Mortality and pulmonary mechanics in relation to respiratory system and transpulmonary driving pressures in ARDS

Abstract

Purpose

The driving pressure of the respiratory system has been shown to strongly correlate with mortality in a recent large retrospective ARDSnet study. Respiratory system driving pressure [plateau pressure−positive end-expiratory pressure (PEEP)] does not account for variable chest wall compliance. Esophageal manometry can be utilized to determine transpulmonary driving pressure. We have examined the relationships between respiratory system and transpulmonary driving pressure, pulmonary mechanics and 28-day mortality.

Methods

Fifty-six patients from a previous study were analyzed to compare PEEP titration to maintain positive transpulmonary end-expiratory pressure to a control protocol. Respiratory system and transpulmonary driving pressures and pulmonary mechanics were examined at baseline, 5 min and 24 h. Analysis of variance and linear regression were used to compare 28 day survivors versus non-survivors and the intervention group versus the control group, respectively.

Results

At baseline and 5 min there was no difference in respiratory system or transpulmonary driving pressure. By 24 h, survivors had lower respiratory system and transpulmonary driving pressures. Similarly, by 24 h the intervention group had lower transpulmonary driving pressure. This decrease was explained by improved elastance and increased PEEP.

Conclusions

The results suggest that utilizing PEEP titration to target positive transpulmonary pressure via esophageal manometry causes both improved elastance and driving pressures. Treatment strategies leading to decreased respiratory system and transpulmonary driving pressure at 24 h may be associated with improved 28 day mortality. Studies to clarify the role of respiratory system and transpulmonary driving pressures as a prognosticator and bedside ventilator target are warranted.

Introduction

Acute respiratory distress syndrome (ARDS) [1, 2] carries a high morbidity and mortality and remains a very common clinical problem [3, 4]. The backbone of current treatment is the use of “lung protective” ventilation, i.e. limiting tidal volumes (V_T) and keeping end-inspiratory plateau pressures low while maintaining sufficiently high positive end-expiratory pressure (PEEP) [5–9]. Lung protective ventilation strategies are thought to reduce mechanical stress by maintaining alveolar aeration (limiting repetitive opening and closing) while preventing overexpansion of the lung, thereby decreasing ventilator-induced lung injury [10–12]. These strategies have been shown to reduce mortality, demonstrating the importance of respiratory mechanics in determining outcomes in patients with ARDS [5–8].

Results from a recent study using data from nine randomized trials suggest that the driving pressure (DP) of the respiratory system (DP_RS), which is easily measured at the bedside (DP_RS = plateau pressure − PEEP), may be a superior marker for the severity of lung injury, providing improved prognostication and correlation with mortality [13]. The authors of this study reported that higher DP_RS correlated with increased mortality even in patients already receiving low-volume lung protective ventilation [13]; however, they did not account for the effects of the chest wall in their analysis [14]. This latter parameter can be obtained using the transpulmonary DP (DP_L = end-inspiratory transpulmonary pressure−end-expiratory transpulmonary pressure), which is the pressure actually applied to the lungs. Using DP_L for monitoring and prognostication of ARDS eliminates the variable effects of the chest wall on the respiratory system. In addition, because chest wall compliance and pleural pressure vary widely between patients [15], measuring DP_L instead of DP_RS may be the more appropriate measure.

Esophageal manometry provides a useful estimate of pleural pressure and can be used to determine separate contributions of lung and chest wall in determining respiratory system mechanics [15–17]. In the EPVent trial, our group tested the use of esophageal manometry for managing mechanical ventilation in patients with ARDS [15]. We found that maintenance of positive transpulmonary pressures resulted in significantly higher PEEP, improved oxygenation (P/F ratio) and improved respiratory system compliance [15]. Maintenance of positive transpulmonary pressures is in accordance with the concept of personalization and “a la carte” ventilatory management in ARDS [18]. In the study reported here, we used esophageal pressure measurements from EPVent to follow changes in DP_RS and DP_L over time in the two treatment groups.

Methods

Study cohort

The EPvent study was approved by the institutional review board at the Beth Israel Deaconess Medical Center in Boston, and written consent was obtained from each patient or surrogate [15]. Patients were included in the study if they had acute lung injury or ARDS as defined by the American–European Consensus Conference [2]. Of the original 61 subjects, 56 had sufficient data at baseline and 24 h to calculate DP_RS and DP_L for further analysis. Of the five patients excluded, three were from the intervention group (1 in the 3 died), and two were from the control group (both died). The full results of the EPVent trial have been published elsewhere [15].

Physiologic measurements

Subjects were monitored while supine with the head of the bed elevated to 30°. An esophageal balloon-catheter was placed, and measurements were obtained to estimate intrathoracic pressures. Airway pressure, tidal volume and air flow were recorded during tidal ventilation and during end-expiratory holds and end-inspiratory holds (plateau) (Fig. 1). Between baseline and 5 min, every patient underwent a recruitment maneuver with an airway pressure increase to 40 cmH₂O for 30 s and V_T set at 6 cc/kg ideal body weight. Patients in the intervention group had PEEP levels adjusted to achieve a positive transpulmonary pressure of 0–10 cm H₂O at end-expiration according to a sliding scale based on the fraction of inspired oxygen (see Fig. 1 in EPvent [15]). The control group had PEEP titrated as per the standard low PEEP ARDSnet tables [5]. Measured variables included total PEEP (measured at end-expiratory hold), plateau pressure, end-expiratory esophageal pressure, end-inspiratory esophageal pressure and V_T; all other variables in our study were calculated from these values (Fig. 1). Transpulmonary pressure was calculated as airway pressure minus esophageal pressure (a surrogate for intrathoracic pressure) (Fig. 1). DP_RS was calculated as the plateau pressure minus total PEEP (Fig. 1). DP_L was calculated from the transpulmonary pressures at the same times (Fig. 1). Elastance of the respiratory system (E_RS) was calculated as the change in airway pressure from end-expiratory hold to plateau divided by V_T, and lung elastance (E_L) was calculated as the change in transpulmonary pressure at the same times. The 28 day mortality was also recorded. Data were analyzed at baseline, at 5 min (after the recruitment maneuver and adjustment of tidal volume and PEEP to protocol settings) and at 24 h.

Fig. 1

Pressure and volume tracings from a study patient. a Time tracings show the pressure and volume change during tidal breathing with expiratory and inspiratory holds. Airway pressure (P_ao) is the total respiratory system pressure, esophageal pressure (P_es) is an estimate of the pleural and trans-chest wall pressure and transpulmonary pressure (P_L) is calculated as P_ao minus P_es. DP _RS Respiratory system driving pressure [plateau pressure−total positive end-expiratory pressure (PEEP)], DP _CW chest wall driving pressure (P_es at end-inspiratory hold−P_es at end-expiratory hold), DP _L transpulmonary driving pressure (P_L at the end-inspiratory hold−P_L at end-expiratory hold). b Pressure–volume (P–V) curves during tidal breathing following respiratory system pressures (P_ao), transpulmonary pressures (P_L) and chest wall pressures (P_es). Dotted lines represent the static compliance of the respiratory system and lung as measured by the slope between end-inspiratory holds and end-expiratory holds (stars), arrows indicate the direction of the inspiration and expiration

Statistical analysis

Continuous variables with a normal distribution were analyzed via analysis of variance (ANOVA) and linear regression. We compared DP_RS and DP_L between 28 day survivors and 28 day non-survivors, and compared DP_RS, DP_L, E_RS, E_L and PEEP between the control and intervention groups at baseline, 5 min and 24 h. Changes in these variables (DP_RS, DP_L, etc.) over time between the control and intervention groups and between survivors and non-survivors were assessed by ANOVA repeated measures analysis with the interaction terms (time × physiological measurement) added into the analysis. We used LOWESS (locally weighted scatterplot smoothing) to compare individual values of DP_RS and DP_L in order to determine if DP_RS is predictive of DP_L in a given patient and if variation of ∆DP_RS resulting from a change in PEEP setting is predictive of the variation of ∆DP_L. Dichotomous and nominal variables were compared using chi-square analysis with Fisher’s exact test.

Results

Data from 29 patients in the control group and 27 patients in the intervention group were analyzed. The cohorts were well matched by age, sex, race, Acute Physiology and Chronic Health Evaluation (APACHE) II score at admission, primary physiologic injury, baseline organ failure, gas exchange (pH, PaO₂, pCO₂), lactate and hemodynamics (Table 1). There were 42 survivors and 14 non-survivors at 28 days. Compared with non-survivors, survivors had a significantly lower APACHE II score (24.7 vs. 31.5; p < 0.0001), higher pH (7.35 vs. 7.27, p < 0.001), lower lactate level (2.1 vs. 5.8, p < 0.0001), but they were otherwise similar in race, gender, age, heart rate and blood pressure at baseline.

Table 1 Baseline group characteristics

To evaluate the correlation between driving pressure and survival we compared 28 day survivors and non-survivors. There was no difference between these groups in baseline DP_RS (13.6 vs. 15.5 cmH₂O; p = 0.08), baseline DP_L (10.1 vs. 10.4 cmH₂O; p = 0.75), 5 min DP_RS (12.3 vs. 14.7 cmH₂O; p = 0.054) or 5 min DP_L (8.5 vs. 10.6 cmH₂O; p = 0.09), although mean DP_L and DP_RS were higher in non-survivors at all time points (Fig. 2a, b). At 24 h, survivors had a significantly lower DP_RS (10.5 vs. 14.7 cmH₂O; p < 0.0001) and DP_L (7.8 vs. 10.1 cmH₂O; p = 0.03) (Fig. 2a, b). From baseline to 24 h, survivors showed a significant decrease in both DP_RS (∆DP_RS −3.29 vs. −0.81 cmH₂O; p = 0.03) and DP_L (∆DP_L −2.3 vs. −0.3 cmH₂O; p = 0.04) compared with non-survivors. Similarly, E_RS and E_L were lower at baseline in survivors (E_RS 28.1 vs. 35.3 cmH₂O/L, p = 0.02; E_L 21.1 vs. 24.3 cmH₂O/L, p = 0.3) and decreased over 24 h (E_RS 25.2 vs. 34.6 cmH₂O/L, p = 0.001; E_L 18.6 vs 24.4 cmH₂O/L, p = 0.05). In both survivors and non-survivors there was no interaction with time (DP_RS, p = 0.12; DP_L, p = 0.59). Notably, ten of 29 (34.5 %) patients in the control group and four of 27 (14.8 %) patients in the intervention group died by 28 days (p = 0.085).

Fig. 2

a, b Respiratory system and transpulmonary driving pressures in survivors (n = 42) and non-survivors (n = 14) at 28 days. c, d Respiratory system and transpulmonary driving pressures in the control group (n = 29) and the intervention group (n = 27). Data points are means with standard errors at baseline, 5 min and 24 h. p values were assessed by analysis of variance (ANOVA)

To evaluate the effects of PEEP adjustment targeting positive transpulmonary pressure on changes in driving pressure, we compared the control and intervention groups. There was no difference between groups in baseline DP_RS (14.0 vs. 14.1 cmH₂O; p = 0.97), baseline DP_L (10.1 vs. 10.3 cmH₂O; p = 0.80), 5 min DP_RS (12.2 vs. 13.6 cmH₂O; p = 0.22) or 5 min DP_L (8.5 vs. 9.5 cmH₂O; p = 0.35). At 24 h there was no difference in DP_RS between groups (12.0 vs. 11.1 cmH₂O; p = 0.31), while DP_L was significantly lower in the intervention group (9.4 vs. 7.2 cmH₂O; p = 0.02) (Table 2; Fig. 2c, d). In terms of changes between baseline and 24 h, the intervention group showed a non-significant change in DP_RS (∆DP_RS −2.39 vs. −2.97 cmH₂O, p = 0.57) and a significant decrease in DP_L (∆DP_L −0.65 vs. −3.07 cmH₂O, p = 0.004). There was a strong interaction between time and DP_RS (p = 0.015) and DP_L (p < 0.001), respectively. The relationship between DP_RS and DP_L at any given time point and the relationship between the ∆DP_RS and ∆DP_L (baseline to 5 min and baseline to 24 h) were assessed by LOWESS, revealing a strong linear relationship, but significant variation in DP_L and ∆DP_L for any given DP_RS or ∆DP_RS, respectively (Electronic Supplemental Material figure). There was no difference in DP_CW at any time point compared by intervention or mortality, and there was wide variability among all patients in both groups (Table 2).

Table 2 Mechanics at baseline, 5 min and 24 h

To evaluate the causes of driving pressure changes within individual subjects, changes in elastance, PEEP and V _T were examined concurrently. The decrease in DP_L at 24 h was explained by a similar decrease in E _L over the same period. There was no difference between control and intervention groups in baseline E _RS (29.9 vs 29.9 cmH₂O/L, p = 0.99), baseline E _L (21.7 vs 22.1 cmH₂O/L, p = 0.86), 5 min E _RS (29.9 vs 32.2 cmH₂O/L, p = 0.48) or 5 min E _L (21.1 vs 22.9 cmH₂O/L, p = 0.58) (Fig. 3). At 24 h the intervention group had a slight decrease in E _RS that did not reach statistical significance (29.8 vs 25.2 cmH₂O/L, p = 0.07) and significantly lower E _L (23.4 vs 16.5 cmH₂O/L, p = 0.007) (Table 2; Fig. 3) and greater change from baseline (ΔE _RS −0.09 vs −4.75 cmH₂O/L, p = 0.01, ΔE _L 1.69 vs −5.66 cmH₂O/L, p = 0.0002) relative to the control group. There was a strong correlation between baseline-to-24 h ∆DP_RS and ΔE _RS (r ² = 0.36, p < 0.0001) and even stronger correlation between ∆DP_L and ΔE _L (r ² = 0.65, p < 0.0001, Fig. 4). In contrast, the improved DP at 24 h did not appear to be related to differences in V_T between groups (Table 2).

Fig. 3

Control group (n = 29) vs. intervention group (n = 27) at baseline, 5 min and 24 h. Means and standard errors are shown for elastance of the respiratory system (a), pulmonary elastance (b), PEEP (c). p values were assessed by ANOVA

Fig. 4

a Change in driving pressure of the respiratory system (∆DP _RS ) vs. change in respiratory system elastance (∆R _SE ) between baseline and 24 h. b Change in transpulmonary driving pressure (∆DP _L ) vs. change in pulmonary elastance (∆EL) between baseline and 24 h. R ² was calculated by the linear fit model and p was calculated by ANOVA

As PEEP was the only adjusted variable between groups, any differences in DP and elastance should be secondary to differences in PEEP between the control and intervention groups. At baseline, PEEP was the same between the control group and intervention group prior to initiating the protocol (13.0 vs. 12.7 cmH₂O; p = 0.79). Targeting positive end-expiratory transpulmonary pressure in the intervention group resulted in increased PEEP at 5 min (12.9 vs. 20.0 cmH₂O; p < 0.0001) and 24 h (11.0 vs. 19.3 cmH₂O, p < 0.0001) (Table 2; Fig. 3.)

Discussion

The data from our study suggest that utilizing PEEP titration to target positive transpulmonary pressure via esophageal manometry results in both improved elastance and driving pressures. These findings suggest that strategies leading to decreased DP and elastance could be associated with improved 28 day mortality.

Determinations of driving pressure change

The relationship between DP and its determining variables (elastance and V_T) was illustrated in our study, with changes in DP_L in the intervention group strongly correlating with improvement in lung elastance. This improvement was seen despite a small increase in mean V_T in the intervention group relative to the control group by 24 h. These results clearly suggest that adjusting PEEP via esophageal manometry to maintain positive transpulmonary pressures resulted in decreases in both elastance and in DP_L. Several studies have suggested possible improved outcomes using higher PEEP strategies in patients with ARDS [7, 19–22]. Recruitment leading to increased size of the “baby lung” with subsequent improved compliance [23–25] might be the dominant reason for this finding. However, high PEEP alone is unlikely to be beneficial in all patients. Inappropriate PEEP may in fact cause hemodynamic compromise [26], increased dead space fraction [27] and direct barotrauma with lung over-distension and worsened compliance [27–29].

Our data illustrate that a more targeted approach utilizing esophageal pressure measurements to account for chest wall dynamics may better characterize a “best PEEP” for an individual patient. Although esophageal manometry represents mid-thorax pleural pressures, the net effect of this PEEP optimization appears to improve overall elastance and DP. Finding this “best PEEP” may optimize alveolar recruitment, increasing the size of the “baby lung” and reducing repetitive alveolar opening and closing (atelectrauma), while limiting over-distension and lung injury. Although mean PEEP increased in the intervention group, PEEP was not increased in all cases and the benefit from esophageal pressure monitoring appears to be more nuanced than simply attributing the improved DP_L to the observed increase in PEEP.

Respiratory system versus transpulmonary monitoring

Amato et al. suggested that DP_RS would be a reasonable surrogate for DP_L in their analysis [13]; however, the results of our study may question this assessment. Although the majority of the respiratory system driving pressure was accounted for by the lungs, a significant portion (roughly 33 % on average) was secondary to the influence of the chest wall. Despite the LOWESS plots reflecting the expected linear relationship between DP_RS and DP_L, these plots illustrate the challenge to estimate the DP_L for any given patient based upon the measured DP_RS, with significant variability in chest wall elastance likely secondary to abdominal distension, obesity or chest wall edema which might contribute noise to the DP_RS signal, not reflecting underlying lung properties. In theory, by excluding chest wall effects, DP_L may be superior to DP_RS as the more accurate marker of lung distending pressures, and utilizing esophageal manometry to estimate and remove the chest wall component may be superior to standard respiratory system measurements using airway pressures. Interestingly, we did not see a significant decrease in DP_RS at 24 h in the intervention group despite the statistically significant decrease in DP_L. While the current study lacks the statistical power to test the hypothesis that DP_L is superior to DP_RS, the observations in our study support further tests of this hypothesis. As DP_RS appeared to be at least equal to DP_L in terms of mortality correlation, it currently remains unclear if either measurement is superior.

Mortality prediction

With respect to the use of DP as an outcome predictor, Amato et al. proposed that scaling V_T to body weight and “normalizing” to lung size was insufficient as functional lung size in ARDS is markedly decreased [13]. These authors hypothesized that this “baby lung” [24] is manifested as lower respiratory system compliance (C_RS) and that “normalizing V_T to C_RS and using the ratio as an index of the “functional’ size of the lung” would be superior to V_T alone and provide a better predictor of outcomes [13]. This “normalization” the authors refer to is the measured DP_RS, which they found to be the strongest predictor of mortality in patients with ARDS. In our study, DP_RS and DP_L both decreased by 24 h in the 28 day survivor group, suggesting its possible use for prognostication. As elastance was similarly lower in survivors, it is unclear if DP is independently prognostic, and DP_RS, E_RS, DP_L and E_L could be further tested in a larger sample size. Ultimately it remains unclear from our data if DP might be useful for prognostication or if higher DP is simply another marker for poorly compliant lungs.

Driving pressure manipulation

It has also been suggested that manipulation of DP could be used for ventilator management at the bedside [13]. Theoretically, DP could be adjusted by changing the V_T (low V_T would similarly lower DP) and by adjusting the PEEP (to optimize compliance). The effects of PEEP adjustment on DP in our study were not seen at the 5 min time point. If there is a delayed response, titration of interventions designed to influence DP in real-time might be challenging. Given that we had data only at 5 min and 24 h, future studies will be needed to clarify the optimal time to determine these changes.

Limitations

There are several significant limitations to this study that will need to be addressed in future investigations. The small sample size and the unequal number of subjects in the survivor and non-survivor groups makes meaningful interpretation of the data challenging, as do the small (but equal) numbers when comparing by intervention. These small numbers do not allow for multivariate analysis to determine if DP might emerge as an independent predictor of mortality and limit our direct comparison of DP_RS and DP_L. Furthermore, the retrospective nature of this analysis weakens the interpretation as driving pressure was not a pre-specified endpoint in the initial study.

Conclusions

To our knowledge this is the first study to evaluate DP_L via esophageal manometry as a tool to optimize ventilatory settings in ARDS patients. Although DP_L appeared to be the superior to DP_RS for monitoring changes in pulmonary mechanics, further investigation is needed to determine if DP_L or DP_RS is better for following mechanics and predicting mortality. These data lend support for future studies on interventions designed to improve driving pressure to determine if DP_L or DP_RS can be directly targeted at the bedside to improve outcomes.