Patient–Ventilator Asynchrony

The incidence of asynchronies has been defined as the asynchrony index, which is a percentage value of the total number of asynchronous events divided by the sum of the total ventilator cycles plus the ineffective efforts.56,84 A high incidence of asynchrony is commonly defined as an asynchrony index > 10%, and it may be related to a patient’s discomfort, increased work of breathing, or prolonged weaning due mainly to wasted diaphragmatic energy.8,48,64 Several studies have reported that an asynchrony index > 10% may significantly increase the duration of mechanical ventilation and the risk of tracheostomy, and it may be associated with a higher mortality rate.3,56,85 Further studies are needed to define its role in predicting patient prognosis.

Ventilator-induced diaphragmatic dysfunction it is an important risk factor for poor patient-ventilator interaction, contributing to prolonged ventilator dependence and poorer outcome. 86-91 During partial ventilator support, asynchronies can have an especially important impact on respiratory muscle function, in particular during ineffective efforts occurring in the exhalation phase of the previous mechanical breath, because the inspiratory muscles contract when they should relax as lung volume decreases to functional residual capacity. 92 The result is a so-called eccentric or plyometric contraction, which leads to ultrastructural muscle damage, cytokine release, and muscle strength reduction with consequent deficit of force and weaning failure.

93-96 due to ineffective efforts had negative effects on the weaning process, significantly prolonging mechanical ventilation in subjects with an asynchrony index > 10% compared to those with an asynchrony index < 10%. More recently, de Wit et al56 demonstrated that asynchrony index > 10% was related to longer duration of mechanical ventilation and shorter ventilator-free survival, along with lower likelihood of home discharge. A similar trend toward longer mechanical ventilation was confirmed by other studies that also noted an association between an asynchrony index > 10% and a higher mortality rate. 48,85

Sleep quality may be deeply influenced by patient-ventilator interaction, and a high percentage of asynchronies appear to be responsible for sleep disruption.97 An improvement of sleep quality may be obtained with the reduction of the ventilatory support, which leads to a more stable breathing pattern, fewer missed efforts, and periodic breathing.92,98 Furthermore, the type of ventilatory support may play a role in sleep quality by reducing the number of asynchronies.66,97,98 However, the relationship between the patient-ventilator interaction and quality of sleep is still controversial. Alexopoulou et al99 did not observe improvements in sleep quality during proportional assist ventilation+ compared to PSV, despite the former being able to improve patient-ventilator interaction, whereas neurally adjusted ventilatory assist was found able to improve sleep quality compared to PSV.100

Dyspnea, defined as breath discomfort, is a common consequence of poor interaction between the patient and the ventilator and is strongly associated with anxiety in mechanically ventilated patients.101 In up to one third of patients, changes in ventilatory settings are able to reduce dyspnea and the associated anxiety, whereas the inability to reduce dyspnea by modifying ventilator settings seems to be associated with delayed extubation.66 The relationship between dyspnea and asynchronies still needs to be thoroughly investigated.81 Finally, asynchronies are associated with persistent neuropsychological alterations in critically ill patients.102 A profound sleep disruption with a high frequency of arousals and awakenings is related with acute onset of impaired cognitive function, visual hallucinations, delusions, and illusions.103,104

Difficult Weaning

Difficult weaning is closely related to asynchronies. Chao et al84 reported that the wasted diaphragmatic energy The importance of an accurate analysis and quantification of asynchronies is mandatory.3,66 However, precise analysis is still challenging in everyday clinical practice.105

Visual Analysis

Different patterns of asynchrony can be detected by visual inspection of flow/time and pressure/time waveforms in ventilated patients. Ineffective effort and double-triggering are the most common and easily detected asynchronies. 92 Although a bedside evaluation of respiratory waveforms is a traditionally accepted and reliable method to identify asynchronies,106-108 this technique requires specific skills and expertise. 109-111 It has also been suggested that an incorrect estimation of the patient’s breathing frequency is one of the consequences of the difficulties in appreciating patient-ventilator asynchronies.

56,81 Furthermore, while the identification of asynchronies appears easy in extreme situations in which the patient “fights the ventilator,” in other circumstances it is more difficult to detect asynchronies because most of them occur without any clinical signs. 48,56 Therefore, specific training appears to be crucial for correct asynchrony detection. Colombo et al110 studied the accuracy of experienced ICU physicians in detecting asynchronies in comparison with less experienced physicians (ie, first-year residents); both groups had poor performance because of the absence of specific training. These results are in line with the data reported by Chacòn et al.

111 In addition, the use of additional signals that reflect the patient’s respiratory efforts is often required to increase the ability to recognize the asynchronies. 112

Diaphragmatic Ultrasound

Another method to detect asynchronies is the diaphragmatic ultrasound. The direct observation of the diaphragm thickening can allow the detection of the patient’s inspiratory effort.117 This simple and noninvasive approach is still not standardized, and it requires the synchronization of ventilator waveforms with the diaphragmatic ultrasound signal, so its use still requires investigation.118

Esophageal Pressure

The use of esophageal pressure allows the clinician to detect every inspiratory effort, thus providing accurate information regarding the patient-ventilator interaction.113 The simultaneous observation of Paw, inspiratory flow, expiratory flow, and esophageal pressure waveforms allows the clinician to correctly match the patient’s inspiratory effort with each mechanical breath. This may enable the identification of ineffective effort as an esophageal pressure deflection that is not followed by a ventilator cycle.105 However, even if this is the standard technique for asynchrony detection, this measurement is still not available yet for routine use in daily practice due to its invasiveness.114,115

Automatic Methods

The real-time automatic detection of asynchronies, based on a machine learning approach, is a promising method aimed at identifying and quantifying asynchronies breath by breath without being affected by any kind of noise, such as secretions and body movements. 105,115 Most systems today are intended to identify the most common asynchronies, such as ineffective efforts. Chen et al119 evaluated software dedicated to the detection of ineffective efforts, using a computerized algorithm based on the characteristic features of flow and Paw deflections. The investigators applied their software to 14 mechanically ventilated adult subjects demonstrating a sensitivity and specificity > 90% in detecting ineffective triggering.

119 Mulqueeny et al120 studied an algorithm embedded in a ventilator system that was able to automatically detect the occurrence of ineffective effort and double-triggering in real time. The software was applied during both invasive and noninvasive ventilation, and it showed an overall accuracy of > 95%. 120 Younes et al121 developed a new approach for monitoring and improving patient-ventilator interaction that uses a signal generated by the equation of motion. More recently, Blanch et al122 validated a software that is able to detect ineffective effort during invasive ventilation, as well as other kinds of asynchronies such as double-triggering, aborted inspiration, and short and prolonged cycling.

Other systems aimed at automatically and noninvasively detecting asynchronies have been developed, such as spectral analysis of airway flow, the comparison between Paw and EAdi waveforms, and specific algorithms. 83,123

EAdi

A specific nasogastric tube provided with a multiple array of electrodes allows the continuous recording of the EAdi.27,37,116 Only one ventilator uses this signal for triggering. EAdi enables the detection of the onset and duration of the neural breath.105 However, like the esophageal pressure measurement, EAdi does not represent a routine measurement in clinical practice.66

Conventional Ventilator Support

Patient-ventilator interaction is strongly influenced by the ventilatory mode and settings used, as well as by the type and level of sedation. In conventional ventilation, trigger settings may affect patient-ventilator interaction. In fact, a low sensitivity setting for the inspiratory trigger may increase triggering effort, while an oversensitive trigger may cause auto-triggering, especially in cases of decreased neuromuscular drive like polyneuromyoathy. 65,89,106 During invasive ventilation, auto-triggering may be caused by noise in the ventilator circuit (eg, condensate in the respiratory circuit), whereas during NIV auto-triggering is caused mainly by nonintentional leak.

46,63 It is worth noting that, among the new algorithms recently developed to improve patient-ventilator interaction, the neural trigger seems to be able to improve all of the drawbacks of triggering asynchronies, including those due to the presence of inspiratory PEEP and leaks. 26-28 High levels of support have several detrimental effects on the ventilated patient, most notably hyperventilation, which may cause ineffective efforts, sleep fragmentation, and eventually apnea. 98 High levels of support should be avoided in patients affected by chronic heart failure, who are particularly exposed to central apnea and abnormal breathing pattern, due to increased chemoreceptor sensitivity.

In patients with COPD, a high level of support, especially when associated with a low expiratory threshold, prolongs the mechanical insufflations after the end of the neural inspiratory time, causing dynamic hyperinflation and consequent ineffective efforts. 48,124 Chao et al84 reported that reducing the level of pressure support in subjects with COPD was the most effective strategy to decrease the number of ineffective efforts. As previously explained, the patient–ventilation interactions worsen because of inappropriate inspiratory flow in continuous mandatory ventilation or an inadequate pressure rise time influencing the duration of a PSV breath.

12,31 Finally, air leaks may affect both pressure control and volume control ventilatory support, but to a greater extent for the latter. 1 Properly setting the inspiratory time is another important aspect of conventional ventilation. Mechanical breaths that are too long or too short may cause asynchronies due to poor matching between the neural and mechanical inspiratory times.

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