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Real-time estimation of mean arterial blood pressure based on photoplethysmography dicrotic notch and perfusion index. A pilot study

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Abstract

Hypotension during general anesthesia is associated with poor outcome. Continuous monitoring of mean blood pressure (MAP) during anesthesia is useful and needs to be reliable and minimally invasive. Conventional cuff measurements can lead to delays due to its discontinuous nature. It has been shown that there is a relationship between MAP and photoplethysmography (PPG) parameters like the dicrotic notch and perfusion index (PI). The objective of the study was to continuously estimate MAP from PPG. Pulse wave analysis based on PPG was implemented using either notch relative amplitude (MAPNRA), notch absolute amplitude (MAPNAA) or PI (MAPPI) to estimate MAP from PPG waveform features during general anesthesia. Estimated MAP values were compared to brachial cuff MAP (MAPcuff) and to radial invasive MAP (MAPinv). Forty-six patients were analyzed for a total of 235 h. Compared to MAPcuff, mean bias and limits of agreement were 1 mmHg (− 26 to +29), − 1 mmHg (− 10 to +8) and − 3 mmHg (− 21 to +13) for MAPNRA, MAPNAA and MAPPI respectively. Compared to MAPinv, mean absolute error (MAE) was 20 mmHg [10 to 39], 11 mmHg [5 to 18] and 16 mmHg [9 to 24] for MAP derived from MAPNRA, MAPNAA and MAPPI respectively. When calibrated every 5 min, MAPNAA showed a MAE of 6 mmHg [5 to 9]. MAPNAA provides the best estimates with respect to brachial cuff MAP and invasive MAP. Regular calibration allows to reduce drift over time. Beat to beat estimation of MAP during general anesthesia from the PPG appears possible with an acceptable average error.

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References

  1. Société Française d’Anesthésie et de Réanimation: Stratégie du remplissage vasculaire périopératoire (2013). https://sfar.org/strategie-du-remplissage-vasculaire-perioperatoire-2/. Accessed 12 Dec 2019.

  2. Perk J, De Backer G, Gohlke H, Graham I, Reiner Z, Verschuren M, Albus C, Benlian P, Boysen G, Cifkova R, Deaton C, Ebrahim S, Fisher M, Germano G, Hobbs R, Hoes A, Karadeniz S, Mezzani A, Prescott E, Ryden L, Scherer M, Syvanne M, Scholte Op Reimer WJM, Vrints C, Wood D, Zamorano JL, Zannad F, Other experts who contributed to parts of the guidelines: Cooney MT, ESC Committee for Practice Guidelines (CPG), Bax J, Baumgartner H, Ceconi C, Dean V, Deaton C, Fagard R, Funck-Brentano C, Hasdai D, Hoes A, Kirchhof P, Knuuti J, Kolh P, McDonagh T, Moulin C, Popescu BA, Reiner Z, Sechtem U, Sirnes PA, Tendera M, Torbicki A, Vahanian A, Windecker S, Document Reviewers: Funck-Brentano C, Sirnes PA, Aboyans V, Ezquerra EA, Baigent C, Brotons C, Burell G, Ceriello A, De Sutter J, Deckers J, Del Prato S, Diener H-C, Fitzsimons D, Fras Z, Hambrecht R, Jankowski P, Keil U, Kirby M, Larsen ML, Mancia G, Manolis AJ, McMurray J, Pajak A, Parkhomenko A, Rallidis L, Rigo F, Rocha E, Ruilope LM, van der Velde E, Vanuzzo D, Viigimaa M, Volpe M, Wiklund O, Wolpert C. European Guidelines on cardiovascular disease prevention in clinical practice (version. the Fifth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of nine societies and by invited experts) * Developed with the special contribution of the European Association for Cardiovascular Prevention and Rehabilitation (EACPR). Eur Heart J. 2012;2012(33):1635–701. https://doi.org/10.1093/eurheartj/ehs092.

  3. Walsh M, Devereaux PJ, Garg AX, Kurz A, Turan A, Rodseth RN, Cywinski J, Thabane L, Sessler DI. Relationship between intraoperative mean arterial pressure and clinical outcomes after noncardiac surgery: toward an empirical definition of hypotension. Anesthesiology. 2013;119:507–15. https://doi.org/10.1097/ALN.0b013e3182a10e26.

    Article  PubMed  Google Scholar 

  4. Monk TG, Saini V, Weldon BC, Sigl JC. Anesthetic management and one-year mortality after noncardiac surgery. Anesth Analg. 2005;100:4–10. https://doi.org/10.1213/01.ANE.0000147519.82841.5E.

    Article  PubMed  Google Scholar 

  5. Sessler DI, Sigl JC, Kelley SD, Chamoun NG, Manberg PJ, Saager L, Kurz A, Greenwald S. Hospital stay and mortality are increased in patients having a “triple low” of low blood pressure, low bispectral index, and low minimum alveolar concentration of volatile anesthesia. Anesthesiology. 2012;116:1195–203. https://doi.org/10.1097/ALN.0b013e31825683dc.

    Article  PubMed  Google Scholar 

  6. Lima AP, Beelen P, Bakker J. Use of a peripheral perfusion index derived from the pulse oximetry signal as a noninvasive indicator of perfusion. Crit Care Med. 2002;30:1210–3.

    Article  PubMed  Google Scholar 

  7. Coutrot M, Joachim J, Dépret F, Millasseau S, Nougué H, Matéo J, Mebazaa A, Gayat E, Vallée F. Non-invasive continuous detection of arterial hypotension during induction of anaesthesia using a photoplethysmographic signal: proof of concept. Br J Anaesth. 2019. https://doi.org/10.1016/j.bja.2019.01.037.

    Article  PubMed  Google Scholar 

  8. Politi MT, Ghigo A, Fernández JM, Khelifa I, Gaudric J, Fullana JM, Lagrée P-Y. The dicrotic notch analyzed by a numerical model. Comput Biol Med. 2016;72:54–64. https://doi.org/10.1016/j.compbiomed.2016.03.005.

    Article  PubMed  Google Scholar 

  9. Shi P, Hu S, Zhu Y, Zheng J, Qiu Y, Cheang PYS. Insight into the dicrotic notch in photoplethysmographic pulses from the finger tip of young adults. J Med Eng Technol. 2009;33:628–33. https://doi.org/10.3109/03091900903150980.

    Article  CAS  PubMed  Google Scholar 

  10. Abramowitz M. Handbook of mathematical functions, with formulas, graphs, and mathematical tables. Mineola: Dover Publications, Incorporated; 1974.

    Google Scholar 

  11. Willmott C, Matsuura K. Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Clim Res. 2005;30:79–82. https://doi.org/10.3354/cr030079.

    Article  Google Scholar 

  12. Myles PS, Cui J. I. Using the Bland-Altman method to measure agreement with repeated measures. Br J Anaesth. 2007;99:309–11. https://doi.org/10.1093/bja/aem214.

    Article  CAS  PubMed  Google Scholar 

  13. Montenij LJ, Buhre WF, Jansen JR, Kruitwagen CL, de Waal EE. Methodology of method comparison studies evaluating the validity of cardiac output monitors: a stepwise approach and checklist ††This Article is accompanied by Editorial Aew110. Br J Anaesth. 2016;116:750–8. https://doi.org/10.1093/bja/aew094.

    Article  CAS  PubMed  Google Scholar 

  14. Armstrong MK, Schultz MG, Picone DS, Andrew Black J, Dwyer N, Roberts-Thomson P, Sharman JE. Brachial and radial systolic blood pressure are not the same. Hypertension. 2019;73:1036–41. https://doi.org/10.1161/HYPERTENSIONAHA.119.12674.

    Article  CAS  PubMed  Google Scholar 

  15. Nichols WW. McDonald’s blood flow in arteries: theoretical, experimental and clinical principles. London: Hodder Arnold; 2010.

    Google Scholar 

  16. Peňáz J. Photoelectric measurement of blood pressure, volume and flow in the finger. In: Digest of the 10th international conference on medical and biological engineering, 1973, p. 104.

  17. Balzer F, Habicher M, Sander M, Sterr J, Scholz S, Feldheiser A, Müller M, Perka C, Treskatsch S. Comparison of the non-invasive Nexfin® monitor with conventional methods for the measurement of arterial blood pressure in moderate risk orthopaedic surgery patients. J Int Med Res. 2016;44:832–43. https://doi.org/10.1177/0300060516635383.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Sharman JE, Marwick TH. Accuracy of blood pressure monitoring devices: a critical need for improvement that could resolve discrepancy in hypertension guidelines. J Hum Hypertens. 2019;33:89–93. https://doi.org/10.1038/s41371-018-0122-6.

    Article  PubMed  Google Scholar 

  19. Stergiou GS, Palatini P, Asmar R, Ioannidis JP, Kollias A, Lacy P, McManus RJ, Myers MG, Parati G, Shennan A, Wang J, O’Brien E, European Society of Hypertension Working Group on Blood Pressure Monitoring. Recommendations and Practical Guidance for performing and reporting validation studies according to the Universal Standard for the validation of blood pressure measuring devices by the Association for the Advancement of Medical Instrumentation/European Society of Hypertension/International Organization for Standardization (AAMI/ESH/ISO). J Hypertens. 2019;37:459–66. https://doi.org/10.1097/HJH.0000000000002039.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We thank anesthetic nurses and the staff of neuroradiology for their support in the conduct of the present study.

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Authors and Affiliations

  1. Department of Anesthesiology, Burn and Critical Care, St-Louis-Lariboisière-Fernand Widal University Hospitals, Assistance Publique - Hôpitaux de Paris, 2 rue Ambroise Paré, 75010, Paris, France

    Jona Joachim, Maxime Coutrot, Joaquim Matéo, Alexandre Mebazaa, Etienne Gayat & Fabrice Vallée

  2. INSERM UMR-942, Paris, France

    Jona Joachim, Maxime Coutrot, Alexandre Mebazaa, Etienne Gayat & Fabrice Vallée

  3. Université de Paris, Paris, France

    Jona Joachim, Maxime Coutrot, Joaquim Matéo, Alexandre Mebazaa, Etienne Gayat & Fabrice Vallée

  4. Pulse Wave Consulting, Saint-Leu-la-Forêt, France

    Sandrine Millasseau

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  1. Jona Joachim
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  4. Joaquim Matéo
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  5. Alexandre Mebazaa
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  7. Fabrice Vallée
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Contributions

JJ, MC, JM, AM, EG, FV conception and design of research; JJ, MC, FV, and JM performed experiments; JJ, MC, FV and EG analyzed data; JJ, MC, FV, EG and SM interpreted results; JJ, MC, FV and SM prepared figures; JJ and FV drafted manuscript; FV, EG, AM, JM and SM edited and revised the manuscript; JJ, JM, FV, EG, AM, SM and MC approved final version of manuscript.

Corresponding author

Correspondence to Jona Joachim.

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Conflict of interest

Assistance Public-Hôpitaux de Paris (AP-HP) applied for a patent for the concepts exposed in this paper as well as the MAP prediction algorithms (preliminary Patent Number INPI 17/62978). Fabrice Vallée, Jona Joachim, Maxime Coutrot, Étienne Gayat and Alexandre Mebazaa are Co-inventors of said patent. Alexandre Mebazaa has received Speaker Honoraria from Abbott, Novartis, Orion, Roche and Servier and Fee as Member of Advisory Board and/or Steering Committee from Cardiorentis, Adrenomed, MyCartis, ZS Pharma and Critical Diagnostics. Etienne Gayat has received Consulting Fees from Magnisense, research support from Sphingotec, Deltex Medical and Retia Medical. Fabrice Vallée has received research support from Radiometer, Deltex Medical and Retia Medical. Sandrine Millasseau has received Consulting Fees from Alam Medical, AtCor Medical, Mesi Medical and Omron.

Ethical approval

This study was approved by the SRLF Ethics Committee (n°CE SRLF 11-356). This was an observational study of “routine care”.

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Patients were included after informed consent was obtained.

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Joachim, J., Coutrot, M., Millasseau, S. et al. Real-time estimation of mean arterial blood pressure based on photoplethysmography dicrotic notch and perfusion index. A pilot study. J Clin Monit Comput 35, 395–404 (2021). https://doi.org/10.1007/s10877-020-00486-y

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