Literature DB >> 21965362

Review article: closed-loop systems in anesthesia: is there a potential for closed-loop fluid management and hemodynamic optimization?

Joseph Rinehart1, Ngai Liu, Brenton Alexander, Maxime Cannesson.   

Abstract

Closed-loop (automated) controllers are encountered in all aspects of modern life in applications ranging from air-conditioning to spaceflight. Although these systems are virtually ubiquitous, they are infrequently used in anesthesiology because of the complexity of physiologic systems and the difficulty in obtaining reliable and valid feedback data from the patient. Despite these challenges, closed-loop systems are being increasingly studied and improved for medical use. Two recent developments have made fluid administration a candidate for closed-loop control. First, the further description and development of dynamic predictors of fluid responsiveness provides a strong parameter for use as a control variable to guide fluid administration. Second, rapid advances in noninvasive monitoring of cardiac output and other hemodynamic variables make goal-directed therapy applicable for a wide range of patients in a variety of clinical care settings. In this article, we review the history of closed-loop controllers in clinical care, discuss the current understanding and limitations of the dynamic predictors of fluid responsiveness, and examine how these variables might be incorporated into a closed-loop fluid administration system.

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Year:  2011        PMID: 21965362     DOI: 10.1213/ANE.0b013e318230e9e0

Source DB:  PubMed          Journal:  Anesth Analg        ISSN: 0003-2999            Impact factor:   5.108


  19 in total

1.  Using non invasive dynamic parameters of fluid responsiveness in children: there is still much to learn.

Authors:  Elena Chung; Maxime Cannesson
Journal:  J Clin Monit Comput       Date:  2012-03-20       Impact factor: 2.502

2.  Closed-loop systems and automation in the era of patients safety and perioperative medicine.

Authors:  Maxime Cannesson; Joseph Rinehart
Journal:  J Clin Monit Comput       Date:  2014-02       Impact factor: 2.502

3.  Control-oriented physiological modeling of hemodynamic responses to blood volume perturbation.

Authors:  Ramin Bighamian; Bahram Parvinian; Christopher G Scully; George Kramer; Jin-Oh Hahn
Journal:  Control Eng Pract       Date:  2018-03-14       Impact factor: 3.475

4.  Feasibility of automated titration of vasopressor infusions using a novel closed-loop controller.

Authors:  Joseph Rinehart; Michael Ma; Michael-David Calderon; Maxime Cannesson
Journal:  J Clin Monit Comput       Date:  2017-01-25       Impact factor: 2.502

5.  The future of intraoperative blood pressure management.

Authors:  Frederic Michard; Ngai Liu; Andrea Kurz
Journal:  J Clin Monit Comput       Date:  2017-02-07       Impact factor: 2.502

Review 6.  Automated systems for perioperative goal-directed hemodynamic therapy.

Authors:  Sean Coeckelenbergh; Cedrick Zaouter; Brenton Alexander; Maxime Cannesson; Joseph Rinehart; Jacques Duranteau; Philippe Van der Linden; Alexandre Joosten
Journal:  J Anesth       Date:  2019-09-25       Impact factor: 2.078

7.  Multimodal noninvasive monitoring of soft tissue wound healing.

Authors:  Michael Bodo; Timothy Settle; Joseph Royal; Eric Lombardini; Evelyn Sawyer; Stephen W Rothwell
Journal:  J Clin Monit Comput       Date:  2013-07-06       Impact factor: 2.502

8.  Evaluation of Fluid Resuscitation Control Algorithms via a Hardware-in-the-Loop Test Bed.

Authors:  Hossein Mirinejad; Bahram Parvinian; Margo Ricks; Yi Zhang; Sandy Weininger; Jin-Oh Hahn; Christopher G Scully
Journal:  IEEE Trans Biomed Eng       Date:  2019-05-08       Impact factor: 4.538

Review 9.  Machine Learning and Artificial Intelligence in Neurocritical Care: a Specialty-Wide Disruptive Transformation or a Strategy for Success.

Authors:  Fawaz Al-Mufti; Michael Kim; Vincent Dodson; Tolga Sursal; Christian Bowers; Chad Cole; Corey Scurlock; Christian Becker; Chirag Gandhi; Stephan A Mayer
Journal:  Curr Neurol Neurosci Rep       Date:  2019-11-13       Impact factor: 5.081

10.  Automated sedation outperforms manual administration of propofol and remifentanil in critically ill patients with deep sedation: a randomized phase II trial.

Authors:  Morgan Le Guen; Ngai Liu; Eric Bourgeois; Thierry Chazot; Daniel I Sessler; Jean-Jacques Rouby; Marc Fischler
Journal:  Intensive Care Med       Date:  2012-12-06       Impact factor: 17.440

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