Closed-loop ventilation: an emerging standard of care?

Computer clinical decision support that automates personalized clinical care: a challenging but needed healthcare delivery strategy

How to deliver best care in various clinical settings remains a vexing problem. All pertinent healthcare-related questions have not, cannot, and will not be addressable with costly time- and resource-consuming controlled clinical trials. At present, evidence-based guidelines can address only a small fraction of the types of care that clinicians deliver. Furthermore, underserved areas rarely can access state-of-the-art evidence-based guidelines in real-time, and often lack the wherewithal to implement advanced guidelines. Care providers in such settings frequently do not have sufficient training to undertake advanced guideline implementation. Nevertheless, in advanced modern healthcare delivery environments, use of eActions (validated clinical decision support systems) could help overcome the cognitive limitations of overburdened clinicians. Widespread use of eActions will require surmounting current healthcare technical and cultural barriers and installing clinical evidence/data curation systems. The authors expect that increased numbers of evidence-based guidelines will result from future comparative effectiveness clinical research carried out during routine healthcare delivery within learning healthcare systems.

Supervisory Algorithm for Autonomous Hemodynamic Management Systems

Future military conflicts will require new solutions to manage combat casualties. The use of automated medical systems can potentially address this need by streamlining and augmenting the delivery of medical care in both emergency and combat trauma environments. However, in many situations, these systems may need to operate in conjunction with other autonomous and semi-autonomous devices. Management of complex patients may require multiple automated systems operating simultaneously and potentially competing with each other. Supervisory controllers capable of harmonizing multiple closed-loop systems are thus essential before multiple automated medical systems can be deployed in managing complex medical situations. The objective for this study was to develop a Supervisory Algorithm for Casualty Management (SACM) that manages decisions and interplay between two automated systems designed for management of hemorrhage control and resuscitation: an automatic extremity tourniquet system and an adaptive resuscitation controller. SACM monitors the required physiological inputs for both systems and synchronizes each respective system as needed. We present a series of trauma experiments carried out in a physiologically relevant benchtop circulatory system in which SACM must recognize extremity or internal hemorrhage, activate the corresponding algorithm to apply a tourniquet, and then resuscitate back to the target pressure setpoint. SACM continues monitoring after the initial stabilization so that additional medical changes can be quickly identified and addressed, essential to extending automation algorithms past initial trauma resuscitation into extended monitoring. Overall, SACM is an important step in transitioning automated medical systems into emergency and combat trauma situations. Future work will address further interplay between these systems and integrate additional medical systems.

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

PURPOSE OF REVIEW

Neurocritical care combines the complexity of both medical and surgical disease states with the inherent limitations of assessing patients with neurologic injury. Artificial intelligence (AI) has garnered interest in the basic management of these complicated patients as data collection becomes increasingly automated.

RECENT FINDINGS

In this opinion article, we highlight the potential AI has in aiding the clinician in several aspects of neurocritical care, particularly in monitoring and managing intracranial pressure, seizures, hemodynamics, and ventilation. The model-based method and data-driven method are currently the two major AI methods for analyzing critical care data. Both are able to analyze the vast quantities of patient data that are accumulated in the neurocritical care unit. AI has the potential to reduce healthcare costs, minimize delays in patient management, and reduce medical errors. However, these systems are an aid to, not a replacement for, the clinician's judgment.

Artificial intelligence in neurocritical care

BACKGROUND

Neurocritical care combines the management of extremely complex disease states with the inherent limitations of clinically assessing patients with brain injury. As the management of neurocritical care patients can be immensely complicated, the automation of data-collection and basic management by artificial intelligence systems have garnered interest.

METHODS

In this opinion article, we highlight the potential artificial intelligence has in monitoring and managing several aspects of neurocritical care, specifically intracranial pressure, seizure monitoring, blood pressure, and ventilation.

RESULTS

The two major AI methods of analytical technique currently exist for analyzing critical care data: the model-based method and data driven method. Both of these methods have demonstrated an ability to analyze vast quantities of patient data, and we highlight the ways in which these modalities of artificial intelligence might one day play a role in neurocritical care.

CONCLUSIONS

While none of these artificial intelligence systems are meant to replace the clinician's judgment, these systems have the potential to reduce healthcare costs and errors or delays in medical management.

Portable mechanical ventilation with closed-loop control of inspired fraction of oxygen maintains oxygenation in the setting of hemorrhage and lung injury

BACKGROUND

Closed-loop controllers (CLCs) embedded within portable mechanical ventilators may allow for autonomous weaning. The ability of CLCs to maintain adequate oxygenation in the setting of hemorrhage and lung injury is unknown. We hypothesized that a portable ventilator with a CLC for inspired fraction of oxygen (FIO2) could provide oxygenation in a porcine model of hemorrhage and lung injury.

METHODS

Female pigs randomized to the study group (n = 6) underwent a pressure-controlled bleed (mean arterial pressure = 40 mm Hg for 30 minutes). Acute lung injury was induced by saline lung lavage followed by intentional infliction of barotrauma. Sham pigs (n = 6) underwent placement of monitoring devices without hemorrhage or lung injury. All pigs were then placed on a portable ventilator modified with a CLC algorithm, which uses feedback from pulse oximetry (SpO2) and FIO2 trends to adjust FIO2 and maintain a target SpO2 of 94% (2%). The initial FIO2 was set at 0.60. Tidal volume, positive end-expiratory pressure, rate, and inspiratory-to-expiratory ratio were constant unless changes were required clinically.

RESULTS

Study pigs had lower mean arterial pressures than shams at all time points except baseline. PaO2/FIO2 ratios were less than 300 and significantly lower than both baseline values and corresponding sham values at all time points. The CLC weaned the FIO2 at a reduced rate in study pigs relative to shams with a final mean FIO2 of 0.54 and 0.29 in study and sham pigs, respectively (p < 0.05). There was a significant divergence in the study and sham FIO2 curves but no significant difference in oxygen saturation or hypoxemia.

CONCLUSION

Adequate oxygenation can be maintained in the setting of hemorrhage and lung injury using a portable ventilator embedded with a CLC of FIO2 based on pulse oximetry. These devices may be valuable for providing advanced medical care in resource-limited environments.

Adaptive support ventilation: State of the art review

Mechanical ventilation is one of the most commonly applied interventions in intensive care units. Despite its life-saving role, it can be a risky procedure for the patient if not applied appropriately. To decrease risks, new ventilator modes continue to be developed in an attempt to improve patient outcomes. Advances in ventilator modes include closed-loop systems that facilitate ventilator manipulation of variables based on measured respiratory parameters. Adaptive support ventilation (ASV) is a positive pressure mode of mechanical ventilation that is closed-loop controlled, and automatically adjust based on the patient's requirements. In order to deliver safe and appropriate patient care, clinicians need to achieve a thorough understanding of this mode, including its effects on underlying respiratory mechanics. This article will discuss ASV while emphasizing appropriate ventilator settings, their advantages and disadvantages, their particular effects on oxygenation and ventilation, and the monitoring priorities for clinicians.

Closed loop mechanical ventilation

Mechanical ventilation is a sophisticated technique with very narrow therapeutic ranges i.e. highly efficient and able to keep alive the most severe patients, but with considerable side effects and unwanted complications if not properly and timely used. Computerized protocols, closed loop systems, decision support, all terms which need to be defined, may help making mechanical ventilation safer and more efficient. The present paper will provide a short overview on technical and engineering considerations regarding closed loop controlled ventilation as well as tangible clinical evidences supporting the previous statement.

Safety and efficacy of a fully closed-loop control ventilation (IntelliVent-ASV®) in sedated ICU patients with acute respiratory failure: a prospective randomized crossover study

PURPOSE

IntelliVent-ASV(®) is a development of adaptive support ventilation (ASV) that automatically adjusts ventilation and oxygenation parameters. This study assessed the safety and efficacy of IntelliVent-ASV(®) in sedated intensive care unit (ICU) patients with acute respiratory failure.

METHODS

This prospective randomized crossover comparative study was conducted in a 12-bed ICU in a general hospital. Two periods of 2 h of ventilation in randomly applied ASV or IntelliVent-ASV(®) were compared in 50 sedated, passively ventilated patients. Tidal volume (V(T)), respiratory rate (RR), inspiratory pressure (P(INSP)), SpO(2) and E(T)CO(2) were continuously monitored and recorded breath by breath. Mean values over the 2-h period were calculated. Respiratory mechanics, plateau pressure (P(PLAT)) and blood gas exchanges were measured at the end of each period.

RESULTS

There was no safety issue requiring premature interruption of IntelliVent-ASV(®). Minute ventilation (MV) and V(T) decreased from 7.6 (6.5-9.5) to 6.8 (6.0-8.0) L/min (p < 0.001) and from 8.3 (7.8-9.0) to 8.1 (7.7-8.6) mL/kg PBW (p = 0.003) during IntelliVent-ASV(®) as compared to ASV. P(PLAT) and FiO(2) decreased from 24 (20-29) to 20 (19-25) cmH(2)O (p = 0.005) and from 40 (30-50) to 30 (30-39) % (p < 0.001) during IntelliVent-ASV(®) as compared to ASV. RR, P(INSP), and PEEP decreased as well during IntelliVent-ASV(®) as compared to ASV. Respiratory mechanics, pH, PaO(2) and PaO(2)/FiO(2) ratio were not different but PaCO(2) was slightly higher during IntelliVent-ASV(®) as compared to ASV.

CONCLUSIONS

In passive patients with acute respiratory failure, IntelliVent-ASV(®) was safe and able to ventilate patients with less pressure, volume and FiO(2) while producing the same results in terms of oxygenation.

Development and implementation of explicit computerized protocols for mechanical ventilation in children

Mechanical ventilation can be perceived as a treatment with a very narrow therapeutic window, i.e., highly efficient but with considerable side effects if not used properly and in a timely manner. Protocols and guidelines have been designed to make mechanical ventilation safer and protective for the lung. However, variable effects and low compliance with use of written protocols have been reported repeatedly. Use of explicit computerized protocols for mechanical ventilation might very soon become a "must." Several closed loop systems are already on the market, and preliminary studies are showing promising results in providing patients with good quality ventilation and eventually weaning them faster from the ventilator. The present paper defines explicit computerized protocols for mechanical ventilation, describes how these protocols are designed, and reports the ones that are available on the market for children.

Evaluation of a novel closed-loop fluid-administration system based on dynamic predictors of fluid responsiveness: an in silico simulation study

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.

Mechanical ventilation in trauma

PURPOSE OF REVIEW

The purpose of this review is to evaluate new concepts in mechanical ventilation in trauma. We begin with the keystone of physiology prior to embarking on a discussion of several new modes of mechanical ventilation. We will discuss the use of noninvasive ventilation as a mode to prevent intubation and then go on to airway pressure release ventilation, high-frequency oscillatory ventilation, and computer-based, closed loop ventilation.

RECENT FINDINGS

The importance of preventing further injury in mechanical ventilation lies at the heart of the introduction of several new strategies of mechanical ventilation. New modes of ventilation have been developed to provide lung recruitment and alveolar stabilization at the lowest possible pressure.

SUMMARY

The old modes of continuous positive airway pressure and bilevel positive airway pressure have been actively introduced in clinical practice in the case of trauma patients. Used with proper pain management protocols, there has been a decrease in the incidence of intubation in blunt thoracic trauma. Airway pressure release ventilation has been gaining a role in the management of thoracic injury and may lead to less incidence of physiologic trauma to mechanically ventilated patients. High-frequency oscillatory ventilation has been shown to be effective in patient care by its ability to open and recruit the lung in trauma patients and in those with acute respiratory distress syndrome but it may not have a role in patients with inhalational injury. Closed loop ventilation is a technology that may better control major pulmonary parameters and lead to more rapid titration from the ventilator to spontaneous breathing.

Adaptive support ventilation versus conventional ventilation for total ventilatory support in acute respiratory failure

OBJECTIVE

To compare the short-term effects of adaptive support ventilation (ASV), an advanced closed-loop mode, with conventional volume or pressure-control ventilation in patients passively ventilated for acute respiratory failure.

DESIGN

Prospective crossover interventional multicenter trial.

SETTING

Six European academic intensive care units.

PATIENTS

Eighty-eight patients in three groups: patients with no obvious lung disease (n = 22), restrictive lung disease (n = 36) or obstructive lung disease (n = 30).

INTERVENTIONS

After measurements on conventional ventilation (CV) as set by the patients' clinicians, each patient was switched to ASV set to obtain the same minute ventilation as during CV (isoMV condition). If this resulted in a change in PaCO(2), the minute ventilation setting of ASV was readjusted to achieve the same PaCO(2) as in CV (isoCO(2) condition).

MEASUREMENTS AND RESULTS

Compared with CV, PaCO(2) during ASV in isoMV condition and minute ventilation during ASV in isoCO(2) condition were slightly lower, with lower inspiratory work/minute performed by the ventilator (p < 0.01). Oxygenation and hemodynamics were unchanged. During ASV, respiratory rate was slightly lower and tidal volume (Vt) slightly greater (p < 0.01), especially in obstructed patients. During ASV there were different ventilatory patterns in the three groups, with lower Vt in patients with restrictive disease and prolonged expiratory time in obstructed patients, thus mimicking the clinicians' choices for setting CV. In three chronic obstructive pulmonary disease patients the resulting Vt was unacceptably high.

CONCLUSIONS

Comparison between ASV and CV resulted either in similarities or in minor differences. Except for excessive Vt in a few obstructed patients, all differences were in favor of ASV.

Lung protective ventilation strategies in paediatrics-A review

Ventilator Associated Lung Injury (VALI) is an iatrogenic phenomena that significantly impacts on the morbidity and mortality of critically ill patients. The hazards associated with mechanical ventilation are becoming increasingly understood courtesy of a large body of research. Barotrauma, volutrauma and biotrauma all play a role in VALI. Concomitant to this growth in understanding is the development of strategies to reduce the deleterious impact of mechanical ventilation. The majority of the research is based upon adult populations but with careful extrapolation this review will focus on paediatrics. This review article describes the physiological basis of VALI and discusses the various lung protective strategies that clinicians can employ to minimise its incidence and optimise outcomes for paediatric patients.

Advanced closed loops during mechanical ventilation (PAV, NAVA, ASV, SmartCare)

New modes of mechanical ventilation with advanced closed loops are now available, and in the future these could assume a greater role in supporting critically ill patients in intensive care units (ICUs) for several reasons. Two modes of ventilation--proportional assist ventilation and neurally adjusted ventilatory assist--deliver assisted ventilation proportional to the patient's effort, improving patient-ventilator synchrony. Also, a few systems that automate the medical reasoning with advanced closed-loops, such as SmartCare and adaptive support ventilation, have the potential to improve knowledge transfer by continuously implementing automated protocols. Moreover, they may improve patient-ventilator interactions and outcomes, and provide a partial solution to the forecast clinician shortages by reducing ICU-related costs, time spent on mechanical ventilation, and staff workload. Preliminary studies are promising, and initial systems are currently being refined with increasing clinical experience. A new era of mechanical ventilation should emerge with these systems.

Automatic versus manual pressure support reduction in the weaning of post-operative patients: a randomised controlled trial

Introduction

Reduction of automatic pressure support based on a target respiratory frequency or mandatory rate ventilation (MRV) is available in the Taema-Horus ventilator for the weaning process in the intensive care unit (ICU) setting. We hypothesised that MRV is as effective as manual weaning in post-operative ICU patients.

Methods

There were 106 patients selected in the post-operative period in a prospective, randomised, controlled protocol. When the patients arrived at the ICU after surgery, they were randomly assigned to either: traditional weaning, consisting of the manual reduction of pressure support every 30 minutes, keeping the respiratory rate/tidal volume (RR/TV) below 80 L until 5 to 7 cmH₂O of pressure support ventilation (PSV); or automatic weaning, referring to MRV set with a respiratory frequency target of 15 breaths per minute (the ventilator automatically decreased the PSV level by 1 cmH₂O every four respiratory cycles, if the patient's RR was less than 15 per minute). The primary endpoint of the study was the duration of the weaning process. Secondary endpoints were levels of pressure support, RR, TV (mL), RR/TV, positive end expiratory pressure levels, FiO₂ and SpO₂ required during the weaning process, the need for reintubation and the need for non-invasive ventilation in the 48 hours after extubation.

Results

In the intention to treat analysis there were no statistically significant differences between the 53 patients selected for each group regarding gender (p = 0.541), age (p = 0.585) and type of surgery (p = 0.172). Nineteen patients presented complications during the trial (4 in the PSV manual group and 15 in the MRV automatic group, p < 0.05). Nine patients in the automatic group did not adapt to the MRV mode. The mean ± sd (standard deviation) duration of the weaning process was 221 ± 192 for the manual group, and 271 ± 369 minutes for the automatic group (p = 0.375). PSV levels were significantly higher in MRV compared with that of the PSV manual reduction (p < 0.05). Reintubation was not required in either group. Non-invasive ventilation was necessary for two patients, in the manual group after cardiac surgery (p = 0.51).

Conclusions

The duration of the automatic reduction of pressure support was similar to the manual one in the post-operative period in the ICU, but presented more complications, especially no adaptation to the MRV algorithm.

Trial Registration

Trial registration number: ISRCTN37456640