The main findings of this study in critically ill patients were: (1) the IEs index, or a value above 10 %, had no correlation with patient outcome; (2) the presence of clusters of IEs, described as events of IEs, was associated with longer duration of mechanical ventilation and higher hospital mortality.
Three studies over the last decade have focused on the incidence of asynchronies and specifically IEs and their effect on outcome of unselected, critically ill patients [1, 7, 8]. In an attempt to identify a threshold of IEs associated with poor outcome, the value of an IEs or asynchronies index greater than 10 % has been used. Using this cut-off value, two of the studies showed an association with increased duration of mechanical ventilation but not mortality [1, 7], while the other study found higher ICU mortality, and a trend towards longer duration of ventilation [8]. An important observation from this last study was the significant variability of IEs over time in the same patient, highlighting the need for continuous recordings to monitor IEs.
While undoubtedly a high incidence of IEs is associated with poor patient outcome, the choice of the 10 % cut-off value has certain limitations. Firstly, it is not derived from a representative sample of patients [13]. Secondly, indexing over time cannot reveal the presence of clusters of IEs. More importantly, the presence of IEs index more than 10 % can only be identified retrospectively, and therefore cannot be used as an alarm on a ventilator.
Indeed, it has been shown that IEs tend to occur in clusters, between often prolonged uneventful periods [8]. A possible explanation for this observation is that the factors affecting the presence of IEs, such as sedation, wakefulness/sleep state, level of assist and ventilatory drive, may vary substantially during the course of mechanical ventilation. We hypothesized that the presence of such clusters could have a stronger link to patient outcome than sporadic, scattered IEs, as biological phenomena are often non-linear. Clearly, when the number of IEs is indexed over a prolonged time period, the presence of such clusters can be missed. We therefore sought to develop a mathematical model to describe those clusters, and thus developed the concept of an event of IEs. Given the lack of previous data, the choice of cutoff values defining an event had to be rather heuristic, and further prospective studies with larger numbers of patients are needed for fine tuning of these thresholds.
In the patient population studied, almost all patients had some IEs, but only 30 % had events. The characteristics of the events, power and duration, remained relatively stable during the observation period. The presence of events, as well as their power and duration, were associated with prolonged duration of mechanical ventilation, even in patients with IEs index less than 10 %. An increased risk of hospital mortality was observed, although a larger cohort may be needed to confirm this.
The presence of clusters of IEs in two different studies [8] highlights the utility of the concept of event of IEs. More importantly, events could be prospectively identified by appropriate software on the ventilator, like IEs [14, 15], and used as alarms. Indeed, in the process of selecting the event definition, the potential use as an alarm was paramount. An event can be identified, by definition, after a 3-min period, while the observed median event duration in our patients was 21 min. Thus, although the presence of events was associated with adverse outcomes in our study, this significant time difference suggests that, if IEs are correctable, an alarm at 3 min could potentially prevent the evolution of an event. Nonetheless, the efficiency of such intervention should be prospectively evaluated.
Some further aspects and limitations of our study need to be detailed. Firstly, we did not study all forms of asynchronies, but focused only on IEs, which is the most common major asynchrony [1]. Moreover, we did not study the whole duration that patients were on ventilators, nor all modes of ventilation. We only studied patients on assisted modes of ventilation, pressure support and proportional assist, as IEs occurring in spontaneously breathing patients are probably different in pathophysiology and effects from those occurring in patients ventilated passively in controlled modes. Indeed, it is increasingly being recognized that IEs observed during inspiration in controlled modes of ventilation often represent reverse-triggering (entrainment) [16–18]. Although all ‘control’ modes in modern ventilators allow assisted breaths, use of those modes in spontaneously breathing patients varies in everyday practice, and is very limited in our ICU. Thus, it should be emphasized that the observed results are derived from the specific population studied, and cannot be generalized without further studies.
The value of the obtained results also relies on the method used to identify IEs. The reported sensitivity of the PVI monitor in identifying IEs is 87 % [11], with most cases of missed IEs occurring in patients with very severe flow limitation. In our study, 24 patients (22 %) had a diagnosis of COPD, and only 11 (10 %) were admitted for exacerbation of COPD, suggesting that at least a similar sensitivity could be expected. A similar accuracy in identification of IEs was reported for the software used in the Blanch et al. study [14]. Furthermore, the main results of the study were the same in an analysis of a subgroup of patients, excluding those with COPD (Table S8).
A rather prolonged duration of ventilation and ICU stay was observed in our patients, which could be attributed to the exclusion of patients on CPAP or low assist, and those expected to proceed to a T-piece trial within 24 h of initiation of assisted ventilation. This could be regarded as one of the strengths of the study, as monitoring of events would be implemented in everyday practice in patients expected to have a relatively long weaning period. However, in our study, the patients were not rigorously classified into weaning category [19].
Finally, this work was not designed to study the cause of IEs or events, and cannot clarify to what extent the presence of events has a causal relationship with patient outcome. It is reasonable to assume that more severely ill patients having ICU-acquired weakness would have more IEs, and would also require prolonged mechanical ventilation [20]. Yet, there are other possible mechanisms by which IEs, and particularly events, could be associated with adverse patient outcome. For example, the presence of IEs during expiration would cause pleiometric contraction to the diaphragm, damaging muscle fibers [21, 22]; discomfort could induce stress [13, 23]; and unrecognized IEs could lead to mistakes in decision-making during weaning [24, 25]. Whether and to what extent IEs are correctable, and whether that would affect patient outcome, were not examined in this study, nor, to our knowledge, in any other past study. However, it is reasonable to assume that appropriate ventilator alarms would significantly facilitate research in this important issue.
In conclusion, this study introduces the concept of events to describe the clusters of ineffective efforts. Notwithstanding that the thresholds used for event definition were rather arbitrary, the presence of events, as well as their power and duration, are associated with prolonged duration of mechanical ventilation and higher hospital mortality. As the computation of an event can be performed in real time, through the use of appropriate software, events could be introduced as alarms on ventilators to facilitate the management of ineffective efforts and improve patient–ventilator interaction.