The main findings of the present study in our unique cohort were that: (1) ΔPrs was significantly associated with patient outcome after controlling for confounding factors, (2) survival was significantly higher in patients with ΔPrs ≤13 cm H 2 O at day 1, (3) survival was significantly higher in patients with mechanical power ≤12 J/min at day 1 and in patients with Pplat < 23 cmH 2 O, and (4) the information given by ΔPrs and Crs is similar. Our main finding was that with V T and Pplat controlled, ΔPrs brings little more additional information independently on Pplat and Crs.

Driving pressure

Rather than confirming the results of Amato et al. [3], the present findings disclosed the limitation of the prognostic role of ΔPrs when Plat,rs, V T , and PEEP are strictly controlled and set according to the ARMA trial. However, we found that the HR of ΔPrs was similar in Amato’s study and in the present investigation. In Amato’s study, in the Cox analysis ΔPrs was associated with 41% increased risk of mortality among the 3080 patients used in the combined analysis [3]. In this study, the authors used a 1-SD increment in ΔPrs for calculating HR, which represented 7 cmH 2 O. Thus, when calculating the HR for 1 cmH 2 O increment, this was associated with a HR of 1.049, which is very close to the present result, as shown in Table 2.

In our study, per each cm H 2 O increase, ΔPrs was associated with 5% increase in the risk of death, which is in the same order of magnitude as Pplat,rs, which was also significantly associated with mortality. PEEP and V T were not significantly associated with mortality in the present cohort, whilst these were associated with a significant 2% and 3% increase in mortality per 1 cm H 2 O and per 1 ml/kg PBW, respectively, in Amato’s study [3]. This can be explained by the narrower range of PEEP and V T used in our cohort. Therefore, in contrast to Amato’s study [3] our findings did not identify ΔPrs as the strongest predictor of death as compared to V T , Crs, and Pplat,rs. To explore this finding further, we used a model-building strategy that consisted of a series of Cox models, which included the collinear variables two-by-two (with their interaction) and these were then compared with the corresponding Cox models that used the collinear variable alone. This strategy showed that ΔPrs and Pplat,rs each provides different information related to patient outcome. However, interaction between them was present, statistically meaning that the effect of each of them on outcome was dependent on the level of the other. In other words, the effect of one covariate modifies the effect of the other on the outcome. When ΔPrs and mechanical power were analyzed two-by-two, ΔPrs remained significant but mechanical power did not. That means that ΔPrs conveys specific information. When ΔPrs and Crs were analyzed together neither of them remained statistically significantly associated with patient outcome. That means that the same information carried by Crs is also carried by ΔPrs. Both shared the same information. The same result, and hence, the same interpretation also applied for Pplat,rs and Crs.

The Lung Safe study [8] was a prospective international observational investigation in 50 countries, in which data were collected for over 2377 patients with ARDS in the winter season. In 703 of these patients data were available to analyze the rate of mortality at the time of hospital discharge over the range of ΔPrs and Pplat,rs. The mortality rate increased linearly with increasing ΔPrs with no threshold. The slope of the increase in mortality over ΔPrs quintiles was steeper than that pertaining to Pplat,rs in the Lung safe study, whereas the slopes were similar in the present study. However, V T was not maintained at 6 ml/kg in these two studies [3, 8] which is at variance with the present study. Furthermore, in the Lung Safe study Pplat,rs was measured in only 40% of the patients [8], a fact that has been highlighted [9, 10].

ΔPrs ranged between 5 and 31 cm H 2 O in our cohort (Fig. 1), which is comparable to the range of 7–32 cm H 2 O in the Amato study, but wider than in the Lung Safe study (9–25 cm H 2 O). It should be stressed that in the Amato study [3] the effect of ΔPrs was related to the adjusted relative risk of death, whereas in our study, as in the Lung Safe study, the probability of death was analyzed. Moreover only patients with a P/F ratio <150 mmHg were included. ΔPrs was also reported to be associated with death in a recent large multicenter cohort of patients with ARDS who had acute cor pulmonale [11].

A more relevant analysis of the data on ΔPrs would require the knowledge of the transpulmonary ΔP (ΔP L ). Talmor et al. found that the reduction in ΔP L was higher in an esophageal pressure-guided group than in a control group, and that ΔP L reduction was higher in survivors than in nonsurvivors, whereas ΔPrs was similar in both experimental and control groups and in survivors and nonsurvivors [12], confirming that the compliance of the chest wall is a key parameter in interpreting ΔPrs and its components. The role of ΔP L to optimize the use of mechanical ventilation in the prone position should be further investigated, in particular regarding PEEP selection [13], by using a physiological approach [14].

Mechanical power

The concept that the magnitude of energy transferred from the ventilator into the lung may contribute to VILI has recently arisen and has been confirmed in an experimental study in normal pigs receiving a combination of a large number of V T and respiratory rates [15]. In this study mechanical power of 12 J/min was found to promote VILI. In the present study, our secondary goal was to explore whether the mechanical power was associated with the outcome. We found that this was the case and the threshold of 12 J/min was associated with significant distinct probabilities of survival. Interestingly, the median value of mechanical power in the present cohort was the same as that found experimentally as the threshold above which VILI occurred [15]. We also found that the value of the mechanical power in J/min was very close to that of ΔPrs in cm H 2 O. The relevance of the present data on mechanical power should be confirmed by further investigations. Should mechanical power be confirmed as a significant independent predictor of survival its computation at the bedside should be recommended. Recently, Gattinoni et al. [16] proposed using the first-order equation to compute mechanical power. Our present approach is much simpler and can be easily implemented at the bedside.

The probability of survival in our study was expressed as unadjusted and adjusted, taking into account the covariates selected by the Cox models. This explains the difference between the data shown in Fig. 1 and Fig. 3. In the former, a linear relationship was observed between survival and ΔPrs, mechanical power, Pplat,rs and Crs. This suggests there is no safe dose of mechanical ventilation. However, when the survival was adjusted with covariates, a threshold was disclosed for the survival across quintiles.

Limitations and strengths

Our study was limited by: (1) the fact that data were collected from two positive trials where survival was markedly affected by the experimental approach subjected to randomization; (2) as in other trials in patients with ARDS, more than 60% of patients meeting the criteria for ARDS were excluded from enrollment into the trials; and (3) lack of generalizability, as patients with PaO2/FiO2 > 150 mmHg at 24 hours were excluded from the analysis. However, as discussed previously, our ARDS sample was more homogeneous in terms of the ventilator settings used and the present results were highly significant.

Clinical implications