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Measurement error of pulse pressure variation

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Dynamic preload parameters are used to guide perioperative fluid management. However, reported cut-off values vary and the presence of a gray zone complicates clinical decision making. Measurement error, intrinsic to the calculation of pulse pressure variation (PPV) has not been studied but could contribute to this level of uncertainty. The purpose of this study was to quantify and compare measurement errors associated with PPV calculations. Hemodynamic data of patients undergoing liver transplantation were extracted from the open-access VitalDatabase. Three algorithms were applied to calculate PPV based on 1 min observation periods. For each method, different durations of sampling periods were assessed. Best Linear Unbiased Prediction was determined as the reference PPV-value for each observation period. A Bayesian model was used to determine bias and precision of each method and to simulate the uncertainty of measured PPV-values. All methods were associated with measurement error. The range of differential and proportional bias were [− 0.04%, 1.64%] and [0.92%, 1.17%] respectively. Heteroscedasticity influenced by sampling period was detected in all methods. This resulted in a predicted range of reference PPV-values for a measured PPV of 12% of [10.2%, 13.9%] and [10.3%, 15.1%] for two selected methods. The predicted range in reference PPV-value changes for a measured absolute change of 1% was [− 1.3%, 3.3%] and [− 1.9%, 4%] for these two methods. We showed that all methods that calculate PPV come with varying degrees of uncertainty. Accounting for bias and precision may have important implications for the interpretation of measured PPV-values or PPV-changes.

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  1. Mlodinow L. The drunkard’s walk: how randomness rules our lives. New York: Pantheon Books; 2008.

    Google Scholar 

  2. Mahmood SS, Pinsky MR. Heart-lung interactions during mechanical ventilation: the basics. Ann Transl Med. 2018;6:349.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Marik PE, Cavallazzi R, Vasu T, Hirani A. Dynamic changes in arterial waveform derived variables and fluid responsiveness in mechanically ventilated patients: a systematic review of the literature. Crit Care Med. 2009;37:2642–7.

    Article  PubMed  Google Scholar 

  4. Michard F. Changes in arterial pressure during mechanical ventilation. Anesthesiology. 2005;103:419–28.

    Article  PubMed  Google Scholar 

  5. Cannesson M, le Manach Y, Hofer CK, Goarin JP, Lehot JJ, Vallet B, Tavernier B. Assessing the diagnostic accuracy of pulse pressure variations for the prediction of fluid responsiveness: a “gray zone” approach. Anesthesiology. 2011;115:231–41.

    Article  PubMed  Google Scholar 

  6. Lansdorp B, Lemson J, van Putten MJAM, de Keijzer A, van der Hoeven JG, Pickkers P. Dynamic indices do not predict volume responsiveness in routine clinical practice. Br J Anaesth. 2012;108:395–401.

    Article  CAS  PubMed  Google Scholar 

  7. de Backer D, Heenen S, Piagnerelli M, Koch M, Vincent JL. Pulse pressure variations to predict fluid responsiveness: influence of tidal volume. Intensive Care Med. 2005;31:517–23.

    Article  PubMed  Google Scholar 

  8. Michard F, Chemla D, Teboul J-L. Applicability of pulse pressure variation: how many shades of grey? Crit Care. 2015;19:144.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Wyffels PAH, Sergeant P, Wouters PF. The value of pulse pressure and stroke volume variation as predictors of fluid responsiveness during open chest surgery. Anaesthesia. 2010;65:704–9.

    Article  CAS  PubMed  Google Scholar 

  10. Alvarado Sanchez JI, Caicedo Ruiz JD, Diaztagle Fernandez JJ, Cruz Martinez LE, Carreno Hernadez FL,Santacruz Herrera CA, Ospina-Tascon GA . Variables influencing the prediction of fluid responsiveness: a systematic review and meta-analysis Crit Care 2023; 27(1):361.

  11. Myatra SN, Prabu NR, Divatia JV, Monnet X, Kulkarni AP, Teboul JL. The changes in pulse pressure variation or stroke volume variation after a “tidal volume challenge” reliably predict fluid responsiveness during low tidal volume ventilation. Crit Care Med. 2017;45:415–21.

    Article  PubMed  Google Scholar 

  12. Messina A, Montagnini C, Cammarota G, Giuliani F, Muratore L, Baggiani M, Bennett V, della Corte F, Navalesi P, Cecconi M. Assessment of fluid responsiveness in prone neurosurgical patients undergoing protective ventilation: role of dynamic indices, tidal volume challenge, and end-expiratory occlusion test. Anesth Analg. 2020;130:752–61.

    Article  CAS  PubMed  Google Scholar 

  13. Wang X, Liu S, Gao J, Zhang Y, Huang T. Does tidal volume challenge improve the feasibility of pulse pressure variation in patients mechanically ventilated at low tidal volimes? A systematic review and meta-analysis. Crit Care. 2023;27(1):45.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Wyffels PAH, de Hert S, Wouters PF. New algorithm to quantify cardiopulmonary interaction in patients with atrial fibrillation: a proof-of-concept study. Br J Anaesth. 2021;126:111–9.

    Article  PubMed  Google Scholar 

  15. Monnet X, Marik P, Teboul JL. Passive leg raising for predicting fluid responsiveness: a systematic review and meta-analysis. Intensive Care Med. 2016;42:1935–47.

    Article  PubMed  Google Scholar 

  16. Mallat J, Fischer M-O, Granier M, et al. Passive leg raising-induced changes in pulse pressure variation to assess fluid responsiveness in mechanically ventilated patients: a multicentre prospective observational study. Br J Anaesth. 2022;129:308–16.

    Article  PubMed  Google Scholar 

  17. Michard F, Boussat S, Chemla D, Anguel N, Mercat A, Lecarpentier Y, Richard C, Pinsky MR, Teboul JL. Relation between respiratory changes in arterial pulse pressure and fluid responsiveness in septic patients with acute circulatory failure. Am J Respir Crit Care Med. 2000;162:134–8.

    Article  CAS  PubMed  Google Scholar 

  18. Kim HK, Pinsky MR. Effect of tidal volume, sampling duration, and cardiac contractility on pulse pressure and stroke volume variation during positive-pressure ventilation. Crit Care Med. 2008;36:2858–62.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Derichard A, Robin E, Tavernier B, Costecalde M, Fleyfel M, Onimus J, Lebuffe G, Chambon JP, Vallet B. Automated pulse pressure and stroke volume variations from radial artery: evaluation during major abdominal surgery. Br J Anaesth. 2009;103:678–84.

    Article  CAS  PubMed  Google Scholar 

  20. Cannesson M, Slieker J, Desebbe O, Bauer C, Chiari P, Hénaine R, Lehot J-J. The ability of a novel algorithm for automatic estimation of the respiratory variations in arterial pulse pressure to monitor fluid responsiveness in the operating room. Anesth Analg. 2008;106:1195–200.

    Article  PubMed  Google Scholar 

  21. Lee H-C, Park Y, Yoon SB, Yang SM, Park D, Jung C-W. VitalDB, a high-fidelity multi-parameter vital signs database in surgical patients. Sci Data. 2022;9:279.

    Article  PubMed  PubMed Central  Google Scholar 

  22. GitHub—vitaldb/pyvital: open source python implementation of medical algorithms. Accessed 18 Jul 2022

  23. Li BN, Dong MC, Vai MI. On an automatic delineator for arterial blood pressure waveforms. Biomed Signal Process Control. 2010;5:76–81.

    Article  Google Scholar 

  24. Aboy M, McNames J, Thong T, Phillips CR, Ellenby MS, Goldstein B. A novel algorithm to estimate the pulse pressure variation index deltaPP. IEEE Trans Biomed Eng. 2004;51:2198–203.

    Article  PubMed  Google Scholar 

  25. Taffé P. Effective plots to assess bias and precision in method comparison studies. Stat Methods Med Res. 2018;27:1650–60.

    Article  PubMed  Google Scholar 

  26. Taffé P, Peng M, Stagg V, Williamson T. MethodCompare: an R package to assess bias and precision in method comparison studies. Stat Methods Med Res. 2019;28:2557–65.

    Article  PubMed  Google Scholar 

  27. 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. Br J Anaesth. 2016;116:750–8.

    Article  CAS  PubMed  Google Scholar 

  28. Mansournia MA, Waters R, Nazemipour M, Bland M, Altman DG. Bland–Altman methods for comparing methods of measurement and response to criticisms. Glob Epidemiol. 2021;3: 100045.

    Article  PubMed  Google Scholar 

  29. van Smeden M, Penning de Vries BBL, Nab L, Groenwold RHH. Approaches to addressing missing values, measurement error, and confounding in epidemiologic studies. J Clin Epidemiol. 2021;131:89–100.

    Article  PubMed  Google Scholar 

  30. van Smeden M, Lash TL, Groenwold RHH. Reflection on modern methods: five myths about measurement error in epidemiological research. Int J Epidemiol. 2020;49:338.

    Article  PubMed  Google Scholar 

  31. Messina A, Montagnini C, Cammarota G, de Rosa S, Giuliani F, Muratore L, della Corte F, Navalesi P, Cecconi M. Tidal volume challenge to predict fluid responsiveness in the operating room: an observational study. Eur J Anaesthesiol. 2019;36:583–91.

    Article  PubMed  Google Scholar 

  32. de Courson H, Ferrer L, Cane G, Verchère E, Sesay M, Nouette-Gaulain K, Biais M. Evaluation of least significant changes of pulse contour analysis-derived parameters. Ann Intensive Care. 2019;9:116.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Messina A, Lionetti G, Foti L, et al. Mini fluid chAllenge aNd End-expiratory occlusion test to assess flUid responsiVEness in the opeRating room (MANEUVER study): a multicentre cohort study. Eur J Anaesthesiol. 2021;38:422–31.

    Article  PubMed  Google Scholar 

  34. Muller L, Toumi M, Bousquet PJ, et al. An increase in aortic blood flow after an infusion of 100 ml colloid over 1 minute can predict fluid responsiveness: the mini-fluid challenge study. Anesthesiology. 2011;115:541–7.

    Article  CAS  PubMed  Google Scholar 

  35. de Backer D, Taccone FS, Holsten R, Ibrahimi F, Vincent JL. Influence of respiratory rate on stroke volume variation in mechanically ventilated patients. Anesthesiology. 2009;110:1092–7.

    Article  PubMed  Google Scholar 

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Authors and Affiliations



All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by PAHW. The first draft of the manuscript was written by PAHW and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Piet A. H. Wyffels.

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The authors have no relevant financial or non-financial interests to disclosure.

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This is an analysis of an open access database and was performed in line with the principles of the Declaration of Helsinki. This database was approved by the Institutional Review Board of Seoul National University Hospital (H-1408-101-605).

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Written informed consent was waived due to anonymity of data in the original study as approved by the Institutional Review Board of Seoul National University Hospital (H-1408-101-605) and as registered at (NCT02914444).

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Wyffels, P.A.H., De Hert, S. & Wouters, P.F. Measurement error of pulse pressure variation. J Clin Monit Comput 38, 313–323 (2024).

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