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Technology, Computing, and Simulation: Research Report

The Accuracy and Responsiveness of Continuous Noninvasive Arterial Pressure During Rapid Ventricular Pacing for Transcatheter Aortic Valve Replacement

Schramm, Christoph MD; Huber, Anja; Plaschke, Konstanze PhD

Author Information
doi: 10.1213/ANE.0b013e3182910df5

Adequate monitoring of periods of fast and extreme arterial blood pressure changes is a matter of great clinical importance, especially for elderly patients. Arterial blood pressure in older people is often not adequately regulated because of various age-related risk factors.1,2

A device called CNAP™ (CNSystems Medizintechnik, Graz, Austria) was developed with continuous noninvasive arterial blood pressure (CNAP) measurement that had been demonstrated to be comparable or superior in comparison with intermittent oscillometric measurements.3–5 On the basis of the volume clamp method, this device monitors blood flow into the finger and translates blood flow oscillations sensed by encircling finger cuffs into a continuous pulse pressure waveform and beat-to-beat values of arterial blood pressure.6

In a previous study, we investigated CNAP and intraarterial blood pressure measurements in elderly and sedated patients during different periods of normotension, hypertension, and hypotension.7 The results of this study showed a good agreement of both of these techniques in periods of stable blood pressure. However, it was not possible to measure the agreement of invasive arterial blood pressure (IAP) and noninvasive arterial blood pressure (NIBP) during short-term phases of rapid blood pressure changes, because the monitor used as the reference system averaged the previous 6 beats to improve readability of values on the display. As many monitors in clinical usage incorporate these “smoothing algorithms” that cannot be switched off completely, studies evaluating rapid changes in blood pressures should use the analysis of raw waveforms rather than values calculated by the monitor. Therefore, a completely different technical setup compared with the previous study was used. A computer program was developed and implemented into the analysis to compare the simultaneous beat-to-beat changes in blood pressure curves of NIBP and IAP measuring techniques under conditions of fast blood pressure changes on patients undergoing elective transfemoral aortic valve implantations.


Selection and Description of Participants

Patients for the present study were recruited between January and May 2011 at the University of Heidelberg (Heidelberg, Germany) after obtaining written informed consent. This prospective human study was approved by the appropriate local ethics committee (number S234/2009) and IRB and was performed in accordance with the ethical standards of the Declaration of Helsinki. The study is registered at

Inclusion criteria were age ≥18 years and elective transfemoral implantation of the aortic valve due to severe aortic stenosis using analgesic sedation. Severe aortic stenosis was defined as a valve area <1 cm2 or a mean pressure gradient >50 mm Hg. Exclusion criteria were advanced peripheral perfusion dysfunction (i.e., pronounced arterial peripheral artery occlusive disease or Raynaud syndrome), arteriovenous shunts for hemodialysis, and vascular surgery of the upper extremities (n = 7).

Anesthetic Management and Procedural Information

Continuous monitoring during the aortic valve implantation consisted of a 5-lead electrocardiogram (ECG), pulse oximetry (SpO2), IAP measured in a radial artery, CNAP on the same arm as IAP, and central venous pressure. The following cannulas and catheters were inserted using local anesthesia in a standardized order: a peripheral venous cannula size 20 gauge (BD Venflon Pro Safety®, Becton Dickinson Infusion Therapy, Helsingborg, Sweden), a 20-gauge arterial line (Leader Cath®, Vygon, Ecouen, France) inserted using Seldinger technique and connected to a pressure transducer (LogiCal® monitoring kit, Smiths Medical International Ltd, Rossendale, Lancashire, United Kingdom), a 9-Fr lock (MAC Two Lumen Central Venous Access Set® with Integral Hemostasis Valve; Arrow Germany, Erding, Germany), a ventricular pacing wire (5 Fr Swan-Ganz® Bipolar Pacing Catheter, Edwards Lifesciences, Irvine, CA) with a threshold of <1 mV connected to a pacemaker (Pacemaker Osypka Pace 101H, Osypka Medical, Berlin, Germany), and a Foley catheter. Analgesic sedation was performed with very low continuous dosages of propofol (mean 1.3 mg·kg−1·h−1) and remifentanil (mean 0.03 µg·kg−1·min−1) throughout the procedure. The anesthetic procedure and the interventional procedure are described in detail in a previous study.7

Rapid Pacing

During transfemoral implantation of the aortic valve, short intervals of very low cardiac output are required during balloon valvuloplasty and release of the aortic valve of certain models of balloon catheters. To achieve a sudden functional cardiocirculatory arrest on command, rapid pacing via a transient ventricular pacing wire is used. Ventricular pacing with frequencies between 180 and 200 per minute results in a sudden decrease of systolic arterial blood pressure from approximately 110 to 40 mm Hg. After valvuloplasty or implantation of the valve, the pacemaker is deactivated or reduced to a frequency of approximately 80 per minute. This usually leads to a recovery of cardiac output and arterial blood pressure.

For analysis of fast blood pressure changes in our study, an episode of severe hypotension was defined from 5 normal arterial blood pressure values before the actual decrease in blood pressure induced by rapid pacing to complete recovery of systolic arterial blood pressure to the value before rapid pacing. In addition, the “rapid pacing period” was divided into 4 phases: “Normal” stands for the 5 values before the actual decrease in blood pressure, which is “Transition to hypotension.” “During hypotension” is the functional circulatory arrest, and “Transition to normal” is the recovery to prepacing arterial blood pressure values. A representative picture of an episode of severe hypotension is illustrated in Figure 1.

Figure 1
Figure 1:
Episode of severe hypotension with definition of phases. The focus of this study is the comparison of the waveforms of continuous noninvasive arterial blood pressure (CNAP) with invasive arterial blood pressure (IAP) during severe hypotension induced by rapid ventricular pacing. For detailed evaluation of the CNAP technique, the hypotensive episodes were divided into 4 phases: normal (5 beats before the start of rapid pacing, only 3 beats are shown for better readability), transition to hypotension (decrease of blood pressure to the first minimum), severe hypotension (functional cardiocirculatory arrest), and transition to normal (stop of rapid pacing until the recovery of the blood pressure to the prepacing values). ECG = electrocardiogram.

Data Acquisition and Data Processing

The finger cuffs of the CNAP device were connected to the controller and the CNAP monitor (model 500at, software version V3.5 R01, hardware revision R06, CNSystems). The CNAP finger values were calibrated with an oscillometric blood pressure cuff on the upper arm of the ipsilateral side of the IAP. The calibration interval of the CNAP monitor was set to 60 minutes and we insured that no calibration took place during rapid pacing by performing an additional calibration just before rapid pacing if needed. Finally, all monitoring devices including CNAP were connected to a Draeger Infinity® Delta monitor (Draeger Medical, Lübeck, Germany) to guarantee absolute accurate waveform synchronization of CNAP and IAP. Because the Draeger monitor averages the numeric values of heart rate and IAP so as not to display rapidly changing values or give false alarms during the drawing of blood samples, the use of numeric values of these parameters for rapid changes has limited validity. We therefore recorded the waveforms of ECG, IAP, and CNAP (ECG at 200 Hz, IAP and CNAP at 100 Hz) with the eData Clinical Research Software V2006.3.28 build 238 (Erasmus® MC, Siemens/Draeger Medical Systems) on a study laptop. The nontime-critical values such as SpO2 and central venous pressure were recorded in 1-second intervals.

To calculate the systolic, diastolic, and mean arterial blood pressure values from the waveforms, to assure the comparison of corresponding values of IAP and CNAP despite a small time offset of the waveforms due to the time needed for the pulse wave to travel from the radial artery to the finger arteries, and to eliminate artifacts with high reliance, we developed a software program consisting of several steps: first, we imported the values describing the waveforms ECG lead II, IAP, and CNAP into an Excel (Microsoft, Redmond, WA) file, synchronized the data, and drew diagrams for the whole recording period of every patient. The CNAP monitor is an approved device for clinical use, which does not have any blood pressure smoothing algorithms. This means that the values displayed by the CNAP monitor respond immediately to any blood pressure change. The reason for us to compare waveform-derived values instead of displayed values was the reference system: the IAP recorded by the routine monitoring system “Infinity Delta” from Draeger Medical. To our knowledge all clinically used monitoring systems (i.e., Infinity Delta) use smoothing algorithms that are especially important during rapid decreases of blood pressure. Therefore, the IAP values calculated by the available standard monitoring systems are not usable as a reference system for rapidly changing blood pressures. To solve this problem, we recorded waveforms of CNAP and IAP and calculated the most accurate values to bypass the smoothing algorithms of the reference method IAP. We manually checked those diagrams for artifacts and deleted invalid episodes such as CNAP calibration intervals or episodes with collection of blood pressure samples for blood gas analysis. Furthermore, we excluded incorrect measurement periods such as extreme patient movements from further analysis. For the conversion of the waveform into systolic and diastolic values, we automatically detected maximum and minimum values and then excluded maximum values that were an increase of ≤5% of the preceding minimum to eliminate dicrotic notches. The last step was the calculation of the mean arterial blood pressures by integrating all points of the waveforms between the corresponding 2 diastoles and the calculation of the heart rates through the distances between systoles. We finally compiled all data into 1 Excel file for further analysis.

Overall, we recorded 16,242,333 waveform data points for CNAP and IAP. In all, 17.7% were deleted due to invalid measurement. The main reasons for excluded data were CNAP calibration intervals (40.4%) or continued recording after termination of the procedure (24.4%). Artifacts had to be deleted at approximately equal parts in IAP and CNAP (17% each). We finally used 156,208 systolic, 153,443 diastolic, and 152,756 mean pairs of blood pressure values for further analysis.

Statistical Analysis

In accordance with the suggestion of the European Society for Hypertension for the validation of new NIBP devices8 and of previous studies,9–13 33 subjects were required, and therefore were included, in the present study.

We assessed the precision for each method separately. The size of percentage measurement error (precision) was calculated by the within-subject standard deviation (SD) divided by the population mean arterial blood pressure. If there were no clinically important differences between the sizes of the measurement errors, we would accept the interchangeability of IAP and CNAP. P-values were calculated using a t test.

The accuracy of CNAP was assessed analyzing bias and limits of agreement using Bland–Altman analysis for repeated measurements.14,15 Bland and Altman have provided a modification of their standard method for analyzing repeated measurements, where repeated data were collected over a period of time. We used the modified Bland and Altman method to check the assumption that the variance of the repeated measurements for each subject by each method is independent of the mean of the repeated measures. In accordance with Bland and Altman, we used 1-way analysis of variance to estimate the within-subject variance.

Bias is the difference between CNAP and IAP; this was calculated by subtracting IAP values from CNAP values. In addition to relative biases, the absolute biases of the differences between both techniques were calculated.

Analysis of the episodes of severe hypotension additionally included the comparison of the magnitude (decrease of amplitude in millimeters of mercury) and time (in seconds) of arterial blood pressure changes.

Statistical handling of the data set was performed using the SPSS statistical program (Version 19.0, IBM SPSS, Chicago, IL) at a significance level of P < 0.05. Normal distribution of data was determined with the Lilliefors method. Arterial blood pressure differences between methods were analyzed using a dependent t test for paired measurements because there were no correlations of the differences to the baseline. The correlation coefficients were calculated according to the Pearson correlation coefficient. Results are presented as mean ± SD unless stated otherwise.


Patients’ Characteristics and Data Recording

Thirty-three patients were enrolled in the study. Analysis of descriptive patients’ data and comorbidities is presented in Table 1. Seventy-three percent of the patients were classified as ASA physical status III and 27% as ASA physical status IV.

Table 1
Table 1:
Patients’ Characteristics and Comorbidities

The mean recording time per patient was 80 ± 20 minutes. Forty-seven episodes of rapid pacing were recorded. We used 46 rapid pacing episodes for final analysis, because 1 was overlaid by artifacts.

Analysis of Blood Pressure Measurements

Analysis of precision of both methods showed a relative error for systolic, diastolic, and mean arterial blood pressure <10% for IAP and CNAP measurements. The CNAP SD of 60 consecutive values from all patients (excluding episodes of severe hypotension) of 7.3 (5.6–9.0), 5.5 (4.2–6.8), and 6.1 (4.6–7.5) mm Hg were not significantly different from IAP precision 8.1 (6.5–9.6), 5.0 (3.8–6.1), and 6.1 (4.9–7.4) mm Hg (SD of systolic, diastolic, and mean arterial blood pressure [95% confidence interval]). In conclusion, no significant differences in measurement errors (precision) between both measurement techniques were observed (P > 0.05).

Concerning all data, the biases of CNAP were −6.3 ± 18.9, 7.4 ± 10.5, and 4.0 ± 11.3 mm Hg for systolic, diastolic, and mean blood pressures. During episodes of severe hypotension, the biases increased to 11.8 ± 14.5, 13.8 ± 12.4, and 12.9 ± 12.4 mm Hg. Table 2 outlines the accuracy of CNAP compared with IAP. The right side of Table 2 shows mean ± SD for the episodes of severe hypotension, and the left side the remaining time without severe hypotension. Because positive and negative biases neutralize each other during averaging, we additionally calculated the absolute values of the biases.

Table 2
Table 2:
Accuracy of CNAP During Severe Hypotension

Figure 2 presents the Bland–Altman plots of the episodes of severe hypotension and the remaining time without severe hypotension for systolic, diastolic, and mean blood pressures. There is a tendency for higher systolic, diastolic, and mean blood pressures measured by CNAP during episodes of severe hypotension to lie above the upper limits of agreement.

Figure 2
Figure 2:
Bland–Altman plots. The biases of continuous noninvasive arterial blood pressure (CNAP) and invasive arterial blood pressure (IAP) are depicted on the y-axis against the mean of CNAP and IAP on the x-axis. The plots for systolic, diastolic, and mean pressures for the episodes of severe hypotension are shown in the right column, the corresponding plots for all other values are in the left column. Each episode of severe hypotension starts with normal blood pressures and ends with the full recovery of blood pressure. Mean biases are depicted with solid lines; limits of agreement (mean ± 1.96 × SD) with dotted lines.

Concerning the time in detecting severe decreases of blood pressure (phase “Transition to hypotension”), duration of cardiocirculatory arrests (phase “During hypotension”), and recovery of adequate circulation (phase “Transition to normal”), responsiveness of CNAP and IAP did not differ significantly (Table 3).

Table 3
Table 3:
Analysis of the Time Needed by CNAP to Detect the Development of and Recovery from Severe Hypotension

Table 4 describes how many bias values lie below a predefined limit of ±10, ±15, and ±20 mm Hg. When comparing the percentages of the episodes of severe hypotension with the remaining time without severe hypotension, it becomes obvious that they differ significantly in diastolic and mean arterial blood pressure (P < 0.05), but not in systolic values.

Table 4
Table 4:
Percentage of Agreements

Correlation of Bias with Different Parameters

We detected no correlation of the bias of the mean blood pressure (95% confidence interval) with the following parameters: peripheral temperature (r = −0.161 [−0.180 to −0.151]), heart rate (r = 0.098 [0.085–1.011]), central venous pressure (r = 0.055 [0.039–0.072]), pulse oximetry (r = −0.218 [−0.235 to −0.199]), perfusion index (r = 0.111 [0.099–0.121]), propofol dosage (r = −0.068, [−0.078 to−0.050]), remifentanil dosage (r = −0.135 [−0.152 to −0.127]), and norepinephrine dosage (r = −0.029 [−0.036 to−0.016]).


A Human Model for Cardiocirculatory Arrest

Rapid ventricular pacing is a clinically significant method to create a transient cardiac standstill. During balloon aortic valvuloplasties, transcatheter aortic valve implantations, and thoracic endovascular aneurysm repairs the accurate positioning of balloons, valves, and stents must be ensured, and any dislodgement prevented. Abrupt initiation of rapid pacing at frequencies of approximately 200 per minute leads to ventricular tachycardia and reduces the systolic arterial blood pressure to approximately 40 mm Hg with minimal pulse pressure. After termination of the pacing or reduction of the pacing frequency to normal values, the blood pressure usually resumes to the prepacing values.16,17 With the onset of rapid pacing, cardiac output decreases markedly. This leads to a congestion of blood in the central venous system and consequently in the peripheral veins. We monitored central venous pressure continuously during rapid pacing and aortic occlusion while the aortic valve was being deployed, and we observed an increase in central venous pressure of approximately 2 to 4 mm Hg. This might be a reason for CNAP’s diastolic pressure to be significantly higher than the diastolic value of IAP in the radial artery (Fig. 2 and Table 2). It is presumed that the diastolic bias is also influenced by the measuring principle of CNAP. The venous stasis caused by the finger cuffs ensure a constant finger volume (vascular unloading technique) and therefore interfere with the increase of venous pressure and volume described earlier. However, rapid pacing is an adequate human model in our opinion to evaluate the accurateness of cardiocirculatory monitoring devices such as CNAP in extreme conditions, without any additional risks to test subjects. In our study, rapid pacing was initiated during a stable phase with arterial blood pressure of 106/43/74 mm Hg (average of systolic/diastolic/mean). Within 2.6 seconds, the blood pressure decreased steeply and reached the lowest value of 36/29/32 mm Hg 9.5 seconds after the start of pacing. The phase of functional cardiocirculatory arrest (phase “During hypotension”) lasted an average of 10.0 seconds. After termination of rapid pacing, the arterial blood pressure recovered to prepacing values in 8.5 seconds. For the exact evaluation of technical possibilities and limits of devices during such major changes of arterial blood pressure, it is very important that the raw waveform data are used for further calculations, because many monitors incorporate stabilizing algorithms to prevent rapidly changing values. For this study, a special computer program was written to create an exact time match of the waveforms and to extract the systolic, diastolic, and mean arterial blood pressure values (see preceding sections). Finally, it is a requirement of the tested device that an automatic recalibration is not initiated during unstable cardiocirculatory phases, because CNAP does not know whether a low reading is caused by hemodynamic collapse, an artifact, or calibration error. However, the clinician is particularly interested in blood pressure during unstable phases.

The new software of the stand-alone CNAP monitor (model 500at, software version V3.5), which was used in this study, allows a maximum calibration interval of 60 minutes and does not recalibrate during severe decreases of blood pressure. These problems were encountered with the Infinity-CNAP-SmartPod® (Draeger Medical) and were also described by McCarthy et al.18 However, whether this new software will be used in routine clinical practice is a subject of further research.

Results of CNAP Technique Compared with Other Studies

We used the clinical setting of rapid pacing to test the accuracy of the CNAP device. Thus, CNAP accuracy, calculated by bias (CNAP-IAP), was −6.3 ± 18.9, 7.4 ± 10.5, and 4.0 ± 11.3 mm Hg (mean ± SD, systolic, diastolic, and mean). Further, the results of the present study show that bias increased during episodes of severe hypotension to 11.8 ± 14.5, 13.8 ± 12.4, and 12.9 ± 12.4 mm Hg. The analysis of differences in the phases of rapid pacing episodes showed no significant difference between CNAP and IAP for systolic blood pressures (Table 2). The responsiveness of mean CNAP and mean IAP concerning time did not differ significantly during the various phases of the episodes of severe hypotension.

Jeleazcov et al.10 conducted a study on 88 patients undergoing elective abdominal surgery, cardiovascular surgery, or neurosurgery. CNAP (SmartPod) was compared with IAP on the ipsilateral upper extremity, and precision and accuracy calculated. Absolute differences of >50 mm Hg were considered as outliers. They found a bias of −6.7 ± 13.9, 5.6 ± 11.4, and 1.6 ±11.0 mm Hg (systolic, diastolic, mean), whereas our biases were −6.3 ± 18.9, 7.4 ± 10.5, and 4.0 ± 11.3 mm Hg. In contrast to Jeleazcov et al.,10 we did not exclude any differences over a certain threshold, but used a sophisticated algorithm to eliminate artifacts. A subanalysis of Jeleazcov et al.10 addressed fast changes in arterial blood pressure (FCAP), defined as absolute differences between the ending and starting point of a linear regression line on systolic arterial blood pressure during intraoperative episodes of 3 minutes in length that were >20 mm Hg, and various intervals of intraoperative hypotension. Jeleazcov et al.10 found similar detection of FCAP for CNAP and IAP and a higher frequency of intraoperative hypotension below systolic values of 90 mm Hg with CNAP than with IAP. The detection of FCAP during smaller variations of blood pressure is comparable with our results during severe variations.

Hahn et al.19 analyzed 524,878 paired measurements in 100 patients undergoing major elective orthopedic surgery during general anesthesia. They compared the accuracy of 2 software versions (V3.0 vs V3.5) of the CNAP500 stand-alone monitor with IAP. The biases −3.4 ± 16, 4.4 ± 10.8, and 2.9 ± 10.6 mm Hg (V3.0) and −0.9 ± 13.2, 2.8 ± 8.6, and 3.1 ± 9.5 mm Hg (V3.5, systolic, diastolic, and mean values) are lower than our findings. The differences may partly be explained by the filter algorithms that excluded pulse pressures <10 and >150 mm Hg, systolic pressures <20 and >300 mm Hg, and diastolic pressures <15 and >250 mm Hg.

Another important point concerns the site to which the CNAP is calibrated and the differing arterial blood pressures and waveforms present in the brachial artery (cuff pressure for CNAP calibration) versus the radial artery (invasive reference standard) versus the digital circulation (measuring finger cuffs of CNAP). To our knowledge, in all existing studies the CNAP values were calibrated with an upper arm cuff, and are compared with the IAP readings from the radial artery. A CNAP calibration with an NIBP cuff on the forearm could yield a better agreement with the IAP from the radial artery, presuming that the forearm cuff readings agree more closely with direct radial artery measurements. It is important to realize that the pressure per se may not necessarily reflect effective perfusion at the capillary level.

In our opinion, the initial sign of a severely compromised cardiovascular system in most cases is a massive decrease of blood pressure, while ECG and SpO2 may continue to show normal values for a time. The CNAP device rapidly reflects the acute changes seen with circulatory arrest. A future study with patients in shock will be important to demonstrate the validity of CNAP in patients with prolonged impairment of peripheral perfusion.


We demonstrate that the stand-alone CNAP monitor (model 500at, software V3.5) accurately and rapidly measures the changes of blood pressure that occur during sudden development of cardiocirculatory arrest and recovery to baseline blood pressures. CNAP monitors the duration of the arrest.


Name: Christoph Schramm, MD.

Contribution: This author helped in the study design, conduct of the study, data collection, data analysis, and manuscript preparation.

Attestation: This author attests to having approved the final manuscript. This author attests the integrity of the original data and the analysis.

Name: Anja Huber.

Contribution: This author helped in the study design, conduct of the study, data collection, data analysis, and manuscript preparation.

Attestation: This author attests to having approved the final manuscript. This author attests the integrity of the original data and the analysis.

Name: Konstanze Plaschke, PhD.

Contribution: This author helped in the study design, conduct of the study, data collection, data analysis, and manuscript preparation.

Attestation: This author attests to having approved the final manuscript. This author attests the integrity of the original data and the analysis.

This manuscript was handled by: Dwayne R. Westenskow, PhD.


We thank our colleagues from the Department of Anesthesia, University of Heidelberg for their kind support during the clinical procedure. Additionally, we thank R. Bekeredjian, MD, PhD, H. Katus, MD, PhD, and U. Krumsdorf, MD, from the Department of Internal Medicine (Cardiology) for their cooperation. We thank K. Maier from CNSystems for her assistance with technical issues.


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