Respiratory care takes a lesson from the airline industry in providing closed-loop technology to its smallest patients

Mechanical ventilation has come a long way since Vesalius first demonstrated it by blowing into a reed inserted into the trachea of an animal and watching the chest rise. Modern mechanical ventilation technology has become more advanced since the inception of the iron lung during the polio epidemic of the 1950s. Medicine, like every industry in the world, developed due to necessity.

Pediatric intensive care is no stranger to necessity. Care for the pediatric intensive care patient is delicate and complex. Because all pediatric patients are unique, they cannot all be put on the same mode. What works for one does not necessarily work for another, and standardized settings for this population are not feasible. Mechanical ventilation requires dynamic assessment, yet even though pediatric patients’ status can change from minute to minute, we often place them on one setting and make no adjustments until the next ventilator check or an alarm comes on. Ventilation for these patients needs vigilance, but with staffing shortages and limited resources, our ability to assess and modify care in a reliable and timely manner is compromised. Intensive care initiatives, such as the Right Care Right NowTM  of the Society of Critical Care Medicine (SCCM), are representative of the need to improve care delivery. Intelligent automated systems and safety “envelopes/checklists” have reduced error rates in aviation and are now being adopted in closed-loop ventilation systems.

Briefly, closed-loop ventilation is the control of one output variable of the mechanical ventilator based on the measurement of an input variable. An example is found in pressure support ventilation, in which flow (output) is constantly changing to maintain pressure (input) at a constant level throughout inspiration.

A Lesson From Industry
Closed-loop control has been adopted in various industries over the past 20-plus years. Many industries, such as airlines (autopilot) and chemical, power, and automotive companies (cruise control), have adopted closed-loop technology. Closed-loop control has had a great impact on our lives, and now we accept this as routine.

Health care providers are learning from the airline industry’s systems approach to error reduction, which is used to analyze and modify procedures. What the airlines (and other) industries have done to prevent accidents1 is now being applied to health care. Several institutions are utilizing these techniques to improve patient safety in the workplace. Health care is in an era of extreme growth that will put further stresses on limited resources. It is well established that, like airplane crashes, the majority of adverse events in health care are the result of human error, particularly failures in communication, leadership, and decision-making.1 

The health care industry is being affected by many change agents, including the Institute for Healthcare Improvement and the SCCM, whose Right Care Right Now initiative asks us to ensure that “the right care is delivered at exactly the right moment in time to achieve optimal patient outcomes.” Problems achieving improvements in health care are in part due to delays in assessment and intervention resulting from high acuity and staff shortages. Closed-loop control helps deliver care to patients by keeping them on a safe course of treatment and alerting clinicians when patients are off course. This intelligent control and monitoring allow ventilators to take care of routine tasks and enable the clinician to be “at the controls” of a more critical patient. This allows more efficient use of time and resources.

Closed-loop control has helped improve quality of life today yet, until recently, has had a modest effect on the health care industry. Now, health care is starting to see the benefits of closed-loop control, and it has been adopted in pharmacy, surgery, respiratory care, and anesthesia areas. Closed-loop control can achieve desirable system performance in the face of the highly uncertain and hostile environments of surgery and the intensive care unit. Benefits associated with closed-loop control are improved safety, reduced errors, and reduced cost of health care.

A Look at Ventilation
Clinicians need to look at mechanical ventilation as comprising three elements2 :
1. Ventilation—CO2 elimination to achieve desired arterial pH
2. Respiratory pump support—short- or long-term support of the respiratory muscles
3. Oxygenation—delivery of arterial blood to provide oxygen to tissues

Each of these areas is important to monitor and adjust to meet the patient’s needs. Closed-loop systems that can control ventilatory support are available today. Researchers are working on closed-loop control systems that address additional aspects of ventilatory support, such as oxygenation.

Closed-loop ventilation provides ventilatory support utilizing “feedback” from measured patient pulmonary mechanics and/or respiratory pattern. Closed-loop control can be based on the patient’s efforts or the patient’s respiratory mechanics (such as expiratory time constant and lung compliance), or the patient’s respiratory “comfort” (looking at spontaneous respiratory rate, tidal volume, and end-tidal CO2). The goal of closed-loop ventilation is to match the ventilator output to the needs of the patient.

Because closed-loop ventilation is centered on the patient, support can be increased or decreased in response to patient feedback in real time. Some closed-loop ventilation systems target optimizing the combination of respiratory rate and tidal volume, thereby selecting the respiratory pattern that minimizes the patient’s work of breathing (WOB) and applying the least stress to the lung. These systems base their algorithms on work done by Otis and Fenn (see Figure 1).

The controller looks at a pattern that is compatible with minimal WOB. This prevents excessive dead space ventilation, avoids inadvertent positive end-expiratory pressure (auto PEEP), and discourages rapid shallow breathing. These systems monitor respiratory drive and mechanics in real time. The level of ventilatory support and settings such as Vt, rate, and inspiratory time are adapted automatically in response to patient feedback. The closed-loop controller promotes better synchrony with the patient, causing fewer alarms, less sedation, and less time on the ventilator (see Figure 2).

Other closed-loop ventilation systems look at physiologic feedback, such as Paco2 (or pH) as a target. This method targets “normal” Paco2  (typically measured as end-tidal CO2/ETco2) and adjusts rate and tidal volume accordingly.4-7 Normal Paco2  can be interpreted differently by various clinicians. A normal Paco2 might not be desired in severe cases of acute respiratory distress syndrome (ARDS). Permissive hypercapnia in severe ARDS might require targeting abnormal Paco28 levels. In addition, ETco2 might not reliably correlate with pH or arterial Paco2  with changes in dead space and/or V/Q mismatch, which are commonly seen in patients requiring ventilatory support.9,10 To address some of these issues, the user can, in some of these systems, input CO2 targets or select from preprogrammed disease categories to individualize targets to patient pathology. Direct measurement of arterial Paco2  currently is available only invasively and has not gained widespread acceptance.

Neurally Adjusted Ventilatory Assist
Neurally adjusted ventilatory assist (NAVA) is a new approach to mechanical ventilation based on neural respiratory output.11,12 The act of breathing depends on the rhythmic electrical discharge from the respiratory center of the brain.13,14 This discharge travels along the phrenic nerve and excites the diaphragm muscle cells, leading to muscle contraction and descent of the diaphragm. As a result, the pressure in the airway drops, causing an inflow of air into the lungs.15

NAVA uses the signal from the respiratory center and communicates with the ventilator to assist the patient’s breath.16 Since the diaphragm and ventilator use the same signal, patient synchrony is achieved. Cycling off the ventilator breath is also determined by neural excitation for expiration. Also, NAVA uses the electrical impulses to determine the amount of support required by the patient.17-19 This system utilizes a special catheter, which is placed into the esophagus to enhance triggering and synchrony. This system does not provide controlled ventilatory support.

Knowledge-based closed-loop control systems also have been developed. This type of system “attempts to capture the experience of human experts”20 and aims to keep alveolar ventilation in an acceptable range by adjusting the levels of pressure support to maintain respiratory rate, tidal volume, and end-tidal CO2 in certain ranges. These ranges are based on an expert set of rules. This type of closed-loop control system is utilized for weaning purposes only and has been shown to enhance the efficiency of the weaning process.

Another approach to ventilation is the servo control, which was developed during World War II for military application. Its application in health care makes it possible for the ventilator tomodify its output based on feedback from the patient.20 This is known as proportional assist ventilation. The ventilator monitors patient flow and volume demands and adjusts ventilatory support to maintain clinician-desired proportion of ventilatory support. As demand increases, support increases to decrease work of breathing. Like the knowledge–based and NAVA control systems, only spontaneous breathing is supported.

Closed-Loop for Kids
Closed-loop control in pediatrics has several distinct advantages. In pediatrics, less sedation and fewer paralytics are used. Because of this, patient-ventilator synchrony is vital. The ability for the ventilator to adjust to the constantly changing status of pediatric patients is critical. The desired effects of an ideal closed-loop control ventilator include:
• the ability to provide full controlled support
•  auto-weaning
• maintaining adequate tidal volume
• ensuring adequate minute ventilation
• titration of Fio2
• patient synchrony
• the ability to adapt settings for both mandatory and spontaneous breaths with changes in respiratory drive and pulmonary mechanics

These benefits can be translated to other patient groups as well. Decreased ventilator days, decreased sedation, and decreased total hospital stay can benefit both the adult and neonatal population. Hospitals are looking for ways to maximize productivity while limiting costs.

Future closed-loop control systems will incorporate other aspects of mechanical ventilation. These will include Fio2 and PEEP. Closed-loop Fio2 systems are being developed to control oxygen and air delivery in order to regulate arterial oxygen saturation and protect the patient from hypoxemia while minimizing the use of oxygen.12,13 This control is very important not only in the pediatric population, but also in the neonatal population. Oxygen toxicity, micro-atelectasis, and retinopathy of prematurity are just a few of many concerns regarding high levels of oxygen in the neonatal population. This is where providing the least amount of oxygen is vital.

Respiratory care is entering an exciting era for mechanical ventilation. Advances in computer technology have helped manufacturers bridge the gap between man and machine. The days of Star Trek are getting closer as advances in medicine are made every day. These advances only benefit our patients. Only time will tell what benefits await our patients in the future.

Justin Tse, RRT-NPS, is clinical implementation specialist, Hamilton Medical Inc, Reno, Nev. For more information, contact [email protected]

1. Murphy K. What pilots can teach hospitals about patient dafety. New York Times. Available at: Accessed October 31, 2006.

2. Slutsky AS. Consensus conference on mechanical ventilation, January 28-30, 1993 at Northbrook, Illinois, USA, Intensive Care Med. 1994; 20:64-79.

3. Otis AB, Fenn WHO. Mechanic of breathing in man. J Appl Physiol. 1950; 2:592-607

4. Coon RL, Zuperku Ej, Kampine JP. Systemic arterial blood pH servocontrol of mechanical ventilation. Anesthesiology. 1978; 49: 201-4.

5. Coon RL, Zuperku Ej, Kampine JP. Systemic arterial pH servocontrolled ventilator simulation of the respiratory control system. Respir Physiol. 1984; 8:345-50.

6. East TD, Westenskow DR, Pace NL, et al: A microcomputer based differential lung ventilation system. IEEE Trans Biomed Eng. 1982; 29:736-40.

7. Schulz V, Ulmer HV, Erdmann W, et al. A system of continuously PaCO2-controlled ventilation [transl]. Pneumonologie. 1974; 150: 319-25.

8. Hickling KG, Henderson SJ, Jackson R. Low mortality associated with low volume pressure limited ventilation with permissive hypercapnia in severe adult respiratory distress syndrome. Intensive Care Med. 1990; 16:372-7.

9. Frumin JM. Clinical use of a physiological respirator producing N2O amnesia analgesia. Anesthesiology 1957; 18:290-9.

10. Lindahl SG, Yates AP, Hatch DJ. Relationship between invasive and noninvasive measurements of gas exchange in anesthetized infants and children. Anesthesiology. 1987; 66:168-75.

11. Sinderby C. Neurally adjusted ventilatory Assist (NAVA). Minerva. Anestesiol. 2002; 86:378-80.

12. Sinderby C. Ventilatory assist driven by patient demand. Am J Respir Crit Care Me. 2003; 168:729-30.

13. Sinderby C, Navalesi P, Beck J, et al. Neural control of mechanical ventilation in respiratory failure. Nature Medicine. 1999; 5:1433-6.

14. Beck J, Gottfried SB, Navalesi P, et al. Electrical activity of the diaphragm during pressure support ventilation in acute respiratory failure. Am J Respir Crit Care Med. 2001; 164: 419-24.

15. Aldrich T, Sinderby C, McKenzie D, Estenne M, Gandevia S. Electrophysiologic techniques for the assessment of respiratory muscle function. In: ATS/ERS Statement on Respiratory Muscle Testing. Am J Respir Cri. Care Med. 2002; 166:518-624.

16. Spahija J, Beck J, DeMarchie M, Comtois A, Sinderby C. Closed-loop control of respiratory drive using pressure support ventilation: target drive ventilation. Am J Respir Crit Care Med. 2005; 171: 1009-14.

17. Beck J, Tucci M, Emeriaud G, Lacroix J, Sinderby C. Prolonged neural expiratory time induced by mechanical ventilation in infants. Pediatr Res. 2004; 55:747-54.

18. Beck J, Weinberg J, Hamnegård C-H, et al. Diaphragm function in advanced Duchenne muscular dystrophy. Neuromuscul Disord. 2006; 16(3):161-7.

19. Emeriaud G, Beck J, Tucci M, Lacroix J, Sinderby C. Diaphragm electrical activity during expiration in mechanically ventilated infants. Pediatr Res 2006; 59:705-10.

20. Chatburn, R. Computer Control of Mechanical Ventilation. Respir Care. 2004; 49:507-17.

21. Ritchie G, Jannett TC. Closed-loop control of oxygen delivery during aeromedical evacuation of patients. Proc IEEE. 1992; 2:763-767

22. Tehrani F, Rogers M, Lo T, et al. Closed-loop control of the inspired fraction of oxygen in mechanical ventilation. J Clin Monit Comput. 2002; 17:367-76.