Research
Evaluation of a novel closed-loop fluid-administration system based on dynamic predictors of fluid responsiveness: an in silico simulation study
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* Corresponding author: Maxime Cannesson mcanness@uci.edu
1 Department of Anesthesiology & Perioperative Care, University of California, Irvine 101 S City Drive, Orange, CA 92868, USA
2 Department of Anesthesiology and Critical Care Medicine, Centre Hospitalier Universitaire Pitié-Salpêtrière, Paris, France
3 Centre for Statistics in Medicine, Wolfson College, University of Oxford, Oxford, UK
4 Institute of Anesthesiology and Intensive Care Medicine, Triemli City Hospital, Zurich, Switzerland
5 Department of Anesthesiology and Critical Care Medicine, Centre Hospitalier Universitaire de Lille, Lille, France
Critical Care 2011, 15:R278 doi:10.1186/cc10562
Published: 23 November 2011Abstract
Introduction
Dynamic predictors of fluid responsiveness have made automated management of fluid resuscitation more practical. We present initial simulation data for a novel closed-loop fluid-management algorithm (LIR, Learning Intravenous Resuscitator).
Methods
The performance of the closed-loop algorithm was tested in three phases by using a patient simulator including a pulse-pressure variation output. In the first phase, LIR was tested in three different hemorrhage scenarios and compared with no management. In the second phase, we compared LIR with 20 practicing anesthesiologists for the management of a simulated hemorrhage scenario. In the third phase, LIR was tested under conditions of noise and artifact in the dynamic predictor.
Results
In the first phase, we observed a significant difference between the unmanaged and the LIR groups in moderate to large hemorrhages in heart rate (76 ± 8 versus 141 ± 29 beats/min), mean arterial pressure (91 ± 6 versus 59 ± 26 mm Hg), and cardiac output (CO; (6.4 ± 0.9 versus 3.2 ± 1.8 L/min) (P < 0.005 for all comparisons). In the second phase, LIR intervened significantly earlier than the practitioners (16.0 ± 1.3 minutes versus 21.5 ± 5.6 minutes; P < 0.05) and gave more total fluid (2,675 ± 244 ml versus 1,968 ± 644 ml; P < 0.05). The mean CO was higher in the LIR group than in the practitioner group (5.9 ± 0.2 versus 5.2 ± 0.6 L/min; P < 0.05). Finally, in the third phase, despite the addition of noise to the pulse-pressure variation value, no significant difference was found across conditions in mean, final, or minimum CO.
Conclusion
These data demonstrate that LIR is an effective volumetric resuscitator in simulated hemorrhage scenarios and improved physician management of the simulated hemorrhages.