Continuous Non-invasive finger cuff CareTaker® comparable to invasive intra-arterial pressure in patients undergoing major intra-abdominal surgery

Irwin Gratz, Edward Deal, Francis Spitz, Martin Baruch, I Elaine Allen, Julia E Seaman, Erin Pukenas, Smith Jean, Irwin Gratz, Edward Deal, Francis Spitz, Martin Baruch, I Elaine Allen, Julia E Seaman, Erin Pukenas, Smith Jean

Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusions: 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: CareTaker; Central blood pressure; Finger cuff; Intra-Arterial pressure; Non-Invasive.

Figures

Fig. 1
Fig. 1
CareTaker Wireless Continuous Blood Pressure and Heart Rate Monitor with Finger Cuff Technology. Copyright 2016. Used with written permission from president and CEO of CareTaker Medical, LLC
Fig. 2
Fig. 2
Sketch of the aorta/arm complex arterial system and its effect on the arterial pressure pulse line shape that is observed at the radial/digital artery. Two reflection sites, one at the height of the renal arteries, the other one in the vicinity of the iliac bifurcation, give rise to the reflected pulses (gray) that trail the primary left ventricular ejection (black). Amplitudinal changes between the left ventricular ejection pulse P1 and the renal reflection pulse P2 as well as timing changes between P1 and the iliac reflection P3 are used to track blood pressure. An arterial stiffness measure is derived from the inversion profile of the pulse envelope
Fig. 3
Fig. 3
(Top) Bland Altman graphs of MAP difference vs. A-line for all timepoints. Correlation (bottom graph, linear fit with 95% confidence bounds)
Fig. 4
Fig. 4
(Top) Bland Altman graphs of Systole difference vs. A-line for all timepoints. Correlation (bottom graph, linear fit with 95% confidence bounds)
Fig. 5
Fig. 5
(Top) Bland Altman graphs of Diastole difference vs. A-line for all timepoints. Correlation (bottom graph, linear fit with 95% confidence bounds)
Fig. 6
Fig. 6
4Q plot of the consecutive changes in the A-line vs. the consecutive changes in CareTaker The 10% zone of inclusion is included
Fig. 7
Fig. 7
Polar plot examining the trend and confidence bounds of the difference between the A-line and the CareTaker
Fig. 8
Fig. 8
Standard Deviation of the differences between a-line and CareTaker data for all patients

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