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Journal of Clinical Monitoring and Computing

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Open Access 01-04-2020 | Review Paper

Journal of Clinical Monitoring and Computing end of year summary 2019: hemodynamic monitoring and management

Authors: Bernd Saugel, Lester A. H. Critchley, Thomas Kaufmann, Moritz Flick, Karim Kouz, Simon T. Vistisen, Thomas W. L. Scheeren

Published in: Journal of Clinical Monitoring and Computing | Issue 2/2020

Excerpt

Hemodynamic monitoring is essential to provide optimal hemodynamic management to patients in perioperative and intensive care medicine. The Journal of Clinical Monitoring and Computing (JCMC) welcomes research articles investigating hemodynamic monitoring technologies, cardiovascular pathophysiology, and hemodynamic treatment strategies that help advance this research field and eventually improve patient care. In this review, we highlight and summarize selected papers on hemodynamic monitoring and management published in the JCMC in 2019. …

Nicklas JY, Beckmann D, Killat J, Petzoldt M, Reuter DA, Rosch T, Saugel B. Continuous noninvasive arterial blood pressure monitoring using the vascular unloading technology during complex gastrointestinal endoscopy: a prospective observational study. J Clin Monit Comput. 2019;33(1):25–30. https://doi.org/10.1007/s10877-018-0131-6.CrossRefPubMed

Henriques TS, Costa MD, Mathur P, Mathur P, Davis RB, Mittleman MA, Khabbaz KR, Goldberger AL, Subramaniam B. Complexity of preoperative blood pressure dynamics: possible utility in cardiac surgical risk assessment. J Clin Monit Comput. 2019;33(1):31–8. https://doi.org/10.1007/s10877-018-0133-4.CrossRefPubMed

Saugel B, Reese PC, Sessler DI, Burfeindt C, Nicklas JY, Pinnschmidt HO, Reuter DA, Sudfeld S. Automated ambulatory blood pressure measurements and intraoperative hypotension in patients having noncardiac surgery with general anesthesia: a prospective observational study. Anesthesiology. 2019;131(1):74–83. https://doi.org/10.1097/ALN.0000000000002703.CrossRefPubMed

Du CH, Glick D, Tung A. Error-checking intraoperative arterial line blood pressures. J Clin Monit Comput. 2019;33(3):407–12. https://doi.org/10.1007/s10877-018-0167-7.CrossRefPubMed

Harrison MJ, Connor CW, Cumin D. Pediatric blood pressures during anesthesia assessed using normalization and principal component analysis techniques. J Clin Monit Comput. 2019;33(4):589–95. https://doi.org/10.1007/s10877-018-0199-z.CrossRefPubMed

Vetrugno L, Bignami E, Barbariol F, Langiano N, De Lorenzo F, Matellon C, Menegoz G, Della Rocca G. Cardiac output measurement in liver transplantation patients using pulmonary and transpulmonary thermodilution: a comparative study. J Clin Monit Comput. 2019;33(2):223–31. https://doi.org/10.1007/s10877-018-0149-9.CrossRefPubMed

Nakwan N, Chichareon P, Khwannimit B. A comparison of ventricular systolic function indices provided by VolumeView/EV1000 and left ventricular ejection fraction by echocardiography among septic shock patients. J Clin Monit Comput. 2019;33(2):233–9. https://doi.org/10.1007/s10877-018-0152-1.CrossRefPubMed

Maeda T, Hamaguchi E, Kubo N, Shimokawa A, Kanazawa H, Ohnishi Y. The accuracy and trending ability of cardiac index measured by the fourth-generation FloTrac/Vigileo system and the Fick method in cardiac surgery patients. J Clin Monit Comput. 2019;33(5):767–76. https://doi.org/10.1007/s10877-018-0217-1.CrossRefPubMed

Suzuki T, Suzuki Y, Okuda J, Minoshima R, Misonoo Y, Ueda T, Kato J, Nagata H, Yamada T, Morisaki H. Cardiac output and stroke volume variation measured by the pulse wave transit time method: a comparison with an arterial pressure-based cardiac output system. J Clin Monit Comput. 2019;33(3):385–92. https://doi.org/10.1007/s10877-018-0171-y.CrossRefPubMed

10.

Tantot A, Caillard A, Le Gall A, Mateo J, Millasseau S, Mebazaa A, Gayat E, Vallee F. Evaluation of cardiac output variations with the peripheral pulse pressure to mean arterial pressure ratio. J Clin Monit Comput. 2019;33(4):581–7. https://doi.org/10.1007/s10877-018-0210-8.CrossRefPubMed

11.

Laurent S, Boutouyrie P, Asmar R, Gautier I, Laloux B, Guize L, Ducimetiere P, Benetos A. Aortic stiffness is an independent predictor of all-cause and cardiovascular mortality in hypertensive patients. Hypertension. 2001;37(5):1236–41. https://doi.org/10.1161/01.hyp.37.5.1236.CrossRefPubMed

12.

van Velzen MHN, Stolker RJ, Loeve AJ, Niehof SP, Mik EG. Comparison between pulse wave velocities measured using Complior and measured using Biopac. J Clin Monit Comput. 2019;33(2):241–7. https://doi.org/10.1007/s10877-018-0165-9.CrossRefPubMed

13.

Schriger DL, Baraff L. Defining normal capillary refill: variation with age, sex, and temperature. Ann Emerg Med. 1988;17(9):932–5. https://doi.org/10.1016/s0196-0644(88)80675-9.CrossRefPubMed

14.

Shinozaki K, Capilupi MJ, Saeki K, Hirahara H, Horie K, Kobayashi N, Weisner S, Kim J, Lampe JW, Becker LB. Low temperature increases capillary blood refill time following mechanical fingertip compression of healthy volunteers: prospective cohort study. J Clin Monit Comput. 2019;33(2):259–67. https://doi.org/10.1007/s10877-018-0159-7.CrossRefPubMed

15.

Thiele RH, Nemergut EC, Lynch C 3rd. The clinical implications of isolated alpha(1) adrenergic stimulation. Anesth Analg. 2011;113(2):297–304. https://doi.org/10.1213/ANE.0b013e3182120ca5.CrossRefPubMed

16.

Wodack KH, Graessler MF, Nishimoto SA, Behem CR, Pinnschmidt HO, Punke MA, Monge-Garcia MI, Trepte CJC, Reuter DA. Assessment of central hemodynamic effects of phenylephrine: an animal experiment. J Clin Monit Comput. 2019;33(3):377–84. https://doi.org/10.1007/s10877-018-0204-6.CrossRefPubMed

17.

Jacobs R, Lochy S, Malbrain M. Phenylephrine-induced recruitable preload from the venous side. J Clin Monit Comput. 2019;33(3):373–6. https://doi.org/10.1007/s10877-018-0225-1.CrossRefPubMed

18.

Reuter DA, Chappell D, Perel A. The dark sides of fluid administration in the critically ill patient. Intensiv Care Med. 2018;44(7):1138–40. https://doi.org/10.1007/s00134-017-4989-4.CrossRef

19.

Vistisen ST, Moody B, Celi LA, Chen C. Post-extrasystolic characteristics in the arterial blood pressure waveform are associated with right ventricular dysfunction in intensive care patients. J Clin Monit Comput. 2019;33(4):565–71. https://doi.org/10.1007/s10877-018-0216-2.CrossRefPubMed

20.

Sottas CE, Cumin D, Anderson BJ. Blood pressure and heart rates in neonates and preschool children: an analysis from 10 years of electronic recording. Paediatr Anaesth. 2016;26(11):1064–70. https://doi.org/10.1111/pan.12987.CrossRefPubMed

21.

Pinsky MR. Expanding the usefulness of hemodynamic waveform analysis in the critically Ill. J Clin Monit Comput. 2019;33(4):563–4. https://doi.org/10.1007/s10877-018-00239-y.CrossRefPubMed

22.

Monge Garcia MI, Jian Z, Settels JJ, Hatib F, Cecconi M, Pinsky MR. Reliability of effective arterial elastance using peripheral arterial pressure as surrogate for left ventricular end-systolic pressure. J Clin Monit Comput. 2019;33(5):803–13. https://doi.org/10.1007/s10877-018-0236-y.CrossRefPubMed

23.

Tusman G, Acosta CM, Pulletz S, Bohm SH, Scandurra A, Arca JM, Madorno M, Sipmann FS. Photoplethysmographic characterization of vascular tone mediated changes in arterial pressure: an observational study. J Clin Monit Comput. 2019;33(5):815–24. https://doi.org/10.1007/s10877-018-0235-z.CrossRefPubMed

24.

Li C, Xu J, Han F, Walline J, Zheng L, Fu Y, Zhu H, Chai Y, Yu X. Identification of return of spontaneous circulation during cardiopulmonary resuscitation via pulse oximetry in a porcine animal cardiac arrest model. J Clin Monit Comput. 2019;33(5):843–51. https://doi.org/10.1007/s10877-018-0230-4.CrossRefPubMed

25.

Lilot M, Ehrenfeld JM, Lee C, Harrington B, Cannesson M, Rinehart J. Variability in practice and factors predictive of total crystalloid administration during abdominal surgery: retrospective two-centre analysis. Br J Anaesth. 2015;114(5):767–76. https://doi.org/10.1093/bja/aeu452.CrossRefPubMed

26.

Shin CH, Long DR, McLean D, Grabitz SD, Ladha K, Timm FP, Thevathasan T, Pieretti A, Ferrone C, Hoeft A, Scheeren TWL, Thompson BT, Kurth T, Eikermann M. Effects of intraoperative fluid management on postoperative outcomes: a hospital registry study. Ann Surg. 2018;267(6):1084–92. https://doi.org/10.1097/SLA.0000000000002220.CrossRefPubMed

27.

Joosten A, Hafiane R, Pustetto M, Van Obbergh L, Quackels T, Buggenhout A, Vincent JL, Ickx B, Rinehart J. Practical impact of a decision support for goal-directed fluid therapy on protocol adherence: a clinical implementation study in patients undergoing major abdominal surgery. J Clin Monit Comput. 2019;33(1):15–24. https://doi.org/10.1007/s10877-018-0156-x.CrossRefPubMed

28.

van Beest PA. Implementation of goal-directed therapy needs a boost, and it is called assisted fluid management. J Clin Monit Comput. 2019;33(1):13–4. https://doi.org/10.1007/s10877-018-0155-y.CrossRefPubMed

29.

Cesur S, Cardakozu T, Kus A, Turkyilmaz N, Yavuz O. Comparison of conventional fluid management with PVI-based goal-directed fluid management in elective colorectal surgery. J Clin Monit Comput. 2019;33(2):249–57. https://doi.org/10.1007/s10877-018-0163-y.CrossRefPubMed

30.

Chandler JR, Cooke E, Petersen C, Karlen W, Froese N, Lim J, Ansermino JM. Pulse oximeter plethysmograph variation and its relationship to the arterial waveform in mechanically ventilated children. J Clin Monit Comput. 2012;26(3):145–51. https://doi.org/10.1007/s10877-012-9347-z.CrossRefPubMed

31.

Yu Y, Dong J, Xu Z, Shen H, Zheng J. Pleth variability index-directed fluid management in abdominal surgery under combined general and epidural anesthesia. J Clin Monit Comput. 2015;29(1):47–52. https://doi.org/10.1007/s10877-014-9567-5.CrossRefPubMed

32.

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. 2019;33(3):365–71. https://doi.org/10.1007/s10877-018-0190-8.CrossRefPubMed

33.

Saugel B, Joosten A, Scheeren TWL. Perioperative goal-directed therapy: what's the best study design to investigate its impact on patient outcome? J Clin Monit Comput. 2019;33(3):361–3. https://doi.org/10.1007/s10877-018-0196-2.CrossRefPubMed

34.

Joosten A, Jacobs A, Desebbe O, Vincent JL, Sarah S, Rinehart J, Van Obbergh L, Hapfelmeier A, Saugel B. 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. 2019;33(5):787–93. https://doi.org/10.1007/s10877-018-00241-4.CrossRefPubMed

35.

Park J, Yang S, Lee JH, Kim JT, Kim HS, Kim HC. The importance of sensor contacting force for predicting fluid responsiveness in children using respiratory variations in pulse oximetry plethysmographic waveform. J Clin Monit Comput. 2019;33(3):393–401. https://doi.org/10.1007/s10877-018-0183-7.CrossRefPubMed

36.

Ali A, Abdullah T, Sabanci PA, Dogan L, Orhan-Sungur M, Akinci IO. Comparison of ability of pulse pressure variation to predict fluid responsiveness in prone and supine position: an observational study. J Clin Monit Comput. 2019;33(4):573–80. https://doi.org/10.1007/s10877-018-0195-3.CrossRefPubMed

37.

Vistisen ST, Berg JM, Boekel MF, Modestini M, Bergman R, Jainandunsing JS, Mariani MA, Scheeren TWL. Using extra systoles and the micro-fluid challenge to predict fluid responsiveness during cardiac surgery. J Clin Monit Comput. 2019;33(5):777–86. https://doi.org/10.1007/s10877-018-0218-0.CrossRefPubMed

38.

Pybus DA. Real-time, spectral analysis of the arterial pressure waveform using a wirelessly-connected, tablet computer: a pilot study. J Clin Monit Comput. 2019;33(1):53–63. https://doi.org/10.1007/s10877-018-0145-0.CrossRefPubMed

39.

Sun S, Peeters WH, Bezemer R, Long X, Paulussen I, Aarts RM, Noordergraaf GJ. Finger and forehead photoplethysmography-derived pulse-pressure variation and the benefits of baseline correction. J Clin Monit Comput. 2019;33(1):65–75. https://doi.org/10.1007/s10877-018-0140-5.CrossRefPubMed

40.

Yoon JH, Mu L, Chen L, Dubrawski A, Hravnak M, Pinsky MR, Clermont G. Predicting tachycardia as a surrogate for instability in the intensive care unit. J Clin Monit Comput. 2019;33(6):973–85. https://doi.org/10.1007/s10877-019-00277-0.CrossRefPubMedPubMedCentral

41.

Donald R, Howells T, Piper I, Enblad P, Nilsson P, Chambers I, Gregson B, Citerio G, Kiening K, Neumann J, Ragauskas A, Sahuquillo J, Sinnott R, Stell A, Brain ITG. Forewarning of hypotensive events using a Bayesian artificial neural network in neurocritical care. J Clin Monit Comput. 2019;33(1):39–51. https://doi.org/10.1007/s10877-018-0139-y.CrossRefPubMed

42.

Matam BR, Duncan H, Lowe D. Machine learning based framework to predict cardiac arrests in a paediatric intensive care unit : Prediction of cardiac arrests. J Clin Monit Comput. 2019;33(4):713–24. https://doi.org/10.1007/s10877-018-0198-0.CrossRefPubMed

43.

Ruminski CM, Clark MT, Lake DE, Kitzmiller RR, Keim-Malpass J, Robertson MP, Simons TR, Moorman JR, Calland JF. Impact of predictive analytics based on continuous cardiorespiratory monitoring in a surgical and trauma intensive care unit. J Clin Monit Comput. 2019;33(4):703–11. https://doi.org/10.1007/s10877-018-0194-4.CrossRefPubMed

44.

Maheshwari K, Cywinski J, Mathur P, Cummings KC 3rd, Avitsian R, Crone T, Liska D, Campion FX, Ruetzler K, Kurz A. Identify and monitor clinical variation using machine intelligence: a pilot in colorectal surgery. J Clin Monit Comput. 2019;33(4):725–31. https://doi.org/10.1007/s10877-018-0200-x.CrossRefPubMed

45.

Vistisen ST, Johnson AEW, Scheeren TWL. Predicting vital sign deterioration with artificial intelligence or machine learning. J Clin Monit Comput. 2019;33(6):949–51. https://doi.org/10.1007/s10877-019-00343-7.CrossRefPubMed

46.

Rush B, Celi LA, Stone DJ. Applying machine learning to continuously monitored physiological data. J Clin Monit Comput. 2019;33(5):887–93. https://doi.org/10.1007/s10877-018-0219-z.CrossRefPubMed

47.

Davies SJ, Vistisen ST, Jian Z, Hatib F, Scheeren TWL. Ability of an arterial waveform analysis-derived hypotension prediction index to predict future hypotensive events in surgical patients. Anesth Analg. 2020;130(2):352–9. https://doi.org/10.1213/ANE.0000000000004121.CrossRefPubMed

48.

Rinehart J, Joosten A, Ma M, Calderon MD, Cannesson M. Closed-loop vasopressor control: in-silico study of robustness against pharmacodynamic variability. J Clin Monit Comput. 2019;33(5):795–802. https://doi.org/10.1007/s10877-018-0234-0.CrossRefPubMed

49.

Rinehart J, Ma M, Calderon MD, Cannesson M. Feasibility of automated titration of vasopressor infusions using a novel closed-loop controller. J Clin Monit Comput. 2018;32(1):5–11. https://doi.org/10.1007/s10877-017-9981-6.CrossRefPubMed

50.

Scholten HJ, Ten Bloemendal E, Botter B, Korsten HHM, Bouwman RA. Barriers to ultrasound guidance for central venous access: a survey among Dutch intensivists and anaesthesiologists. J Clin Monit Comput. 2019;33(6):1023–31. https://doi.org/10.1007/s10877-018-00246-z.CrossRefPubMedPubMedCentral

Title: Journal of Clinical Monitoring and Computing end of year summary 2019: hemodynamic monitoring and management
Authors: Bernd Saugel
Lester A. H. Critchley
Thomas Kaufmann
Moritz Flick
Karim Kouz
Simon T. Vistisen
Thomas W. L. Scheeren
Publication date: 01-04-2020
Publisher: Springer Netherlands
Published in: Journal of Clinical Monitoring and Computing / Issue 2/2020
Print ISSN: 1387-1307
Electronic ISSN: 1573-2614
DOI: https://doi.org/10.1007/s10877-020-00496-w

ACC 2024 Congress

Springer Medicine

Journal of Clinical Monitoring and Computing end of year summary 2019: hemodynamic monitoring and management

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Springer Medicine

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