Skip to main content
SpringerLink
Log in

Monitoring of pulse pressure variation using a new smartphone application (Capstesia) versus stroke volume variation using an uncalibrated pulse wave analysis monitor: a clinical decision making study during major abdominal surgery

  • Original Research
  • Published:
Journal of Clinical Monitoring and Computing Aims and scope Submit manuscript

Abstract

Pulse pressure variation (PPV) and stroke volume variation (SVV) can be used to assess fluid status in the operating room but usually require dedicated advanced hemodynamic monitors. Recently, a smartphone application (Capstesia™), which automatically calculates PPV from a picture of the invasive arterial pressure waveform from any monitor screen (PPVCAP), has been developed. The purpose of this study was to compare PPVCAP with SVV from an uncalibrated pulse wave analysis monitor (SVVPC). In 40 patients undergoing major abdominal surgery, we compared PPVCAP with SVVPC at post-induction, pre-incision, post-incision, end of surgery, and during every hypotensive episode (mean arterial pressure < 65 mmHg). We classified PPVCAP and SVVPC into three categories reflecting the thresholds used for the decision to administer fluids: no fluid administration (PPV and SVV < 9%), gray zone (PPV and SVV 9–13%), and fluid administration (PPV and SVV > 13%). The agreement between SVVPC and PPVCAP for these three categories was measured by the number of concordant paired measurements divided by the total number of paired measurements and Cohen’s kappa coefficient. In the 549 pairs of PPV–SVV data obtained, the overall agreement of PPVCAP with SVVPC was 79%, and the kappa coefficient was moderate (0.55). The highest agreement and kappa coefficient value were observed after the induction of anesthesia before surgical incision. PPVCAP and SVVPC would have resulted in completely opposite clinical decisions regarding fluid administration in 1% of the cases. In this clinical decision making study in patients undergoing major abdominal surgery, we observed a moderate agreement between PPVCAP and SVVPC with regard to categories used to guide fluid administration.

Trial Registration: Clinical Trials.gov (NCT03137901).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. Carstensen et al. [22]

References

  1. Michard F, Chemla D, Richard C, et al. Clinical use of respiratory changes in arterial pulse pressure to monitor the hemodynamic effects of PEEP. Am J Respir Crit Care Med. 1999;159:935–9.

    Article  CAS  PubMed  Google Scholar 

  2. Michard F, Boussat S, Chemla D, et al. 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 

  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. Monnet X, Marik PE, Teboul JL. Prediction of fluid responsiveness: an update. Ann Intensive Care. 2016;6:111.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Yang X, Du B. Does pulse pressure variation predict fluid responsiveness in critically ill patients? a systematic review and meta-analysis. Crit Care. 2014;18:650.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Joosten A, Tircoveanu R, Arend S, Wauthy P, Gottignies P, Van der Linden P. Impact of balanced tetrastarch raw material on perioperative blood loss: a randomized double blind controlled trial. Br J Anaesth. 2016;117:442–9.

    Article  CAS  PubMed  Google Scholar 

  7. Michard F, Giglio MT, Brienza N. Perioperative goal-directed therapy with uncalibrated pulse contour methods: impact on fluid management and postoperative outcome. Br J Anaesth. 2017;119:22–30.

    Article  CAS  PubMed  Google Scholar 

  8. Ramsingh DS, Sanghvi C, Gamboa J, Cannesson M, Applegate RL. Outcome impact of goal directed fluid therapy during high risk abdominal surgery in low to moderate risk patients: a randomized controlled trial. J Clin Monit Comput. 2013;27:249–57.

    Article  PubMed  Google Scholar 

  9. Malbouisson LMS, Silva JM Jr, Carmona MJC, et al. A pragmatic multi-center trial of goal-directed fluid management based on pulse pressure variation monitoring during high-risk surgery. BMC Anesthesiol. 2017;17:70.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Cannesson M, Ramsingh D, Rinehart J, et al. Perioperative goal-directed therapy and postoperative outcomes in patients undergoing high-risk abdominal surgery: a historical-prospective, comparative effectiveness study. Crit Care. 2015;19:261.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Rinehart J, Islam T, Boud R, et al. Visual estimation of pulse pressure variation is not reliable: a randomized simulation study. J Clin Monit Comput. 2012;26:191–6.

    Article  PubMed  Google Scholar 

  12. Barrachina B, Cobos R, Mardones N, Castaneda A, Vinuesa C. Assessment of a smartphone app (Capstesia) for measuring pulse pressure variation: agreement between two methods: a cross-sectional study. Eur J Anaesthesiol. 2017;34:75–80.

    Article  PubMed  Google Scholar 

  13. Desebbe O, Joosten A, Suehiro K, et al. A novel mobile phone application for pulse pressure variation monitoring based on feature extraction technology: a method comparison study in a simulated environment. Anesth Analg. 2016;123:105–13.

    Article  PubMed  Google Scholar 

  14. Joosten A, Boudart C, Vincent JL, et al. Ability of a new smartphone pulse pressure variation and cardiac output application to predict fluid responsiveness in patients undergoing cardiac surgery. Anesth Analg. 2018. https://doi.org/10.1213/ANE.0000000000003652 (Epub ahead of print).

    Article  Google Scholar 

  15. Shah SB, Bhargava AK, Hariharan U, Vishvakarma G, Jain CR, Kansal A. Cardiac output monitoring: a comparative prospective observational study of the conventional cardiac output monitor Vigileo and the new smartphone-based application Capstesia. Indian J Anaesth. 2018;62:584–91.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Joosten A, Coeckelenbergh S, Delaporte A, et al. Implementation of closed-loop-assisted intra-operative goal-directed fluid therapy during major abdominal surgery: a case-control study with propensity matching. Eur J Anaesthesiol. 2018;35:650–8.

    PubMed  Google Scholar 

  17. Joosten A, Delaporte A, Ickx B, et al. Crystalloid versus colloid for intraoperative goal-directed fluid therapy using a closed-loop system: a randomized, double-blinded, controlled trial in major abdominal surgery. Anesthesiology. 2018;128:55–66.

    Article  CAS  PubMed  Google Scholar 

  18. Lima MF, Mondadori LA, Chibana AY, Gilio DB, Giroud Joaquim EH, Michard F. Outcome impact of hemodynamic and depth of anesthesia monitoring during major cancer surgery: a before-after study. J Clin Monit Comput. 2018. https://doi.org/10.1007/s10877-018-0190-8 (Epub ahead of print).

    Article  PubMed  Google Scholar 

  19. Cannesson M, Le Manach Y, Hofer CK, et al. 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 

  20. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33:159–74.

    Article  CAS  PubMed  Google Scholar 

  21. Carstensen B. Comparing clinical measurement methods:a practical guide.New Jersey:Wiley;2010.

  22. Carstensen B, Gurrin L, Ekstrom C, Figurski M. MethComp: functions for analysis of agreement in method comparison studies. R package version 1.22.2. https://CRAN.R-project.org/package=MethComp (2015).

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

    Article  PubMed  PubMed Central  Google Scholar 

  24. Biais M, Ehrmann S, Mari A, et al. Clinical relevance of pulse pressure variations for predicting fluid responsiveness in mechanically ventilated intensive care unit patients: the grey zone approach. Crit Care. 2014;18:587.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Salzwedel C, Puig J, Carstens A, et al. Perioperative goal-directed hemodynamic therapy based on radial arterial pulse pressure variation and continuous cardiac index trending reduces postoperative complications after major abdominal surgery: a multi-center, prospective, randomized study. Crit Care. 2013;17:R191.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Saugel B, Reuter DA. Perioperative goal-directed therapy using invasive uncalibrated pulse contour analysis. Front Med (Lausanne). 2018;5:12.

    Article  Google Scholar 

  27. Biais M, Stecken L, Martin A, Roullet S, Quinart A, Sztark F. Automated, continuous and non-invasive assessment of pulse pressure variations using CNAP((R)) system. J Clin Monit Comput. 2017;31:685–92.

    Article  PubMed  Google Scholar 

  28. Monnet X, Dres M, Ferre A, et al. Prediction of fluid responsiveness by a continuous non-invasive assessment of arterial pressure in critically ill patients: comparison with four other dynamic indices. Br J Anaesth. 2012;109:330–8.

    Article  CAS  PubMed  Google Scholar 

  29. Wacharasint P, Lertamornpong A, Wattanathum A, Wongsa A. Predicting fluid responsiveness in septic shock patients by using 3 dynamic indices: is it all equally effective? J Med Assoc Thail. 2012;95(Suppl 5):149-56.

    Google Scholar 

  30. Hong JQ, He HF, Chen ZY, et al. Comparison of stroke volume variation with pulse pressure variation as a diagnostic indicator of fluid responsiveness in mechanically ventilated critically ill patients. Saudi Med J. 2014;35:261–8.

    PubMed  Google Scholar 

  31. Zhang Z, Lu B, Sheng X, Jin N. Accuracy of stroke volume variation in predicting fluid responsiveness: a systematic review and meta-analysis. J Anesth. 2011;25:904–16.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

All the Anesthesiology department for their assistance.

Funding

This work was supported by the Department of Anesthesiology, Erasme Hospital, Brussels.

Author information

Authors and Affiliations

  1. Department of Anesthesiology, CUB Erasme University Hospital, Université Libre de Bruxelles, 808 Route de Lennik, 1070, Brussels, Belgium

    Alexandre Joosten, Alexandra Jacobs, Saxena Sarah & Luc Van Obbergh

  2. Department of Anesthesiology and Intensive Care, Hôpitaux Universitaires Paris-Sud, Université Paris-Sud, Université Paris-Saclay, Hôpital De Bicêtre, Assistance Publique Hôpitaux de Paris (AP-HP), Le Kremlin-Bicêtre, France

    Alexandre Joosten

  3. Department of Anesthesiology and Intensive Care, Clinique de la Sauvegarde, 80 Avenue Ben Gourion, 69009, Lyon, France

    Olivier Desebbe

  4. Department of Intensive Care, CUB Erasme University Hospital, Université Libre de Bruxelles, 808 Route de Lennik, 1070, Brussels, Belgium

    Jean-Louis Vincent

  5. Department of Anesthesiology and Perioperative Care, University of California Irvine, 101 the City Drive South, Orange, USA

    Joseph Rinehart

  6. Institute of Medical Informatics, Statistics and Epidemiology, Technische Universität München, Munich, Germany

    Alexander Hapfelmeier

  7. Department of Anesthesiology, Center of Anesthesiology and Intensive Care Medicine, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246, Hamburg, Germany

    Bernd Saugel

Authors
  1. Alexandre Joosten
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alexandra Jacobs
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Olivier Desebbe
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jean-Louis Vincent
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Saxena Sarah
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Joseph Rinehart
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Luc Van Obbergh
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Alexander Hapfelmeier
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Bernd Saugel
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

AJ: Designed the study, analyzed the data and drafted the manuscript. AJ, OD: Designed the study, analyzed the data and edited the manuscript. JLV, SS, JR, LVO: Analyzed the data and edited the manuscript. AH: Analyzed the data (statistical analysis) and edited the manuscript. BS: Analyzed the data and drafted the manuscript. All authors read and approved the final version of the manuscript.

Corresponding author

Correspondence to Alexandre Joosten.

Ethics declarations

Conflict of interest

Alexandre Joosten: Consultant for Edwards Lifesciences (Irvine, CA, USA). Olivier Desebbe: Collaborates with Medtronic (Dublin, Ireland) as a consultant and received honoraria for giving lectures. Jean-Louis Vincent is Editor-in-Chief of Critical Care. He has no other conflicts related to this article. Joseph Rinehart: Ownership interest in Sironis, a company developing closed-loop medical software, consultant for Edwards Lifesciences (Irvine, CA, USA). Bernd Saugel: Collaborates with Pulsion Medical Systems (Feldkirchen, Germany) as a member of the medical advisory board and received honoraria for giving lectures and refunds of travel expenses from Pulsion Medical Systems. BS received institutional research grants, unrestricted research grants, and refunds of travel expenses from Tensys Medical (San Diego, CA, USA). BS received honoraria for giving lectures and refunds of travel expenses from CNSystems Medizintechnik (Graz, Austria). BS received honoraria for giving lectures and research support from Edwards Lifesciences (Irvine, CA, USA). All other authors have no conflicts of interest to declare.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (GIF 14 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Joosten, A., Jacobs, A., Desebbe, O. et al. Monitoring of pulse pressure variation using a new smartphone application (Capstesia) versus stroke volume variation using an uncalibrated pulse wave analysis monitor: a clinical decision making study during major abdominal surgery. J Clin Monit Comput 33, 787–793 (2019). https://doi.org/10.1007/s10877-018-00241-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10877-018-00241-4

Keywords

Search

Navigation