Physiological response to increasing levels of neurally adjusted ventilatory assist (NAVA)

This study evaluated the response to increasing levels of neurally adjusted ventilatory assist (NAVA), a mode converting electrical activity of the diaphragm (EAdi) into pressure, regulated by a proportionality constant called the NAVA level. Fourteen rabbits were studied during baseline, resistive loading and ramp increases of the NAVA level. EAdi, airway (Paw) and esophageal pressure (Pes), Pes pressure time product (PTPes), breathing pattern, and blood gases were measured. Resistive loading increased PTPes and EAdi. P(a)(CO)(2) increased with high load but not during low load. Increasing NAVA levels increased Paw until a breakpoint where the Paw increase was reduced despite increasing NAVA level. At this breakpoint, Pes, PTPes, EAdi, and P(a)(CO)(2) were similar to baseline. Further increase of the NAVA level reduced Pes, PTPes and EAdi without changes in ventilation. In conclusion, observing the trend in Paw during a ramp increase of the NAVA level allows determination of a level where the inspiratory effort matches unloaded conditions.

Can neurally adjusted ventilatory assist (NAVA) improve patient-ventilator interaction? A preliminary study

INTRODUCTION. NAVA is a new spontaneous-assisted ventilatory mode based on thedetection of diaphragmatic electrical activity (Eadi) and its feedback to adjust ventilatorsettings. NAVA uses the Eadi, an expression of the respiratory center's activity, to initiatepressurization, set the level of pressure support and cycle the ventilator into exhalation.Therefore, NAVA should theoretically allow near-perfect synchronization between the patientand the ventilator. However there are few data documenting these effects in intensive carepatients.OBJECTIVES. To determine whether NAVA can improve patient-ventilator synchronycompared to standard pressure support (PS) in intubated intensive care patients.METHODS. Comparative study of patient-ventilator interaction during PS with cliniciandetermined ventilator settings and NAVA with NAVA gain (proportionality factor betweenEadi and the amount of delivered inspiratory pressure) set as to obtain the same peak airwaypressure as the total pressure obtained in PS. A 20 min continuous recording with eachventilatory mode was performed allowing determination of trigger delay (Td), patient neuralinspiratory time (Tin), duration of pressurization by the ventilator (Tiv), excess durationof pressurization (Ti excess = Tiv - Tin/Tin 9 100) and number of asynchrony events byminute: non-triggering breaths, auto-triggering, double triggering, premature and delayedcycling.Results are given in mean ± SD. p is considered significant if\0.05.RESULTS. Preliminary results (mean ± SD): five patients (age 75 ± 12 years, 1 M/4F,BMI 25.7 ± 4.1 kg m-2), two pts with COPD, 1 with restrictive disease, initial settings: PS14.6 ± 1.7 cm H2O, PEEP 6.4 ± 1.5 cm H2O, NAVA gain 2.8 ± 1.3PS NAVA % reduction NAVAversus PSTd (ms) 210.4 ± 63.0 51.8 ± 12.1* 74.5 ± 5.0Ti excess (%) 12.9 ± 19.6 2.2 ± 0.6 70.8 ± 37.8n asynchrony/minute 7.6 ± 6.4 4.1 ± 3.7* 47.5 ± 17.0Respiratory rate (min-1) 16.8 ± 2.6 20.4 ± 4.7 NA* p\0.05CONCLUSION. Compared to standard PS, NAVA improves patient ventilator interaction byreducing Td and the overall incidence of asynchrony events. There is also a strong trend inreducing delayed cycling. This ongoing trial should provide evidence that NAVA can indeedimprove patient-ventilator synchrony in intubated patients undergoing PS.REFERENCE(S). 1. Sinderby C, Navalesi P et al (1995) Neural control of mechanicalventilation in respiratory failure. Nat Med 5(12):1433-1436.2. Colombo D, Cammarota G et al (2008) Physiologic response to varying levels of pressuresupport and neurally adjusted ventilator assist in patients with acute respiratory failure.Intensive Care Med 34(11):2010-2018.

Physiologic response to changing positive end-expiratory pressure during neurally adjusted ventilatory assist in sedated, critically ill adults

Neurally adjusted ventilatory assist (NAVA) delivers airway pressure (Paw) in proportion to neural inspiratory drive as reflected by electrical activity of the diaphragm (EAdi). Changing positive end-expiratory pressure (PEEP) impacts respiratory muscle load and function and, hence, EAdi. We aimed to evaluate how PEEP affects the breathing pattern and neuroventilatory efficiency during NAVA.

Identification of adequate neurally adjusted ventilatory assist (NAVA) during systematic increases in the NAVA level

Neurally adjusted ventilatory assist (NAVA) delivers airway pressure (P(aw)) in proportion to the electrical activity of the diaphragm (EAdi) using an adjustable proportionality constant (NAVA level, cm·H(2)O/μV). During systematic increases in the NAVA level, feedback-controlled down-regulation of the EAdi results in a characteristic two-phased response in P(aw) and tidal volume (Vt). The transition from the 1st to the 2nd response phase allows identification of adequate unloading of the respiratory muscles with NAVA (NAVA(AL)). We aimed to develop and validate a mathematical algorithm to identify NAVA(AL). P(aw), Vt, and EAdi were recorded while systematically increasing the NAVA level in 19 adult patients. In a multistep approach, inspiratory P(aw) peaks were first identified by dividing the EAdi into inspiratory portions using Gaussian mixture modeling. Two polynomials were then fitted onto the curves of both P(aw) peaks and Vt. The beginning of the P(aw) and Vt plateaus, and thus NAVA(AL), was identified at the minimum of squared polynomial derivative and polynomial fitting errors. A graphical user interface was developed in the Matlab computing environment. Median NAVA(AL) visually estimated by 18 independent physicians was 2.7 (range 0.4 to 5.8) cm·H(2)O/μV and identified by our model was 2.6 (range 0.6 to 5.0) cm·H(2)O/μV. NAVA(AL) identified by our model was below the range of visually estimated NAVA(AL) in two instances and was above in one instance. We conclude that our model identifies NAVA(AL) in most instances with acceptable accuracy for application in clinical routine and research.

Neurally adjusted ventilatory assist in patients with critical illness-associated polyneuromyopathy

Diaphragmatic electrical activity (EA(di)), reflecting respiratory drive, and its feedback control might be impaired in critical illness-associated polyneuromyopathy (CIPM). We aimed to evaluate whether titration and prolonged application of neurally adjusted ventilatory assist (NAVA), which delivers pressure (P (aw)) in proportion to EA(di), is feasible in CIPM patients.

Effect of various neutrally adjusted ventilator assist (NAVA) gains on the relationship between diaphragmatic activity (Eadi max) and tidal volume

INTRODUCTION. Neurally Adjusted Ventilatory Assist (NAVA) is an assisted ventilatorymode in which the ventilator is driven by the electrical activity of the diaphragm (Eadi).NAVAimproves patient-ventilator synchrony [1] but little is known about how to set the NAVA gaini.e., how to choose the ratio between Eadi and delivered pressure. The aim of the present studywas to assess the relationship between Eadi and tidal volume (Vt) at various NAVA gainsettings and to evaluate whether modifying the gain influenced this relationship in non-invasivelyventilated (NIV) patients.METHODS. Prospective interventional study comparing 3 values of NAVA gain during NIV(20 min each). NAVA100 was set by the clinician according to the manufacturer's recommendations.In NAVA50 and NAVA150 the gain was set as -50% and +50% of NAVA100gain respectively. Vt and maximal Eadi value (Eadi max) were recorded. The ratio Vt/Eadi wasthen assessed for each breath. 5-95% range (range 90) of Vt/Eadi was calculated for eachpatient at each NAVA gain setting. Vt/Eadi ratio has the advantage to give an objectiveassessment Vt/Eadi max relationship independently from the nature of this relationship. Asmaller Range90 indicates a better matching of Vt to Eadi max.RESULTS. 12 patients were included, 5 had obstructive pulmonary disease and 2 mixedobstructive and restrictive disease. For NAVA100, the median [IQR] Range 90 was 32[19-87]. For NAVA150 Range 90 was 37 [20-95] and for NAVA50 Range 90 was 33 [16-92].That means that globally NAVA100 allowed a better match between Eadi max and Vt thanNAVA50 and 150. However, by patient, NAVA100 had the lowest Range 90 value for only 4patients (33%), NAVA150 for 2 (17%) and NAVA50 for 6 (50%) patients, indicating thatNAVA100 was not the best NAVA gain for minimizing Range 90 in every patients.Comparing the lowest Range 90 value to the next lowest for each patient, showed that 3 patientshad differences of less than 10% (one each for NAVA50, NAVA100 and NAVA150). Theremainder had differences from 17 to 24%, indicating that most patients (9/12 or 75%) had aclear better match between Eadi and Vt for one specific NAVA gain.CONCLUSIONS. Different NAVA gains yielded markedly different ability to match Vt toEadi max. This approach could be a new way to determine optimalNAVAgain for each patientbut require further investigations.REFERENCE. Piquilloud L, et al. Intensive Care Med 2011;37:263-71.

Nava enhances ventilatory variability and diaphragmatic activity/tidal volume coupling

INTRODUCTION. Neurally Adjusted Ventilatory Assist (NAVA) is a new ventilatory mode in which ventilator settings are adjusted based on the electrical activity detected in the diaphragm (Eadi). This mode offers significant advantages in mechanical ventilation over standard pressure support (PS) modes, since ventilator input is determined directly from patient ventilatory demand. Therefore, it is expected that tidal volume (Vt) under NAVA would show better correlation with Eadi compared with PS, and exhibit greater variability due to the variability in the Eadi input to the ventilator. OBJECTIVES. To compare tidal volume variability in PS and NAVA ventilation modes, and its correlation with patient ventilatory demand (as characterized by maximum Eadi). METHODS. Acomparative study of patient-ventilator interaction was performed for 22 patients during standard PS with clinician determined ventilator settings; and NAVA, with NAVA gain set to ensure the same peak airway pressure as the total pressure obtained in PS. A 20 min continuous recording was performed in each ventilator mode. Respiratory rate, Vt, and Eadi were recorded. Tidal volume variance and Pearson correlation coefficient between Vt and Eadi were calculated for each patient. A periodogram was plotted for each ventilator mode and each patient, showing spectral power as a function of frequency to assess variability. RESULTS. Median, lower quartile and upper quartile values for Vt variance and Vt/Eadi correlation are shown in Table 1. The NAVA cohort exhibits substantially greater correlation and variance than the PS cohort. Power spectrums for Vt and Eadi are shown in Fig. 1 (PS and NAVA) for a typical patient. The enlarged section highlights how changes in Eadi are highly synchronized with NAVA ventilation, but less so for PS. CONCLUSIONS. There is greater variability in tidal volume and correlation between tidal volume and diaphragmatic electrical activity with NAVA compared to PS. These results are consistent with the improved patient-ventilator synchrony reported in the literature.

Optimizing patient-ventilator synchrony during invasive ventilator assist in children and infants remains a difficult task.

OBJECTIVES: To document and compare the prevalence of asynchrony events during invasive-assisted mechanical ventilation in pressure support mode and in neurally adjusted ventilatory assist in children. DESIGN: Prospective, randomized, and crossover study. SETTING: Pediatric and Neonatal Intensive Care Unit, University Hospital of Geneva, Switzerland. PATIENTS: Intubated and mechanically ventilated children, between 4 weeks and 5 years old. INTERVENTIONS: Two consecutive ventilation periods (pressure support and neurally adjusted ventilatory assist) were applied in random order. During pressure support, three levels of expiratory trigger setting were compared: expiratory trigger setting as set by the clinician in charge (PSinit), followed by a 10% (in absolute values) increase and decrease of the clinician's expiratory trigger setting. The pressure support session with the least number of asynchrony events was defined as PSbest. Therefore, three periods were compared: PSinit, PSbest, and neurally adjusted ventilatory assist. Asynchrony events, trigger delay, and inspiratory time in excess were quantified for each of them. MEASUREMENTS AND MAIN RESULTS: Data from 19 children were analyzed. Main asynchrony events during PSinit were autotriggering (3.6 events/min [0.7-8.2]), ineffective efforts (1.2/min [0.6-5]), and premature cycling (3.5/min [1.3-4.9]). Their number was significantly reduced with PSbest: autotriggering 1.6/min (0.2-4.9), ineffective efforts 0.7/min (0-2.6), and premature cycling 2/min (0.1-3.1), p < 0.005 for each comparison. The median asynchrony index (total number of asynchronies/triggered and not triggered breaths ×100) was significantly different between PSinit and PSbest: 37.3% [19-47%] and 29% [24-43%], respectively, p < 0.005). With neurally adjusted ventilatory assist, all types of asynchrony events except double-triggering and inspiratory time in excess were significantly reduced resulting in an asynchrony index of 3.8% (2.4-15%) (p < 0.005 compared to PSbest). CONCLUSIONS: Asynchrony events are frequent during pressure support in children despite adjusting the cycling off criteria. Neurally adjusted ventilatory assist allowed for an almost ten-fold reduction in asynchrony events. Further studies should determine the clinical impact of these findings.

Respiratory variability in mechanically ventilated patients. Critical Care 2011

Introduction: Increased respiratory pattern variability is associated with improved oxygenation. Pressure support (PS) is a widely used partial-assist mechanical ventilation (MV) mode, in which each breathing cycle is initiated by flow or pressure variation at the airway due to patient inspiratory effort. Neurally adjusted ventilatory assist (NAVA) is relatively new and uses the electrical activity of the diaphragm (Eadi) to deliver ventilatory support proportional to the patient's inspiratory demand. We hypothesize that respiratory variability should be greater with NAVA compared with PS.Methods: Twenty-two patients underwent 20 minutes of PS followed by 20 minutes of NAVA. Flow and Eadi curves were used to obtain tidal volume (Vt) and ∫Eadi for 300 to 400 breaths in each patient. Patient-specific cumulative distribution functions (CDF) show the percentage Vt and ∫Eadi within a clinically defined (±10%) variability band for each patient. Values are normalized to patient-specific medians for direct comparison. Variability in Vt (outcome) is thus expressed in terms of variability in ∫Eadi (demand) on the same plot.Results: Variability in Vt relative to variability in ∫Eadi is significantly greater for NAVA than PS (P = 0.00012). Hence, greater variability in outcome Vt is obtained for a given demand in ∫Eadi, under NAVA, as illustrated in Figure 1 for a typical patient. A Fisher 2 × 2 contingency analysis showed that 45% of patients under NAVA had a Vt variability in equal proportion to ∫Eadi variability, versus 0% for PS (P < 0.05).Conclusions: NAVA yields greater variability in tidal volume, relative to ∫Eadi demand, and a better match between Vt and ∫Eadi. These results indicate that NAVA could achieve improved oxygenation compared with PS when sufficient underlying variability in ∫Eadi is present, due to its ability to achieve higher tidal volume variability from a given variability in ∫Eadi.

Interactive effects of mechanical ventilation, inhaled nitric oxide and oxidative stress in acute lung injury

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Low pressure support changes the rapid shallow breathing index (RSBI) in critically ill patients on mechanical ventilation

Background: The rapid shallow breathing index (RSBI) is the most widely used index within intensive care units as a predictor of the outcome of weaning, but differences in measurement techniques have generated doubts about its predictive value. Objective: To investigate the influence of low levels of pressure support (PS) on the RSBI value of ill patients. Method: Prospective study including 30 patients on mechanical ventilation (MV) for 72 hours or more, ready for extubation. Prior to extubation, the RSBI was measured with the patient connected to the ventilator (Drager (TM) Evita XL) and receiving pressure support ventilation (PSV) and 5 cmH(2)O of positive end expiratory pressure or PEEP (RSBI_MIN) and then disconnected from the VM and connected to a Wright spirometer in which respiratory rate and exhaled tidal volume were recorded for 1 min (RSBI_ESP). Patients were divided into groups according to the outcome: successful extubation group (SG) and failed extubation group (FG). Results: Of the 30 patients, 11 (37%) failed the extubation process. In the within-group comparison (RSBI_MIN versus RSBI_ESP), the values for RSBI_MIN were lower in both groups: SG (34.79 +/- 4.67 and 60.95 +/- 24.64) and FG (38.64 +/- 12.31 and 80.09 +/- 20.71; p<0.05). In the between-group comparison, there was no difference in RSBI_MIN (34.79 +/- 14.67 and 38.64 +/- 12.31), however RSBI_ESP was higher in patients with extubation failure: SG (60.95 +/- 24.64) and FG (80.09 +/- 20.71; p<0.05). Conclusion: In critically ill patients on MV for more than 72h, low levels of PS overestimate the RSBI, and the index needs to be measured with the patient breathing spontaneously without the aid of pressure support.

Pulmonary morphofunctional effects of mechanical ventilation with high inspiratory air flow

Objective: Uncertainties about the numerous degrees of freedom in ventilator settings leave many unanswered questions about the biophysical determinants of lung injury. We investigated whether mechanical ventilation with high air flow could yield lung mechanical stress even in normal animals. Design. Prospective, randomized, controlled experimental study. Setting: University research laboratory. Subjects. Thirty normal male Wistar rats (180-230 g). Interventions: Rats were ventilated for 2 hrs with tidal volume of 10 mL/kg and either with normal inspiratory air flow (V`) of 10 mL/s (F10) or high V` of 30 mL/s (F30). In the control group, animals did not undergo mechanical ventilation. Because high flow led to elevated respiratory rate (200 breaths/min) and airway peak inspiratory pressure (PIP,aw = 17 cm H2O), two additional groups were established to rule out the potential contribution of these variables: a) normal respiratory rate = 100 breaths/min and V` = 30 mL/sec; and b) PIP,aw = 17 cm H2O and V` 10 mL/sec. Measurements and Main Results: Lung mechanics and histology (light and electron microscopy), arterial blood gas analysis, and type III procollagen messenger RNA expression in lung tissue were analyzed. Ultrastructural microscopy was similar in control and F10 groups. High air flow led to increased lung plateau and peak pressures, hypoxemia, alveolar hyperinflation and collapse, pulmonary neutrophilic infiltration, and augmented type III procollagen messenger RNA expression compared with control rats. The reduction of respiratory rate did not modify the morphofunctional behavior observed in the presence of increased air flow. Even though the increase in peak pressure yielded mechanical and histologic changes, type III procollagen messenger RNA expression remained unaltered. Conclusions: Ventilation with high inspiratory air flow may lead to high tensile and shear stresses resulting in lung functional and morphologic compromise and elevation of type III procollagen messenger RNA expression.

Effects of different mechanical ventilation strategies on the mucociliary system

To evaluate the effects of different mechanical ventilation (MV) strategies on the mucociliary system. Experimental study. Twenty-seven male New Zealand rabbits. After anesthesia, animals were tracheotomized and ventilated with standard ventilation [tidal volume (Vt) 8 ml/kg, positive end expiratory pressure (PEEP) 5 cmH(2)O, flow 3 L/min, FiO(2) 0.4] for 30 min. Next, animals were randomized into three groups and ventilated for 3 h with low volume (LV): Vt 8 ml/kg, PEEP 5 cmH(2)O, flow 3 L/min (n = 6); high volume (HV): Vt 16 ml/kg, PEEP 5 cmH(2)O, flow 5 L/min (n = 7); or high pressure (HP): Ppeak 30 cmH(2)O, PEEP 12 cmH(2)O (n = 8). Six animals (controls) were ventilated for 10 min with standard ventilation. Vital signals, blood lactate, and respiratory system mechanics were verified. Tracheal tissue was collected before and after MV. Lung and tracheal tissue sections were stained to analyze inflammation and mucosubstances by the point-counting method. Electron microscopy verified tracheal cell ultrastructure. In situ tracheal ciliary beating frequency (CBF), determined using a videoscopic technique, and tracheal mucociliary transport (TMCT), assessed by stereoscopic microscope, were evaluated before and after MV. Respiratory compliance decreased in the HP group. The HV and HP groups showed higher lactate levels after MV. Macroscopy showed areas of atelectasis and congestion on HV and HP lungs. Lung inflammatory infiltrate increased in all ventilated groups. Compared to the control, ventilated animals also showed a reduction of total and acid mucus on tracheal epithelium. Under electron microscopy, injury was observed in the ciliated cells of the HP group. CBF decreased significantly after MV only in the HP group. TMCT did not change significantly in the ventilated groups. Different MV strategies induce not only distal lung alterations but also morphological and physiological tracheal alterations leading to mucociliary system dysfunction.