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Update in computer-driven weaning from mechanical ventilation.

SUMMARY

Weaning from mechanical ventilation is a complex process requiring assessment and interpretation of both objective and subjective clinical parameters For many years, automated computerised systems for various medical processes, including respiratory management, have been proposed to optimise decision-making and reduce variation amongst clinicians SmartCare[TM]/PS, available since 2003 as a software application for the EvitaXL ventilator (Dragar Medical AG & Co. KG, Lubek, Germany), is one of the first such ventilator systems to be made commercially available SmartCare/PS can be described as a knowledge-based weaning system, which adjusts pressure support based on measurement of the patient's respiratory status specifically the spontaneous respiratory rate, tidal volume and end-tidal carbon dioxide with the aim of optimising the weaning process The primary proposed advantage of this system is an ability to provide management of ventilatory weaning through continuous physiological monitoring and real-time interventions The relatively small number of available clinical studies indicate the system is able to deliver appropriate ventilation during pressure support weaning from both short-term and prolonged ventilation. Of potential clinical note a recent study suggested that use of SmartCare/PS might be associated with useful reductions in the duration of weaning compared to existing clinical practice using weaning protocols One recently published randomised trial supports this conclusion. However, given the known large variation in international critical care ventilatory practices further randomised trials are desirable

Key Words: mechanical ventilation, weaning, automatic weaning, closed-loop ventilation

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The management of mechanical ventilation and its successful removal, termed weaning, is a complex process integrating clinical expertise with the capabilities, and limitations, of mechanical ventilators. Frequent monitoring is necessary to titrate ventilator settings in response to changes in each patient's physiological status. Due to clinical organisational constraints, it may not be possible to have an optimum level of expertise and monitoring available to all ventilated patients at all times. Therefore, alternative clinical support tools have been proposed which may improve the delivery of mechanical ventilation and hasten the weaning process. These methods consist of organisational interventions including outcome managers, weaning teams, clinical guidelines and non-physician weaning protocols (1). In addition, progress in ventilator microprocessor technology has enabled the long anticipated development of computer-assisted management of ventilation and weaning (2). More recently a computerised knowledge-based system, SmartCare[TM]/PS, has become available commercially as a software application for the EvitaXL ventilators (Drager Medical AG & Co. KG, Lubeck, Germany). This review aims to summarise the available data relevant to the clinical utility of the adaptive weaning offered by SmartCare/PS.

AUTOMATIC VENTILATORY MANAGEMENT

Automated computerised systems may standardise bedside decision-making, reduce variation amongst clinicians and assist with interpretation of clinical information (3-4). Clinical applications extend from ventilatory management through to administration of drug infusions for regulation of arterial blood pressure and blood glucose (5-10).

The knowledge-based SmartCare[TM] system, developed and supplemented since 1999, enables automated control of medical devices based on established clinical guidelines (11). The definition of a knowledge-based system implies the medical device is provided with more knowledge than is contained within a simple mathematical model (12). The first clinical application of the SmartCare system is the automated control of ventilator weaning (SmartCare/PS) based on the work of Dojat and others (10,13-15).

Automatic ventilatory management is based on closed-loop control systems that have been in development since the 1950s (16). Examples of closed-loop systems in everyday life include thermostat-controlled heating systems and cruise control in cars (17). These systems consist of three elements: the input that activates the system, the output, which is the product of the system and the protocol that links the two. Therefore, a closed-loop system directs activation and conditioning of the input by the feedback from the output (18).

Pressure support ventilation is an example of a straightforward closed-loop ventilatory system that utilises negative feedback control. The ventilator monitors inspiratory pressure and adjusts flow to achieve the target pressure support (16). More complex closed-loop systems include dual control modes that switch between pressure control and volume control and applications that enable titration and weaning of ventilatory support without clinician manipulation of ventilator controls.

The goal of many computerised ventilation applications is to provide improved adaptation of ventilatory support to the patient's needs through continuous monitoring and real-time interventions (13). Moreover, these computerised systems often aim to reduce the duration of ventilation and result in better patient outcomes (15). Multiple commercial computerised ventilation and weaning programs have been developed, with various levels of clinical acceptance, including adaptive support ventilation (ASV) and proportional assist ventilation (PAV). Like these other systems, SmartCare/PS has been developed over many years, originating from prototypes named "Ganesh" and "NeoGanesh" (10,14).

SmartCare/PS was designed to respond to a specific phase of ventilatory support, namely weaning in the presence of spontaneous ventilation, and to incorporate only one mode of ventilation, namely pressure support based on the earlier work of Brochard and others (20,21). SmartCare/PS continuously monitors the patient's respiratory status and periodically adapts pressure support aiming for a rapid, safe and efficient weaning process. At present, there is only limited published data examining the clinical application of the SmartCare/PS system, despite its availability on the commercial market within Australia. The device has received recent Food and Drug Administration marketing approval in the United States (22).

DESCRIPTION OF THE SMARTCARE/PS SYSTEM

The SmartCare/PS system uses patient respiratory rate, tidal volume ([V.sub.T]) and end-tidal carbon dioxide ([E.sub.T][CO.sub.2]) to control the level of pressure support to maintain the patient in a proprietary "respiratory zone of comfort". The defining ranges for the "respiratory zone of comfort" parameters are shown in Table 1. Early studies supported the utility of these ranges as decision thresholds for the knowledge-based system's effective titration and weaning of ventilation (10,13,14). Respiratory rate is the most influential parameter, as it was considered the best indicator of the ability of the respiratory muscles to adapt to changes in workload (15). [V.sub.T] and [E.sub.T][CO.sub.2] are incorporated to assist in the identification of ventilatory failure.

The SmartCare/PS system acquires data on the patient's current respiratory status (frequency, VT and [E.sub.T][CO.sub.2]) and its time-course, establishes a respiratory status diagnosis (Table 2), determines the intervention and acts on the ventilator to increase or decrease pressure support, or leave it unchanged (10,15). SmartCare/PS continues to sample these parameters and classifies ventilation based on the mean values calculated every two or five minutes and adjusts the pressure support level to maintain the patient in the "respiratory zone of comfort" (Table 1). If no change has been made to pressure support, a two-minute timeframe applies, whereas a five-minute interval is used if an adjustment to pressure support has just occurred.

The SmartCare/PS system divides the control processes into three steps: the first step consists of stabilising the patient within the "respiratory zone of comfort". The second step decreases the pressure support setting without the patient leaving the comfort zone. The third step tests readiness for extubation by maintaining and monitoring the patient at the lowest level of pressure support. The lowest level of pressure varies according to the presence of an endotracheal or tracheostomy tube, the use of a heat and moisture exchanger (HME) or an active humidifier and the use of automatic tube compensation (ATC) (15) (Table 1). Once the minimum pressure support level is reached, a one-hour observation period is commenced during which the patient's spontaneous breathing frequency, [V.sub.T] and [E.sub.T][CO.sub.2] are monitored. This observation period is extended to two hours if the initial pressure support setting was greater than 15 cm[H.sub.2]O. If the PEEP setting is above 5 cm[H.sub.2]O, when the minimum pressure support setting has been achieved, a screen message alerts the clinician that the monitoring period will not be initiated until the PEEP is reduced to 5 cm[H.sub.2]O. On successful completion of this observation period, SmartCare/PS suggests, via a screen message, the potential for disconnecting from the ventilator, termed "consider separation".

ACTIVATION OF SMARTCARE/PS

Activation of a SmartCare/PS session is possible by touching the screen key 'SmartCare' in the "ventilator settings" options, once the patient is in pressure support ventilation (PSV). Once SmartCare/PS is selected, the clinician enters the patient's body weight, designates the airway access as endotracheal or tracheostomy, indicates whether the humidification is active, inferring a heated humidification system, or via a heat and moisture exchanger (HME), specifies if night rest from pressure support weaning is required and indicates whether the patient has chronic obstructive pulmonary disease (COPD) or a neurological disorder (Figure 1). SmartCare/PS then determines the values of maximum permissible spontaneous breath rate, [E.sub.T][CO.sub.2] and minimum [V.sub.T] based on this medical history data.

[FIGURE 1 OMITTED]

The "patient session" screen key is then touched and the 'on' key selected. In addition, the SmartCare/PS system requires activation of [CO.sub.2] monitoring via the [CO.sub.2] sensor (Capnosmart 68 71 500, Drager Medical, Lubeck, Germany).

Initial weaning of pressure support takes into account the pressure support setting as well as the patient's breathing pattern history. If the pressure support is below 15 cm [H.sub.2]O it will be decreased by 2 cm [H.sub.2]O once the patient's ventilation has been stable for 30 minutes; if the pressure support level is higher than 15 cm [H.sub.2]O, it will be decreased by 4 cm [H.sub.2]O if the ventilation has been acceptable for 60 minutes (15). SmartCare/PS tolerates transient instabilities for two to four minutes depending on the level of pressure support. SmartCare/PS continues to adjust pressure support by 2 to 4 cm [H.sub.2]O increments based on repeated respiratory status diagnosis until a minimum setting is reached (Figure 2).

EVALUATION AND CLINICAL APPLICATION STUDIES

Several studies have reported on the efficacy of the SmartCare/PS system. In a small study of 19 patients published 14 years ago, the original

prototype of the SmartCare/PS system, interfaced with a Hamilton Veolar ventilator (Hamilton Medical, Bonaduz, Switzerland) and laptop computer, was tested to determine its ability to maintain a patient's breathing pattern within the predetermined "respiratory zone of comfort" and decrease pressure support in patients considered ready to wean (10). Patients were maintained in the "respiratory zone of comfort" for 95% and 75% of the total ventilation time in both weanable patients and non-weanable patients, the classification of which was correctly distinguished by the test program.

In a second published study (13), the same authors examined the ability of a later development of the system to accurately predict the correct timing of extubation in 38 patients undergoing weaning from mechanical ventilation. This study compared the accuracy of extubation readiness suggestions by the knowledge-based test system to conventional weaning tests used to predict weaning success, including an ability to tolerate a two-hour T -piece trial and post-extubation outcome. The knowledge-based system demonstrated a positive predictive value of 89%, compared to 77% in the conventional weaning tests and 81% from calculation of the rapid shallow breathing index, a weaning readiness predictor proposed by Yang and Tobin (23). This study indicated the knowledge-based system may have been more accurately predictive of successful weaning and extubation than conventional methods.

[FIGURE 2 OMITTED]

A further published study evaluated a precursor of SmartCare/PS versus physician-controlled management of pressure support. The knowledge-based system was interfaced to a Hamilton Veolar ventilator and a mainstream gas monitor (Novametrix 1260, Wallingford, CT) for assessing [E.sub.T][CO.sub.2] (15). Each patient was ventilated consecutively with the knowledge-based system and physician-controlled pressure support manipulation for 24 hours in a random order. The study reported that patients spent a longer time within the "respiratory zone of comfort" (93% compared to 66%) and experienced reduced periods of excessive workload as measured by [P.sub.0.1] (11% compared to 34%), while receiving the knowledge-based system management of pressure support (15).

Bouadma and others (24) evaluated the use of the knowledge-based system in a heterogeneous patient group undergoing prolonged mechanical ventilation. The study provided evidence of the clinical applicability of SmartCare/PS as it confirmed the system's ability to successfully manage pressure support for prolonged periods. The knowledge-based system identified the potential for extubation earlier than clinicians in 52% of the patients and contemporaneously in 33%. Patients were extubated as soon as either the clinician or system predicted potential success, if no contraindications were present. However, the extubation failure rate of 21% was higher than rates reported in some studies of weaning readiness prediction, suggesting extubation readiness prediction by the system needed further evaluation (25-27).

More recently, Lellouche and others (28) conducted the only large, multi-site, randomised, controlled study comparing the knowledge-based system (implemented in Drager Evita 4 ventilators) to weaning protocols established as usual care within the participating units. The study of 144 patients reported a 40% reduction in weaning duration and significant reductions in the duration of total ventilation, intensive care (ICU) length of stay and the use of non-invasive ventilation post-extubation. This study suggested the knowledge-based system had the potential to substantially reduce the total duration of ventilation and weaning compared to a standardised clinical protocol.

OTHER AUTOMATED WEANING SYSTEMS

A review of the literature, using the search terms closed loop, weaning and mechanical ventilation both individually and in combination, identified published reports on several automated weaning systems (8,9,29-31). Two commercially available automated ventilatory modes include adaptive support ventilation (ASV) and proportional assist ventilation (PAV).

ASV incorporates pressure control (PCV) and PSV, with automatic adaptation of respiratory rate and pressure levels based on a clinician-set desired percentage of minute ventilation (2). In the absence of spontaneous ventilation, ASV delivers Synchronised Intermittent Mandatory Ventilation (SIMV)-style PCV, using lung mechanics measured during each breath to guide closed loop adjustment of ventilator settings (32). During spontaneous respiratory effort, the ventilator switches from PCV to PSV and reverts to PCV if the patient's minute ventilation decreases below the guaranteed minimum. The level of pressure support is also adapted to provide adequate tidal volumes according to the desired percentage of minute ventilation. Titration of the desired percentage of minute ventilation in ASV requires clinician decision input to enable progression to readiness for extubation. This differs from SmartCare/PS which only requires activation of the program to progress the patient from high levels of pressure support to a state of readiness for extubation.

The clinical application of ASV has been investigated in a number of small studies (33,34). These studies describe the ability of ASV to deliver effective and safe weaning with less patient-ventilator dyssynchrony and fewer signs of increased respiratory muscle load when compared to the more traditional approach of SIMV with pressure support (2,35-37). To the present, ASV has not been described as a mode used clinically in any of several large studies of international mechanical ventilation practices (38-40).

Proportional assist ventilation (PAV), based on the original prototype developed by Younes and others (41), delivers positive pressure throughout inspiration in proportion to patient generated effort and dependent on the set levels of flow assist (offsets elastance) and volume assist (offsets resistance) (42). There are no set targets of pressure, volume or flow, rather the airway pressure is increased or decreased in proportion to the patient effort via positive feedback control using respiratory elastance and resistance as the feedback signals (16,43). The patient's respiratory drive determines the respiratory rate and inspiratory time. PAV has been described as the only mode to be primarily designed on a physiological basis rather than the technical abilities of ventilators (41).

Reported clinical studies of PAV have failed to identify important clinical benefits compared to PSV These studies demonstrate PAV does not improve gas exchange (44,45). Moreover, PAV is described as resulting in respiratory muscle unloading and thus less respiratory muscle effort due to high tidal volumes which negatively affect respiratory muscle training and potential weaning success (46,47). In addition, increased numbers of missed triggers with high levels of pressure support and delayed cessation of inspiratory flow, with resultant alveolar overdistension and gas trapping, suggest PAV is not as promising a mode as was initially thought (42,45,46,41-50).

DISCUSSION

Weaning from mechanical ventilation is a major international research priority aimed at reducing morbidity and cost associated with prolonged mechanical ventilation (51,52).

Both automatic ventilatory management and weaning protocols based on expert opinion have been proposed as methods of reducing unnecessary or inappropriate variation or delays in ventilatory processes that may arise from organisational constraints. The SmartCare/PS system can be viewed as an automated form of weaning protocol with several advantages over the written format. The computer system is not open to the same individual manipulation and subjective interpretation. Compliance with written protocols is difficult to guarantee and requires additional human resources to assist in their adoption and ongoing use in clinical practice (11,53-55).

On the other hand, protocols are often criticised as restricting clinical discretion and autonomy resulting in repression of analytic thought, critical thinking, clinical innovation and individualised care (56-58). Similar criticism may also be directed at the SmartCare/PS system. However, the designers claim the system reproduces the cognitive behaviour of health professionals while maintaining user control over the system and is not intended as a substitute for clinical judgment and can be overridden at any time (11).

SmartCare/PS is one of the first commercial applications to 'close the loop' in management of weaning from mechanical ventilation. However, SmartCare/ PS is limited in its ability to control the weaning process. First, activation of SmartCare/PS relies on clinician decision-making and recognition of a patient's potential to wean. Second, SmartCare/PS only titrates pressure support and thus has no influence over other ventilator settings such as PEEP and [FiO.sub.2]. Finally, SmartCare/PS is unable to take into consideration disparate patient and organisational factors that influence weaning and extubation. Notable among these are upper airway obstruction, excess respiratory secretions, inability to protect the airway, cardiovascular failure or ischaemia, abnormal mental status, respiratory failure, sepsis and seizures (59). Organisational factors that influence weaning and extubation management include the time of day, planned patient transport or procedures, or unavailability of medical staff for reintubation purposes.

CONCLUSION

Automatic ventilatory weaning systems offer the promise of improved patient outcomes. SmartCare/ PS is one of the first commercially available software applications for automation of a clinical protocol within a knowledge-based system. The key aspect of this technology is an ability to provide continuous monitoring and real-time interventions which aim to deliver a rapid, safe and efficient weaning process. SmartCare/PS is the product of greater than 10 years of development in Europe, is laudably based on clinically acceptable parameter limits and initial reports of its clinical utility are encouraging. However, further clinical studies will clarify whether SmartCare/ PS is to become the first widely implemented product in the long-anticipated era of automated clinical care systems.

ACKNOWLEDGEMENTS

We thank Stefan Mersmann, Knowledge Engineer and Technical Architect of SmartCare and Michael Rodda, Application Specialist, Drager Medical for helpful communication clarifying aspects of the detail of the SmartCare/PS program.

CONFLICT OF INTEREST

The authors have no financial interest in the products described in this paper, but report that SmartCare/PS software, and associated technical upgrades, have been provided to the Drager EvitaXL ventilators owned by the Intensive Care Unit of the Royal Melbourne Hospital, by Drager Medical, Australia.

REFERENCES

(1.) Burns SM, Dempsey E. Long-term ventilator management strategies: experiences of two hospitals. AACN Clin Issues 2000;11:424-441.

(2.) Petter A, Chiolero R, Cassina T, Chassot PG, Muller XM, Revelly JP Automatic respirator weaning with adaptive support ventilation: the effect on duration of endotracheal intubation and patient management. Anesth Analg 2003; 97:1743-1750.

(3.) Morris AH. Decision support and safety of clinical environments. Qua] Saf Health Care 2002; 11:69-75.

(4.) MacGill I, Cade J, Siganporia R, Packer J. VAD: ventilation management in the ICU. Proceedings of the Symposium on Computer-Based Medical Systems; 1990; Chapel Hill; 1990. p. 345-349. Available from: http://ieeexplore.ieee.org/iel2/483/3324/00109418.pdf?arnumber=109418 Accessed May 20, 2006.

(5.) Xu Z, Packer J, Cade J. A hybrid fuzzy-neural control system for management of mean arterial pressure of seriously ill patients. Proceedings of the IEEE International Conference on Neural Networks; 1995; Perth; 1995. p. 2281-2286. Available from: http://ieeexplore.ieee.org/xpls/absprintf.jsp?arnumber=487717 Accessed May 20, 2006.

(6.) Mason D, Cade J, Siganporia R, Packer J. Closed-loop control of multiple drug infusions. Proceedings from the 11th IEEE Conference on Engineering in Medicine and Biology; 1989; Seattle; 1989. Available from: http://ieeexplore.ieee.org/iel2/846/3080/00095711.pdf?arnumber=95711 Accessed May 20, 2006.

(7.) Chee F, Fernando T, Savkin A, van Heedon V Expert PID control system for blood glucose control in critically ill patients. IEEE Trans Inf Technol Biomed 2003; 7:419-425.

(8.) Strickland JH, Jr., Hasson JH. A computer-controlled ventilator weaning system. A clinical trial. Chest 1993; 103:1220-1226.

(9.) Iotti G, Brunner J, Braschi A, Laubscher T, Olivei M, Palo A et al. Closed-loop control of airway occlusion pressure at 0.1 second (P0.1) applied to pressure-support ventilation: algorithm and application in intubated patients. Crit Care Med 1996;24:771-779.

(10.) 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.

(11.) Mersmann S, Dojat M. Smartcare-automated clinical guidelines in critical care. Proceedings from the 16th European Conference on Artificial Intelligence; 2004; Valencia; 2004. 745-749. Available from: http:/www.openclinical.org/docs/ext/ais/smartcare/MersmannDojat-ECAI2004.pdf Accessed May 20, 2006.

(12.) Chatburn R. Computer control of mechanical ventilation. Respir Care 2004; 49:507-517.

(13.) Dojat M, Harf A, Touchard D, Laforest M, Lemaire F, Brochard L. Evaluation of a knowledge-based system providing ventilatory management and decision for extubation. Am J Respir Crit Care Med 1996; 153:997-1004.

(14.) Dojat M, Pachet F, Guessoum Z, Touchard D, Harf A, Brochard L. NeoGanesh: a working system for the automated control of assisted ventilation in ICUs. Artif Intel] Med 1997; 11:97-117.

(15.) Dojat M, Harf A, Touchard D, Lemaire F, Brochard L. Clinical evaluation of a computer-controlled pressure support mode. Am J Respir Crit Care Med 2000; 161:1161-1166.

(16.) Branson R, Johannigman J, Campbell R, Davis K. Closed-loop mechanical ventilation. Respir Care 2002; 47:427-451.

(17.) Barr M. Closed-loop control. Embedded Systems Programming 2002:55-56. Available from www.netrino.com/Publications/Glossary/PID.html Accessed December 20, 2005.

(18.) Ranieri V Optimization of patient ventilator interactions: closed loop technology to turn the century. Intensive Care Med 1997; 23:936-939.

(19.) Jolliet P Servo controlled ventilation. Proceedings from the International Consensus Conference in Intensive Care Medicine; 2005; Budapest; 2005. 119-121.

(20.) Brochard L, Pluskwa F, Lemaire E Improved efficacy of spontaneous breathing with inspiratory pressure support. Am Rev Respir Dis 1987; 136:411-415.

(21.) Brochard L, Harf A, Lorino H, Lemaire E Inspiratory pressure support prevents diaphragmatic fatigue during weaning from mechanical ventilation. Am Rev Respir Dis 1989;139:513-521.

(22.) U. S. E D. A. Centre for Devices and Radiological Health. 510 (k) Premarket notification database no: K051263. Available from: http://www.accessdata.fda.gov/scripts/cdrh/cfdocs/search/ search.cfm?db=PMN&ID=K051263 Accessed May 20, 2006.

(23.) Yang KL, Tobin MI. A prospective study of indexes predicting the outcome of trials of weaning from mechanical ventilation. N Eng] J Med 1991; 324:1445-1450.

(24.) Bouadma L, Lellouche F, Cabello B, Taille S, Mancebo J, Dojat M et al. Computer-driven management of prolonged mechanical ventilation and weaning: a pilot study. Intensive Care Med 2005; 31:1446-1450.

(25.) Leitch EA, Moran JL, Grealy B. Weaning and extubation in the intensive care unit. Clinical or index-driven approach? Intensive Care Med 1996; 22:752-759.

(26.) Conti G, Montini L, Pennisi MA, Cavaliere F, Arcangeli A, Bocci MG et al. A prospective, blinded evaluation of indexes proposed to predict weaning from mechanical ventilation. Intensive Care Med 2004; 30:830-836.

(27.) Vallverdu I, Calaf N, Subirana M, Net A, Benito S, Mancebo J. Clinical characteristics, respiratory functional parameters, and outcome of a two-hour T -piece trial in patients weaning from mechanical ventilation. Am J Respir Crit Care Med 1998; 158:1855-1862.

(28.) Lellouche F, Mancebo J, Jolliet P, Roeseler J, Schortgen F, Dojat M, et al. A multicenter randomized trial of computer-driven protocolized weaning from mechanical ventilation. Am J Respir Crit Care Med 2006; 174:894-900.

(29.) Strickland JH, Jr., Hasson JH. A computer-controlled ventilator weaning system. Chest 1991; 100:1096-1099.

(30.) East T, Heermann L, Bradshaw R, Lugo A, Sailors R, Ershler L et al. Efficacy of computerized decision support for mechanical ventilation: results of a prospective multi-center randomized trial. Proc AMIA SGMP 1999; 251-255.

(31.) Fernando T, Cade J, Packer J. Automatic control of arterial carbon dioxide tension in mechanically ventilated patients. IEEE Trans Inf Technol Biomed 2002; 6:269-276.

(32.) Brunner J, Iotti G. Adaptive support ventilation. Minerva Anestesiol 2002; 68:365-368.

(33.) Laubscher T, Frutiger A, Fanconi S, Jutzi H, Brunner J. Automatic selection of tidal volume, respiratory frequency and minute ventilation in intubated ICU patients as startup procedure for closed-loop controlled ventilation. Int J Clin Monit Comput 1994; 11:19-30.

(34.) Laubscher T, Frutiger A, Fanconi S, Brunner J. The automatic selection of ventilation parameters during the initial phase of mechanical ventilation. Intensive Care Med 1996; 22:199207.

(35.) Tassaux D, Dalmas E, Gratadour P, Jolliet P Patient-ventilator interactions during partial ventilatory support: a preliminary study comparing the effects of adaptive support ventilation with synchronised intermittent mandatory ventilation plus inspiratory pressure support. Crit Care Med 2002; 30:801-807.

(36.) Sulzer C, Chiolero R, Chassot P, Mueller Y, Revelly J. Adaptive support ventilation for fast tracheal extubation after cardiac surgery. Anesthesiology 2001; 95:1339-1345.

(37.) Cassina T, Chiolero R, Mauri R, Revelly J. Clinical experience with adaptive support ventilation for fast-track cardiac surgery. J Cardiothorac Vasc Anesth 2003; 17:571-575.

(38.) Esteban A, Alia I, Ibanez J, Benito S, Tobin MJ. Modes of mechanical ventilation and weaning. A national survey of Spanish hospitals. The Spanish Lung Failure Collaborative Group. Chest 1994; 106:1188-1193.

(39.) Esteban A, Anzueto A, Alia I, Gordo F, Apezteguia C, Palizas F et al. How is mechanical ventilation employed in the intensive care unit? An international utilization review. Am J Respir Crit Care Med 2000; 161:1450-1458.

(40.) Esteban A, Anzueto A, Frutos F, Alia I, Brochard L, Stewart TE et al. Characteristics and outcomes in adult patients receiving mechanical ventilation: a 28-day international study. JAMA 2002; 287:345-355.

(41.) Younes M. Proportional assist ventilation, a new approach to ventilatory support. Theory. Am Rev Respir Dis 1992; 145:114-120.

(42.) Navalesi P, Costa R. New modes of mechanical ventilation: proportional assist ventilation, neurally adjusted ventilatory assist, and fractal ventilation. Curr Opin Crit Care 2003; 9:51-58.

(43.) Branson R. Understanding and implementing advances in ventilator capabilities. Cuff Opin Crit Care 2004; 10:23-32.

(44.) Giannouli E, Webster K, Roberts D, Younes M. Response of ventilator-dependent patients to different levels of pressure support and proportional assist. Am J Respir Crit Care Med 1999;159:1716-1725.

(45.) Passam F, Hoing S, Prinianakis G, Siafakas N, Milic-Emili J. Effect of different levels of pressure support and proportional assist ventilation on breathing pattern, work of breathing and gas exchange in mechanically ventilated hypercapnic COPD patients with acute respiratory failure. Respiration 2003; 70:355-361.

(46.) Ranieri V, Giuliani R, Mascia L, Grasso S, Petruzzelli V, Puntillo N et al. Patient-ventilator interaction during acute hypercapnia: pressure support vs proportional-assist ventilation. J Appl Physiol 1996; 81:426-436.

(47.) Grasso S, Puntillo F, Mascia L, Ancona G, Fiore T, Bruno F et al. Compensation for increase in respiratory workload during mechanical ventilation. Am J Respir Crit Care Med 2000; 161:819-826.

(48.) Du H, Ohtsuji M, Shigeta M, Chao D, Sasaki K, Usuda Y et al. Expiratory asynchrony in proportional assist ventilation. Am J Respir Crit Care Med 2002; 165:972-977.

(49.) Wysocki M, Meshaka P, Richard J, Similowski T. Proportional-assist ventilation compared with pressure-support ventilation during exercise in volunteers with external thoracic restriction. Crit Care Med 2004; 32:409-414.

(50.) MacIntyre N, Branson R. Mechanical ventilation. Philadelphia: Saunders; 2001.

(51.) MacIntyre NR. Evidence-based ventilator weaning and discontinuation. Respir Care 2004; 49:830-836.

(52.) National Health Service Modernisation Agency. Critical care programme: weaning and long term ventilation. Leicester: NHS Modernisation Agency; 2002.

(53.) Ely EW. Challenges encountered in changing physicians' practice styles: the ventilator weaning experience. Intensive Care Med 1998; 24:539-541.

(54.) Ely EW, Baker AM, Dunagan DP, Burke HL, Smith AC, Kelly PT et al. Effect on the duration of mechanical ventilation of identifying patients capable of breathing spontaneously. N Engl J Med 1996; 335:1864-1869.

(55.) Burns SM, Earven S, Fisher C, Lewis R, Merrell P, Schubart JR et al. Implementation of an institutional program to improve clinical and financial outcomes of mechanically ventilated patients: one-year outcomes and lessons learned. Crit Care Med 2003; 31:2752-2763.

(56.) Byrnes M, West S. Registered nurses' clinical reasoning abilities: a study of self perception. Aust J Adv Nurs 2000; 17:1823.

(57.) Kingston ME, Krumberger JM, Peruzzi WT Enhancing outcomes: guidelines, standards and protocols. AACN Clin Issues 2000; 11:363-374.

(58.) Paley G. A framework for clinical protocols. Nurs Stand 1995; 9:33-35.

(59.) Rothaar RC, Epstein SK Extubation failure: magnitude of the problem, impact on outcomes, and prevention. Curr Opin Crit Care 2003; 9:59-66.

L. Rose *, J. J. Presneill ([dagger]), J. E Cade ([dagger]) RMIT University Bundoora and The University of Melbourne and Intensive Care Unit, The Royal Melbourne Hospital, Melbourne; Victoria, Australia

* M.N., Adult Ed. Cert., B.N., ICU Cert., Dip.Nurs., Critical Care Course Coordinator, RMIT University and PhD candidate, The University of Melbourne, The Royal Melbourne Hospital.

([dagger]) M.B., B.S., Ph.D., Senior Physician, Intensive Care Unit, The Royal Melbourne Hospital.

([double dagger])M.D., Ph.D., Director, Intensive Care Unit, The Royal Melbourne Hospital.

Address for reprints: Ms L. Rose, Critical Care Course Coordinator, RMIT University, PO Box 71, Bundoora, vie. 3083.
TABLE 1
Upper and lower limits of main SmartCare/PS parameters in
patients > 35kg

Parameter Values

Spontaneous breathing
frequency:

Lower limit 15 bpm, for all patients

Upper limit 30 bpm, without neurological disorders
 34 bpm, with neurological disorders

Maximum limit 36 bpm, for all patients

Tidal volume:

Lower limit 250 ml, for body weight <_55 kg
 300 ml, for body weight >55 kg

[ETC0.sub.2]

Upper limit 55 mm g, without COPD
 65 mm g, with COPD

Pressure support target When ATC is deactivated

 5 cm [Hsub.2]O, if the patient is
 tracheostomised, with active
 humidifier
 7 cm [Hsub.2]O, if the patient is
 endotracheally intubated, with active
 humidifier
 9 cm [Hsub.2]O, if the patient is
 tracheostomised, with HME
 12 cm [Hsub.2]O, if the patient is
 endotracheally intubated with HME

 When ATC is activated

 0 cm [Hsub.2]O with active humidifier
 5 cm [Hsub.2]O with HME

Upper limit of pressure 40 cm [Hsub.2]O
support above PEEP

bpm: breaths per minute, [ETCo.sub.2]: end-tidal carbon dioxide,
COPD: chronic obstructive pulmonary disease, ATC: automatic
tube compensation, HME: heat moisture exchanger.

Table adapted from: SmartCare/PS Knowledge-based system for
automating clinical guidelines Supplement to Instructions for use
on EvitaXL from software version 6.n onwards (1st ed.). Dr5ger
Medical: Lubeck, Germany; 2004.

TABLE 2
SmartCare/PS diagnosis of patient ventilatory status

Limits breached

Diagnosis fspn VT
 (ml)

Normal ventilation 15-30 ([dagger]) >300 ([double dagger])

Hyperventilation <15 >300

Hypoventilation <15 >300

Acute tachypnoea >36 >300

Insufficient >15 >300
ventilation

Insufficient >15 <300
ventilation

Tachypnoea >30 >300

Central <15 <300
hypoventilation

Unexplained >30 >300
hyperventilation

Diagnosis [ETCO.sub.2] PS
 (mmHg)

Normal ventilation <55 ([section]) will be
 reduced **,
 weaning

Hyperventilation >55 will be
 reduced

Hypoventilation >55 increased

Acute tachypnoea [greater than or increased
 equal to]20 to
 <55

Insufficient >55 increased
ventilation

Insufficient <55 increased
ventilation

Tachypnoea [greater than or increased
 equal to]20 and
 <55

Central >55 no
hypoventilation change ([dagger][dagger])

Unexplained <20 no
hyperventilation mmHg change ([dagger][dagger])

spn: spontaneous breathing frequency, VT: tidal volume, [ETCO.sub.2]:
end-tidal carbon dioxide, PS: pressure support.

* in patients >55 kg without a diagnosis of neurological disorder
or COPD.

([dagger]) 34 bpm in patients with a neurological disorder.

([double dagger]) 250 ml for body weight <55 kg.

([section]) > 65 mmHg in patients with COPD.

** pressure support increment is 2 cm [H.sub.2]O except when a
diagnosis of hyperventilation or acute tachypnoea is made, then
pressure support increment is 4 cm [H.sub.2]O.

([dagger][dagger]) central hypoventilation and unexplained
hyperventilation indicate a respiratory status in which pressure
support ventilation may no longer be advisable. In this event
SmartCare/PS displays an alarm message to alert the clinician to
evaluate the patient's condition and discontinue the SmartCare/PS
session if necessary.

Table adapted from: SmartCare/PS Knowledge-based system for
automating clinical guidelines Supplement to Instructions for use
on EvitaXL from software version 6.n onwards (1st ed.). Dr5ger
Medical: Lubeck, Germany; 2004.
COPYRIGHT 2007 Australian Society of Anaesthetists
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Article Details
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Author:Rose, L.; Presneill, J.J.; Cade, J.F.
Publication:Anaesthesia and Intensive Care
Article Type:Clinical report
Geographic Code:8AUST
Date:Apr 1, 2007
Words:5553
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