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
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.
Mobile technology Feature extraction technology Monitoring Fluid responsiveness
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All the Anesthesiology department for their assistance.
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.
This work was supported by the Department of Anesthesiology, Erasme Hospital, Brussels.
Compliance with ethical standards
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.
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.CrossRefPubMedGoogle Scholar
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.CrossRefPubMedGoogle Scholar
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.CrossRefPubMedGoogle Scholar
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.CrossRefPubMedGoogle Scholar
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.CrossRefPubMedGoogle Scholar
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.CrossRefPubMedGoogle Scholar
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.CrossRefPubMedGoogle Scholar
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.CrossRefPubMedGoogle Scholar
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.CrossRefPubMedGoogle Scholar
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.CrossRefPubMedGoogle Scholar
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.CrossRefPubMedGoogle Scholar
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.CrossRefPubMedGoogle Scholar
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).Google Scholar
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.CrossRefPubMedGoogle Scholar
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.PubMedGoogle Scholar
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.CrossRefPubMedGoogle Scholar
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.CrossRefPubMedGoogle Scholar
Michard F, Chemla D, Teboul JL. Applicability of pulse pressure variation: how many shades of grey? Crit Care. 2015;19:144.CrossRefPubMedGoogle Scholar
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.CrossRefPubMedGoogle Scholar
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.CrossRefPubMedGoogle Scholar
Saugel B, Reuter DA. Perioperative goal-directed therapy using invasive uncalibrated pulse contour analysis. Front Med (Lausanne). 2018;5:12.CrossRefGoogle Scholar
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.CrossRefPubMedGoogle Scholar
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.CrossRefPubMedGoogle Scholar
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
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.PubMedGoogle Scholar
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.CrossRefPubMedGoogle Scholar
1.Department of Anesthesiology, CUB Erasme University HospitalUniversité Libre de BruxellesBrusselsBelgium
2.Department of Anesthesiology and Intensive CareHôpitaux Universitaires Paris-Sud, Université Paris-Sud, Université Paris-Saclay, Hôpital De Bicêtre, Assistance Publique Hôpitaux de Paris (AP-HP)Le Kremlin-BicêtreFrance
3.Department of Anesthesiology and Intensive CareClinique de la SauvegardeLyonFrance
4.Department of Intensive Care, CUB Erasme University HospitalUniversité Libre de BruxellesBrusselsBelgium
5.Department of Anesthesiology and Perioperative CareUniversity of California IrvineOrangeUSA
6.Institute of Medical Informatics, Statistics and EpidemiologyTechnische Universität MünchenMunichGermany
7.Department of Anesthesiology, Center of Anesthesiology and Intensive Care MedicineUniversity Medical Center Hamburg-EppendorfHamburgGermany