Validation of the Next-Generation Caretaker Continuous Physiological Monitor Using Invasive Intra-Arterial Pressures in Abdominal Surgery Patients

Main Article Content

Irwin Gratz Martin Baruch Isabel Elaine Allen Julia Seaman Magdy Takla Brian McEniry Edward Deal




The reliable detection and, ultimately, prediction of hypotensive events in post-operative settings remains an unsolved problem, as patients are currently only monitored intermittently because of the lack of validated, non-invasive/non-intrusive and continuous physiological monitoring technologies.

With this goal in mind, the aim of this study was to validate a next-generation platform version of the currently FDA-cleared non-invasive Caretaker (CT) physiological monitor in the hemodynamically challenging environment of abdominal surgeries in comparison with blood pressures obtained from arterial catheters, evaluated against ANSI/AAMI/ISO 81060–2:2019 standards as well as against current non-invasive standard of care measurements provided by clinical-grade automatic oscillometric cuffs.


Comparison data from 41 major abdominal surgery patients at Cooper Hospital (Camden NJ) were analyzed in this IRB approved study. Each patient was monitored with a radial arterial catheter and CT using a finger cuff applied to the contralateral middle finger. Systolic and diastolic blood pressures continuously collected from the arterial catheter and CT were compared using Pearson correlation coefficients and Bland-Altman analysis.  In addition, a trend analysis using 4Q plots was performed. Both the CT’s continuous BP tracking and the CT’s self-calibration capability were analyzed.


The continuous data comparisons were performed with and without taking the CT recalibrations into account. With the recalibrations the mean differences and standard deviations (STDs) for systole and diastole were, respectively, -1.14 mmHg (13.82 mmHg) and -2.49 mmHg (9.42 mmHg), while the correlations were 0.80 and 0.78. Mean differences and STDs for an initial calibration and no subsequent recalibrations were, respectively for systole and diastole, -0.42 mmHg (16.73 mmHg) and -2.57 mmHg (10.36 mmHg), while the correlations were 0.64 and 0.67. For the CT’s self-calibrations alone, correlations for systole and diastole were, respectively, 0.83 and 0.75, while corresponding mean differences (STD) were -3.19 mmHg (10.86 mmHg) and -2.41 mmHg (8.18 mmHg). For 41% of total surgery time, both systole and diastole were within 8 mmHg of the arterial catheter Gold Standard. The concordances for systolic and diastolic blood pressure changes on a 30-second time scale were 0.87 and 0.86. The same comparison analysis for the automatic cuff and the arterial catheter data yielded: correlations for systole and diastole: 0.69 and 0.61, mean differences and STDs: 2.48 mmHg (15.82 mmHg) and 0.65 mmHg (10.68 mmHg).


The results of this study are significant in that they validate the future use of the CT physiological monitor, which utilizes Pulse Decomposition Analysis (PDA), in the post-operative monitoring scenario both as a monitor to detect hypotensive events to facilitate clinical intervention as well as provide signal inputs that could enable anticipatory measures.


Article Details

How to Cite
GRATZ, Irwin et al. Validation of the Next-Generation Caretaker Continuous Physiological Monitor Using Invasive Intra-Arterial Pressures in Abdominal Surgery Patients. Medical Research Archives, [S.l.], v. 9, n. 7, july 2021. ISSN 2375-1924. Available at: <>. Date accessed: 20 apr. 2024. doi:
Research Articles


Turan, Alparslan, Christine Chang, Barak Cohen, Wael Saasouh, Hani Essber, Dongsheng Yang, Chao Ma, et al. Incidence, Severity, and Detection of Blood Pressure Perturbations after Abdominal Surgery: A Prospective Blinded Observational Study. Anesthesiology 130, no. 4 (April 1, 2019): 550–59.
Sessler, Daniel I., Christian S. Meyhoff, Nicole M. Zimmerman, Guangmei Mao, Kate Leslie, Skarlet M. Vásquez, Packianathaswamy Balaji, et al. Period-Dependent Associations between Hypotension during and for Four Days after Noncardiac Surgery and a Composite of Myocardial Infarction and Death: A Substudy of the POISE-2 Trial. Anesthesiology 128, no. 2 (February 2018): 317–27.
Liem, Victor G. B., Sanne E. Hoeks, Kristin H. J. M. Mol, Jan Willem Potters, Frank Grüne, Robert Jan Stolker, and Felix van Lier. Postoperative Hypotension after Noncardiac Surgery and the Association with Myocardial Injury. Anesthesiology 133, no. 3 (September 2020): 510–22.
Smischney, Nathan J., Andrew D. Shaw, Wolf H. Stapelfeldt, Isabel J. Boero, Qinyu Chen, Mitali Stevens, and Ashish K. Khanna. Postoperative Hypotension in Patients Discharged to the Intensive Care Unit after Non-Cardiac Surgery Is Associated with Adverse Clinical Outcomes. Critical Care (London, England) 24, no. 1 (December 7, 2020): 682.
Baruch, M.C. (2019). ‘Pulse Decomposition Analysis Techniques’, Delgado-Gonzalo, R. (2019). The Handbook of Cuffless Blood Pressure Monitoring: A Practical Guide for Clinicians, Researchers, Engineers. Germany: Springer International Publishing, pp. 75-106.
Baruch MC, Warburton DE, Bredin SS, Cote A, Gerdt DW, Adkins CM. Pulse decomposition analysis of the digital arterial pulse during hemorrhage simulation. Nonlinear Biomed Phys. 2011;5(1):1
Kríz J, Seba P. Force plate monitoring of human hemodynamics. Nonlinear Biomedical Physics. 2008;2(1):1.
Latham RD, Westerhof N, Sipkema P, Rubal BJ, Reuderink P, Murgo JP. Regional wave travel and reflections along the human aorta: a study with six simultaneous micromanometric pressures. Circulation. 1985;72(6):1257-69.
Nichols WW, O'Rourke MF 1990: McDonald's blood flow in arteries, third edition.
Epstein S, Willemet M, Chowienczyk PJ, Alastruey J, Reducing the number of parameters in 1D arterial blood flow modeling: less is more for patient-specific simulations, Am J Physiol Heart Circ Physiol. 2015 Jul 1;309(1):H222-34.
Bright MG, Croal PL, Blockley NP, Bulte DP, Multiparametric measurement of cerebral physiology using calibrated fMRI, Neuroimage. 2019 Feb 15;187:128-144.
Couceiro R, Carvalho P, Paiva RP, Muehlsteff J, Henriques J, Schulze V, Ritz A, Characterization of surrogate parameters for blood pressure regulation in neurally-mediated syncope, Conf Proc IEEE Eng Med Biol Soc. 2013;2013:5381-5.
Sorelli M, Perrella A, Bocchi L, Detecting Vascular Age Using the Analysis of Peripheral Pulse, IEEE Trans Biomed Eng. 2018 Dec;65(12):2742-2750.
Michard, Frederic, Thomas W. L. Scheeren, and Bernd Saugel. A Glimpse into the Future of Postoperative Arterial Blood Pressure Monitoring. British Journal of Anaesthesia 125, no. 2 (August 1, 2020): 113–15.
ANSI/AAMI/ISO 81060-2:2013 - Non-Invasive Sphygmomanometers - Part 2: Clinical Investigation of Automated Measurement Type.
Callaghan, F. J., C. F. Babbs, J. D. Bourland, and L. A. Geddes. The Relationship between Arterial Pulse-Wave Velocity and Pulse Frequency at Different Pressures. Journal of Medical Engineering & Technology 8, no. 1 (February 1984): 15–18.
Saugel B, Grothe O, Wagner JY., Tracking Changes in Cardiac Output: Statistical Considerations on the 4-Quadrant Plot and the Polar Plot Methodology, Anesth Analg. 2015 Aug;121(2):514-24.
Kim SH, Lilot M, Sidhu KS, Rinehart J, Yu Z, Canales C, Cannesson M. Accuracy and precision of continuous noninvasive arterial pressure monitoring compared with invasive arterial pressure: a systematic review and meta-analysis. Anesthesiology. 2014;120(5):1080–97.
Picone DS, Accuracy of Cuff-Measured Blood Pressure: Systematic Reviews and Meta-Analyses, J Am Coll Cardiol. 2017 Aug 1;70(5):572-586.
Babbs CF, Oscillometric measurement of systolic and diastolic blood pressures validated in a physiologic mathematical model, Biomed Eng Online. 2012 Aug 22;11:56.
Armstrong MK, Brachial and Radial Systolic Blood Pressure Are Not the Same, Hypertension, 2019; 1036–42.
Moore C, Dobson A, Kinagi M, Dillon B, Comparison of blood pressure measured at the arm, ankle and calf, Anaesthesia. 2008 Dec;63(12):1327-31.
Sareen P, Saxena K, Sareen B, Taneja B, Comparison of arm and calf blood pressure, Indian J Anaesth. 2012 Jan;56(1):83-5.
Lantelme P, Mestre C, Lievre M, Gressard A, Milon, Heart rate: an important confounder of pulse wave velocity assessment, Hypertension. 2002 Jun;39(6):1083-7.
Solà J. et al. (2018) Performance of Systolic Blood Pressure estimation from radial Pulse Arrival Time (PAT) in anesthetized patients. In: Eskola H., Väisänen O., Viik J., Hyttinen J. (eds) EMBEC 2017, NBC 2017. IFMBE Proceedings, vol 65. Springer, Singapore
Delgado-Gonzalo, R. (2019). The Handbook of Cuffless Blood Pressure Monitoring: A Practical Guide for Clinicians, Researchers, and Engineers. Germany: Springer International Publishing.
Takazawa K, Tanaka N, Fujita M, Matsuoka O, Saiki T, Aikawa M, et al:Assessment of vasoactive agents and vascular aging by second derivative of the photoplethysmograph waveform. Hypertension 1998, 32:365-370.
Millasseau SC, Kelly RP, Ritter JM, Chowienczyk PJ, Determination of age-related increases in large artery stiffness by digital pulse contour analysis, Clin Sci (Lond). 2002 Oct;103(4):371-7.