![]() | Only 14 pages are availabe for public view |
Abstract The respiratory system is both remarkable and complicated. Knowledge of pulmonary anatomy provides a sound foundation for understanding the complex processes of respiration ( Pierce, 2006). Over the past decades, the respiratory physiology research has greatly improved our understanding of the respiratory system. Successful mechanical ventilation requires a basic understanding of respiratory physiology and ventilator mechanics ( Davenport et al.,2010). Mechanical ventilation is a commonly used technique in the intensive care unit (ICU) (Slutsky and Brochard, 2006). Many factors affect the decision to begin mechanical ventilation. Because no mode of mechanical ventilation can cure a disease process, the patient should have a correctable underlying problem that can be resolved with the support of mechanical ventilation. This intervention should not be started without thoughtful consideration because intubation and positive-pressure ventilation are not without potentially harmful effects. Mechanical ventilation is indicated when the patient’s spontaneous ventilation is inadequate to sustain life ( Byrd et al., 2013). The evidence base for the use of non-invasive ventilation (NIV) in a number of different clinical situations has increased greatly in recent years; however, there remain a number of contraindications to its use. despite increasing interest in its use, NIV should not be considered as a replacement for MV and should not delay intubation and MV in those patients who fail to respond to or deteriorate on NIV (McNeill and Glossop, 2012). Patient-ventilator asynchrony, defined as a mismatch between the patient’s neural inspiratory time and the ventilator’s insufflation time (Thille et al., 2008). Given the multiple interactions between the patient’s innate control of breathing and ventilator operation, it is not surprising that patient-ventilator synchrony is more often the exception than the rule (Branson, 2011). The goal of patient-ventilator synchrony is to have the various parts of ventilator-assisted breathing coincide with the patient’s intrinsic breathing pattern (De Wit, 2011). Patient-ventilator interaction is influenced by factors related to the patient and factors related to the ventilator. Patient-related factors such as respiratory center output, respiratory mechanics, disease states or conditions and endotracheal tube type or size influence the patient-ventilator interaction (Mellott et al., 2009). Synchronous patient-ventilator interaction requires a ventilator to be sensitive to respiratory efforts and responsive to airflow demand. Two major factors contributing to PVD are ventilator triggering (signal opens inspiratory valve) and cycling (signal opens expiratory valve at end inspiration) (Racca et al., 2005). Patient-ventilator asynchrony is common, and its prevalence depends on numerous factors, including timing and duration of observation; detection technique; patient population; type of asynchrony; ventilation mode and settings (eg, trigger, flow, and cycle criteria); and confounding factors (eg, state of wakefulness, sedation) (Epstein, 2011 ). Monitoring of patient-ventilator interactions at the bedside is an integral part of caring for the critically ill patient. Caring for the mechanically ventilated patient involves examining the impact of patient breathing and behavior on ventilator settings, and vice versa (MacIntyre and Branson, 2009). Accurate assessment of patient-ventilator interactions and work of breathing (WOB) requires invasive measurements of pleural pressure and/or respiratory muscle electromyogram. Use of an esophageal balloon, which permits determination of pleural pressure, and respiratory muscle electromyograms have been used to measure a variety of patient-ventilator interactions and to compute WOB. However, these devices are not used during routine patient care and clinicians must rely on physical examination of the patient as well as visual inspection of waveforms to assess for patient-ventilator synchrony and asynchrony. Visual inspection of waveforms has been shown to correlate well with esophageal-balloon readings, but is not without error (Spahija et al., 2010). It is important for clinicians not to assume that ventilator settings are optimal for the patient. Rather, clinicians must evaluate the patient and response to ventilator settings before drawing conclusions about patient-ventilator synchrony. The patient is the focus point and the clinician must adjust the mechanical ventilator to meet the patient’s ventilatory requirements. The goal is to have the “right tool for the right job,” and clinicians must not assume that one “tool” (ie, set of ventilator parameters) satisfies the needs of different patients. It is only after careful observation of the patient and examination of ventilator waveforms that clinicians should assume the patient and ventilator are synchronous. When a patient appears uncomfortable, physical examination and evaluation of ventilator waveforms are the first steps in the management of the patient (de Wit, 2011). Ventilator graphics are available on almost all current mechanical ventilators and have been available for evaluating the patient-ventilator interface. Both direct and anecdotal evidence, however, suggests that bedside use of ventilators’ graphics capabilities is widely underutilized and standard approaches or guidelines for graphics interpretation are often lacking. The use of guidelines, standards and protocols for assessing and treating disease states improves patient outcomes. Similarly, a standard approach to analysis of ventilator waveforms should improve Evaluation of patient-ventilator synchrony (Nilsestuen and Hargett, 2005). Dividing the breath into 4 phases, simplify the analysis of patient-ventilator asynchrony. Trigger Asynchrony (Phase 1): Trigger asynchrony is fairly easy to identify on the flow and pressure waveforms. The patient’s missed trigger often appear as a sudden movement of the expiratory flow waveform toward the zero baseline (convexity) and a concomitant DROP in the airway pressure waveform toward baseline (concavity). In Doubletriggering the airway pressure waveforms indicate inadequate flow (concave or dished out pressure waveform) and the continuation of patient effort, leading to double-triggering. In Autotriggering the absence of the initial pressure DROP below end-expiratory pressure is indicative of autotriggering. (Nilsestuen and Hargett, 2005). Flow Asynchrony (Phase 2): Evaluating Flow Asynchrony during Volume-Controlled Ventilation. 1. Inadequate flow is evidenced by an inward buckling on the initial part of the ascending limb of the pressure waveform 2. To evaluate flow adequacy, the clinician needs to be familiar with the normal, relaxed, pressure waveforms associated with the various flow options. 3. Careful evaluation of the pressure waveform may reveal over-distention ( Hasan, 2010). Pressure ventilation with variable flow. Flow starvation during PSV results in a loss of the usual peak on the flow-time waveform. On the pressure–time scalar, such increased efforts are also evident during the triggering phase, as deep negative deflections that precede the machine assisted breaths ( Hasan, 2010). Evaluating Rise Time. 1. Rise time can be evaluated by observing the pressure and flow waveforms. 2. Usually the pressure waveform should achieve near target pressure early in the inspiratory cycle. Short (fast) rise time may cause a pressure spike near the beginning of the pressure waveform. 3. The flow waveform should smoothly reach the peak flow and then appropriately decrease. 4. In general, faster rise time should reduce patient WOB (Gonzales et al., 2013). Termination Asynchrony (Phase 3): Delayed Termination. Delayed breath-termination is evidenced by a pressure spike at the end of the breath and rapid decrease in the flow, which can cause subsequent failed trigger attempts (Correger et al., 2012). Premature Termination. Premature breath-termination can be identified on the pressure waveform, which will show a posttermination concavity (indicating continued patient effort) and on the flow waveform, which will show rapid deceleration and a convex pattern in the expiratory flow waveform, which indicates continued patient effort (Georgopoulos et al., 2006). Expiratory Asynchrony (Phase 4): The major consideration during the expiratory phase is the presence or creation of auto-PEEP, which can be caused by insufficient expiratory time or by asynchrony created during the flow or termination phases. 1. Routinely check for auto-PEEP by inspecting the end of the expiratory flow waveform and by measuring auto-PEEP (most commonly performed at the bedside with the expiratory-hold technique) ( Hasan, 2010). To date, detection of asynchrony has required well trained clinicians at the bedside. More recently, several investigators have explored the use of machine learning and pattern recognition to automatically detect asynchrony (Branson et al., 2013 ). Patient-ventilator asynchrony is associated with adverse effects, including ineffective ventilation, impaired gas exchange, lung overdistention, increased/wasted WOB and patient discomfort. Far more common than previously recognized, it also predisposes to respiratory muscle dysfunction and other complications, leads to excessive use of sedation, interferes with weaning, prolonged mechanical ventilation, longer ICU and hospital stay and possibly higher mortality. Whether asynchrony is a marker of poor prognosis or causes these adverse outcomes remains to be determined (Pierson, 2011). Assisted/supported modes of mechanical ventilation offer significant advantages over controlled modes in terms of ventilator muscle function/recovery and patient comfort (and sedation needs). Assisted/supported ventilation is designed to interact with patient muscle activity and “share” the work of breathing. If properly done, assisted/supported ventilation facilitates ventilatory muscle recovery and generally requires less sedation. For this to occur, however, the ventilator’s flow and pressure delivery must synchronize with patient effort during all three phases of breath delivery: breath initiation, flow delivery and breath termination (Gilstrap and MacIntyre, 2013). In applying conventional ventilation modes, several design features can be used to improve patient-ventilator synchrony (MacIntyre, 2011). Optimizing Breath Triggering: The clinician should choose the trigger sensor (flow vs pressure) that is most sensitive and responsive to patient effort (Sassoon, 2011). In the setting of intrinsic PEEP trigger dyssynchrony, there are several clinical strategies. First, clinicians should try reducing the intrinsic PEEP as much as possible by reducing minute ventilation (e.g., reduce set rate, reduce set PI, reduce set VT, reduce ventilation needs driving patient efforts), lengthening the expiratory time, or improving airway mechanics. In addition, the triggering load from intrinsic PEEP can be reduced by applying 70–80% of measured intrinsic PEEP as circuit PEEP (Chen et al., 2008). Managing an extra-triggering phenomenon depends on the cause. Ventilator autotriggering can be managed with a careful search for reversible causes (e.g., water in the circuit, small leaks) and/or adjustments to the trigger sensitivity settings. Managing entrainment effects can be more problematic as this phenomenon is less well studied. Additional sedation seems counterproductive as entrainment is associated with the use of heavy sedation. Conceptually, a reduction in sedation and mandatory breath delivery might be useful, but this has not been studied (Chen et al., 2008). Optimizing Flow Delivery: With a fixed-flow breath, because the size of the VT can impact synchrony, the VT itself can be adjusted (Kahn et al., 2005). In addition to VT magnitude, the magnitude and shape (sinusoidal vs square vs decelerating) of the flow can be adjusted to enhance synchrony. Inspiratory-time adjustments can also be made with the application of an inspiratory pause. These manipulations are usually applied with a trial-and-error approach while constantly monitoring the airway pressure graphic and patient comfort (Chiumello et al., 2002). Pressure-targeted breaths may offer synchrony advantages over flow-targeted breaths. This is because pressure targeting allows the ventilator to deliver whatever flow is needed to attain the set pressure target. Flow thus varies with patient effort and this feature has been shown in many clinical studies to thereby enhance flow synchrony (Yang et al., 2007). The pressure-targeted breath also has several features that can enhance synchrony. One is adjustment of the rate of pressure rise to the target. A way to titrate this adjustment is simply to look at the airway pressure graphic and try to create a smooth square wave of pressure (Gilstrap and MacIntyre, 2013). Optimizing Breath Cycling: Achieving breath cycling synchrony involves delivery of an appropriate VT in accordance with patient demands and matching of neural and machine TI. With flow–volume targeting, adjusting the VT and machine TI is relatively straightforward as these are set independent variables that produce the machine TI. With pressure targeting, adjusting the VT and machine TI is more complex and involves the interactions of applied PI, respiratory system mechanics, patient effort and cycling criteria. Altering any of these parameters often results in changes in others. In general, higher PI settings, better mechanics, increased effort and longer cycling criteria settings (higher set TI in pressure assist control ventilation, lower expiratory flow criteria with PSV) extend the machine TI. The pressure rise time in PSV can also affect machine TI depending on its effects on the resulting patient ventilator drive and its impact on peak flow and the flow cycling criteria (Gentile, 2011). The Distribution of Ventilator Breaths May Affect Synchrony: It would seem that the best clinical strategy is to provide as consistent a breath pattern as possible (ie, avoiding SIMV and supplying the fewest possible controlled backup breaths with assist-control modes). This is the most direct approach to stabilizing respiratory drive, which, conceptually, makes it easier to synchronize the ventilator and the patient (MacIntyre, 2011). It is important to point out that evidence-based reviews of the weaning process, done over the last 20 years, have never shown an advantage from gradual reduction in support, versus simply providing stable support and doing daily spontaneous breathing trials. Thus, the notion of protocolized or automated reduction in inspiratory pressure in between spontaneous breathing trials must be challenged as a desirable strategy. It may be that, if one does daily spontaneous breathing trials, the level of support in between the trials is irrelevant, so aggressive pressure-reduction strategies may only increase the need for sedation from asynchrony (MacIntyre, 2011). Ventilator manufacturers have developed new ventilation modes that target both pressure and volume and have added adjuncts to pressure-targeted ventilation that are designed to improve synchrony: rise time and breath-termination (ie, cycle) criteria. Some ventilator manufacturers have tried to automate these functions to ensure that gas delivery changes as patient demand changes, but despite these new options, asynchrony is still a major problem (Kacmarek, 2011). Proportional assist ventilation (PAV) and neurally adjusted ventilatory support (NAVA), both of these modes are designed to improve patient-ventilator synchrony. Although each controls gas delivery by a different method, both are designed primarily to respond to changes in the patient’s ventilatory demand and to decrease patient effort. PAV is controlled by changes in the patient’s work of breathing and NAVA is controlled by changes in the electromyographic (EMG) activity of the diaphragm. It is critical to understand that with both PAV and NAVA the clinician does not set pressure, flow, volume or time: all those variables are under the complete control of the patient. Essentially, the ventilator proportionally unloads patient effort, in both PAV and NAVA, based on the setting of ventilator work: proportion (%) unloaded by the ventilator (PAV), or cm H2O pressure applied per millivolt of diaphragmatic EMG activity (NAVA) (Kacmarek, 2011). Airway pressure release ventilation (APRV) is a mode of mechanical ventilation that is best described as a partial ventilatory support and is based on the open lung concept. The primary goals of this mode were to provide both safety and comfort: safety in that adequate or superior ventilatory support is provided without dangerously high applied pressures. While comfort in that unrestricted spontaneous breathing would be allowed, which is a feature unavailable in conventional ventilatory modes, thus minimizing patient-ventilator asynchrony (Porhomayon et al., 2010). Sedation has become an important part of critical care practice in minimizing patient discomfort and agitation during mechanical ventilation. Pain, delirium and anxiety must all be assessed and treated to reduce the critically ill patient’s agitation. A multimodal approach to the treatment of pain appears to be the best approach (Bennett and Hurford, 2011). Historically, benzodiazepines have been the first line of therapy in the ICU setting for sedating mechanically ventilated patients. Typical benzodiazepines used in the ICU are midazolam and lorazepam (Jacobi et al., 2002). Preventing delirium by identifying and modifying risk factors is the best treatment. The key to successful management of delirium is prompt recognition utilizing a validated screening tool; then efforts should be made at identifying the etiology and pharmacotherapy, if appropriate (Otter et al., 2005). Achieving an adequate state of sedation and ventilator synchrony in some critically ill patients may require the use of anesthetics such as propofol, dexmedetomidine and NMBAs (Pohlman et al., 2008). As a general guideline, the use of NMBAs should be uncommon, the dose and duration minimized and guided by peripheral neuromuscular monitoring and adequate sedation and analgesia must be provided (Papazian et al., 2010). Nonpharmacological, complementary therapies may be an important alternative or adjunct to pharmacological interventions to treat Patients receiving mechanical ventilation symptoms such as pain, anxiety, agitation and lack of sleep while in the intensive care unit (Tracy and Chlan, 2011). Noninvasive ventilation (NIV) has received considerable academic and clinical attention in recent years. There is arguably more evidence to support the use of NIV than any other practice related to the care of patients with acute respiratory failure. It is unrealistic to expect NIV to avoid intubation in all patients. There are a number of potential causes of NIV failure. Some of these failures potentially relate to asynchrony, although the relationship between asynchrony and NIV failure has not been well studied. Good NIV tolerance has been associated with success of NIV and improved comfort has been associated with better synchrony (Hess, 2011). For acute-care applications there is value in being able to use the same ventilator for invasive ventilation, where leaks are usually absent, and for NIV, where leaks are always present. Leak compensation (control of trigger, cycle and flow delivery) in critical-care ventilators is in its infancy. Probably this will improve as engineers develop more sophisticated algorithms for leak detection and compensation. Improvements in the design of interfaces will reduce the amount of leak. Clinicians will better fit the interface with experience in the application of NIV. With the combination of improved ventilator performance in the setting of leaks, better interfaces and increased clinician experience, problems related to leaks should improve (Hess, 2012). The ability to detect ineffective trigger efforts noninvasively and automatically during NIV is attractive. This could conceivably prompt clinicians of the presence of asynchrony and the need to make ventilator adjustments, such as PEEP to counter-balance auto-PEEP. It could also be used to assess patient response to efforts to improve synchrony. However, additional evaluation is necessary before such systems are ready for incorporation into clinical practice (Antonelli et al., 2013). With an understanding of potential causes of asynchrony during NIV, a number of strategies can be implemented to address this clinical problem. These strategies are a combination of ventilator adjustments and treatment of the underlying disease process (Hess, 2011). Ventilator adjustments to improve synchrony should be systematically applied, and each intervention assessed by patient examination, the patient’s subjective reports of dyspnea and comfort, and careful assessment of the ventilator waveforms. For many patients receiving NIV, the underlying physiology is dynamic and there may be moment-by-moment changes in respiratory drive. This may require frequent manipulations of ventilator settings by clinicians, particularly when the patient is at an unstable point in the disease process (Hess, 2011). Neurally adjusted ventilatory assist (NAVA) and proportional assist ventilation (PAV) are modes intended to improve patientventilator synchrony. NAVA and PAV have been reported to improve synchrony during NIV (Kacmarek, 2011). While sedation represents the mainstay of treatment in the care of patients suffering from end-of-life respiratory failure, it can be a dangerous if improperly employed, especially during NIV. Since lack of cooperation is a well-recognised cause of NIV failure, sedation could theoretically improve patient–ventilator interaction; however, if the altered mental status of a fighting or agitated patient is the direct consequence of hypoxia and hypercapnia, then sedation would only cause an already unstable clinical situation to deteriorate (Nava et al., 2009). A reasonable choice, at present, is to administer very small doses of opioids (fentanyl and morphine) but only in cases where a moderate blunting of respiratory drive is highly desirable. Among the benzodiazepines, a small dose of lorazepam may be recommended since it has the advantage of fewer drug interactions compared with diazepam and midazolam (Nava et al., 2009). |