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A computer program for automatic measurement of respiratory mechanics in artificially ventilated patients
computer methods and programs in biomedicine
Computer Methods and Programs in Biomedicine 47 (1995) 205-220
ELSEVIER
A computer program for automatic measurement of respiratory mechanics in artificially ventilated patients Pierre F. Baconnier* a, Pierre-Yves Carryb, Andr6 Eberhardc, Jean-Pierre Perdrixb, Jean-Marc Fargnolid aPRETA-TIMC/lhiAG. Laboraloire TMC, Faculte de M&iecine de Grenoble, 38706 La Tronche, bDPpartemenr d;4nesthksie-R&animation, CHU Lyon&d, Pierre-Benite. France CLMC/IMAG, VniversitC Joseph Fourier, Grenoble, France ‘Dkpartement d;4nesthkie-Rkanimation. CHU Grenoble, Lo Tronche, France
France
Received 2 August 1994; revision received IO May 1995; accepted 2 June 1995
A program for automatic and periodic determination of respiratory mechanics in artificially ventilated patients is described.Airway pressureand flow signalsare obtainedfrom the ventilator in the controlled ventilation modewith constantflow inflation and end-inspiratorypause.Periodically,the programrecordsboth signalsfor a giventime and it deliits a ventilatory cycle and its componentsout of this record.Then, four mechanicalparametersof the respiratory systemare calculated:(1) Rinit, the resistanceobtained with the end-inflation occlusiontechnique;(2) E,, the elastance. (inspiratory) calculatedfrom the slopeof the airway pressureprofile during inflation; (3) 7, the expiratory timeconstant;(4) PEEP,the globalpositiveendexpiratory pressure.All parametermeasurements havebeenevaluated in experimentalconditions,and are in good agreementwith referencevalues.The completesoftwareincludesthe displayof the signalsand of the trendstogetherwith automaticdisk file backups.An additional programallowsone to displaythe trendsagainandto createtabletext tilescontainingall the recordeddata for further analysis.The system proved to work in ICU and anaesthesia patientswith various ventilators. Keywords: Respiratorymechanics;Signal analysis;Monitoring; Artificially ventilated patient
1. Introduction
It is common for patients to ventilated during anaesthesia or units (ICU). A detailed analysis tory mechanics can readily be * Corresponding author.
be mechanically in intensive care of their respiraperformed with
available methods [l-6], based on simple models able to satisfactorily describe the transfer function between airway pressure (considered as the input variable) and flow (considered as the output variable). Several microprocessor-controlled ventilators available for clinical use contain optional computer software programs capable of performing nearly instantaneous determination of respira-
0169-2607/95/$09.50 0 1995 Elsevier Science Ireland Ltd. All rights reserved SSDZ 0169-2607(95)01651-Z
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tory system resistance and compliance [7]: (a) the resistance value is usually obtained as the total pressure drop during an end inspiratory pause divided by the flow immediately before interruption (this resistance (&,J is not a good estimation of airway resistance as it also includes lung tissue and rib cage viscances); (b) the compliance value is obtained as tidal volume divided by plateau pressure at the end of an end inspiratory pause without correction for global positive end expiratory pressure (PEEP). However, although many of today’s microprocessor-controlled ventilators offer one or a number of algorithmically controlled manoeuvres, the paucity of supportive or critical data in the literature suggests that these features are little used [8]. That these parameters are only obtained on demand with almost all the ventilators, is a possible reason for the little use of this option. Modern ventilators may provide voltage signals corresponding to pressure in airways and flow profiles.. The system proposed in the present study uses this information to build a signal processing system which periodically analyses the airway pressure and flow curves in order to provide an automatic system for detecting early trouble of the ventilatory mechanical system in artificially ventilated patients. The aim is to propose a continuous, automatic and non-invasive determination of ventilatory mechanics parameters: airway resistance, respiratory system elastance, global PEEP, and expiratory time constant. Global PEEP must be obtained without any end-expiratory pause or any manoeuvre from the clinical staff, and the elastance value (inverse of compliance) must be independent of global PEEP. The clinicians should be able to further analyse information gathered during the monitoring phase on a spreadsheet software. In the first section, the physiological theory and related computational methods are described. The second section deals with the description of the aigorithms in handling real signals. Validation and applicability of methods are presented in the third section. The fourth section is devoted to a detailed presentation of the program written in Pascal.
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methods and theory
2.1. Characterisation of the mechanical respiratory system The mechanical respiratory system is usually considered as a linear system made up of one elastic compartment connected to the outside pressure through a flow resistive component [9]. Its motion equation is then: P(t) = E. V(t) + R- V’(t)
(1)
where, at any time t, P(t) is the driving pressure imposed by the ventilator at the tracheal tube, V(t) is the compartment volume above its relaxation level and the flow V’(t)= dV/dt; R is the resistance to flow and E the elastance of the compartment, R and E being constant. For patients with a normal ventilatory function, simple estimates of R and E usually provide adequate information to the physician about the state of the patient’s mechanical respiratory system even though such a linear system is not a perfect reflection of the real system. When the system is relaxed (P(t) = 0) from any given volume above the relaxation level, the resulting passive deflation flow presents an exponential profile. Asstmring that the respiratory system is linear and made up of one compartment, a simple parameter may be obtained from the flow curve during passive expiration, namely the expiratory time constant (7) of the system [lo]. If the system considered behaves as a single compartment, then one gets r = R/E. In the real situation, this is not the case and differences arise for two main reasons: (1) at expiration, the time constant of the patient-ventilator system includes the effect of the expiratory limb of the ventilatory circuit, while at inspiration, R and E deal only with the portion situated between the Y connector and alveoli; (2) in some patients, some flow limitation occurs during expiration due to dynamic compression of the airways. In some circumstances (increased expiratory resistance, lowered elastance, or both), the system cannot reach its relaxation volume before the end of expiration. The lung volume at the end of expiration then increases with each cycle until a
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dynamic equilibrium is reached. At this equilibrium, the pressure in the lungs at the end of expiration is positive and called ‘intrinsic positive end expiratory pressure’ (intrinsic PEEP or PEEPi). To avoid ruptures of the alveolar wall, the physician needs to monitor this PEEPi. A simple means of measurement is to close the airways at the end of expiration and to measure the airway pressure. This manoeuvre requires active participation on the part of the physician explaining why PEEPi is not commonly monitored in clinical situations. In some other circumstances, the physician may have to impose an external PEEP which is made easy by modern ventilators. Both PEEPi and imposed PEEP may be operating at the same time in some cases and when this occurs, the clinician is interested in the variations of the global PEEP. In the present study, we will develop a simple mathematical way for estimating E, R, r and global PEEP from pressure and flow signals [l 11. 2.2. The three phases imposed by the ventilator The ventilator cycle we will consider includes three phases, namely active inflation, pause, and passive deflation (see Fig. 1). Each phase is utilised for estimating one or two mechanical parameters of the respiratory system. For each phase, the signal processing principle will be described below (for detailed computations, see Section 3 - Algorithms). 2.2.1. Inflation Among the various inflation profiles that can be chosen by the physician, a constant flow inflation is usually available in most modem ventilators. The breathing cycle considered here (see Fig. 1) then has inflation at constant flow. The first derivative of Eq. 1 gives: P’(t) = E. V’(t) + R. V”(t) where P’(t) = dPldt and V”(t) = dV’ldt. During a constant flow inflation, V” theoretically zero. Then (2) can be written P’(t) = E- v’(t)
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.
-Inflation-Pause 1 ::
.
. . . . .
. . . . . .
Expiration b 2
4
6
Fig. I. A typical ventilatory cycle. Flow (V’) and airway pressure (P) profiles for a breathing cycle as imposed by a mechanical ventilator for a patient. During inflation, the ventilator imposes a constant flow. I valve: inspiratory valve; E valve: expiratory valve; Pm,: the maximal pressure reached during the cycle; Pp: the pressure at the end of the pause.
and E is obtained as P’(t)lV’(t) [12]. To obtain this estimation of E one does not need to wait for a stable occlusion pressure and then E can be estimated on any normal cycle provided that a constant pressure slope is observed. As one can see on Fig. 1, the slope of P(t) during inflation is far from constant from the very beginning. This is due to: (a) the time the ventilator takes to establish the desired constant inflation flow; (b) the time the respiratory system takes to reach a dynamic steady state. However, as is obvious in Fig. 1, P(t) presents a linear portion on almost all inflation. This happened to have been verified in all patients and ventilators studied, which allowed us to look for, and find, a linear relationship between P(t) and time during some part of inflation. 2.2.2. Pause At the beginning of the pause, the inflation valve rapidly closes while the deflation valve remains closed. Abruptly interrupting the inflation flow induces: (a) a rapid drop of P(t) from its maximal value, P,,,; (b) a slower decrease during the pause (see Fig. 1).
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The interrupter method [l] relies on the hypothesis that the fast initial drop in P(t) is due to the vanishing of the resistive pressure associated with air flow entering the airways. P(t) generally reaches a stable plateau (the elastic recoil pressure of the respiratory system, Pat.) in approximately 5 s [6]. This slow decrease i.s usually attributed to one or both of two phenomena: (1) gas redistribution between ventilatory units previously inflated differently because of time constant differences; (2) stress relaxation in tissues of the respiratory system [14]. Airway resistance. Following the interrupter method, the instantaneous resistance of the respiratory system (Ri”i,) is obtained by dividing the immediate pressure drop due to the occlusion by the flow preceding the occlusion. In order to measure this pressure drop, one needs the pressures before and after the inflation valve closes. If the pressure immediately before occlusion is easily determined, the estimation of the pressure at the time the valve is entirely closed remains controversial [13]. Indeed, the pressure profile presents at the beginning of the pause an oscillatory behaviour linked both to valve functioning and to inertia of air moving through the ventilator tube. Moreover, the usual exponential lit proposed for the pressure during the pause is not adapted to the actual clinical situation where repetitive pauses cannot exceed 10% of the whole ventilatory cycle. We chose to lit the pressure curve with a straight line at the part of the pause situated after oscillations vanished. The estimation of the pressure after inflation valve closure is obtained as the back extrapolation of the straight line to the instant at which occlusion begins. Global PEEP. In the actual clinical situation, where repetitive pauses cannot exceed 10% of the whole ventilatory cycle, the plateau value is never reached (see Fig. 1) and we called Pp the pressure at the end of the pause. Then, the total pressure drop during the pause (P,,, - Pp, see Fig. 1) slightly underestimates the pressure needed to impose air flow and movement of the respiratory system during inflation (dynamic pressure). During inflation, after a dynamic steady state has been established, the pressure imposed by the ventilator at any time t includes this dynamic pressure and
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the elastic recoil pressure corresponding level of pulmonary volume (Paa( V(t)): P(t) = Pm, -
PP
+ PER(V(t))
to the
(4)
This elastic recoil pressure includes the global PEEP (PEEP) and the elastic recoil pressure due to the volume imposed by the ventilator (V”(t)). At the very beginning of inflation (t = O+) this elastic recoil pressure is zero. Then PaR( I/(0+)) = PEEP
(5)
One can then compute global PEEP as PEEP = P(O+) - (Pmax - Pp)
(6)
As Pp overestimates PEL, P,,,,, - Pp underestimates Pm,, - PEL and then the calculated PEEP overestimates real global PEEP. 2.2.3. Deflation
At the end of the pause, the deflation valve opens, letting air flow out of the lung through the patient’s airways, the tracheal tube, and the expiratory part of the ventilator. This passive deflation begins with a rapid increase of the expiratory flow followed by an exponential like evolution of this flow towards zero (flow may not reach zero during expiration when some PEEPi is present). The proposed signal processing system waits until the exponential evolution is established and then a first order regression of flow versus volume (calculated as flow integral) is carried out and the slope of this regression line gives the time constant of these curves [lo]. 3. Algorithms
Periodically, when a measure occurs (see Section 5.3), we dispose of both pressure and flow signals sampled for a period of time which ensures recording a complete ventilatory cycle. The cycle must first be delimited, which means identifying the instants the cycle starts and ends. Then the three phases imposed by the ventilator must be identified. Furthermore, for each phase, we use appropriate algorithms intending to identify the four
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&nit: the instantaneous resistance when the inflation is interrupted, E,: the elastance of the respiratory system, 7: the expiratory time constant. PEEP: the positive end expiratory pressure, 3.1. CyeLe &li~itati~n
The flow signal is essential to fix cycle delimitation and because cycle delimitation is based on zero flow, it is very important to get a good zerovalue calibration at the beginning of each experiment (see Section 5.1). Theoretically, we know that the flow must be equal to zero during the pause, before it becomes negative with deflation. It can also be equal to zero at the end of deflation, before it becomes positive with next inflation. Actually, at the end of some expirations, the Bow oscillates around the zero value. We define the canning of a cycle as the last ascending zero crossing before the flow reaches a positive validation threshold (Fig. 2). The method used is presented elsewhere [la The cycle is deli~ted when we End two such successive zero crossings. The first is called LZC (left zero crossing) and the second is called RZC (right zero crossing). 3.2. Pause
Once the ventilatory cycle is delimited, we look for the maximum pressure between LZC and RZC. At this instant, called MPI (maximum pres-
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sure index), the pressure value is P,,,,, and the flow value is VP,,. It is at this instant that the inflation valve begins to close. During the pause, the sampled flow values are not strictly zero. We consider that the inflation valve stops closing when the flow decreases below another positive threshold. This instant is called ZFI (zero flow index). Similarly, we locate the instant at which the deflation valve opens, called ES1 (expiration start index), where the flow falls below a negative threshold {Fig. 3). At the beginning of the pause, the pressure drops rapidly and presents oscillations which damp down, followed by a slower decrease. We chose this last phase of the pause (the second half of the interval ZFI-ESI) to carry out a linear regression on the pressure. At the two extremities of the pause, this line gives us noteworthy values. At ES1 it gives Pp, the elastic recoil pressure. Back extrapolated at MPI, it gives PO, an approximate value of the airway pressure i~ediately after occlusion. The pressure drop Pm, - PO divided by the flow value just before occlusion (VP,,,,,) gives us &nit, an approximation of the resistance of the system when inflation is interrupted. The total pressure drop during the pause (Pm,, - Pr) is called dPdif and is used for the determination of global PEEP. 3.3. In~at~on Normally, during the constant flow inflation imposed by the ventilator, the pressure should increase linearly. We need to know the slope S of
Fig. 2. Cycle deIi~~ti~n using flow. At the end of expiration, the flow signal can oscillate around 0. The end of a cycle (and the beginning of the next one) is the last ascending zero crossing before the flow passesa threshold. The cycle we analyse goes from the first end of cycle encountered: left zero crossing (LZC), to the second one: right zero crossing (RZC).
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this increase to determine the elastance. In practice, even after waiting for oscillation delay (necessary in order to eliminate a transient phase) we can observe different behaviours. More often, the pressure increases in a truly linear fashion all along the remainder of inflation until MPI (see Fig. 4a). Sometimes, however, we distinguish two different slopes at the beginning and at the end of inflation (see Fig. 4b and c). At other times, generally associated with a strong resistance, the pressure increases rapidly at the beginning and then increases more and more slowly preceding a linear behaviour at the end of inflation (Fig. 4~). The question in such cases is: what is the correct slope S to use for the calculation of the elastance? Our program proceeds in the following way: after an oscillation delay, the remainder of the inspiration is divided into two equal parts and a linear regression of the pressure is performed on each interval. Thus we obtain two linear approximations of the pressure: Pi(t) with a slope S, and P*(t) with a slope S,. Three cases may be encountered: (a) The two slopes are not significantly different (the ratio S,& lies between 0.9 and 1.1). In this case, the slope we will use is the mean value of the two slopes: S = (S, + ST)/2
ES1
Fig. 3. Pressure fitting during the pause. (1) We look for MPI (maximum pressure index) * P,,,,, and V’ Pm (2) We define ZFI (zero flow index) and ES1 (expiration start index) and we tit the pressure curve with a straight line during the second half of the interval ZFI-ESI. At ES1 abscissa, this line gives Pp. Back-extrapolated at MPI abscissa, this line gives PO The total pressure drop during the pause is dPdif = P,, - P,.
dpdif
PEEP ::: UC
a - Rtz = 0.95
MPI
MPI
b _R12 Ql
= 0.67
C - RIZ = 1.53
@
Fig. 4. Pressure fitting during inflation. To calculate elastance, the pressure slope during the constant flow inflation must be known. After an oscillation delay (OD), the remainder of the inflation is divided in two equal parts. A linear regression of pressure is performed for each part and we look at the ratio of the slopes: R,,. (a) RI, is close to 1 (0.9 < RQ < 1.1) - the slope we use is the mean of the two slopes. If the ratio is significantly different from 1, we look to the mean squared error for the first part (Q,), and for the second part (Q& (b) Qt < Q2 * we use.the slope found when fitting during the first part of the inflation; (c) Q2 < Qt * we use the slope found when fitting during the second part of the inflation. In a11cases,the value of the first regression line at LZC abscissa abated of dPdif gives global PEEP.
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If the slopes are different, we look to the mean squared errors that we obtained for each half: Qi for the first half, and Q2 for the second. (b) Qi < Q2 * we will use the slope obtained when fitting the first half: S = S,; (c) Q2 < Qi * we will use the slope obtained when fitting the second half: S = &. The slope S obtained, divided by VMean (the mean value of the flow during the retained regression interval) gives the elastance E,. In all cases, the value of the first regression line P,(t) at LZC abated of dPdif gives global PEEP. 3.4. Deflation In order to determine r, the time constant of the passive deflation, we suppose that the volume profile during this phase is described by
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V’bi, and then oscillates preceding an exponential behaviour which tends towards zero (Fig. 5). In order to eliminate oscillations, we define RSI (regression start index) as the instant where the flow is two thirds of V’min. By integrating flow we get a volume value, and we perform a linear regression on the ratio flow/volume from RSI to RZC: V = kV’. The absolute value of the slope k of this regression line gives the expiratory time constant 7. 3.5. Formulas &it
summary
= (pm*x -
pOYV’pmx
E, = S/V’ Mean ~=l kl PEEP = P,(LzC)
- (P,,
- Pr)
V(t) = VO exp(-f/r). Then the flow is given by
4. Validation
V’(t) = -1/7V0 exp(-r/r),
4.1. Validation of mechanical parameters on a test lung In order to assessthe validity of our method, we have carried out a preliminary experiment on a test system: a Training Test Lung (Model 26OOi Dual Adult TTL/REG/, Michigan InstrumentsTM) connected via a conventional patient circuit, including an empty humidifier (Model 3000 HPD MedicalTM), to a CESAR@ ventilator (TAEMATM) set
and the following linear relationship holds true between volume and flow: V(r) = -TV’(t). In fact, when the deflation valve opens (ESI), the flow signal drops abruptly to a negative peak
Fig. 5. Flow/volume regression during deflation. First we look for the minimum flow during deflation, and then we define the regression start index (RSI) as the instant where flow equals two thirds of this minimum. By integrating flow we obtain a volume value, and we perform a linear regression on the flow/volume ratio from RSI to RZC. The absolute value of the slope of this line gives the expiratory time constant.
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in the controlled ventilation mode with constant flow inflation. This TTL is designed to simulate the mechanics of the adult ventilatory system from upper airways to the lung. Human lungs are simulated using two elastomer bellows. Elastance is simulated through a precision steel alloy spring stretched between the top plate of each lung and the body of the TTL (See Fig. 6). Elastance is adjusted by positioning the spring at various points along the top plate. Resistance is modified using different combinations of resistors (PneuFloTM Airway Resistors) placed on the hose assemblies simulating the airways. The PneuFlo resistors exhibit parabolic pressure change as a function of flow. The pressure and flow signals of the ventilator were fed into a micro-computer (AmstradTM 1640) via an ADC card (DC&C/TM/-O3 12 bits AD/DA card). The micro-computer determined the ventilatory mechanics parameters with the above described algorithm implemented with BorlandTM TurboPascal programming language. We determined ErS, Rinit and r for various pre-set resistances (23 different values) and elastances (four different values) and we compared measured and simulated values. The mean measurements of &nit, E,, and r for five consecutive automatic estimations were obtained for each resistor/elastance combination (mean variation less than 5%) and compared to the corresponding pre-set values. 4.1.1. Ri,it. We first calculated the true resistance (R,,) corresponding to each resistor combination and each imposed flow. The mean value
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“‘o-0 Rtrue (cm Hz 0. I-‘. s)
Fig. 7. Comparison between measured (Ri”it) and calculated (R,,) resistance of TTL.
of five consecutive automatic estimations of Ri,i( was compared to the corresponding Rtrue. The result is presented on Fig. 7. There is a significant correlation between measured and calculated values (Ri,it = 0.836 Rt, + 2.88 cm HzO.l-’ -s, r = 0.99, P C 0.001). The intercept corresponds to the resistance of tubing between the ventilator and the test lung. The slope is well explained by a model of compressibility of air in the humidifier [ 161. This slope effect
Measured Ers (cmHz0.V) 40
T
Ventilator
0
20 Preset Ers (cm HzO. I .‘I
40
Fig. 8. Comparison between measured and pre-set elastance Fig. 6. Side view (schematic) of the training test lung (TTLI.
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measures for each elastance. The reproducibility of the E measurement is such that, whatever the resistance, when comparing measured to pre-set values of E, one can see only four different points on the representative graph (Fig. 8). It is for this reason that each point is labelled with the corres~nding number of estimations. One can easily see that E,, is measured quite accurately. The relationship is very close to the identity line (measured E, = 0.92 preset E,, + 0.22, r = 0.99 P < 0.001). 41.3. 7. The expiratory time constant of the TTL is set by the values of both elastance and resistance. When looking to &it results, one notices that R, is probably underestimated by around 3 cm H20. 1-l -s. In order to assess the accuracy of time constant estimation, measured 7 ( I k I) was then compared to a calculated value obtained as R/E with R = R,,, + 3 (see Fig. 9). Our results show that the algorithm is valid (Ik I = 0.87 (R, + 3)/E- 0.07, r = 0.99, P < O.~l}, even in the present case where the expiratory resistance is
/ 0)
Fig. 9. Comparison between measured and estimated f.
may become important in high lung resistance situations. 4.1.2. E,,. As mentioned above, we used four different elastance values and several resistance
Table I PEEP values obtained on nine patients with the end expiratory occlusion method (measured PEEP) and our method (calculated PEEP) Patient
Measured PEEP
Calculated PEEP
Patient
Measured PEEP
Calculated PEEP
Patient
Measured PEEP
Calculated PEEP
1
0.1
1.7
6
5.5 2.5 2.9 7.0 6.6 7.4
3.5 2.2 4.0 6.7 5.6 7.6
3
8.5
8.8
4
1.3 8.4
5.0 9.2
11.7 10.8 10.9 13.7 15.6 16.6 16.0 17.1 15.5 16.0 15.6 15.2 15.0
9
2
10.0 11.0 11.0 12.0 13.0 13.0 13.0 15.0 15.0 15.0 16.0 16.0 16.0
5
5.7 5.1 7.4 6.2
6.8 6.4 7.1 9.2
7
6.8 8.2
8.4 6.2
8
1.0
3.5
2.0 2.0 2.0 2.0 2.0 6.0 6.0 9.0 9.0 9.0 11.0 11.0 11.0 13.0 13.0 16.0 16.0 16.0 16.0
4.6 2.2 3.1 5.0 3.5 6.1 6.0 10.0 9.9 8.3 10.9 il.2 13.5 15.1 15.1 14.6 14.5 14.5 14.2
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Calcutsted PEEP (cm Hz 0)
01 0
Measured
10 PEEP (cm H2 0)
20
Fig. 10. Comparison between calculated and measured PEEP.
not really constant since the PneuFlo resistors exhibit parabolic pressure change as a function of flow. 4.2. Global PEEP Contrary to previous parameters, direct measurement of global PEEP can be easily accomplished under real conditions with the help of a reference method: by occluding the airways at the
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end of a normal expiration, the pressure measured in the airways after occlusion is equal to global PEEP. We have experimented the validity of our method for estimating global PEEP on nine intensive care patients (see Table 1,). For patients 6 and 9, we benefited from the ‘best PEEP trial procedure’ [ 171 to get numerous values of PEEP. Briefly, this procedure consists of increasing progressively the imposed PEEP until m~imum oxygen transport is obtained. Measures have been done by imposing three to five end expiratory pauses at each tested PEEP level, with at least 10 ’ between each step. The comparison between the PEEP calculated by our program and the measured PEEP indicates a good correlation, and this was redemonstrated in every patient tested (see Fig. 10). There is a significant correlation between calculated and measured values (calculated PEEP = 0.91 measured PEEP + 1.53 cm H,O, r = 0.95, P < 0.001). The positive intercept corresponds to the slight overestimation already mentioned Section 2.2.2. 4.3. Applicability to different ventilators
The flow and pressure signals provided by three modern ventilators (Bennett 7200, Taema
)
~~~~t(s) ~~ y+ -1
Bennett
7200
Taema
Cesar
Siemens
LMA 900
Fig. 11. Flow and pressure signals provided by three ventilators. Ventilators operated under same conditions: test lung with same settings, controlled ventilation mode, constant flow inflation.
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CESAR, Siemens 900C) were recorded using the test lung with similar settings and we have tested the possibility of processing them with the present
As the signals ventilators, the characteristics of but the mechanics
are measured internally to the curves reflect not only the the patient’s respiratory system of the patient-ventilator system.
1 Ask for a RootLetter 1 1 Zero-valwscalibration )
Run algorithms for parameters’extraction :
Rinit , Ers ,Z & PEEP
I
Storeresults (and eventually save ii .RES file)
in END.RES file
Fig. 12. Program flow chart. User’s action process is described in Fig. 12
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F4
Fig. 13. User’s action processing.
As can be seen in Fig. 11, all signals present a linear pressure increase during inflation, with different transition times. Elastance is then easily measurable with our program. The pause profile, however, is very different from one ventilator to the other; for while the 9OOC and the CESAR exhibit a rapid closure (less than 50 ms in general), the 7200 requires at least 120 ms to close the inflation valve. Therefore, Rinit cannot be measured on patients ventilated with this device. The program developed by our team proved itself capable of calculating global PEEP from the signals emitted by each ventilator tested, since the total pressure drop during pause was measurable for each ventilation device. Finally, the expiratory time constant may be calculated from each of the expiratory flow curves shown, but the Siemens 9OOC has a peculiar PEEP control system which varies the expiratory resistance in order to impose the desired PEEP. In this situation, the expiratory time constant is modified by the respirator itself during the expiration and any estimation becomes impossible. In the specification file (see Section 5.9) the ventilator used is mentioned, and the program automatically discards the corresponding unvalid parameters.
5. Program description The program contains two main parts: the initialisation procedures and a main loop managing the automatic measurements and the processing of user’s actions (see Figs. 12 and 13). Two presentation modes are proposed to the user: an oscilloscope mode and a trend mode. In the present version, the oscillo mode has been chosen as the default mode as required by our users. However, the trend mode may be chosen as default mode very easily. 5.1. Initialisation First, the program asks the user for a ‘root letter’ to identify the experiment. Then the program needs a zero-value calibration: the respirator tube must be disconnected (0 pressure = atmospheric pressure) and the flow has to be set to 0 for a short time (5 s)‘. ’ Because of drift of zero lines, zero-value calibration is very important and has to be performed at the beginning of each experiment. On the contrary, the scaling factors depend essentially on the ventilator and on the AD converter. So the full scale calibration is performed previously by a special program for each ventilator-AD converter coupIe, and the scaling factors for pressure and flow so obtained are put in the specification file (see Section 5.9).
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Following which, the program runs automatically and no longer requires intervention on the part of the user. 5.2. The os~i~lo mode Both flow and pressure signals are sampled with a slow rate (about 20 Hz) and they are drawn on the screen (Fig. 14). 5.3. measure Periodically (every minute, or every m minute, depending on the corresponding specification parameter) a measure occurs: (a) curves are no longer displayed and a vertical straight line is drawn (Fig. 14); (b) both pressure and flow signals are sampled with a higher rate (about 100 Hz) until 1200 points are obtained for each of them; (c) the digital values are zerocorrected and brought to scale using two other specification parameters and then stored in buffers; (d) the program attempts to apply the algorithms described in section 3 and an error code is associated to the measure. When the algorithms fails (error code # 0), a bell rings and special values are stored instead of ventilation parameters. Afterwards, the program reenters the oscillo mode. 5.4. Trend mode When desired, the user can strike the space bar
Fig. 14. 0scillo mode screen. Pressure and flow are displayed with a slow rate {about 20 Hz). The vertical straight line means that a measure has been performed just before.
Fig. 15. Trend mode screen. This is an example of a trend screen after 26 measures. A042 1 means that the ‘root letter’ was A and the date was the 21st of April. Letters r, f and g are marks struck by the user before measures 9, 16 and 19.fmeans that the sampling values of the measure IO were saved in a .WKS file.
on the keyboard of the computer. Immediately (or at the end of the measure, if one is occurring) the screen displays the evolution of the four ventilatory mechanics parameters (Fig. 15). The X axes represent the time elapsed from the beginning of the experiment (time scale is adjusted automatically). For each measure a dash is drawn for each parameter. If the value is negative, a double depth dash is drawn at level 0 (see measures 7, 8 and 15 for the global PEEP). If the value exceeds the maximum of the scale, a double depth d .j is drawn at the top level (see measures 19 and 2b or the E,,). After a delay (10 s), the program automatically re-enters the oscillo mode. If a measure occurs during the trend mode, a square drawn in the middle of the screen advises the user. 5.5. Manual interventions Fl This key (after a conflation message) terminates execution. F2 This key induces creation of a disk file with a suffrx .WKS (see Section 5.7), containing the sampled values (both of flow and pressure) of the last measure, whatever the error code and the character f appears for the corresponding values on the trend screen (see measure 10 in Fig. 15).
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F3 Alternately, this key multiplies and divides the vertical scales of the current drawing (either in oscillo mode or in trend mode) by two. Original scales are initialised with specification parameters. F4 This key operates only if the last measure is successful. It induces the program to work in a particular way called the ‘burst’ mode: from this moment the measures follow one another without any delay between them. The screen displays only the number of the current measure, This feature is very useful when the user expects rapid variations of any ventilatory mechanics parameter consecutive to an action performed. The same key induces leaving ‘burst’ mode. Any other key (except the space bar which is used to switch from oscillo mode to trend mode) the user strikes during the program run is considered as a mark which will be associated with the next measure (see measures 9, 16 and 19 in Fig. 15).
of these tiles are successively Prefix-Ol.RES, Prefix-02.RES,... (the present example is: AO42LOl.RES, AO42L02.RES ,... ). This allows reconstruction not only of the four parameters (giving the missing PrefixEND.RES tile), but also various parameters (cycle duration, inflated volume, inflation duration,...) for the ventilatory cycle analysed for each measure. All .RES files are binary files. They are accessible by another program, either for review of the trend screen of an ex~riment, or to make text files in order to read them with a spreadsheet program such as ExcelTM. . WKSfiles: We have Seen (Section 5.5) that the F2 key induced the creation of a text file which contains the sample values of flow and pressure signals of the last measure. The names of these files are, successively Prefix_01 .WKS, Prefix-02. WKS, . .. {for our example: A042L01. WKS, A042L02. WKS,. . .).
5.6. Automatic stop Due to limitations of the memory buffers, if the key Fl (voluntary stop) is not used, the program will run until 480 measures have been performed. This allows observation of the ventilatory mechanics parameters for 8 h if M (specification parameter giving the minutes delay between two consecutive measures) is one, and a whole day (24 h) if m is three! Of course, use of the ‘burst’ mode decreases duration.
.?,8. hardware and software ~pe~~~~ation~ Our monitoring program, called ‘MON’, runs on any PC compatible computer with 640 kB memory (a) linked to different respirators: Siemens @OOC), Taema (CESAR), Bennett (7200); (b) equipped with different analogue to digital cards; (c) in different medical situations (intensive care, anaesthesiology, neonatology...); (d) with different purposes (monitoring, expe~mentation, equipment’s test...). File backups can be done on floppy or hard disks. The prolgram works on real time mode, the computer time needed for signal analysis varying from less than 1 (80386) to 5 s (8086) following the CPU performance. The programming language used is BorlandfM TurboPascal. An external specification file allows the program to adapt to each situation. It contains various specification parameters (see Section 5.9). Several specification files may be present in the current directory (all of them have the suffix DON), and the user chooses whichever he prefers during the run. For example, if he enters mon myspec, the program will read the environment settings in the file MYSPEC.~N (if he only
5.7. Files created by the program The ‘root letter’ entered at the beginning of the execution (see Section 5.1) and the date of the day are used to construct the Prejx: for example, if the ‘root letter’ is A and if the date of the day is the 21st of April, the Prefix will be AO421. This prefix is used to produce the names of all the files created by the program during execution. . RESfiles: When the program is stopped (either automati~ly or vol~~rily), the results of all measures are saved in a file so called PrefixEND.RES (the present example is: AO421END. RES). Nevertheless, in order to avoid losing everything if the program crashes, every 15 measures, all the values for each measure are saved. The names
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enters mon, the program lets the user choose from among all DON tiles which are present in the current directory).
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ters are also different from one situation (anaesthesia) to the other (neonates,...). Threshold values result from successive trials and errors for each ventilator-AD converter couple.
5.9. Specification file
This is the text tile read when the program starts. It contains information which permits the program to adapt to each hardware and software situation: (1) Hardware (ADC card and ventilator characteristics): (a) ADC indicator: 0, 1 or 2 (as three different ADC cards are currently used); (b) Physical channel numbers for flow and pressure; (c) Lag (ms) pressure/flow; (d) OD: oscillations delay (s); (e) Scaling factors for flow and pressure. (2) Software: (a) Sampling rate during measures (Hz); (b) Maximum number of measures (5 480); (c) Maximum scale values for flow and pressure in oscillo mode; (d) Maximum scale values for each ventilatory parameter in trend mode; (e) Delay between two measures (m min); (f) Thresholds for cycle delimitation. Some ventilators do not provide perfectly simultaneous flow and pressure signals. We then measure (and compensate by the program) the ‘lag (ms) pressure/flow’, determined previously from high speed paper recording of flow and pressure signals. The oscillation delay (OD) depends on the ventilator valve speed and has been determined in the same way (high speed paper recording). The sampling rate used is 100 Hz for adults and 250 Hz for neonates. The maximum number of measures, together with the delay between two measures, limit the total duration of the program run. The maximum number of measures is limited to 480 by the computer memory, then a 3-min delay has been chosen for 24-h monitoring. Maximum scales for flow and pressure are respectively 1 1. s-’ and 40 cm Hz0 for adult anaesthesia. They were modified at demand for intensive care and neonates. Maximum scale values for ventilatory parame-
6. Discussion The respiratory system resistance usually calculated in ventilators is obtained as the total pressure drop during an end inspiratory pause divided by the flow immediately before interruption (&J. Rtot includes the viscoelastic properties of lung and chest wall, as well as gas redistribution among units having different time constants. Moreover, the calculation of R,,, requires that a plateau pressure has been reached, which implies that a specific cycle has been imposed to the patient. This manoeuvre, even automatically controlled, has to be decided and commanded. Either this is done periodically and then a rapid variation of R may be missed, or it is done at demand and this will not provide a way to detect any change as the demand will probably follow the observation of a change in the clinical state of the patient. The compliance value proposed by ventilators is obtained as tidal volume divided by plateau pressure - PEEP. In the Cesar ventilator, a periodic end-expiratory pause for global PEEP measurement is automatically performed, allowing the correction with ‘auto-PEEP’. As said above, the method we use is independent of PEEP and does not require end expiratory pauses. Moreover, ventilatory mechanics measured during specific cycles, a,s proposed by some ventilators, may not be the exact reflection of ventilatory mechanics during normal cycles. 7 is very useful in neonatal intensive care since the expiratory time constant may vary quickly, inducing, for example, intrinsic PEEP if expiratory time is not immediately lengthened. The most important difference between the present system and others designed for ventilatory mechanics monitoring, is that it allows automatic measurement of mechanical parameters without any operation by nursing or medical staff. It has been designed to run with low cost materials and
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without any additional measurement devices. Therefore, it demands no additional manoeuvres, except for signal connections and zero calibration, but the results are only valid on control mode with constant flow inflation. Moreover, some physical characteristics of the ventilator may affect the results (see Section 4.3). The program has been running every day in the Anaesthesia Department in Grenoble and in the ICU of Lyon-Sud hospitals for several months. The most important result, from our point of view, is that after initial adjustment of the thresholds on the first patients, each system connected to a ventilator proved to work, without any modification, on all other investigated patients ventilated with this ventilator. 6.1. Availability
Program authors.
listings may be obtained
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Acknowledgements The authors wish to thank the direction and staff of the Anaesthesia and Intensive Care Departments of CHU Lyon&d (Pr Banssillon) and CHU Grenoble (Pr Girardet), where patient data were acquired. The study was possible only because of the co-operation and assistance of all of the members of the ‘Groupe de Recherche et de Modelisation en Mecanique Ventilatoire’. The authors are also grateful to Kathryn Wright for her technical assistance in the preparation of this manuscript in English. This work was supported by ‘Region RhoneAlpes’, ‘Delegation Regionale a la Recherche Clinique du CHU Grenoble’ and TAEMA. References [I] J.H.T. Bates, A. Rossi and J. Milk-Emili, Analysis of the behavior of the respiratory system with constant inspiratory flow, J. Appt. Physiol. 58 (1985) 1840-1848 [2] A. Rossi, S.B. Gottfried, B.D. Higgs, L. Zocchi, A. Grassjno and J. Milic-Emili, Respiratory mechanics in mechanically ventilated patients with respiratory failure, J. Appl. Physiol. 58 (1985) 1849-1858 [3] R. Peslin and J.J. Fredberg, Oscillation mechanics of the
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respiratory system,in: Handbook of Physiology. Section 3: The Respiratory system.Vol. III: Mechanics of breathing, Ed. P.T. Macklem, pp. 145-177 (American Physiological Society, Bethesda, MD; 1986). 141 P.F.Baconnier, P.A. Levy and J. Milic-Emih, Techniques d’etude de la mtcanique ventilatoire chez les patients en ventilation artiftcielle, RCanim. Soins intensifs Med. Urgence 3 (1987) 75-79. ]51 M. Bemasconi, Y. Ploysongsang, S.B. Gottfried, J. Mihc-Emih and A. Rossi, Respiratory compliance and resistance in mechanically ventilated patients with acute respiratory failure, Intensive Care Med. 14 (1988) 547-553. [61 J.H.T. Bates and J. Milic-Emili, The flow interruption technique for measuring respiratory resistance, J. Crit. Care 6 (1991) 227-238 I71 R.J. Korst, R. Orlando III, N.S. Yeston, M. Mohn, A.C. de GraR and E. Gluck, Validation of respiratory mechanics software in microprocessor-controlled ventilators, Crit. Care Med. 20 (1992) 1152-I 156. [sl W.G. Sanbom, Microprocessor-based mechanical ventilation, Respir. Care 38 (1993) 72-109. 191 A.M. Lorino, D. Benhamou, H. Lorino and A. Harf, A computer&d method for measuring respiratory mechanics during mechanical ventilation, Bull. Eur. Physiopathol. Respir. 22 (1986) 8 l-84. [101 J.P. Mortola, J.T. Fisher, B. Smith, G. Fox and S. Weeks, Dynamics of breathing in infants, J. Appl. Physiol.: Respir. Environ. Exercise Physiol. 52 (1982) 1209-1215. 1111P. Baconnier, A. Eberhard, P.-Y. Carry, J.-P. Perdrix, J.M. Fargnoli and F. Coppo, Continuous monitoring of PEEPi, Intensive Care Med. 18 (1992) S94. VI P.M. Suratt, D.H. Owens and W.T. Kilgore, A pulse method of measuring respiratory system compliance, J. Appl. Physiol.: Respir. Environ. Exercise Physiol. 49 (1980) 1116-1121. 1131 J.H.T. Bates, I.-V. Hunter, P.D. Sly, S. Okubo, S. Fihatrauh and J. Milic-Emili, Effect of valve closure time on the determination of respiratory resistance by flow interruption, Med. Biol. Eng. Comput. 25 (1987) 136-140. 1141 J.H.T. Bates, P. Baconnier and J. Milic-Emili, A theoretical analysis of the interrupter technique for measuring respiratory mechanics, J. Appl. Physiol. 64 (1988) 2204-2214. iI51 J.-P. Bachy, A. Eberhard, P. Baconnier and G. Benchetrit, A cycle by cycle shape analysis of biological rhythms: application to respiratory rhythm, Comput. Methods Programs Biomed. 23 (1986) 297-307. 1161P. Baconnier, A. Eberhard, J.-P. Perdrix, P.-Y. Carry and J.-M. Fargnoh, Validation of respiratory resistance monitoring using a test lung, Intensive Care Med. 20 (1994) S32. P.M. Suter, H.B. Fairley and M.D. Isenberg, Optimum end-expiratory pressure in patients with acute pulmonary failure, N. Engl. J. Med. 6 (1975) 284-289.
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ELSEVIER
A computer program for automatic measurement of respiratory mechanics in artificially ventilated patients Pierre F. Baconnier* a, Pierre-Yves Carryb, Andr6 Eberhardc, Jean-Pierre Perdrixb, Jean-Marc Fargnolid aPRETA-TIMC/lhiAG. Laboraloire TMC, Faculte de M&iecine de Grenoble, 38706 La Tronche, bDPpartemenr d;4nesthksie-R&animation, CHU Lyon&d, Pierre-Benite. France CLMC/IMAG, VniversitC Joseph Fourier, Grenoble, France ‘Dkpartement d;4nesthkie-Rkanimation. CHU Grenoble, Lo Tronche, France
France
Received 2 August 1994; revision received IO May 1995; accepted 2 June 1995
A program for automatic and periodic determination of respiratory mechanics in artificially ventilated patients is described.Airway pressureand flow signalsare obtainedfrom the ventilator in the controlled ventilation modewith constantflow inflation and end-inspiratorypause.Periodically,the programrecordsboth signalsfor a giventime and it deliits a ventilatory cycle and its componentsout of this record.Then, four mechanicalparametersof the respiratory systemare calculated:(1) Rinit, the resistanceobtained with the end-inflation occlusiontechnique;(2) E,, the elastance. (inspiratory) calculatedfrom the slopeof the airway pressureprofile during inflation; (3) 7, the expiratory timeconstant;(4) PEEP,the globalpositiveendexpiratory pressure.All parametermeasurements havebeenevaluated in experimentalconditions,and are in good agreementwith referencevalues.The completesoftwareincludesthe displayof the signalsand of the trendstogetherwith automaticdisk file backups.An additional programallowsone to displaythe trendsagainandto createtabletext tilescontainingall the recordeddata for further analysis.The system proved to work in ICU and anaesthesia patientswith various ventilators. Keywords: Respiratorymechanics;Signal analysis;Monitoring; Artificially ventilated patient
1. Introduction
It is common for patients to ventilated during anaesthesia or units (ICU). A detailed analysis tory mechanics can readily be * Corresponding author.
be mechanically in intensive care of their respiraperformed with
available methods [l-6], based on simple models able to satisfactorily describe the transfer function between airway pressure (considered as the input variable) and flow (considered as the output variable). Several microprocessor-controlled ventilators available for clinical use contain optional computer software programs capable of performing nearly instantaneous determination of respira-
0169-2607/95/$09.50 0 1995 Elsevier Science Ireland Ltd. All rights reserved SSDZ 0169-2607(95)01651-Z
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tory system resistance and compliance [7]: (a) the resistance value is usually obtained as the total pressure drop during an end inspiratory pause divided by the flow immediately before interruption (this resistance (&,J is not a good estimation of airway resistance as it also includes lung tissue and rib cage viscances); (b) the compliance value is obtained as tidal volume divided by plateau pressure at the end of an end inspiratory pause without correction for global positive end expiratory pressure (PEEP). However, although many of today’s microprocessor-controlled ventilators offer one or a number of algorithmically controlled manoeuvres, the paucity of supportive or critical data in the literature suggests that these features are little used [8]. That these parameters are only obtained on demand with almost all the ventilators, is a possible reason for the little use of this option. Modern ventilators may provide voltage signals corresponding to pressure in airways and flow profiles.. The system proposed in the present study uses this information to build a signal processing system which periodically analyses the airway pressure and flow curves in order to provide an automatic system for detecting early trouble of the ventilatory mechanical system in artificially ventilated patients. The aim is to propose a continuous, automatic and non-invasive determination of ventilatory mechanics parameters: airway resistance, respiratory system elastance, global PEEP, and expiratory time constant. Global PEEP must be obtained without any end-expiratory pause or any manoeuvre from the clinical staff, and the elastance value (inverse of compliance) must be independent of global PEEP. The clinicians should be able to further analyse information gathered during the monitoring phase on a spreadsheet software. In the first section, the physiological theory and related computational methods are described. The second section deals with the description of the aigorithms in handling real signals. Validation and applicability of methods are presented in the third section. The fourth section is devoted to a detailed presentation of the program written in Pascal.
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methods and theory
2.1. Characterisation of the mechanical respiratory system The mechanical respiratory system is usually considered as a linear system made up of one elastic compartment connected to the outside pressure through a flow resistive component [9]. Its motion equation is then: P(t) = E. V(t) + R- V’(t)
(1)
where, at any time t, P(t) is the driving pressure imposed by the ventilator at the tracheal tube, V(t) is the compartment volume above its relaxation level and the flow V’(t)= dV/dt; R is the resistance to flow and E the elastance of the compartment, R and E being constant. For patients with a normal ventilatory function, simple estimates of R and E usually provide adequate information to the physician about the state of the patient’s mechanical respiratory system even though such a linear system is not a perfect reflection of the real system. When the system is relaxed (P(t) = 0) from any given volume above the relaxation level, the resulting passive deflation flow presents an exponential profile. Asstmring that the respiratory system is linear and made up of one compartment, a simple parameter may be obtained from the flow curve during passive expiration, namely the expiratory time constant (7) of the system [lo]. If the system considered behaves as a single compartment, then one gets r = R/E. In the real situation, this is not the case and differences arise for two main reasons: (1) at expiration, the time constant of the patient-ventilator system includes the effect of the expiratory limb of the ventilatory circuit, while at inspiration, R and E deal only with the portion situated between the Y connector and alveoli; (2) in some patients, some flow limitation occurs during expiration due to dynamic compression of the airways. In some circumstances (increased expiratory resistance, lowered elastance, or both), the system cannot reach its relaxation volume before the end of expiration. The lung volume at the end of expiration then increases with each cycle until a
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dynamic equilibrium is reached. At this equilibrium, the pressure in the lungs at the end of expiration is positive and called ‘intrinsic positive end expiratory pressure’ (intrinsic PEEP or PEEPi). To avoid ruptures of the alveolar wall, the physician needs to monitor this PEEPi. A simple means of measurement is to close the airways at the end of expiration and to measure the airway pressure. This manoeuvre requires active participation on the part of the physician explaining why PEEPi is not commonly monitored in clinical situations. In some other circumstances, the physician may have to impose an external PEEP which is made easy by modern ventilators. Both PEEPi and imposed PEEP may be operating at the same time in some cases and when this occurs, the clinician is interested in the variations of the global PEEP. In the present study, we will develop a simple mathematical way for estimating E, R, r and global PEEP from pressure and flow signals [l 11. 2.2. The three phases imposed by the ventilator The ventilator cycle we will consider includes three phases, namely active inflation, pause, and passive deflation (see Fig. 1). Each phase is utilised for estimating one or two mechanical parameters of the respiratory system. For each phase, the signal processing principle will be described below (for detailed computations, see Section 3 - Algorithms). 2.2.1. Inflation Among the various inflation profiles that can be chosen by the physician, a constant flow inflation is usually available in most modem ventilators. The breathing cycle considered here (see Fig. 1) then has inflation at constant flow. The first derivative of Eq. 1 gives: P’(t) = E. V’(t) + R. V”(t) where P’(t) = dPldt and V”(t) = dV’ldt. During a constant flow inflation, V” theoretically zero. Then (2) can be written P’(t) = E- v’(t)
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-Inflation-Pause 1 ::
.
. . . . .
. . . . . .
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Fig. I. A typical ventilatory cycle. Flow (V’) and airway pressure (P) profiles for a breathing cycle as imposed by a mechanical ventilator for a patient. During inflation, the ventilator imposes a constant flow. I valve: inspiratory valve; E valve: expiratory valve; Pm,: the maximal pressure reached during the cycle; Pp: the pressure at the end of the pause.
and E is obtained as P’(t)lV’(t) [12]. To obtain this estimation of E one does not need to wait for a stable occlusion pressure and then E can be estimated on any normal cycle provided that a constant pressure slope is observed. As one can see on Fig. 1, the slope of P(t) during inflation is far from constant from the very beginning. This is due to: (a) the time the ventilator takes to establish the desired constant inflation flow; (b) the time the respiratory system takes to reach a dynamic steady state. However, as is obvious in Fig. 1, P(t) presents a linear portion on almost all inflation. This happened to have been verified in all patients and ventilators studied, which allowed us to look for, and find, a linear relationship between P(t) and time during some part of inflation. 2.2.2. Pause At the beginning of the pause, the inflation valve rapidly closes while the deflation valve remains closed. Abruptly interrupting the inflation flow induces: (a) a rapid drop of P(t) from its maximal value, P,,,; (b) a slower decrease during the pause (see Fig. 1).
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The interrupter method [l] relies on the hypothesis that the fast initial drop in P(t) is due to the vanishing of the resistive pressure associated with air flow entering the airways. P(t) generally reaches a stable plateau (the elastic recoil pressure of the respiratory system, Pat.) in approximately 5 s [6]. This slow decrease i.s usually attributed to one or both of two phenomena: (1) gas redistribution between ventilatory units previously inflated differently because of time constant differences; (2) stress relaxation in tissues of the respiratory system [14]. Airway resistance. Following the interrupter method, the instantaneous resistance of the respiratory system (Ri”i,) is obtained by dividing the immediate pressure drop due to the occlusion by the flow preceding the occlusion. In order to measure this pressure drop, one needs the pressures before and after the inflation valve closes. If the pressure immediately before occlusion is easily determined, the estimation of the pressure at the time the valve is entirely closed remains controversial [13]. Indeed, the pressure profile presents at the beginning of the pause an oscillatory behaviour linked both to valve functioning and to inertia of air moving through the ventilator tube. Moreover, the usual exponential lit proposed for the pressure during the pause is not adapted to the actual clinical situation where repetitive pauses cannot exceed 10% of the whole ventilatory cycle. We chose to lit the pressure curve with a straight line at the part of the pause situated after oscillations vanished. The estimation of the pressure after inflation valve closure is obtained as the back extrapolation of the straight line to the instant at which occlusion begins. Global PEEP. In the actual clinical situation, where repetitive pauses cannot exceed 10% of the whole ventilatory cycle, the plateau value is never reached (see Fig. 1) and we called Pp the pressure at the end of the pause. Then, the total pressure drop during the pause (P,,, - Pp, see Fig. 1) slightly underestimates the pressure needed to impose air flow and movement of the respiratory system during inflation (dynamic pressure). During inflation, after a dynamic steady state has been established, the pressure imposed by the ventilator at any time t includes this dynamic pressure and
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the elastic recoil pressure corresponding level of pulmonary volume (Paa( V(t)): P(t) = Pm, -
PP
+ PER(V(t))
to the
(4)
This elastic recoil pressure includes the global PEEP (PEEP) and the elastic recoil pressure due to the volume imposed by the ventilator (V”(t)). At the very beginning of inflation (t = O+) this elastic recoil pressure is zero. Then PaR( I/(0+)) = PEEP
(5)
One can then compute global PEEP as PEEP = P(O+) - (Pmax - Pp)
(6)
As Pp overestimates PEL, P,,,,, - Pp underestimates Pm,, - PEL and then the calculated PEEP overestimates real global PEEP. 2.2.3. Deflation
At the end of the pause, the deflation valve opens, letting air flow out of the lung through the patient’s airways, the tracheal tube, and the expiratory part of the ventilator. This passive deflation begins with a rapid increase of the expiratory flow followed by an exponential like evolution of this flow towards zero (flow may not reach zero during expiration when some PEEPi is present). The proposed signal processing system waits until the exponential evolution is established and then a first order regression of flow versus volume (calculated as flow integral) is carried out and the slope of this regression line gives the time constant of these curves [lo]. 3. Algorithms
Periodically, when a measure occurs (see Section 5.3), we dispose of both pressure and flow signals sampled for a period of time which ensures recording a complete ventilatory cycle. The cycle must first be delimited, which means identifying the instants the cycle starts and ends. Then the three phases imposed by the ventilator must be identified. Furthermore, for each phase, we use appropriate algorithms intending to identify the four
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&nit: the instantaneous resistance when the inflation is interrupted, E,: the elastance of the respiratory system, 7: the expiratory time constant. PEEP: the positive end expiratory pressure, 3.1. CyeLe &li~itati~n
The flow signal is essential to fix cycle delimitation and because cycle delimitation is based on zero flow, it is very important to get a good zerovalue calibration at the beginning of each experiment (see Section 5.1). Theoretically, we know that the flow must be equal to zero during the pause, before it becomes negative with deflation. It can also be equal to zero at the end of deflation, before it becomes positive with next inflation. Actually, at the end of some expirations, the Bow oscillates around the zero value. We define the canning of a cycle as the last ascending zero crossing before the flow reaches a positive validation threshold (Fig. 2). The method used is presented elsewhere [la The cycle is deli~ted when we End two such successive zero crossings. The first is called LZC (left zero crossing) and the second is called RZC (right zero crossing). 3.2. Pause
Once the ventilatory cycle is delimited, we look for the maximum pressure between LZC and RZC. At this instant, called MPI (maximum pres-
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sure index), the pressure value is P,,,,, and the flow value is VP,,. It is at this instant that the inflation valve begins to close. During the pause, the sampled flow values are not strictly zero. We consider that the inflation valve stops closing when the flow decreases below another positive threshold. This instant is called ZFI (zero flow index). Similarly, we locate the instant at which the deflation valve opens, called ES1 (expiration start index), where the flow falls below a negative threshold {Fig. 3). At the beginning of the pause, the pressure drops rapidly and presents oscillations which damp down, followed by a slower decrease. We chose this last phase of the pause (the second half of the interval ZFI-ESI) to carry out a linear regression on the pressure. At the two extremities of the pause, this line gives us noteworthy values. At ES1 it gives Pp, the elastic recoil pressure. Back extrapolated at MPI, it gives PO, an approximate value of the airway pressure i~ediately after occlusion. The pressure drop Pm, - PO divided by the flow value just before occlusion (VP,,,,,) gives us &nit, an approximation of the resistance of the system when inflation is interrupted. The total pressure drop during the pause (Pm,, - Pr) is called dPdif and is used for the determination of global PEEP. 3.3. In~at~on Normally, during the constant flow inflation imposed by the ventilator, the pressure should increase linearly. We need to know the slope S of
Fig. 2. Cycle deIi~~ti~n using flow. At the end of expiration, the flow signal can oscillate around 0. The end of a cycle (and the beginning of the next one) is the last ascending zero crossing before the flow passesa threshold. The cycle we analyse goes from the first end of cycle encountered: left zero crossing (LZC), to the second one: right zero crossing (RZC).
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this increase to determine the elastance. In practice, even after waiting for oscillation delay (necessary in order to eliminate a transient phase) we can observe different behaviours. More often, the pressure increases in a truly linear fashion all along the remainder of inflation until MPI (see Fig. 4a). Sometimes, however, we distinguish two different slopes at the beginning and at the end of inflation (see Fig. 4b and c). At other times, generally associated with a strong resistance, the pressure increases rapidly at the beginning and then increases more and more slowly preceding a linear behaviour at the end of inflation (Fig. 4~). The question in such cases is: what is the correct slope S to use for the calculation of the elastance? Our program proceeds in the following way: after an oscillation delay, the remainder of the inspiration is divided into two equal parts and a linear regression of the pressure is performed on each interval. Thus we obtain two linear approximations of the pressure: Pi(t) with a slope S, and P*(t) with a slope S,. Three cases may be encountered: (a) The two slopes are not significantly different (the ratio S,& lies between 0.9 and 1.1). In this case, the slope we will use is the mean value of the two slopes: S = (S, + ST)/2
ES1
Fig. 3. Pressure fitting during the pause. (1) We look for MPI (maximum pressure index) * P,,,,, and V’ Pm (2) We define ZFI (zero flow index) and ES1 (expiration start index) and we tit the pressure curve with a straight line during the second half of the interval ZFI-ESI. At ES1 abscissa, this line gives Pp. Back-extrapolated at MPI abscissa, this line gives PO The total pressure drop during the pause is dPdif = P,, - P,.
dpdif
PEEP ::: UC
a - Rtz = 0.95
MPI
MPI
b _R12 Ql
= 0.67
C - RIZ = 1.53
@
Fig. 4. Pressure fitting during inflation. To calculate elastance, the pressure slope during the constant flow inflation must be known. After an oscillation delay (OD), the remainder of the inflation is divided in two equal parts. A linear regression of pressure is performed for each part and we look at the ratio of the slopes: R,,. (a) RI, is close to 1 (0.9 < RQ < 1.1) - the slope we use is the mean of the two slopes. If the ratio is significantly different from 1, we look to the mean squared error for the first part (Q,), and for the second part (Q& (b) Qt < Q2 * we use.the slope found when fitting during the first part of the inflation; (c) Q2 < Qt * we use the slope found when fitting during the second part of the inflation. In a11cases,the value of the first regression line at LZC abscissa abated of dPdif gives global PEEP.
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If the slopes are different, we look to the mean squared errors that we obtained for each half: Qi for the first half, and Q2 for the second. (b) Qi < Q2 * we will use the slope obtained when fitting the first half: S = S,; (c) Q2 < Qi * we will use the slope obtained when fitting the second half: S = &. The slope S obtained, divided by VMean (the mean value of the flow during the retained regression interval) gives the elastance E,. In all cases, the value of the first regression line P,(t) at LZC abated of dPdif gives global PEEP. 3.4. Deflation In order to determine r, the time constant of the passive deflation, we suppose that the volume profile during this phase is described by
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21
V’bi, and then oscillates preceding an exponential behaviour which tends towards zero (Fig. 5). In order to eliminate oscillations, we define RSI (regression start index) as the instant where the flow is two thirds of V’min. By integrating flow we get a volume value, and we perform a linear regression on the ratio flow/volume from RSI to RZC: V = kV’. The absolute value of the slope k of this regression line gives the expiratory time constant 7. 3.5. Formulas &it
summary
= (pm*x -
pOYV’pmx
E, = S/V’ Mean ~=l kl PEEP = P,(LzC)
- (P,,
- Pr)
V(t) = VO exp(-f/r). Then the flow is given by
4. Validation
V’(t) = -1/7V0 exp(-r/r),
4.1. Validation of mechanical parameters on a test lung In order to assessthe validity of our method, we have carried out a preliminary experiment on a test system: a Training Test Lung (Model 26OOi Dual Adult TTL/REG/, Michigan InstrumentsTM) connected via a conventional patient circuit, including an empty humidifier (Model 3000 HPD MedicalTM), to a CESAR@ ventilator (TAEMATM) set
and the following linear relationship holds true between volume and flow: V(r) = -TV’(t). In fact, when the deflation valve opens (ESI), the flow signal drops abruptly to a negative peak
Fig. 5. Flow/volume regression during deflation. First we look for the minimum flow during deflation, and then we define the regression start index (RSI) as the instant where flow equals two thirds of this minimum. By integrating flow we obtain a volume value, and we perform a linear regression on the flow/volume ratio from RSI to RZC. The absolute value of the slope of this line gives the expiratory time constant.
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in the controlled ventilation mode with constant flow inflation. This TTL is designed to simulate the mechanics of the adult ventilatory system from upper airways to the lung. Human lungs are simulated using two elastomer bellows. Elastance is simulated through a precision steel alloy spring stretched between the top plate of each lung and the body of the TTL (See Fig. 6). Elastance is adjusted by positioning the spring at various points along the top plate. Resistance is modified using different combinations of resistors (PneuFloTM Airway Resistors) placed on the hose assemblies simulating the airways. The PneuFlo resistors exhibit parabolic pressure change as a function of flow. The pressure and flow signals of the ventilator were fed into a micro-computer (AmstradTM 1640) via an ADC card (DC&C/TM/-O3 12 bits AD/DA card). The micro-computer determined the ventilatory mechanics parameters with the above described algorithm implemented with BorlandTM TurboPascal programming language. We determined ErS, Rinit and r for various pre-set resistances (23 different values) and elastances (four different values) and we compared measured and simulated values. The mean measurements of &nit, E,, and r for five consecutive automatic estimations were obtained for each resistor/elastance combination (mean variation less than 5%) and compared to the corresponding pre-set values. 4.1.1. Ri,it. We first calculated the true resistance (R,,) corresponding to each resistor combination and each imposed flow. The mean value
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“‘o-0 Rtrue (cm Hz 0. I-‘. s)
Fig. 7. Comparison between measured (Ri”it) and calculated (R,,) resistance of TTL.
of five consecutive automatic estimations of Ri,i( was compared to the corresponding Rtrue. The result is presented on Fig. 7. There is a significant correlation between measured and calculated values (Ri,it = 0.836 Rt, + 2.88 cm HzO.l-’ -s, r = 0.99, P C 0.001). The intercept corresponds to the resistance of tubing between the ventilator and the test lung. The slope is well explained by a model of compressibility of air in the humidifier [ 161. This slope effect
Measured Ers (cmHz0.V) 40
T
Ventilator
0
20 Preset Ers (cm HzO. I .‘I
40
Fig. 8. Comparison between measured and pre-set elastance Fig. 6. Side view (schematic) of the training test lung (TTLI.
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measures for each elastance. The reproducibility of the E measurement is such that, whatever the resistance, when comparing measured to pre-set values of E, one can see only four different points on the representative graph (Fig. 8). It is for this reason that each point is labelled with the corres~nding number of estimations. One can easily see that E,, is measured quite accurately. The relationship is very close to the identity line (measured E, = 0.92 preset E,, + 0.22, r = 0.99 P < 0.001). 41.3. 7. The expiratory time constant of the TTL is set by the values of both elastance and resistance. When looking to &it results, one notices that R, is probably underestimated by around 3 cm H20. 1-l -s. In order to assess the accuracy of time constant estimation, measured 7 ( I k I) was then compared to a calculated value obtained as R/E with R = R,,, + 3 (see Fig. 9). Our results show that the algorithm is valid (Ik I = 0.87 (R, + 3)/E- 0.07, r = 0.99, P < O.~l}, even in the present case where the expiratory resistance is
/ 0)
Fig. 9. Comparison between measured and estimated f.
may become important in high lung resistance situations. 4.1.2. E,,. As mentioned above, we used four different elastance values and several resistance
Table I PEEP values obtained on nine patients with the end expiratory occlusion method (measured PEEP) and our method (calculated PEEP) Patient
Measured PEEP
Calculated PEEP
Patient
Measured PEEP
Calculated PEEP
Patient
Measured PEEP
Calculated PEEP
1
0.1
1.7
6
5.5 2.5 2.9 7.0 6.6 7.4
3.5 2.2 4.0 6.7 5.6 7.6
3
8.5
8.8
4
1.3 8.4
5.0 9.2
11.7 10.8 10.9 13.7 15.6 16.6 16.0 17.1 15.5 16.0 15.6 15.2 15.0
9
2
10.0 11.0 11.0 12.0 13.0 13.0 13.0 15.0 15.0 15.0 16.0 16.0 16.0
5
5.7 5.1 7.4 6.2
6.8 6.4 7.1 9.2
7
6.8 8.2
8.4 6.2
8
1.0
3.5
2.0 2.0 2.0 2.0 2.0 6.0 6.0 9.0 9.0 9.0 11.0 11.0 11.0 13.0 13.0 16.0 16.0 16.0 16.0
4.6 2.2 3.1 5.0 3.5 6.1 6.0 10.0 9.9 8.3 10.9 il.2 13.5 15.1 15.1 14.6 14.5 14.5 14.2
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Calcutsted PEEP (cm Hz 0)
01 0
Measured
10 PEEP (cm H2 0)
20
Fig. 10. Comparison between calculated and measured PEEP.
not really constant since the PneuFlo resistors exhibit parabolic pressure change as a function of flow. 4.2. Global PEEP Contrary to previous parameters, direct measurement of global PEEP can be easily accomplished under real conditions with the help of a reference method: by occluding the airways at the
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end of a normal expiration, the pressure measured in the airways after occlusion is equal to global PEEP. We have experimented the validity of our method for estimating global PEEP on nine intensive care patients (see Table 1,). For patients 6 and 9, we benefited from the ‘best PEEP trial procedure’ [ 171 to get numerous values of PEEP. Briefly, this procedure consists of increasing progressively the imposed PEEP until m~imum oxygen transport is obtained. Measures have been done by imposing three to five end expiratory pauses at each tested PEEP level, with at least 10 ’ between each step. The comparison between the PEEP calculated by our program and the measured PEEP indicates a good correlation, and this was redemonstrated in every patient tested (see Fig. 10). There is a significant correlation between calculated and measured values (calculated PEEP = 0.91 measured PEEP + 1.53 cm H,O, r = 0.95, P < 0.001). The positive intercept corresponds to the slight overestimation already mentioned Section 2.2.2. 4.3. Applicability to different ventilators
The flow and pressure signals provided by three modern ventilators (Bennett 7200, Taema
)
~~~~t(s) ~~ y+ -1
Bennett
7200
Taema
Cesar
Siemens
LMA 900
Fig. 11. Flow and pressure signals provided by three ventilators. Ventilators operated under same conditions: test lung with same settings, controlled ventilation mode, constant flow inflation.
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CESAR, Siemens 900C) were recorded using the test lung with similar settings and we have tested the possibility of processing them with the present
As the signals ventilators, the characteristics of but the mechanics
are measured internally to the curves reflect not only the the patient’s respiratory system of the patient-ventilator system.
1 Ask for a RootLetter 1 1 Zero-valwscalibration )
Run algorithms for parameters’extraction :
Rinit , Ers ,Z & PEEP
I
Storeresults (and eventually save ii .RES file)
in END.RES file
Fig. 12. Program flow chart. User’s action process is described in Fig. 12
I
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F4
Fig. 13. User’s action processing.
As can be seen in Fig. 11, all signals present a linear pressure increase during inflation, with different transition times. Elastance is then easily measurable with our program. The pause profile, however, is very different from one ventilator to the other; for while the 9OOC and the CESAR exhibit a rapid closure (less than 50 ms in general), the 7200 requires at least 120 ms to close the inflation valve. Therefore, Rinit cannot be measured on patients ventilated with this device. The program developed by our team proved itself capable of calculating global PEEP from the signals emitted by each ventilator tested, since the total pressure drop during pause was measurable for each ventilation device. Finally, the expiratory time constant may be calculated from each of the expiratory flow curves shown, but the Siemens 9OOC has a peculiar PEEP control system which varies the expiratory resistance in order to impose the desired PEEP. In this situation, the expiratory time constant is modified by the respirator itself during the expiration and any estimation becomes impossible. In the specification file (see Section 5.9) the ventilator used is mentioned, and the program automatically discards the corresponding unvalid parameters.
5. Program description The program contains two main parts: the initialisation procedures and a main loop managing the automatic measurements and the processing of user’s actions (see Figs. 12 and 13). Two presentation modes are proposed to the user: an oscilloscope mode and a trend mode. In the present version, the oscillo mode has been chosen as the default mode as required by our users. However, the trend mode may be chosen as default mode very easily. 5.1. Initialisation First, the program asks the user for a ‘root letter’ to identify the experiment. Then the program needs a zero-value calibration: the respirator tube must be disconnected (0 pressure = atmospheric pressure) and the flow has to be set to 0 for a short time (5 s)‘. ’ Because of drift of zero lines, zero-value calibration is very important and has to be performed at the beginning of each experiment. On the contrary, the scaling factors depend essentially on the ventilator and on the AD converter. So the full scale calibration is performed previously by a special program for each ventilator-AD converter coupIe, and the scaling factors for pressure and flow so obtained are put in the specification file (see Section 5.9).
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Following which, the program runs automatically and no longer requires intervention on the part of the user. 5.2. The os~i~lo mode Both flow and pressure signals are sampled with a slow rate (about 20 Hz) and they are drawn on the screen (Fig. 14). 5.3. measure Periodically (every minute, or every m minute, depending on the corresponding specification parameter) a measure occurs: (a) curves are no longer displayed and a vertical straight line is drawn (Fig. 14); (b) both pressure and flow signals are sampled with a higher rate (about 100 Hz) until 1200 points are obtained for each of them; (c) the digital values are zerocorrected and brought to scale using two other specification parameters and then stored in buffers; (d) the program attempts to apply the algorithms described in section 3 and an error code is associated to the measure. When the algorithms fails (error code # 0), a bell rings and special values are stored instead of ventilation parameters. Afterwards, the program reenters the oscillo mode. 5.4. Trend mode When desired, the user can strike the space bar
Fig. 14. 0scillo mode screen. Pressure and flow are displayed with a slow rate {about 20 Hz). The vertical straight line means that a measure has been performed just before.
Fig. 15. Trend mode screen. This is an example of a trend screen after 26 measures. A042 1 means that the ‘root letter’ was A and the date was the 21st of April. Letters r, f and g are marks struck by the user before measures 9, 16 and 19.fmeans that the sampling values of the measure IO were saved in a .WKS file.
on the keyboard of the computer. Immediately (or at the end of the measure, if one is occurring) the screen displays the evolution of the four ventilatory mechanics parameters (Fig. 15). The X axes represent the time elapsed from the beginning of the experiment (time scale is adjusted automatically). For each measure a dash is drawn for each parameter. If the value is negative, a double depth dash is drawn at level 0 (see measures 7, 8 and 15 for the global PEEP). If the value exceeds the maximum of the scale, a double depth d .j is drawn at the top level (see measures 19 and 2b or the E,,). After a delay (10 s), the program automatically re-enters the oscillo mode. If a measure occurs during the trend mode, a square drawn in the middle of the screen advises the user. 5.5. Manual interventions Fl This key (after a conflation message) terminates execution. F2 This key induces creation of a disk file with a suffrx .WKS (see Section 5.7), containing the sampled values (both of flow and pressure) of the last measure, whatever the error code and the character f appears for the corresponding values on the trend screen (see measure 10 in Fig. 15).
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F3 Alternately, this key multiplies and divides the vertical scales of the current drawing (either in oscillo mode or in trend mode) by two. Original scales are initialised with specification parameters. F4 This key operates only if the last measure is successful. It induces the program to work in a particular way called the ‘burst’ mode: from this moment the measures follow one another without any delay between them. The screen displays only the number of the current measure, This feature is very useful when the user expects rapid variations of any ventilatory mechanics parameter consecutive to an action performed. The same key induces leaving ‘burst’ mode. Any other key (except the space bar which is used to switch from oscillo mode to trend mode) the user strikes during the program run is considered as a mark which will be associated with the next measure (see measures 9, 16 and 19 in Fig. 15).
of these tiles are successively Prefix-Ol.RES, Prefix-02.RES,... (the present example is: AO42LOl.RES, AO42L02.RES ,... ). This allows reconstruction not only of the four parameters (giving the missing PrefixEND.RES tile), but also various parameters (cycle duration, inflated volume, inflation duration,...) for the ventilatory cycle analysed for each measure. All .RES files are binary files. They are accessible by another program, either for review of the trend screen of an ex~riment, or to make text files in order to read them with a spreadsheet program such as ExcelTM. . WKSfiles: We have Seen (Section 5.5) that the F2 key induced the creation of a text file which contains the sample values of flow and pressure signals of the last measure. The names of these files are, successively Prefix_01 .WKS, Prefix-02. WKS, . .. {for our example: A042L01. WKS, A042L02. WKS,. . .).
5.6. Automatic stop Due to limitations of the memory buffers, if the key Fl (voluntary stop) is not used, the program will run until 480 measures have been performed. This allows observation of the ventilatory mechanics parameters for 8 h if M (specification parameter giving the minutes delay between two consecutive measures) is one, and a whole day (24 h) if m is three! Of course, use of the ‘burst’ mode decreases duration.
.?,8. hardware and software ~pe~~~~ation~ Our monitoring program, called ‘MON’, runs on any PC compatible computer with 640 kB memory (a) linked to different respirators: Siemens @OOC), Taema (CESAR), Bennett (7200); (b) equipped with different analogue to digital cards; (c) in different medical situations (intensive care, anaesthesiology, neonatology...); (d) with different purposes (monitoring, expe~mentation, equipment’s test...). File backups can be done on floppy or hard disks. The prolgram works on real time mode, the computer time needed for signal analysis varying from less than 1 (80386) to 5 s (8086) following the CPU performance. The programming language used is BorlandfM TurboPascal. An external specification file allows the program to adapt to each situation. It contains various specification parameters (see Section 5.9). Several specification files may be present in the current directory (all of them have the suffix DON), and the user chooses whichever he prefers during the run. For example, if he enters mon myspec, the program will read the environment settings in the file MYSPEC.~N (if he only
5.7. Files created by the program The ‘root letter’ entered at the beginning of the execution (see Section 5.1) and the date of the day are used to construct the Prejx: for example, if the ‘root letter’ is A and if the date of the day is the 21st of April, the Prefix will be AO421. This prefix is used to produce the names of all the files created by the program during execution. . RESfiles: When the program is stopped (either automati~ly or vol~~rily), the results of all measures are saved in a file so called PrefixEND.RES (the present example is: AO421END. RES). Nevertheless, in order to avoid losing everything if the program crashes, every 15 measures, all the values for each measure are saved. The names
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enters mon, the program lets the user choose from among all DON tiles which are present in the current directory).
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ters are also different from one situation (anaesthesia) to the other (neonates,...). Threshold values result from successive trials and errors for each ventilator-AD converter couple.
5.9. Specification file
This is the text tile read when the program starts. It contains information which permits the program to adapt to each hardware and software situation: (1) Hardware (ADC card and ventilator characteristics): (a) ADC indicator: 0, 1 or 2 (as three different ADC cards are currently used); (b) Physical channel numbers for flow and pressure; (c) Lag (ms) pressure/flow; (d) OD: oscillations delay (s); (e) Scaling factors for flow and pressure. (2) Software: (a) Sampling rate during measures (Hz); (b) Maximum number of measures (5 480); (c) Maximum scale values for flow and pressure in oscillo mode; (d) Maximum scale values for each ventilatory parameter in trend mode; (e) Delay between two measures (m min); (f) Thresholds for cycle delimitation. Some ventilators do not provide perfectly simultaneous flow and pressure signals. We then measure (and compensate by the program) the ‘lag (ms) pressure/flow’, determined previously from high speed paper recording of flow and pressure signals. The oscillation delay (OD) depends on the ventilator valve speed and has been determined in the same way (high speed paper recording). The sampling rate used is 100 Hz for adults and 250 Hz for neonates. The maximum number of measures, together with the delay between two measures, limit the total duration of the program run. The maximum number of measures is limited to 480 by the computer memory, then a 3-min delay has been chosen for 24-h monitoring. Maximum scales for flow and pressure are respectively 1 1. s-’ and 40 cm Hz0 for adult anaesthesia. They were modified at demand for intensive care and neonates. Maximum scale values for ventilatory parame-
6. Discussion The respiratory system resistance usually calculated in ventilators is obtained as the total pressure drop during an end inspiratory pause divided by the flow immediately before interruption (&J. Rtot includes the viscoelastic properties of lung and chest wall, as well as gas redistribution among units having different time constants. Moreover, the calculation of R,,, requires that a plateau pressure has been reached, which implies that a specific cycle has been imposed to the patient. This manoeuvre, even automatically controlled, has to be decided and commanded. Either this is done periodically and then a rapid variation of R may be missed, or it is done at demand and this will not provide a way to detect any change as the demand will probably follow the observation of a change in the clinical state of the patient. The compliance value proposed by ventilators is obtained as tidal volume divided by plateau pressure - PEEP. In the Cesar ventilator, a periodic end-expiratory pause for global PEEP measurement is automatically performed, allowing the correction with ‘auto-PEEP’. As said above, the method we use is independent of PEEP and does not require end expiratory pauses. Moreover, ventilatory mechanics measured during specific cycles, a,s proposed by some ventilators, may not be the exact reflection of ventilatory mechanics during normal cycles. 7 is very useful in neonatal intensive care since the expiratory time constant may vary quickly, inducing, for example, intrinsic PEEP if expiratory time is not immediately lengthened. The most important difference between the present system and others designed for ventilatory mechanics monitoring, is that it allows automatic measurement of mechanical parameters without any operation by nursing or medical staff. It has been designed to run with low cost materials and
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without any additional measurement devices. Therefore, it demands no additional manoeuvres, except for signal connections and zero calibration, but the results are only valid on control mode with constant flow inflation. Moreover, some physical characteristics of the ventilator may affect the results (see Section 4.3). The program has been running every day in the Anaesthesia Department in Grenoble and in the ICU of Lyon-Sud hospitals for several months. The most important result, from our point of view, is that after initial adjustment of the thresholds on the first patients, each system connected to a ventilator proved to work, without any modification, on all other investigated patients ventilated with this ventilator. 6.1. Availability
Program authors.
listings may be obtained
from the
Acknowledgements The authors wish to thank the direction and staff of the Anaesthesia and Intensive Care Departments of CHU Lyon&d (Pr Banssillon) and CHU Grenoble (Pr Girardet), where patient data were acquired. The study was possible only because of the co-operation and assistance of all of the members of the ‘Groupe de Recherche et de Modelisation en Mecanique Ventilatoire’. The authors are also grateful to Kathryn Wright for her technical assistance in the preparation of this manuscript in English. This work was supported by ‘Region RhoneAlpes’, ‘Delegation Regionale a la Recherche Clinique du CHU Grenoble’ and TAEMA. References [I] J.H.T. Bates, A. Rossi and J. Milk-Emili, Analysis of the behavior of the respiratory system with constant inspiratory flow, J. Appt. Physiol. 58 (1985) 1840-1848 [2] A. Rossi, S.B. Gottfried, B.D. Higgs, L. Zocchi, A. Grassjno and J. Milic-Emili, Respiratory mechanics in mechanically ventilated patients with respiratory failure, J. Appl. Physiol. 58 (1985) 1849-1858 [3] R. Peslin and J.J. Fredberg, Oscillation mechanics of the
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