Abstract
Objective
To describe and evaluate a new weaning and decision support system for mechanical ventilation.
Background
FLEX is a computerized weaning and decision support system for mechanical ventilation that unlike previous rule-based systems derives many of its rules on the basis of the conditions of individual patients. This system can be used in a wide range of ventilatory modes as well as automatic control of weaning. It incorporates the features of the patented ventilatory mode known as Adaptive Support Ventilation (ASV) along with other new features for control of weaning, and control of patient’s oxygenation by adjustment of PEEP and the fraction of inspired oxygen.
Methods
Ventilator data was collected for 10 patients in medical/surgical ICU at baseline and about 24 hours later. Required data fields for each patient for these two␣time points were also entered into the FLEX program. Comparison of clinical data and FLEX recommendations were made with regard to minute ventilation, alarms, weaning institution and other variables.
Results
At baseline, 7 patients were being treated with AC, the remainder with IMV/PS. There was good agreement between the measured and recommended minute ventilations; variances were seen in some patients being treated with permissive hypercapnea and those with evidence of␣high oxygen needs or other metabolic derangements. At 24 hours, there was improved correlation between measured minute ventilation and that recommended by FLEX, suggesting that clinical adjustments were in-line with Flex recommendations over time. Furthermore, FLEX made recommendations with regard to FIO2 and PEEP that would potentially diminish the risk of oxygen toxicity, hypoxemia, and barotrauma in selected patients. FLEX has also been implemented as a closed loop system in an initial set up.
Conclusion
A new weaning and decision support system for mechanical ventilation is presented. The recommendations made by the system were found to be in line with clinical determinations. Further refinements in the FLEX predictions can be easily made by including inputs which represent permissive hypercapnea or increased metabolic demand for selected patients.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Fagan LM, Kunz JC, Feigenbaum EA, Osborn JJ. Extensions to the rule-based formalism for a monitoring task. In: Buchanan BG, Shortliffle EH (eds) Rule-based expert systems; the MYCIN experiments of the Stanford heuristic programming project. Reading, MA: Addison-Wesley, 1985: 397–423.
Miller P. Goal-directed critiquing by computer: ventilator management. Comput Biomed Res 1985; 18: 422–438.
Hernandez-Sande C, Moret-Bonillo V, Alonso-Betanzos A. ESTER: an expert system for management of respiratory weaning therapy. IEEE Trans Biomed Eng 1989; 36: 559–564.
Sittig DF, Pace NL, Gardner RM, Beck E, Morris AH. Implementation of a computerized patient advice system using the HELP clinical information system. Comput Biomed Res 1989; 22: 474–487.
Tong DA. Weaning patients from mechanical ventilation. A knowledge-based system approach. Comput Meth Progr Biomed 1991; 35: 267–278.
Henderson S, Crapo RO, Wallace CJ, East TD, Morris AH, Gardner RM. Performance of computerized protocols for the management of arterial oxygenation in an intensive care unit. Int J Clin Monit Comput 1992; 8: 271–280.
McKinley BA, Moore FA, Sailors RM, Cocanour CS, Marquez A, Wright RK, Tonnesen AS, Wallace CJ, Morris AH, East TD. Computerized decision support for mechanical ventilation of trauma induced ARDS: results of a randomized clinical trial. J Trauma 2001; 50(3): 415–425.
Hernandez C, Moret V, Arcay B, Hermida RC. Weaning from mechanical ventilation using a prototype closed-loop system. Microcomput Appl 1988; 7(3): 128–130.
Strickland Jr. JH, Hassan JH. A computer-controlled weaning system. Chest 1991; 100: 1096–1099.
Dojat M, Brochard L, Lemaire F, Harf A. A knowledge-based system for assisted ventilation of patients in intensive care units. Int J Clin Monit Comput 1992; 9: 239–250.
Nemoto T, Hatzakis G, Thorpe CW, Olivenstein R, Dial S, Bates JHT. Automatic control of pressure support mechanical ventilation using Fuzzy logic. Am J Respir Crit Care Med 1999; 160: 550–556.
Rudowski R, Frostell C, Gill H. A knowledge-based expert system for mechanical ventilation of the lungs. The KUSIVAR concept and prototype. Comput Meth Prog Biomed 1989; 30: 59–70.
Rutledge GW, Thomsen GE, Farr BR, Tovar MA, Polaschek JX, Beinlich IA, Sheiner LB, Fagan LM. The design and implementation of a ventilator-management advisor. Art Intell Med 1993; 5: 67–82.
Rees SE, Allerod C, Murley D, Zhao Y, Smith BW, Kjargaard S, Thorgaard P, Andreassen S. Using physiological models and decision theory for selecting appropriate ventilator settings. J Clin Monit Comput 2006; 20: 421–429.
Tehrani FT. A new decision support system for mechanical ventilation. Proc IEEE EMBS 2007; 29: 3569–3572.
Otis AB, Fenn WO, Rahn H. Mechanics of breathing in man. J Appl Physiol 1950; 2: 592–607.
Mersmann S, Kuck K. SmartCare-optimizing workflow processes in critical care through automation. Int J Clin Monit Comput 2006; 20: 119–120.
Tehrani FT. Method and apparatus for controlling an artificial respirator. US Patent No. 4,986,268, issued Jan. 22, 1991.
Tehrani FT, Rogers M, Lo T, Malinowski T, Afuwape S, Lum M, Grundl B, Terry M. Closed-loop control of the inspired fraction of oxygen in mechanical ventilation. J Clin Monit Comput 2002; 17: 367–376.
Tehrani FT, Rogers M, Lo T, Malinowski T, Afuwape S, Lum M, Grundl B, Terry M. A dual closed loop control system for mechanical ventilation. J Clin Monit Comput 2004; 18:111–129.
Hewlett AM, Platt AS, Terry VG. Mandatory minute volume. Anaesthesia 1977; 32: 163–169.
Author information
Authors and Affiliations
Corresponding author
Additional information
Tehrani FT, Roum JH. Flex: A new computerized system for mechanical ventilation.
Rights and permissions
About this article
Cite this article
Tehrani, F.T., Roum, J.H. Flex: A New Computerized System for Mechanical Ventilation. J Clin Monit Comput 22, 121–130 (2008). https://doi.org/10.1007/s10877-008-9113-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10877-008-9113-4