measures, in our study and in others: the transition time of the pulse wave is correlated most to SBP, and both the pre-ejection period and the transition time of the pulse wave are correlated with DBP [21]. Inaccuracies in BP measurement and detection of BP changes by the Finometer device are also possible. Although validation studies suggest that the Finapres serves as a reliable alternative to intra-arterial BP measures in terms of absolute BP and BPV [14,15], validation data specific to the Finometer are limited, and neither device is as precise in BPV estimation as intra-arterial measurement. Furthermore, the volume clamp method has potential operational shortcomings, as discussed earlier. In our study, the risk of operational errors was minimized, as measurements were made by an experienced researcher in a dedicated, temperature-controlled research room; output files were visually inspected to detect artefact and potential finger-cuff application issues; and output signals were calibrated with a brachial cuff BP measurement. Limitations of this study include the following: limited precision of the estimates because of the small sample size and the lack of comparison with BPV from intra-arterial BP measures; BP fluctuations were only physiological, and we cannot comment on the ability of the SOMNOtouch to detect larger fluctuations in BP; potential inaccuracy in calibration, as casual cuff measurements were performed on the right arm but the SOMNOtouch was applied onto the left hand, and there was a slight, unavoidable time delay between casual BP measurement and the commencement of BP recordings. These potential sources of error were minimized by the measurement of BP in both arms before the monitoring period and exclusion of those with a greater than 5 mmHg difference, and by ensuring a minimal (few
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A novel method for measuring short-term BPV Manning et al. 367
seconds) delay between calibration and study commencement. The different sampling rates of the SOMNOtouch (64 samples/s) and Finometer (200 samples/s) devices also made comparing the two systems more complex. Whereas the Finometer outputs a continuous recording of BP, the SOMNOtouch provides either systolic or diastolic values that are averaged for a few heart cycles and then presented to the output as a ‘sample and hold’ value. Although downsampling the Finometer signal to 64 samples/s would be an option, the alternative of extending the SOMNOtouch output to 200 samples/s was preferred to provide good visualization of the BP changes during the cardiac cycle and help detect any potential artefact. As the final analysis was based on data resampled for each cardiac cycle, the change in the sampling rate for SOMNOtouch did not have any influence on the BPV metrics presented above. Our study demonstrated poor agreement between the SOMNOtouch device and the Finometer device in the assessment of BPV, which may in part reflect an inability of the PTT method to sensitively detect BP fluctuations. Furthermore, poor correlation and wide limits of agreement were seen between absolute BP readings from the two devices. For HR and HR variability, good agreement was observed. We would not currently recommend using the SOMNOtouch device to estimate short-term BPV. The ability of PTT-derived BP measurements to measure BPV and track BP changes, outside of the sleep medicine setting, warrants further investigation before such techniques can be relied upon to provide accurate estimates of BPV.
Acknowledgements L.M. is supported by a programme grant from the British Heart Foundation and United Kingdom Stroke Association (TSA BHF 2012/01). The authors thank SOMNOmedics for the loan of the SOMNOtouch device.
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Conflicts of interest
There are no conflicts of interest.
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