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(Chest. 2006;130:350-361.)
© 2006 American College of Chest Physicians

Bench Model To Simulate Upper Airway Obstruction for Analyzing Automatic Continuous Positive Airway Pressure Devices*

Jordi Rigau, PhD; Josep M. Montserrat, MD; Holger Wöhrle, MD; Diana Plattner, MS; Matthias Schwaibold, MS; Daniel Navajas, PhD and Ramon Farré, PhD

* From Science and Research (Dr. Rigau, Ms. Plattner, and Mr. Schwaibold), Measure, Check & Control GmbH & Co. KG, Karlsruhe, Germany; Pneumologia, Hospital Clínic (Dr. Montserrat) and Unitat de Biofísica i Bioenginyeria, Facultat de Medicina (Drs. Navajas and Farré), Universitat de Barcelona, Institut d’Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain; and Department of Internal Medicine II (Dr. Wöhrle), University Hospital, Ulm, Germany.

Correspondence to: Ramon Farré, PhD, Unitat de Biofísica i Bioenginyeria, Facultat de Medicina, Universitat de Barcelona, Barcelona, Spain; e-mail: rfarre{at}ub.edu

Abstract

Background: Automatic positive airway pressure (APAP) devices are increasingly being used in patients with obstructive sleep apnea. Some APAP devices present an unstable behavior when subjected to some events or artifacts. The aims were to develop a bench model capable of reproducing real flow, snoring, and obstructive patterns and to compare the response of APAP devices based on flow and snoring with other devices using, in addition, the forced oscillation technique (FOT).

Methods: The bench model subjected APAP devices to apneas with and without obstruction, obstructive hypopneas with and without snoring, periods of flow limitation, and artifacts such as leaks and mouth expiration.

Results: Almost all the devices increased the pressure when subjected to apneas with obstruction, but at different rates. The time required by each device to reach 10 cm H2O ranged from 2.5 to 13 min. In the presence of apneas without obstruction, all the devices based on flow and snoring increased the pressure at the same rate as during apneas with obstruction. However, the devices using FOT did not modify the pressure. Four devices did not modify the pressure in the presence of obstructive hypopneas, and all but one device increased the pressure in the presence of snoring. Mask leaks had little effect on the response of the devices, but four devices increased the pressure during mouth expiration artifacts.

Conclusions: When, in addition to the flow and snoring signals, the measurement of the upper airway resistance is included, the accuracy of the event detection algorithms is improved.

Key Words: automatic positive airway pressure • bench testing • continuous positive airway pressure • forced oscillation technique • sleep apnea syndrome • upper airway obstruction

Continuous positive airway pressure (CPAP) is conventionally used for the treatment of patients with obstructive sleep apnea syndrome (OSAS).1 The optimal pressure required for treatment is determined during polysomnography by progressively increasing the pressure until all the respiratory events are eliminated. This treatment modality has proved to be effective in most patients with compliance rates at approximately 75%.2345 Noncompliance is usually attributed to an absence of benefits and side effects such as rhinitis and leaks,56789 associated in part with excessive mask pressures.1011

The automatic positive airway pressure (APAP) devices currently available on the market are aimed at improving compliance and diminishing the side effects during treatment. These devices reduce the mean pressure during the night by automatically adjusting the applied pressure according to the changing requirements of the patient.91012131415 Although there is no clear evidence that favors treatment with APAP with respect to fixed CPAP in unselected OSAS patients,12 a number of studies1617181920 have suggested that APAP devices could be suitable for treating a subgroup of patients with different pressure demands during sleep depending on body posture, on sleep stage, or on night-to-night variability. Moreover, these devices could also be a useful tool to automatically determine the optimal pressure level, both in attended and unattended settings19202122232425 and, hence, to avoid a costly CPAP titration study and reduce hospital waiting lists.

However, the APAP devices present relevant differences. Some of them are not able to appropriately handle some breathing patterns and may show an unstable behavior such as transient pressure increases when applied to patients. These instabilities are probably related to an incorrect identification of events and/or artifacts (such as leaks or mouth expiration). Specifically, some devices are not able to correctly identify central and obstructive apneas.2627 One reason for these shortcomings could be that most of the commercial APAP devices base their detection algorithms only on the analysis of the flow and/or snoring signals. These devices can easily identify apneas when no flow is detected. However, they are not able to differentiate apneas with upper airway closure (either with an obstructive or central etiology) from central apneas without airway obstruction, since they can only use one variable (flow) for detecting these events. Consequently, these devices usually increase the applied pressure regardless of the central or obstructive nature of the apnea, which may demand different pressure levels.

To improve APAP, new devices have been developed for a better detection of the phenomena that occur in the upper airway.2829 To this end, some APAP devices include, in addition to the analysis of the flow and snoring signal, technology such as the forced oscillation technique (FOT) for identifying upper airway obstructions that may increase the robustness and accuracy of the detection algorithms.3031 The FOT is based on superimposing an oscillatory pressure onto the spontaneous breathing of the patient. The quotient between the oscillatory pressure and the associated oscillatory flow measured at the entrance of the respiratory system provides an overall measure of total respiratory impedance, which, when applied to patients with OSAS, is assumed to reflect upper airway patency.3132

We previously developed a bench model to test the performance of several APAP devices in the presence of different breathing patterns.33 However, given that our first model was not able to simulate upper airway patency, it was not suitable for testing the new generation of APAP devices that include technology to evaluate upper airway resistance. Therefore, the aim of this study was to develop a bench model that, in addition to reproducing different flow patterns, is able to simulate upper airway obstructions. To evaluate its efficacy, the response of several APAP devices including FOT was evaluated when subjected to respiratory events with and without obstruction and/or snoring. Moreover, the behavior of APAP devices in the presence of some artifacts such as leaks and mouth expiration was also analyzed. Their pressure response was compared to that of conventional APAP devices based only on the flow signal.

Materials and Methods

Patient Simulator
We modified the patient simulator model previously described33 by including an obstructive valve servocontrolled by a motor (HS-325BB; Hitec RCD; Powey, CA). This new model was able to reproduce not only real flow and snoring signals obtained from patients’ recordings, but also the corresponding resistance of the upper airway (Fig 1 ). A driving signal generated by the computer was fed into the analog servocontrol of the motor, which regulated the aperture of the valve. The obstructive valve was able to modify the airway caliber according to obstructive patterns similar to the patterns previously recorded in patients by means of the FOT applied simultaneously to CPAP during titration studies.34 The simulator included a flow generator33 that was synchronized with the obstructive valve for reproducing increases in airway resistance during periods of obstructive apneas or hypopneas (ie, upper airway obstruction could be modified within the respiratory cycle). Thus, different degrees of airway obstruction could be reproduced during apneas, hypopneas, or periods of flow limitation. Moreover, to assess the capability of the APAP devices in detecting typical artifacts such as mouth expiration, a second breathing circuit, in parallel to the main circuit, allowed us to simulate the mouth-breathing route. An additional exhalation valve in this second breathing circuit was electronically controlled and synchronized with the flow generator and the obstructive valve. During mouth expiration, the exhalation valve was opened allowing the expired air to flow through the simulated mouth route while the obstructive valve was closed. A leak valve was used for simulating leaks through the mask usually found during conventional CPAP treatment in patients.


Figure 1
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  		Figure 1.. Diagram of the patient simulator. PNT = pneumotachograph; EP = exhalation port; Obstr = obstructive; Exhal = exhalation; V’ = flow; M = motor; P = pressure (modified from Rigau et al34).

 
Patterns of Disturbed Breathing
Two different sets of flow patterns were used for evaluating the APAP devices. The first set consisted of six different flow events based on the concatenation of identical breathing cycles previously recorded in patients. Five of these events were previously described.33 For each flow pattern, the obstructive valve generated a specific pattern of airway obstruction with the appropriate magnitude and duration for simultaneously mimicking the obstructive phenomena and the flow shapes observed in typical OSAS respiratory events. The flow and obstructive patterns were combined for generating seven different breathing patterns shown in Figure 2 . During normal breathing with a breathing frequency of 16 breaths/min, the obstructive valve was completely open showing low values of airway resistance (Fig 2, panel A). Two different types of apnea with exactly the same flow shape were reproduced. Panel B in Figure 2 shows an apnea with obstruction in which high resistance values (approximately 75 cm H2O·s/L) were reproduced during the period without breathing flow. Another apnea without obstruction, as indicated by normal low values in the resistance signal during the absence of breathing flow, is shown in panel C (Fig 2). Panel D shows a pattern of mild obstructive hypopnea with transient increases in airway resistance (approximately 20 cm H2O·s/L) only during the inspiratory portion of the flow-limited breathing cycles (corresponds to hypopnea with a U-shaped inspiratory flow contour and a tidal volume equal to 70% of the normal cycle, in our previous work33 with a flow limitation index21 of 0.12). The same flow and obstructive pattern, but with the addition of snoring vibrations synchronized with the inspirations, is shown in panel E (Fig 2). Panel F shows a prolonged period of flow limitation (based on hypopnea with a square-like inspiratory flow contour and a tidal volume equal to 70% of the normal cycle, from our previous study33 with flow limitation index of 0.01) with mild transient increases in resistance (approximately 15 cm H2O·s/L) during inspirations. Finally, a pattern of mouth expiration characterized by an absence of expiratory flow with a simultaneous increase in airway resistance during expiration is shown in panel G (Fig 2).


Figure 2
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  		Figure 2.. Breathing patterns recorded at the nasal side of the bench model during tests 1 to 7 (panel A through panel G). Flow is given as liters per second, and resistance is given as centimeters of water per liter per second.

 
A second set of five breathing patterns was used to simulate the behavior of a real patient when subjected to treatment with an APAP device (Fig 3 ). These breathing patterns (based on previously described flow patterns33) were complete events recorded in patients. Therefore, they reflect the within cycle variability found in real events (the flow amplitude and shape progressively changed along the event). Panel A in Figure 3 shows the same normal breathing pattern as panel A in Figure 2. A prolonged period of flow limitation and a mild hypopnea with transient mild increases in resistance during inspirations are shown in panels B and C, respectively. Panel D shows a severe hypopnea with a progressive reduction in tidal volume accompanied by progressive transient increases in resistance during inspirations. Finally, panel E shows an apnea with obstruction (approximately 70 cm H2O·s/L). Neither of these breathing patterns included snoring.


Figure 3
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  		Figure 3.. Breathing patterns reproduced by the simulated OSAS patient during test 8 depending on the CPAP level applied by APAP devices (panel A through panel E). Flow is given as liters per second, and resistance is given as centimeters of water per liter per second.

 
APAP Devices Evaluated
Single units of 10 different APAP devices currently available on the market were evaluated with this bench test. The only criterion used when selecting the devices was their availability. Seven of these devices based their detection algorithms on the analysis of the flow shape and the high frequency vibrations produced in the airways during snoring: PV10i (Breas AB; Mölnlycke Sweden); Autoset Spirit (Resmed; North Ryde, NSW, Australia); REMstar auto (Respironics; Murrysville, PA); Delphinus (Jaeger Tonnies/Viasys Healthcare; Höchberg, Germany); Magellan (MAP; Munich, Germany); Goodknight 420E (Puritan Bennett/Tyco Healthcare; Pleasanton, CA); and Horizon LT plus (DeVilbiss/Sunrise Medical; Carlsbad, CA). These seven devices were designated as F1, F2, F3, F4, F5, F6, and F7. The three other devices, in addition to the analysis of the flow shape and snoring, included a simplified method of FOT for detecting increases in airway resistance. The Autoset II Plus (Resmed) generated a small pressure oscillation (5 Hz) when no breathing flow was detected in the course of 8 s. This capability allowed the device to detect obstructions only during apneas. The SOMNOsmart 2 (Weinmann GmbH; Hamburg, Germany) and the AutoTREND (Hoffrichter GmbH; Schwerin, Germany) detected airway obstructions by continuously generating a small pressure oscillation at 20 Hz during the whole treatment. These three devices were identified as O1, O2, and O3, respectively. All devices were programmed with a minimum CPAP of 4 cm H2O, a maximum CPAP of 16 cm H2O, an initial CPAP level of 4 cm H2O, and the initial waiting time or the ramp period were set to 0 min (when possible). All the other parameters were set at their default value.

Measurement Protocol
Each APAP device was connected to the patient simulator with its own tubing. A Whisper Swivel valve (Respironics) was used for all the devices, except for the SOMNOsmart 2, in which case its own exhalation port was used. At the beginning of each test run, the patient simulator reproduced normal breathing for at least 5 min (or the minimum initial time required by each device), and the maximum duration of the tests was 20 min. Eight independent test runs were performed based on the reproduction of the flow and obstructive patterns described above. Tests 1 and 2 (Fig 4and 5 , respectively) were based on the continuous repetition of apneas with and without obstruction, respectively (patterns from panels B and C in Fig 2). During tests 3 and 4, the simulator continuously reproduced hypopneic obstructive events without and with snoring (patterns from panels D and E in Fig 2), respectively. Tests 5 and 6 were based on a prolonged period of flow limitation and of mouth expiration artifact (panels F and G in Fig 2, respectively) for > 10 min. To assess the effect of air leaks in the response of the devices, test 7 was based on apneas with obstruction with the addition of a leak (0.5 L/s at 4 cm H2O). Finally, test 8 was based on the simulation of a real patient when subjected to APAP treatment. To this end, a closed loop was programmed in the simulator in order to change the breathing pattern of the simulated patient depending on the pressure applied by each APAP device. As shown in Figure 3, the simulated patient experienced apneas with obstruction when the CPAP level was < 5 cm H2O (panel E), severe hypopneas when the pressure was between 5 and 7 cm H2O (panel D), mild hypopneas between 7 and 10 cm H2O (panel C), and prolonged periods of flow limitation between 10 and 12 cm H2O (panel B). Finally, when the pressure applied by the devices was > 12 cm H2O, the breathing pattern of the simulated patient was normalized and the simulator reproduced normal breathing (panel A).


Figure 4
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  		Figure 4.. Pressure response of the different APAP devices when subjected to a continuous repetition of apneas with obstruction (test 1). R = resistance. Dashed horizontal lines indicate 10 cm H2O. See Figure 1 for expansion of abbreviation.

 

Figure 5
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  		Figure 5.. Pressure response of the different APAP devices when subjected to a continuous repetition of apneas without obstruction (test 2). Dashed horizontal lines indicate 10 cm H2O. See Figures 1and 4 for expansion of abbreviations.

 
Before each test run, the devices were switched off and on for resetting. For each device, the profile of the pressure applied during each test was evaluated. Moreover, the speed of pressure increase during tests 1 to 7 was assessed by measuring the time required for each device to reach a certain threshold. Some APAP devices included a pressure limit above which they did not further increase the pressure during apneas. Since most of these devices had this pressure limit at ≥ 10 cm H2O, this value was selected as the CPAP threshold for measuring the speed of pressure increase. The response of each APAP device during test 8 was analyzed by evaluating its capability of normalizing the breathing pattern of the simulated patient and by measuring the maximum pressure applied by each device and the time to reach this pressure. Institutional review board approval was not necessary in this study because it did not involve human subjects.

Results

Tables 1and 2 summarize the results of the different tests. The responses of the devices when subjected to a continuous repetition of apneas with obstruction (test 1, panel B in Fig 2) are shown in Figure 4. All the devices increased the pressure in response to this event but with different strategies. Devices F1, O1, and O3 increased the pressure linearly up to the maximum pressure allowed but with different speeds. Devices F2, F3, F4, F5, and O2 increased the pressure stepwise with differences in magnitude and duration. Some of these devices reached a plateau at different pressure levels depending on each APAP device. Device F6 increased the pressure linearly up to 10 cm H2O, and device F7 did not increase the pressure. The time required for each device to reach a pressure level of 10 cm H2O is shown in Table 1. When the APAP devices were subjected to the test with an identical flow pattern of apneas but without obstruction (test 2, panel C in Fig 2), all the devices based on the flow shape and snoring (F1 to F7) showed exactly the same pressure response as during the test sequence of apneas with obstruction (Fig 5, Table 1). However, the three devices that included the oscillatory detection of increases in airway resistance (O1 to O3) did not increase the applied pressure. Therefore, as expected, their pressure response was modified depending not only on the events detected with the flow signal, but also on the presence or absence of obstructions during these apneic events.


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  		Table 1.. Response of the APAP Devices to the Different Breathing Patterns*

 

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  		Table 2.. Response of the APAP Devices When Subjected to a Simulated Patient Based on a Closed Loop Model*

 
Table 1 also shows the results for tests 3 to 7. Devices F1, F3, F4, F5, F7, and O2 increased the pressure at different rates in the presence of obstructive hypopneas (test 3, panel D in Fig 2), but devices F2, F6, O1, and O3 did not modify the applied pressure. All the devices except O3 increased the pressure in the presence of obstructive hypopneas with snoring (test 4, panel E in Fig 2), some of them (devices F2, F3, F6, F7, and O1) with a higher speed than without snoring. Those devices responding to snoring, except F5, increased the pressure up to the maximum level allowed (16 cm H2O). During a prolonged period of flow limitation (test 5, panel F in Fig 2), devices F2, F4, F5, O1, and O2 increased the pressure at different rates while the other devices did not show any response. When the APAP devices were subjected to a period of mouth expiration (test 6, panel G in Fig 2), six of the devices (F2, F3, F5, F6, F7, and O2) did not increase the applied pressure. However, four devices (F1, F4, O1, and O3) detected this artifact as an event and increased the pressure above 10 cm H2O. During the test in the presence of leaks (test 7), devices F3, F4, F5, F7, O2, and O3 modified their response during apneas with obstruction. Devices F3 and O2 increased the pressure more rapidly than without leaks, devices F4 and O3 slightly reduced the speed of pressure increase, F5 did not modify the pressure and F7 increased the pressure up to 5 cm H2O. The other devices were not affected by the presence of leaks and increased the pressure with the same rate as in the test without leaks.

Table 2 and Figure 6 show the results of test 8 based on the closed loop model. Only three devices (F1, F4, and O2) were able to do the following: (1) correctly identify the respiratory events, (2) increase the pressure above 12 cm H2O, and consequently (3) normalize the breathing pattern of the simulated patient (Table 2). Devices F1 and F4 increased the pressure up the 14 cm H2O in 5.5 min and 7 min, respectively. Device O2 increased the pressure up to 12 cm H2O in 14.5 min. The other devices did not increase the pressure above 12 cm H2O (the optimal CPAP level for this simulated patient) and, therefore, were not able to normalize the breathing pattern of the patient. Figure 6 shows the response of two APAP devices (F4 in top panel and O1 in bottom panel) when subjected to the simulated patient. Device F4 was able to recognize all the events (apneas, severe and mild hypopneas, and prolonged periods of flow limitation) and increased the pressure until these events were abolished and the breathing pattern of the simulated patient was normalized. After 3 min of normal breathing, the device started to reduce the pressure slowly until the pressure was < 12 cm H2O and flow limitation reappeared (indicated by an arrow in Fig 6). At this point, the device increased the pressure again up to 14 cm H2O and the simulated patient resumed normal breathing. Device O1 recognized apneic and hypopneic events but did not identify prolonged flow limitation as an event. Therefore, the device increased the pressure only up to 11 cm H2O, and the breathing pattern of the patient was not completely normalized.


Figure 6
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  		Figure 6.. Flow patterns and pressure response of APAP devices F4 (top panel) and O1 (bottom panel) when subjected to a simulated OSAS patient during test 8 (flow is given as liters per second; pressure is given as centimeters of water). Tracings on the right side of the flow subpanels indicate the breathing pattern at the maximum CPAP level applied by the devices. Dashed lines at 12 cmH2O indicate the optimal CPAP level for the simulated patient. See Figure 1 for expansion of abbreviations.

 
Discussion

In this study, we developed a bench model to mimic not only the flow and snoring patterns obtained from patients, but also the corresponding upper airway obstruction. With this model, the new generation of APAP devices can be tested in the bench by reproducing the phenomena that occur in obstructive events. We analyzed several APAP devices capable of detecting the upper airway patency with respect to other devices based only on the analysis of the flow shape and snoring. The responses of the devices when subjected to the same pattern of apneas were considerably different. As expected, the devices that were not based on detecting increases in airway resistance responded to apneas without obstruction with the same pressure profile as to apneas with obstruction. However, the devices based on the forced oscillation technique modified their pressure response depending on the presence or absence of airway obstruction. The responses of the devices in the presence of obstructive hypopneas, prolonged flow limitation and snoring were also different. Artifacts such as mouth expiration caused a relevant pressure increase in some devices.

APAP devices have been evaluated both in clinical studies and on the bench.101333353637 Although some studies38394041 in the literature report a brief description of the algorithms implemented in the first prototypes of APAP devices, the most recent versions of these devices probably include a number of technical modifications that may be relevant in their clinical application. Clinical studies performed to date allow the evaluation of these devices in real situations. However, these tests cannot be performed under systematic and well-controlled conditions because of the intersubject and intrasubject variabilities. Bench tests have been recently used to evaluate the response of APAP devices when subjected to different breathing patterns.3337 Although bench tests and clinical studies are both useful and should be considered complementary when evaluating a specific device,42 this study was focused on developing a patient simulator for the bench evaluation of APAP devices.

Several approaches have been used to simulate on the bench the typical events found in patients with OSAS.3243 Our earlier patient simulator model was able to reproduce any flow and snoring pattern recorded in patients,33 but it did not include airway obstructions. The inclusion of a servocontrolled obstructive valve in our patient simulator allowed us to reproduce any pattern of airway resistance synchronized with the flow pattern and previously recorded in real patients by using the forced oscillation technique.34 Other authors have used a Starling resistor to generate increased upper airway resistance during simulated sleep respiratory events.37 Although this model is able to reproduce the pathophysiology of obstructive sleep apnea, it does not allow us to precisely reproduce flow shapes previously recorded in patients. The shape of the inspiratory flow using a Starling resistor is indirectly controlled by the breathing effort, the pressure surrounding the collapsible tube and the elastic properties of the tube wall. Since most of the APAP devices base their detection algorithms on the analysis of the flow shape, it is crucial to precisely mimic the flow morphology and to independently control the degree of airway obstruction for evaluating the devices in exactly the same conditions in terms of the physiologic signals. This independent control of the flow shape and the obstructive pattern allowed us to adjust the degree of obstruction during the events and to reproduce artifacts such as mouth expiration. Moreover, a closed loop model could be programmed in our simulator for reproducing the changes in the breathing pattern of a patient with OSAS during APAP application.

For the specific purpose of this study, two sets of breathing patterns were used to evaluate the APAP devices. In the first set, the flow patterns of apnea with and without obstruction were exactly the same, with the result that the only difference was the degree of airway obstruction generated by the obstructive valve. The breathing cycles prior to the apneic periods did not include any volume reduction, flow limitation, or snoring in order to avoid interference of these phenomena in the detection of apneas by the APAP devices. The degree of airway obstruction during the inspiratory phase of the flow-limited cycles in obstructive hypopneas and prolonged flow limitation was adjusted to reproduce the increases in resistance observed in patient studies3031 during the simultaneous application of CPAP and FOT. Hypopneas with snoring reproduced events in typical OSAS patients, whereas hypopneas without snoring could simulate patients in whom uvulopalatopharyngoplasty only succeeded in eliminating snoring. During the mouth expiration pattern, the obstructive valve reproduced high transient increases in airway resistance while expiration to simulate the closure of the nasal pathway during mouth expiration,44 allowing us to evaluate the devices not only when subjected to typical respiratory events but also in the presence of artifacts. The second set of breathing patterns was used to simulate a more realistic situation, reproducing the within cycle variability in each event observed in patients. Since most devices showed a high sensitivity to snoring, this phenomenon was not included in this set of patterns in order to evaluate the devices in a more challenging situation. Many other breathing patterns and artifacts (eg, mixed apneas, other flow limited shapes, and coughing) could be programmed in the patient simulator to extensively evaluate APAP devices. However, since this was not our aim, we used a fixed number of patterns covering the most usual events found in patients with OSAS.

As previously described in other studies,3337 our results confirm the existence of a great variability in the response of APAP devices when subjected to the same breathing patterns under well-controlled conditions. Regardless of the speed of the pressure increase during apneas, the response of the devices that based their detection algorithms exclusively on the analysis of the flow shape and snoring was the same in the presence of apneas with and without obstruction. However, the devices that included the detection of increases in resistance changed their pressure reaction according to the presence or absence of airway obstructions. Most APAP devices based on flow and snoring included a certain pressure threshold above which no pressure increase was applied in the presence of apneas. Accordingly, if apneas without obstruction had been applied at high pressure levels, neither device would have increased the pressure. The response of the devices when subjected to obstructive hypopneas or persistent flow limitation showed the full spectrum of possible pressure reactions, from devices increasing the pressure up to the maximum level allowed at a high speed to devices that did not modify the pressure. The more rapid increase in pressure in the majority of the devices during snoring demonstrates a high sensitivity of these devices to this event. These different event detection algorithms and pressure regulation strategies may have an influence when the devices are used both for treatment (some devices may allow an excessive number of residual events) and for titration of CPAP (with the possibility of an inappropriate optimal pressure level recommended by the device). Indeed, when these devices were subjected to a simulated patient in whom the breathing pattern changed according to the pressure applied, only three devices were able to normalize the breathing pattern of the simulated patient. It should be noted, however, that the closed loop tests were carried out in nonsnoring breathing patterns. In the light of the open loop results (Table 1), it is expected that more APAP devices would normalize breathing if snoring was included in the closed loop patterns. It is also worth noting that, although the presence of leaks does not have a major influence on the pressure reaction of the devices, four devices increased the pressure significantly in the presence of artifacts such as mouth expiration. These inappropriate pressure increases reduce the robustness of these devices and might induce low compliance in some patients during treatment with APAP45 or elevated recommended pressures during unattended automatic titration of CPAP.

The differences in the response of APAP devices raise the question of the best strategy for modifying the pressure in the presence of a specific respiratory event. While it is currently accepted that during obstructive apneas the pressure applied to the patient should be increased, the pressure strategy is not well established in the presence of a central apnea. One reason for this is that central apnea can occur with the upper airway closed or open.46 Some devices limit their pressure increases in the presence of apneas to avoid an excessive pressure during central apneas (devices F2 to F6). APAP devices using FOT or other techniques such as the detection of cardiac oscillations4748 may be useful when central apneas occur with the open airway. However, the effectiveness of these techniques measuring upper airway resistance will depend on the correct application of this technology (eg, increases in airway resistance should be taken into account only during inspiration to avoid a pressure increase during mouth expiration), and on the percentage of central events with the upper airway open in each patient. Therefore, although the best pressure strategy should be determined with clinical studies instead of with a simple bench test, our findings reveal that an accurate identification of sleep respiratory disturbances is necessary for determining the suitable pressure treatment for the patient.

The conventional methods for detecting and classifying respiratory events during polysomnography are based on the analysis of at least two independent physiologic variables (flow and thoracoabdominal bands and/or oxygen desaturation and/or arousal).49 This strategy enables us to assess the concordance between two or more signals. Since the main aim of the APAP devices during treatment is to normalize the breathing pattern with minimal side effects, their detection algorithms should be focused on improving their reliability and specificity, on correctly classifying the respiratory disturbances, and on reinforcing their robustness in the presence of artifacts. To this end, we strongly believe that APAP devices should base their detection algorithms on more than one independent variable, as in polysomnography, in order to analyze the concordance of the different measured signals, which would allow us to better detect and characterize respiratory events.

The differences between commercial APAP devices found in this work and other studies demand a consensus on APAP technology. This agreement could include the following: (1) a basic definition of the characteristics of APAP devices (number and type of measured signals), (2) the detection algorithms (detailed definition of events and artifacts), (3) the strategies to modify nasal pressure, and (4) the methodology for evaluation. This consensus, as in the case of spirometry,50 in which repetitive clinical or bench evaluations of devices are not required, would considerably improve the technology and outcomes of APAP.

In conclusion, this bench study shows that the use of flow and airway resistance signals as independent physiologic variables to identify respiratory events can improve the detection algorithms of APAP devices. Consequently, when this strategy is appropriately used (ie, the information obtained from FOT measurements are correctly interpreted), it could allow a more suitable correction of the respiratory events during APAP application. Bench studies should be followed by clinical studies to ascertain the clinical usefulness of measuring airway obstruction during APAP application.

Acknowledgements

The authors thank Mr. M. A. Rodriguez for technical assistance.

Footnotes

Abbreviations: APAP = automatic positive airway pressure; CPAP = continuous positive airway pressure; FOT = forced oscillation technique; OSAS = obstructive sleep apnea syndrome

Dr. Rigau was an employee of Measure, Check & Control GmbH & Co. KG at the time that this study was carried out and at present is employed by Sibel S.A. Josep M. Montserrat has no declared conflict of interest. Dr. Wöhrle received 38.500 Euros from Weinmann GmbH and 27.000 Euros from ResMed/MAP for lectures between 2002 and 2004. Dr. Wöhrle also received 25.000 Euros from Measure, Check & Control GmbH & Co. KG as a research grant. Ms. Plattner is an employee of Measure, Check & Control GmbH & Co. KG. Mr. Schwaibold is an employee of Measure, Check & Control GmbH & Co. KG. Dr. Navajas has no declared conflict of interest. Dr. Farré has no declared conflict of interest.

This study was carried out in the Unitat de Biofísica i Bioenginyeria (Universat de Barcelona, Spain) within the framework of a research contract with Measure, Check & Control GmbH & Co. KG.

This work was supported in part by Measure, Check & Control GmbH & Co. KG, by Fondo de Investigación Sanitaria (V-2003-RED C11 F-O), and by Ministerio de Ciencia y Tecnología (SAF2002–03616 and SAF2004–00684).

Received for publication November 8, 2005. Accepted for publication February 17, 2006.

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