BMC Anesthesiol. 2017; 17: 48.
Published online 2017 Mar 21. doi: 10.1186/s12871-017-0337-z
Continuous Non-invasive finger cuff CareTaker® comparable to invasive intra-arterial pressure in patients undergoing major intra-abdominal surgery
Irwin Gratz,1 Edward Deal,1 Francis Spitz,1 Martin Baruch,2 I. Elaine Allen,3 Julia E. Seaman,4 Erin Pukenas,1 and Smith Jean1
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Data Availability Statement
The datasets generated during and analysed for the current study are available from the corresponding author on reasonable request.
Despite increased interest in non-invasive arterial pressure monitoring, the majority of commercially available technologies have failed to satisfy the limits established for the validation of automatic arterial pressure monitoring by the Association for the Advancement of Medical Instrumentation (AAMI). According to the ANSI/AAMI/ISO 81060–2:2013 standards, the group-average accuracy and precision are defined as acceptable if bias is not greater than 5 mmHg and standard deviation is not greater than 8 mmHg. In this study, these standards are used to evaluate the CareTaker® (CT) device, a device measuring continuous non-invasive blood pressure via a pulse contour algorithm called Pulse Decomposition Analysis.
A convenience sample of 24 patients scheduled for major abdominal surgery were consented to participate in this IRB approved pilot study. Each patient was monitored with a radial arterial catheter and CT using a finger cuff applied to the contralateral thumb. Hemodynamic variables were measured and analyzed from both devices for the first thirty minutes of the surgical procedure including the induction of anesthesia. The mean arterial pressure (MAP), systolic and diastolic blood pressures continuously collected from the arterial catheter and CT were compared. Pearson correlation coefficients were calculated between arterial catheter and CT blood pressure measurements, a Bland-Altman analysis, and polar and 4Q plots were created.
The correlation of systolic, diastolic, and mean arterial pressures were 0.92, 0.86, 0.91, respectively (p < 0.0001 for all the comparisons). The Bland-Altman comparison yielded a bias (as measured by overall mean difference) of −0.57, −2.52, 1.01 mmHg for systolic, diastolic, and mean arterial pressures, respectively with a standard deviation of 7.34, 6.47, 5.33 mmHg for systolic, diastolic, and mean arterial pressures, respectively (p < 0.001 for all comparisons). The polar plot indicates little bias between the two methods (90%/95% CI at 31.5°/52°, respectively, overall bias = 1.5°) with only a small percentage of points outside these lines. The 4Q plot indicates good concordance and no bias between the methods.
In this study, blood pressure measured using the non-invasive CT device was shown to correlate well with the arterial catheter measurements. Larger studies are needed to confirm these results in more varied settings. Most patients exhibited very good agreement between methods. Results were well within the limits established for the validation of automatic arterial pressure monitoring by the AAMI.
Keywords: Non-Invasive, CareTaker, Central blood pressure, Finger cuff, Intra-Arterial pressure
Accurate real-time continuous non-invasive blood pressure monitors (cNIBP) can bridge the gap between invasive arterial pressure monitoring and intermittent non-invasive sphygmomanometry. Latest developments in this field promise accuracy and the potential to lower risk and improve patient outcomes. However, a recent systematic review and meta-analysis of 28 studies using non-invasive technologies by Kim et al. reported that all failed to satisfy the limits that have been established for the validation of automatic arterial pressure monitoring by the Association for the Advancement of Medical Instrumentation (AAMI) . According to this standard, the group-average accuracy and precision are defined as acceptable if bias is not greater than 5 mmHg and standard deviation is not greater than 8 mmHg. Kim et.al. obtained similar results when currently commercially available technologies were examined . In addition, ease of use and patient comfort issues have been impediments to wider acceptance of current noninvasive cNIBP measurement methods. Their results suggest that currently available devices may not have the accuracy and precision for reliable clinical decisions, and there is a need for better devices.
We evaluated the CareTaker® (CT) device (Empirical Technologies Corporation, Charlottesville, Virginia) which has been described in detail elsewhere . Briefly, the CT is a physiological sensing system that communicates physiological data wirelessly via Bluetooth (Fig. 1). The device uses a low pressure [35–45 mmHg], pump-inflated, cuff surrounding the proximal phalange of the thumb that pneumatically couples arterial pulsations via a pressure line to a custom-designed piezo-electric pressure sensor. This sensor converts the pressure pulsations, using transimpedance amplification, into a derivative voltage signal that is then digitized at 500 Hz, transmitted to and recorded on a computer.
The CT measures continuous noninvasive blood pressure via a pulse contour analysis algorithm called Pulse Decomposition Analysis (PDA) . It is based on the concept that five individual component pressure pulses constitute the peripheral arterial pressure pulse. These component pulses are due to the left ventricular ejection and the reflections and re-reflections of the first component pulse from two central arteries reflection sites  . The first reflection site is the juncture between thoracic and abdominal aorta, at the height of the renal arteries, while the second site arises from the interface between abdominal aorta and the common iliac arteries. The renal site reflects the pressure pulse because the juncture of the aortic arteries there features significant changes in arterial diameter and wall elasticity. The two reflected arterial component pressure pulses, the renal reflection pulse (P2) and the iliac reflection pulse (P3), counter-propagate with respect to the original pulse due to the left ventricular contraction (Fig. 2) and arrive in the arterial periphery, specifically at the radial or digital arteries, with distinct time delays . The basic validity of the PDA model was recently corroborated in a detailed and comprehensive arterial tree numerical modeling analysis  that examined the effect of the different arterial segments of the central arteries, the iliac arteries and beyond on the pressure/flow pulse patterns in the digital arteries. The results clearly identified the central arterial reflection sites, as opposed to more distal sites, as being the primary contributors to the pulse patterns observed in the digits.
Quantification and validation of physiological parameters is accomplished by extracting pertinent component pulse parameters . Since the device relies on pulse analysis to track blood pressure, the coupling pressure of the finger cuff is maintained constant and well below diastole, avoiding potential blood flow impediments.
The aim of the present study was to specifically compare the non-invasive arterial pressure values obtained with the CT to the reference invasive arterial pressure technique.
The Cooper Health System Institutional Review Board approved the study, and all subjects gave informed written consent. Data from twenty-four adult patients requiring hemodynamic monitoring during major open abdominal surgery were analyzed in this study. Patients were not excluded due to other medical conditions.
Measurements were obtained during general anesthesia in these patients starting with induction. The induction of anesthesia was chosen because the blood pressure fluctuations and variability typically found during this period provided an opportunity to compare tracking accuracy under baseline and induced controlled dynamic conditions. The data was evaluated using the ANSI/AAMI/ISO 81060–2:2013-related standards of accuracy and precision .
After a stable signal was recorded, patients were induced under general anesthesia by using propofol (2-4 mg/kg) and fentanyl 250ug. Tracheal intubation was facilitated by the administration of rocuronium (0.6 mg/kg). Mechanical ventilation was started using a volume controlled ventilator to maintain an adequate saturation and an end-tidal carbon dioxide of 35 mmHg. Inhalational anesthetic (Isoflurane) was added to maintain a BIS monitoring of 40–45. Vasoactive drugs were used to maintain a MAP greater than 60 mmHg based on the catheter value. Hemodynamic variables were measured from both devices for the entire procedure. The MAP, systolic and diastolic blood pressures were continuously collected from the arterial catheter and CT and averaged over 10 s periods for both devices.
Invasive arterial pressure measurement
Standard arterial blood pressure monitoring was performed prior to the induction of anesthesia using a 20G intra-arterial catheter inserted in the radial artery under local anesthesia using ultra sound guidance. The catheter was connected to a disposable pressure transducer with standard low compliant tubing. The transducer was placed at heart level and zeroed to ambient pressure. The transducer data was digitized, processed and collected using the Datex-Ohmeda S/5 Collect system (Datex-Ohmeda Division, Instrumentarium Corporation, Helsinki, Finland). For analysis, MAP, systolic and diastolic blood pressures were averaged over 10 s intervals.
Non-invasive CareTaker arterial pulse signal recording
The arterial pressure pulse signal was continuously measured using the CT device. For this study the CT device was calibrated using the arterial line blood pressure, but calibration can also be based on non-invasive oscillometric or oscillometric/auscultatory measurements. A fifteen second window at the start of the 30 min overlap section was used to obtain an arterial stiffness reading averaged across 5 beats, which was then used to calculate the PDA parameters for the blood pressure conversions (Fig. 2). With the exception of the four cases mentioned above, patient-specific PDA parameters, once established, were not changed for the matching procedure, irrespective of arterial stiffness or heart rate changes. On four occasions for the entire data set, the offsets of the linear conversion equations were changed as a result of persistent changes in arterial stiffness or heart rate changes exceeding 30%. The PDA algorithm has recently been validated and described elsewhere .
Arterial catheter data were visually inspected and sections of obvious catheter failure, characterized by either continuous or spurious nonsensical reading, were excluded. Sections contaminated by excessive motion artifact such that the peak detection algorithm was no longer able to identify heart beats were also excluded. In the case of the CT data, a custom signal/noise factor (SNF) was used to identify poor quality data sections which were excluded. The factor is based on the standard ratio of the variances of the physiological signal band to the noise band and obtained using Fourier spectral analysis over an 8-s window with 1 s overlap . The frequency range of the band associated with the physiological signal was set to 1–10 Hz, based on data by the authors and results by others,  while the noise band was set to the 100–250 Hz frequency range, which is subject to ambient noise but contains no signal relevant to the base band phenomena of the arterial pressure pulse or its propagation characteristics. Data sections with an SNＦ
below 80 were excluded from the analysis.
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