Frederico C. Jandre

Positive end-expiratory pressure at minimal respiratory elastance represents the best compromise between mechanical stress and lung aeration in oleic acid induced lung injury.

IntroductionProtective ventilatory strategies have been applied to prevent ventilator-induced lung injury in patients with acute lung injury (ALI). However, adjustment of positive end-expiratory pressure (PEEP) to avoid alveolar de-recruitment and hyperinflation remains difficult. An alternative is to set the PEEP based on minimizing respiratory system elastance (Ers) by titrating PEEP. In the present study we evaluate the distribution of lung aeration (assessed using computed tomography scanning) and the behaviour of Ers in a porcine model of ALI, during a descending PEEP titration manoeuvre with a protective low tidal volume.MethodsPEEP titration (from 26 to 0 cmH2O, with a tidal volume of 6 to 7 ml/kg) was performed, following a recruitment manoeuvre. At each PEEP, helical computed tomography scans of juxta-diaphragmatic parts of the lower lobes were obtained during end-expiratory and end-inspiratory pauses in six piglets with ALI induced by oleic acid. The distribution of the lung compartments (hyperinflated, normally aerated, poorly aerated and non-aerated areas) was determined and the Ers was estimated on a breath-by-breath basis from the equation of motion of the respiratory system using the least-squares method.ResultsProgressive reduction in PEEP from 26 cmH2O to the PEEP at which the minimum Ers was observed improved poorly aerated areas, with a proportional reduction in hyperinflated areas. Also, the distribution of normally aerated areas remained steady over this interval, with no changes in non-aerated areas. The PEEP at which minimal Ers occurred corresponded to the greatest amount of normally aerated areas, with lesser hyperinflated, and poorly and non-aerated areas. Levels of PEEP below that at which minimal Ers was observed increased poorly and non-aerated areas, with concomitant reductions in normally inflated and hyperinflated areas.ConclusionThe PEEP at which minimal Ers occurred, obtained by descending PEEP titration with a protective low tidal volume, corresponded to the greatest amount of normally aerated areas, with lesser collapsed and hyperinflated areas. The institution of high levels of PEEP reduced poorly aerated areas but enlarged hyperinflated ones. Reduction in PEEP consistently enhanced poorly or non-aerated areas as well as tidal re-aeration. Hence, monitoring respiratory mechanics during a PEEP titration procedure may be a useful adjunct to optimize lung aeration.

Effects of descending positive end-expiratory pressure on lung mechanics and aeration in healthy anaesthetized piglets

IntroductionAtelectasis and distal airway closure are common clinical entities of general anaesthesia. These two phenomena are expected to reduce the ventilation of dependent lung regions and represent major causes of arterial oxygenation impairment in anaesthetic conditions. The behaviour of the elastance of the respiratory system (Ers), as well as the lung aeration assessed by computed tomography (CT) scan, was evaluated during a descendent positive end-expiratory pressure (PEEP) titration. This work sought to evaluate the potential usefulness of Ers monitoring to set the PEEP in order to prevent tidal recruitment and hyperinflation of healthy lungs under general anaesthesia.MethodsPEEP titration (from 16 to 0 cmH2O, tidal volume of 8 ml/kg) was performed, and at each PEEP, CT scans were obtained during end-expiratory and end-inspiratory pauses in six healthy, anaesthetized and paralyzed piglets. The distribution of lung aeration was determined and the tidal re-aeration was calculated as the difference between end-expiratory and end-inspiratory poorly aerated and normally aerated areas. Similarly, tidal hyperinflation was obtained as the difference between end-inspiratory and end-expiratory hyperinflated areas. Ers was estimated from the equation of motion of the respiratory system during all PEEP titration with the least-squares method.ResultsHyperinflated areas decreased from PEEP 16 to 0 cmH2O (ranges decreased from 24–62% to 1–7% at end-expiratory pauses and from 44–73% to 4–17% at end-inspiratory pauses) whereas normally aerated areas increased (from 30–66% to 72–83% at end-expiratory pauses and from 19–48% to 73–77% at end-inspiratory pauses). From 16 to 8 cmH2O, Ers decreased with a corresponding reduction in tidal hyperinflation. A flat minimum of Ers was observed from 8 to 4 cmH2O. For PEEP below 4 cmH2O, Ers increased in association with a rise in tidal re-aeration and a flat maximum of the normally aerated areas.ConclusionIn healthy piglets under a descending PEEP protocol, the PEEP at minimum Ers presented a compromise between maximizing normally aerated areas and minimizing tidal re-aeration and hyperinflation. High levels of PEEP, greater than 8 cmH2O, reduced tidal re-aeration but increased hyperinflation with a concomitant decrease in normally aerated areas.

A closed-loop mechanical ventilation controller with explicit objective functions

A closed-loop lung ventilation controller was designed, aiming to: 1) track a desired end-tidal CO/sub 2/ pressure (P/sub et/CO/sub 2/), 2) find the positive end-expiratory pressure (PEEP) of minimum estimated respiratory system elastance (E/sub rs,e/), and 3) follow objective functions conjectured to reduce lung injury. After numerical simulations, tests were performed in six paralyzed piglets. Respiratory mechanics parameters were estimated by the recursive least squares (RLS) method. The controller incorporated a modified PI controller for P/sub et/CO/sub 2/ and a gradient descent method for PEEP. In each animal, three automated PEEP control runs were performed, as well as a manual PEEP titration of E/sub rs,e/ and a multiple P/sub et/CO/sub 2/ step change trial. Overall performance indexes were obtained from PEEP control, such as minimum E/sub rs,e/ (37.0/spl plusmn/4.5cmH/sub 2/O.L/sup -1/), time to reach the minimum E/sub rs,e/ (235/spl plusmn/182 s) and associated PEEP (6.5/spl plusmn/1.0 cmH/sub 2/O), and from P/sub et/CO/sub 2/ control, such as rise time (53 /spl plusmn/ 22 s), absolute overshoot/undershoot of P/sub et/CO/sub 2/ (3/spl plusmn/1 mmHg), and settling time (145 /spl plusmn/ 72 s). The resulting CO/sub 2/ controller dynamics approximate physiological responses, and results from PEEP control were similar to those obtained by manual titration. Multiple dependencies linking the involved variables are discussed. The present controller can help to implement and evaluate objective functions that meet clinical goals.

Detection of tidal recruitment/overdistension in lung-healthy mechanically ventilated patients under general anesthesia.

BACKGROUND:The volume-dependent single compartment model (VDSCM) has been applied for identification of overdistension in mechanically ventilated patients with acute lung injury. In this observational study we evaluated the use of the VDSCM to identify tidal recruitment/overdistension induced by tidal volume (VT) and positive end-expiratory pressure (PEEP) in lung-healthy anesthetized subjects. METHODS:Fifteen patients (ASA physical status I–II) undergoing general anesthesia for elective plastic breast reconstruction surgery were mechanically ventilated in volume-controlled ventilation (VCV), with VT of 8 mL•kg−1 and PEEP of 0 cm H2O. With these settings, ventilatory mode was randomly adjusted in VCV or pressure-controlled ventilation (PCV) and PEEP was sequentially increased from 0 to 5 and 10 cm H2O, 5 min per step. Thereafter, PEEP was decreased to 0 cm H2O, VT increased to 10 mL•kg−1 and, keeping minute ventilation constant, PEEP was similarly increased to 5 and 10 cm H2O. Airway pressure and flow were continuously recorded and fitted to the VDSCM with or without considering flow-dependencies. A “distension index” (%E2) derived from the VDSCM was used to assess VT and PEEP-induced recruitment/overdistension. Positive and negative values of %E2 suggest tidal overdistension or tidal recruitment, respectively. In addition, the linear respiratory system elastance was calculated. Comparisons among variables at each PEEP value, VT setting, ventilatory mode, and regression model considering or not considering flow-dependencies were performed with the Wilcoxon-sign rank test for paired samples (P < 0.05). Multiple comparisons were corrected with the Bonferroni method. The relative change in the estimated noisy variance was used as an index of the goodness of fit of the models. RESULTS:VDSCM including the flow-dependent parameter significantly improved estimated noisy variance in almost all experimental conditions (11.2 to 71.4, smallest of the lower and highest of the upper 95% confidence intervals). No differences in %E2 were observed between VCV and PCV, at comparable VT and PEEP levels, when flow-dependencies were included in the regression model. The negligence of the flow-dependent parameter systematically led to an underestimation of %E2 in PCV compared to VCV mode (all P < 0.02). At a given VT, %E2 was negative at a PEEP of 0 cm H2O and significantly increased with PEEP, being almost 0 at a PEEP of 5 cm H2O. At a given level of PEEP, %E2 significantly increased with VT. CONCLUSIONS:The distension index %E2, derived from the VDSCM considering flow-dependencies, seems able to identify tidal recruitment/overdistension induced by VT and PEEP independent of flow waveform in healthy lung-anesthetized patients.

Volume-independent elastance: a useful parameter for open-lung positive end-expiratory pressure adjustment.

BACKGROUND:A decremental positive end-expiratory pressure (PEEP) trial after full lung recruitment allows for the adjustment of the lowest PEEP that prevents end-expiratory collapse (open-lung PEEP). For a tidal volume (Vt) approaching zero, the PEEP of minimum respiratory system elastance (PEEPminErs) is theoretically equal to the pressure at the mathematical inflection point (MIP) of the pressure-volume curve, and seems to correspond to the open-lung PEEP in a decremental PEEP trial. Nevertheless, the PEEPminErs is dependent on Vt and decreases as Vt increases. To circumvent this dependency, we proposed the use of a second-order model in which the volume-independent elastance (E1) is used to set open-lung PEEP. METHODS:Pressure-volume curves and a recruitment maneuver followed by decremental PEEP trials, with a Vt of 6 and 12 mL/kg, were performed in 24 Wistar rats with acute lung injury induced by intraperitoneally injected (n = 8) or intratracheally instilled (n = 8) Escherichia coli lipopolysaccharide. In 8 control animals, the anterior chest wall was surgically removed after PEEP trials, and the protocol was repeated. Airway pressure (Paw) and flow (F) were continuously acquired and fitted by the linear single-compartment model (Paw = Rrs·F + Ers·V + PEEP, where Rrs is the resistance of the respiratory system, and V is volume) and the volume-dependent elastance model (Paw = Rrs·F + E1 + E2·V·V + PEEP, where E2·V is the volume-dependent elastance). From each model, PEEPs of minimum Ers and E1 (PEEPminE1) were identified and compared with each respective MIP. The accuracy of PEEPminE1 and PEEPminErs in estimating MIP was assessed by bias and precision plots. Comparisons among groups were performed with the unpaired t test whereas a paired t test was used between the control group before and after chest wall removal and within groups at different Vts. All P values were then corrected for multiple comparisons by the Bonferroni procedure. RESULTS:In all experimental groups, PEEPminErs, but not PEEPminE1, tended to decrease as Vt increased. The difference between MIP and PEEPminE1 exhibited a lower bias compared with the difference between MIP and PEEPminErs (P < 0.001). The PEEPminE1 was always significantly higher than the PEEPminErs (7.7 vs 3.8, P < 0.001) and better approached MIP (7.7 vs 7.3 cm H2O with P = 0.04 at low Vt, and 7.8 vs 7.1 cm H2O with P < 0.001 at high Vt). CONCLUSIONS:PEEPminE1 better identifies the open-lung PEEP independently of the adjusted Vt, and may be a practical, more individualized approach for PEEP titration.

Cardio-respiratory interactions and relocation of heartbeats within the respiratory cycle during spontaneous and paced breathing

The capability of respiratory sinus arrhythmia (RSA) to generate privileged locations for the occurrence of R-peaks within the respiratory cycle has been questioned in recent works, challenging the hypothesis that RSA might play a role in improving pulmonary gas exchange. We assessed such a capability submitting healthy humans to spontaneous and paced breathing (SB and PB) protocols, estimating the fraction of beats occurring during inspiration, at low, medium, and high respiratory volumes, and during the first and second half of inspiration and expiration. Then, the same fractions were computed assuming a random uniform distribution of heartbeats, and the differences were compared. The results found are as follows: (1) during PB at 6 rpm, heartbeats redistribute toward inspiration; (2) during SB and PB at 12 rpm, heartbeats tend to cluster when respiratory volume is high; (3) since such redistributions are limited in magnitude, it is possible that its physiological relevance is marginal, for instance, in terms of within-cycle variations in lung perfusion; (4) two groups of subjects with considerably different levels of RSA showed similar redistribution of heartbeats, suggesting that this phenomenon might be an underlying effect of the overall cardio-respiratory interactions, and not directly of RSA.

Effects of filtering and delays on the estimates of a nonlinear respiratory mechanics model.

Estimation of mechanical properties of the respiratory system may be disturbed by instrumentation and physical set-up. The effects of lowpass filtering, filter mismatch and inter-channel delay in the digital converter are assessed on numerically simulated signals from a nonlinear model of the respiratory system. Large biases in model parameter estimates (up to about -300% for some parameters) were caused by these instrumental interferences and were reduced by including an inertance in the retrieved model. The results reinforce the importance of a careful evaluation of the instrumental set-up used in physiological measurements.

Comparison of objective methods to classify the pattern of respiratory sinus arrhythmia during mechanical ventilation and paced spontaneous breathing

Respiratory sinus arrhythmia (RSA) is a fluctuation of heart period that occurs during a respiratory cycle. It has been suggested that inspiratory heart period acceleration and expiratory deceleration during spontaneous ventilation (henceforth named positive RSA) improve the efficiency of gas exchange compared to the absence or the inversion of such a pattern (negative RSA). During mechanical ventilation (MV), for which maximizing the efficiency of gas exchange is of critical importance, the pattern of RSA is still the object of debate. In order to gain a better insight into this matter, we compared five different methods of RSA classification using the data of five mechanically ventilated piglets. The comparison was repeated using the data of 15 volunteers undergoing a protocol of paced spontaneous breathing, which is expected to result in a positive RSA pattern. The results showed that the agreement between the employed methods is limited, suggesting that the lack of a consensus about the RSA pattern during MV is, at least in part, of methodological origin. However, independently of the method used, the pattern of RSA within the respiratory cycle was not consistent among the subjects and conditions of MV considered. Also, the outcomes showed that even during paced spontaneous breathing a negative RSA pattern might be present, when a low respiratory frequency is imposed.

Changes in dead space can explain part of the reduction in gas exchange efficiency found, not necessarily linked to respiratory sinus arrhythmia.

That respiratory sinus arrhythmia (RSA) improves pulmonary gas exchange and circulatory efficiency is an intriguing hypothesis (Yasuma & Hayano, 2004). J. Hayano and colleagues pioneered the research in this area and suggested that RSA-related changes in physiological dead space to tidal volume ratio (V D,phys/V T) and the fraction of intrapulmonary shunt could be the links between RSA and efficiency of gas exchange, given that in a canine model both parameters increase when RSA is present under negative pressure ventilation produced by diaphragm pacing and under RSA changes induced by direct vagal stimulation (Hayano et al. 1996). From this point of view, the paper of Ito et al. (2006) is a necessary and valuable effort to investigate to what extent such a suggestion can be extended to humans during spontaneous ventilation and RSA. The results presented by the authors clearly indicate that vagal blockade using atropine results in attenuation of RSA, increase of V D,phys (mainly the anatomical dead space, V D,an) and deterioration of pulmonary oxygenation. It would seem natural to take such evidence as confirmation that changes in V D,phys are likely to be one of the mechanisms linking variation of RSA with those of pulmonary oxygenation. However, in the Discussion, the authors state that ‘the deterioration of pulmonary oxygenation after atropine administration in the present study appears to result from the mechanism of an increase in venous admixture associated with a decrease in RSA magnitude’ and also report that ‘the reduction in alveolar ventilation by the increase in physiological dead space [. . .] results in a negligible calculated reduction in PaO2 (<0.01 mmHg)’ [is the arterial partial pressure of O2]. To critically evaluate this last statement, we performed simulations using mathematical models available in the literature. The results found do not support the interpretation of the authors that the reduction found in V D,phys did not play a role in worsening pulmonary oxygenation. To explain our point, we briefly report the methods used and the outcomes of the simulations. The simulations were based on the unicompartmental model proposed by Ursino et al. (2001). We eliminated the part of the model performing ventilation control, since respiration was paced, and the part simulating blood flow regulation (imposing a constant value of 5 l min–1), to eliminate possible sources of PaO2 changes other than V D,phys. Given the specific objectives of the investigation, we added to the overall model a model of alveolar flow and volume during spontaneous ventilation (an adaptation of that presented in Section 2.3 of Khoo (1999) was used), an alveolar dead space in parallel with the alveolar compartment (modelled as a gas mixer, as the alveolar compartment, but unperfused), and an anatomical dead space (modelled as a series of gas mixers as, for example, in Hardman & Aitkenhead, 2003) in series with the two; a gas mixer being a numerical implementation of the massconservation equation: d(Vj Pj )/dt = V̇IN PIN, j − V̇OUT Pj where j is O2 or CO2, Pj and V j are the partial pressure and the volume in the mixer, V̇IN and V̇OUT the gas flow in and out of the mixer, and PIN,j the partial pressure of the gas entering the mixer. Simulations were made using the average values of V D,an and V D,alv reported by the authors, V T = 980 ml (this intermediate value was chosen since V T did not change significantly between preand post-atropine), and a fraction of inspired O2 of 12%. The outcomes of the simulations for average PaO2 were 50.2 mmHg for baseline (V D,an = 185.4 ml and V D,alv = 93.4 ml) and 48.9 mmHg for post-atropine (V D,an = 210.3 ml and V D,alv = 105.3 ml), hence resulting in an overall decrease of 1.3 mmHg, of the same order of magnitude as the 2.0 mmHg found in the experiments performed by the authors (and much bigger than their prediction of <0.01 mmHg). It is thus undeniably possible that the magnitude of the PaO2 decrease obtained with our simulations is to some extent the result of some of the simplifications and assumptions that mathematical modelling inevitably involves. However, our point is that is seems plausible to us that an increase of about 4% in V D,phys (39 ml out a V T of 980 ml) is capable of causing a decrease in PaO2 of about the same fraction, with a validated model of the underlying physiological phenomena supporting this idea. From this point of view, the evidence shown by Ito et al. (2006) cannot be interpreted as a rejection of the hypothesis that changes in V D,phys are, at least in part, the mechanism linking changes in RSA and those in gas exchange efficiency. However, further simulations we performed in which we increased only V D,an from baseline to post-atropine values showed that 1 mmHg out of the 1.3 mmHg overall PaO2 decrease (more than 75%) can be related to the increase in V D,an alone. It is well established in the literature that an increase in V D,an following atropine administration (as reported by the authors) is a direct effect of the atropine-induced reduction in tonic activity of the pulmonary vagal nerves (Severinghaus & Stupfel, 1955). Hence, it appears likely that a non-negligible part of the decrease in PaO2 reported by the Ito et al. (2006) is a direct effect of atropine on tonic pulmonary vagal activity, rather than on phasic cardiac vagal activity mediated by RSA reduction.

Could Postural Strategies Be Assessed with the Microsoft Kinect v2

Quantification of body movement strategies to maintain balance may be useful to understand changes in postural control. Some methods for this purpose require special preparations, such as placement of inertial sensors, goniometers or EMG electrodes. In this study, the capability of the Microsoft Kinect v2, a markerless motion sensor, to assess postural control strategies was tested. Forty-six young healthy subjects had the trajectories of 25 “joints”, provided by a Kinect v2, recorded during upright stance with eyes open or close, on rigid (force platform) and soft (foam pad) surfaces. Postural strategies were characterized by a strategy index (SI) based on the phase difference between the accelerations of upper (trunk) and lower (hip) segments of the body, measured by the Kinect in anterior-posterior and medial-lateral direction. Ankle and hip strategies were identified by in-phase or counterphase accelerations respectively, the phase being estimated from the covariance between 2-s sliding windows of the two signals. The trajectories of center of mass (COM) and center of pressure (COP) were also computed from the Kinect and the force plate, respectively. The SI and the velocities of COP and COM were significantly different between conditions (Friedman p < 0.001 for SI), suggesting effects of sensory information. These results are in line with other studies, showing coexistence of both strategies during stance and the predominance of ankle rather than hip strategy on foam or with closed eyes instead of on rigid surface with open eyes. These results support using the Kinect v2 to assess postural strategies.