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Pulse contour analysis of arterial waveform in a high fidelity human patient simulator

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Abstract

The measurement of cardiac output (CO) may be useful to improve the assessment of hemodynamics during simulated scenarios. The purpose of this study was to evaluate the feasibility of introducing an uncalibrated pulse contour device (MostCare, Vytech, Vygon, Padova, Italy) into the simulation environment. MostCare device was plugged to a clinical monitor and connected to the METI human patient simulator (HPS) to obtain a continuous arterial waveform analysis and CO calculation. In six different simulated clinical scenarios (baseline, ventricular failure, vasoplegic shock, hypertensive crisis, hypovolemic shock and aortic stenosis), the HPS-CO and the MostCare-CO were simultaneously recorded. The level of concordance between the two methods was assessed by the Bland and Altman analysis. 150-paired CO values were obtained. The HPS-CO values ranged from 2.3 to 6.6 L min−1 and the MostCare-CO values from 2.8 to 6.4 L min−1. The mean difference between HPS-CO and MostCare-CO was − 0.3 L min−1 and the limits of agreement were − 1.5 and 0.9 L min−1. The percentage of error was 23%. A good correlation between HPS-CO and MostCare-CO was observed in each scenario of the study (r = 0.88). Although MostCare-CO tended to underestimate the CO over the study period, good agreements were found between the two methods. Therefore, a pulse contour device can be integrated into the simulation environment, offering the opportunity to create new simulated clinical settings.

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Abbreviations

CO:

Cardiac output

HPS:

Human patient simulator

PAC:

Pulmonary artery catheter

PRAM:

Pressure recording analytical method

SV:

Stroke volume

References

  1. Zevin B, Aggarwal R, Grantcharov TP. Surgical simulation in 2013: why is it still not the standard in surgical training? J Am Coll Surg. 2014;218:294–301.

    Article  Google Scholar 

  2. Issenberg SB, McGaghie WC, Petrusa ER, Lee Gordon D, Scalese RJ. Features and uses of high-fidelity medical simulations that lead to effective learning: a BEME systematic review. Med Teach. 2005;27:10–28.

    Article  Google Scholar 

  3. Jackson KM, Cook TM. Evaluation of four airway training manikins as patient simulators for the insertion of eight types of supraglottic airway devices. Anaesthesia. 2007;62:388–93.

    Article  CAS  Google Scholar 

  4. Berthiaume LR, Peets AD, Schmidt U, Shahpori R, Doig CJ, Boiteau PJE, et al. Time series analysis of use patterns for common invasive technologies in critically ill patients. J Crit Care. 2009;24:471.e9–14.

    Article  Google Scholar 

  5. Vincent J-L, Pelosi P, Pearse R, Payen D, Perel A, Hoeft A, et al. Perioperative cardiovascular monitoring of high-risk patients: a consensus of 12. Crit Care. 2015;19:224.

    Article  Google Scholar 

  6. Scolletta S, Romano SM, Biagioli B, Capannini G, Giomarelli P. Pressure recording analytical method (PRAM) for measurement of cardiac output during various haemodynamic states. Br J Anaesth. 2005;95:159–65.

    Article  CAS  Google Scholar 

  7. Romano SM, Pistolesi M. Assessment of cardiac output from systemic arterial pressure in humans. Crit Care Med. 2002;30:1834–41.

    Article  Google Scholar 

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

    Article  CAS  Google Scholar 

  9. Lorello GR, Cook DA, Johnson RL, Brydges R. Simulation-based training in anaesthesiology: a systematic review and meta-analysis. Br J Anaesth. 2014;112:231–45.

    Article  CAS  Google Scholar 

  10. Bruppacher HR, Alam SK, LeBlanc VR, Latter D, Naik VN, Savoldelli GL, et al. Simulation-based training improves physicians’ performance in patient care in high-stakes clinical setting of cardiac surgery. Anesthesiology. 2010;112:985–92.

    Article  Google Scholar 

  11. Rajaram SS, Desai NK, Kalra A, Gajera M, Cavanaugh SK, Brampton W, et al. Pulmonary artery catheters for adult patients in intensive care. Cochrane database Syst Rev. 2013;2:CD003408.

    Google Scholar 

  12. Connors AF, Speroff T, Dawson NV, Thomas C, Harrell FE, Wagner D, et al. The effectiveness of right heart catheterization in the initial care of critically ill patients. JAMA. 1996;276:889–97.

    Article  Google Scholar 

  13. Scolletta S, Franchi F, Romagnoli S, Carlà R, Donati A, Fabbri LP, et al. Comparison Between Doppler-Echocardiography and Uncalibrated Pulse Contour Method for Cardiac Output Measurement: A Multicenter Observational Study. Crit Care Med. 2016;44:1370–9.

    Article  Google Scholar 

  14. Chew MS, Åneman A. Haemodynamic monitoring using arterial waveform analysis. Curr Opin Crit Care. 2013;19:234–41.

    Article  Google Scholar 

  15. de Waal EEC, Wappler F, Buhre WF. Cardiac output monitoring. Curr Opin Anaesthesiol. 2009;22:71–7.

    Article  Google Scholar 

  16. Donati A, Carsetti A, Tondi S, Scorcella C, Domizi R, Damiani E, et al. Thermodilution vs pressure recording analytical method in hemodynamic stabilized patients. J Crit Care. 2013;29:260–4.

    Article  Google Scholar 

  17. Cecconi M, Dawson D, Casaretti R, Grounds RM, Rhodes A. A prospective study of the accuracy and precision of continuous cardiac output monitoring devices as compared to intermittent thermodilution. Minerva Anestesiol. 2010;76:1010–7.

    CAS  PubMed  Google Scholar 

  18. Saraceni E, Rossi S, Persona P, Dan M, Rizzi S, Meroni M, et al. Comparison of two methods for cardiac output measurement in critically ill patients. Br J Anaesth. 2011;106:690–4.

    Article  CAS  Google Scholar 

  19. Compton FD, Zukunft B, Hoffmann C, Zidek W, Schaefer J-H. Performance of a minimally invasive uncalibrated cardiac output monitoring system (Flotrac/Vigileo) in haemodynamically unstable patients. Br J Anaesth. 2008;100:451–6.

    Article  CAS  Google Scholar 

  20. Sakka SG, Kozieras J, Thuemer O, van Hout N. Measurement of cardiac output: a comparison between transpulmonary thermodilution and uncalibrated pulse contour analysis. Br J Anaesth. 2007;99:337–42.

    Article  CAS  Google Scholar 

  21. Vozenilek J, Huff JS, Reznek M, Gordon JA. See one, do one, teach one: advanced technology in medical education. Acad Emerg Med. 2004;11:1149–54.

    Article  Google Scholar 

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Correspondence to Paolo Persona.

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Conflict of interest

P. Persona has received unrestricted educational support in the form of payment of conferences registration fees (ISICEM, Brussels − 2013, 2015, 2016) from Vygon–Vytech, the manufacturer of the MostCare device. He does not have any financial relationship with this nor other companies. The remaining authors have no conflict of interest to declare.

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Persona, P., Saraceni, E., Facchin, F. et al. Pulse contour analysis of arterial waveform in a high fidelity human patient simulator. J Clin Monit Comput 32, 677–681 (2018). https://doi.org/10.1007/s10877-017-0066-3

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  • DOI: https://doi.org/10.1007/s10877-017-0066-3

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