Accuracy and precision of cardiac output estimation by an automated,brachial cuff-based oscillometric device in patients with shock

Abstract

Non-invasive monitoring of cardiac output is a technological and clinical challenge, especially for critically ill, surgically operated, or intensive care unit patients. A brachial cuff-based, automated, oscillometric device used for blood pressure and arterial stiffness ambulatory monitoring (Mobil-O-Graph) provides a non-invasive estimation of cardiac output values simultaneously with regular blood pressure measurement. The aim of the study was to evaluate the feasibility of this apparatus to estimate cardiac output in intensive care unit patients and to compare the non-invasive estimated cardiac output values with the respective gold standard method of thermodilution during pulmonary artery catheterization. Repeated sequential measurements of cardiac output were performed, in random order, by thermodilution (reference) and Mobil-O-Graph (test), in 24 patients hospitalized at intensive care unit. Reproducibility and accuracy of the test device were evaluated by Bland–Altman analysis, intraclass correlation coefficient, and percentage error. Mobil-O-Graph underestimated significantly the cardiac output by −1.12 ± 1.38 L/min (p < 0.01) compared to thermodilution. However, intraclass correlation coefficient was >0.7 indicating a fair agreement between the test and the reference methods, while percentage error was approximately 39% which is considered to be within the acceptable limits. Cardiac output measurements were reproducible by both Mobil-O-Graph (intraclass correlation coefficient = 0.73 and percentage error = 27.9%) and thermodilution (intraclass correlation coefficient = 0.91 and percentage error = 26.7%). We showed for the first time that cardiac output estimation in intensive care unit patients using a non-invasive, automated, oscillometric, cuff-based apparatus is reproducible (by analyzing two repeated cardiac output measurements), exhibiting similar precision to thermodilution. However, the accuracy of Mobil-O-Graph (error compared to thermodilution) could be considered fairly acceptable. Future studies remain to further examine the reliability of this technology in monitoring cardiac output or stroke volume acute changes which is a more clinically relevant objective.

Keywords

Pulse wave analysis Mobil-O-Graph brachial artery aortic hemodynamics blood flow measurement

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References

Alhashemi

Cecconi

Hofer

. Cardiac output monitoring: an integrative perspective. Crit Care 2011; 15: 214.

Pugsley

Lerner

. Cardiac output monitoring: is there a gold standard and how do the newer technologies compare? Semin Cardiothorac Vasc Anesth 2010; 14: 274–282.

Bossert

Gummert

Bittner

, et al. Swan-Ganz catheter-induced severe complications in cardiac surgery: right ventricular perforation, knotting, and rupture of a pulmonary artery. J Card Surg 2006; 21: 292–295.

Altamirano-Diaz

Welisch

Dempsey

, et al. Non-invasive measurement of cardiac output in children with repaired coarctation of the aorta using electrical cardiometry compared to transthoracic Doppler echocardiography. Physiol Meas 2018; 39: 055003.

Chew

Aneman

. Haemodynamic monitoring using arterial waveform analysis. Curr Opin Crit Care 2013; 19: 234–241.

Papaioannou

Vardoulis

Stergiopulos

. The “systolic volume balance” method for the noninvasive estimation of cardiac output based on pressure wave analysis. Am J Physiol Heart Circ Physiol 2012; 302: H2064–H2073.

Sangkum

Liu

, et al. Minimally invasive or noninvasive cardiac output measurement: an update. J Anesth 2016; 30: 461–480.

Wassertheurer

Mayer

Breitenecker

. Modeling arterial and left ventricular coupling for non-invasive measurements. Simul Model Pract Th 2008; 16: 988–997.

Protogerou

Argyris

Nasothimiou

, et al. Feasibility and reproducibility of noninvasive 24-h ambulatory aortic blood pressure monitoring with a brachial cuff-based oscillometric device. Am J Hypertens 2012; 25: 876–882.

10.

Papaioannou

Argyris

Protogerou

, et al. Non-invasive 24 hour ambulatory monitoring of aortic wave reflection and arterial stiffness by a novel oscillometric device: the first feasibility and reproducibility study. Int J Cardiol 2013; 169: 57–61.

11.

Weber

Wassertheurer

Rammer

, et al. Validation of a brachial cuff-based method for estimating central systolic blood pressure. Hypertension 2011; 58: 825–832.

12.

Weber

Wassertheurer

Hametner

, et al. Noninvasive methods to assess pulse wave velocity: comparison with the invasive gold standard and relationship with organ damage. J Hypertens 2015; 33: 1023–1031.

13.

Ganz

Donoso

Marcus

, et al. A new technique for measurement of cardiac output by thermodilution in man. Am J Cardiol 1971; 27: 392–396.

14.

Hadian

Pinsky

. Evidence-based review of the use of the pulmonary artery catheter: impact data and complications. Crit Care 2006; 10(Suppl. 3): S8.

15.

Alkhodair

Tsang

MYC

Cairns

, et al. Comparison of thermodilution and indirect Fick cardiac outputs in pulmonary hypertension. Int J Cardiol 2018; 258: 228–231.

16.

Wassertheurer

Kropf

Weber

, et al. A new oscillometric method for pulse wave analysis: comparison with a common tonometric method. J Hum Hypertens 2010; 24: 498–504.

17.

Kusunoki

Iwashima

Kawano

, et al. Circadian hemodynamic characteristics in hypertensive patients with primary aldosteronism. J Hypertens 2018; 36: 2260–2268.

18.

Kusunoki

Iwashima

Kawano

, et al. Association between circadian hemodynamic characteristics and target organ damage in patients with essential hypertension. Am J Hypertens 2019; 32: 742–751.

19.

Vardoulis

Papaioannou

Stergiopulos

. Validation of a novel and existing algorithms for the estimation of pulse transit time: advancing the accuracy in pulse wave velocity measurement. Am J Physiol Heart Circ Physiol 2013; 304: H1558–H1567.

20.

Papaioannou

Karatzis

Papamichael

, et al. Circadian variation of arterial pressure wave reflections. Am J Hypertens 2006; 19: 259–263.

21.

Papaioannou

Protogerou

Nasothimiou

, et al. Assessment of differences between repeated pulse wave velocity measurements in terms of “bias” in the extrapolated cardiovascular risk and the classification of aortic stiffness: is a single PWV measurement enough? J Hum Hypertens 2012; 26: 594–602.

22.

Vidal-Petiot

Joseph

Resche-Rigon

, et al. External validation and comparison of formulae estimating 24-h sodium intake from a fasting morning urine sample. J Hypertens 2018; 36: 785–792.

23.

Bartko

. The intraclass correlation coefficient as a measure of reliability. Psychol Rep 1966; 19: 3–11.

24.

Bravo

Potvin

. Estimating the reliability of continuous measures with Cronbach’s alpha or the intraclass correlation coefficient: toward the integration of two traditions. J Clin Epidemiol 1991; 44: 381–390.

25.

Koo

. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med 2016; 15: 155–163.

26.

Peyton

Chong

. Minimally invasive measurement of cardiac output during surgery and critical care: a meta-analysis of accuracy and precision. Anesthesiology 2010; 113: 1220–1235.

27.

Critchley

. A meta-analysis of studies using bias and precision statistics to compare cardiac output measurement techniques. J Clin Monit Comput 1999; 15: 85–91.

28.

Karamanou

Papaioannou

Tsoucalas

, et al. Blood pressure measurement: lessons learned from our ancestors. Curr Pharm Des 2015; 21: 700–704.

29.

Cicchetti

. Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology. Psychol Assessment 1994; 6: 284–290.

30.

Linton

. Is comparison of changes in cardiac output, assessed by different methods, better than only comparing cardiac output to the reference method? Br J Anaesth 2002; 89: 336–337; author reply 337–339.

31.

Williams

Lacy

Thom

, et al. Differential impact of blood pressure-lowering drugs on central aortic pressure and clinical outcomes: principal results of the Conduit Artery Function Evaluation (CAFE) study. Circulation 2006; 113: 1213–1225.

32.

Nguyen

Squara

. Non-invasive monitoring of cardiac output in critical care medicine. Front Med 2017; 4: 200.