Journal Logo

Feature

Understanding ventilator waveforms—and how to use them in patient care

Lian, Jin Xiong RN

Author Information
doi: 10.1097/01.CCN.0000343236.47814.d8
  • Free

Ventilator waveforms provide real-time information about patient-ventilator interaction and ventilator function. You can observe the change in a patient's condition from breath to breath, detect problems related to mechanical ventilation, evaluate the patient's response to interventions, assess lung mechanics, and use this information to adjust therapy as needed. Unfortunately, most bedside clinicians aren't familiar with ventilator waveforms.1–3 In this article, I'll describe the basics of ventilator waveforms, how they're interpreted, and how you can use this information when caring for your patient.

Basics of ventilator waveforms

Ventilator waveforms show three key parameters: pressure, flow, and volume. The curves in a ventilator waveform can represent pressure, flow, or volume over time; the loops can represent pressure and flow plotted against volume.1,4

Time (in seconds) is always plotted on the horizontal axis; pressure, flow, and volume are plotted on the vertical axis. Airway pressure (Paw) is measured in cm H2O, and tidal volume (VT) is measured in milliliters.

If the patient is on volume-controlled ventilation, the clinician will choose the volume and flow pattern (more on this shortly). Pressure is variable and is influenced by a patient's airway resistance, chest wall and lung compliance, and the selected flow pattern.1,4 Inspiratory pressure rises until the predetermined tidal volume is delivered.

In pressure-controlled ventilation, the pressure is fixed by the clinician, and pressure rises rapidly to the set level and is maintained on that level during inspiration. Volume and flow vary depending on the patient's airway resistance and chest wall and lung compliance.4,5 Ventilator breaths are triggered by the ventilator (time-triggered).

Pressure-support ventilation is similar—pressure rises rapidly to the set level of pressure support and is maintained on that level during inspiration—but the ventilator breaths are triggered by the patient. Volume and flow vary depending on the pressure-support setting, the patient's inspiratory effort and inspiratory time, and the patient's airway resistance and compliance.

Pressure breaths (pressure control or pressure support) produce a square configuration in pressure-time curves.4,6

Now let's look at the types of waveforms.

Catching up with curves

In pressure-time curves such as Figures 1, 2 and 3, positive pressure is plotted above the horizontal axis and negative pressure is plotted below it. The curve begins at the baseline of zero or the preset extrinsic positive end-expiratory pressure (PEEPe). You can measure peak inspiratory pressure (PIP) on this type of curve.

Figure 1
Figure 1:
Pressure-time curve of volume-control ventilationA ventilator-initiated mandatory breath (A) is characterized by positive pressure rising immediately at the beginning of inspiration. In contrast, a patient-initiated mandatory breath (B) has a negative deflection at the beginning. PEEPe is set at 5 cm H2O in this example.
Figure 2
Figure 2:
Pressure-time curve of pressure-control ventilationThe square waveforms are characteristic of pressure-control ventilation. In this example, PEEPe is set at 5 cm H2O. Pressure rising directly from the baseline (A) indicates a ventilator-initiated breath. A small negative deflection before the second positive-pressure rise (B) suggests a patient-initiated breath.
Figure 3
Figure 3:
Pressure-time curve of spontaneous breathsCompare a spontaneous breath without pressure support or PEEPe (A) to one with pressure support of 10 cm H2O (B). Note the rapid rise of pressure to the predetermined level of pressure support, which gives the inspiratory portion of waveform B a square shape.

In a volume-time curve such as Figure 4, the inspiratory volume is plotted as an upslope and expiratory volume as a down slope.

Figure 4
Figure 4:
Volume-time curveA normal volume-time curve is shown in (A); in (B), the expiratory curve hasn't returned to baseline, indicating an air leak from the ventilator's expiratory limb or auto-PEEP. In (C), the expiratory curve drops below the baseline because of active exhalation or inaccurate calibration of the flow transducer.

In a flow-time curve such as Figure 5, inspiratory flow is plotted above the horizontal axis and expiratory flow below it.2,4,5 Inspiratory and expiratory times can be monitored by inspecting volume-time and flow-time curves.

Figure 5
Figure 5:
Various flow-time curvesThe square flow pattern (A) leading to a higher PIP and shorter inspiratory time may be seen in volume-control ventilation. Curves (B) and (C) show decelerating and descending ramps, respectively, which are associated with lower PIP and longer inspiratory time. They occur in pressure-control and pressure-support ventilation. The sine waveform (D) may increase PIP and may be used in volume-control ventilation.

Most modern ventilators have several flow patterns. Because there aren't enough studies comparing the advantages and disadvantages of the various flow patterns, the choice is up to the clinician.6,7–11

With volume control ventilation, the operator usually can select square, decelerating, descending ramp, or sine flow patterns. Decelerating or descending flow patterns occur in pressure control or pressure support ventilation.2,6,10,11

  • A square flow pattern (Figure 5, A) has a constant air flow during inspiration, which shortens inspiratory time and prolongs expiratory time. Unfortunately, this flow pattern also is associated with a higher PIP and greater risk of ventilator-induced lung injury (VILI).
  • In decelerating and descending ramp flow patterns, (Figure 5, B and C, respectively) the peak flow is delivered at the beginning of inspiration and the flow is subsequently decreased until the set volume is delivered or the targeted pressure is reached. Compared with square flow patterns, ramp flow patterns produce a lower PIP, but increase mean airway pressure and prolong inspiratory time.
  • The sine flow pattern (Figure 5, D) mimics spontaneous breaths and is characterized by gradual acceleration and tapering. This flow pattern may increase PIP and cause patient discomfort.

A decelerating flow pattern is recommended for patients with acute respiratory distress syndrome (ARDS) and acute lung injury, because in addition to reducing the risk of VILI, the slow air flow rate and increase in mean airway pressure more evenly distribute gas, reduce alveolar collapse and dead space, increase alveolar recruitment, decrease collapse of small airways, and improve oxygenation.1,9,10,12,13

The disadvantage of decelerating flow is that the shortened expiratory time may produce air trapping and increase auto positive end-expiratory pressure (auto-PEEP). Therefore, a square waveform is commonly used for patients with asthma or chronic obstructive pulmonary disease (COPD).10,14 However, some studies show a decelerating waveform is more beneficial to patients with COPD because it reduces airway resistance, the ventilator work of breathing, and improves gas distribution.8,15

Looking at loops

Plotting two variable parameters against one another creates a loop, such as a pressure-volume (PV) or flow-volume (FV) loop.

The PV loop displays the relationship between pressure and volume. Spontaneous breaths without PEEPe or pressure support create negative pressure during inspiration and positive pressure on expiration. The inspiratory curve is plotted on the left side of the vertical axis and the expiratory curve on the right side (Figure 6). The loop starts at the intersection of the axes (zero point) and is plotted in a clockwise direction.4,5

Figure 6
Figure 6:
PV loop of a spontaneous breath without PEEPe or pressure supportThe loop starts at the zero point and is plotted clockwise.

With volume-control, pressure-control, or pressure-support ventilation, pressure increases during inspiration and decreases on expiration, so the PV loop always travels counterclockwise. You'll see minor differences between the PV loop configurations in volume-control, pressure-control, and pressure-support ventilation. (Figures 7 and 8 show volume-control breaths.)4,5

Figure 7
Figure 7:
PV loop of a ventilator-initiated mandatory breath with volume control ventilationThe loop starts at the set PEEPe of 5 cm H2O and travels counterclockwise.
Figure 8
Figure 8:
PV loop of a patient-initiated mandatory breath with volume control ventilationThe patient's effort produces a small “trigger-tail” waveform on the left side of the PV loop at the beginning of inspiration. PEEPe is set to 5 cm H2O.

Ventilator-initiated breaths are time-triggered (Figure 7). Patient-initiated breaths create negative or positive pressure less than the set PEEPe to form a “trigger-tail” at the beginning of inspiration (Figure 8). The size of the “trigger-tail” reflects the work of breathing needed by the patient to trigger the ventilator (it's also influenced by the sensitivity setting).5,9,16 An insensitive sensitivity setting requires a greater patient effort to trigger the ventilator. As a result, the work of breathing is increased.

With FV loops, the inspiratory flow can be depicted above or below the horizontal axis depending on the ventilator's con figuration. The loop's shape is determined by the patient's lung mechanics, the preset flow pattern, and the ventilator mode (Figure 9). The key value of FV loops is to evaluate bronchodilator therapy. These loops also can be used to identify air leaks or auto-PEEP, shown as the loop not closing back at the zero point.5,16,17 (Air trapping, or air remaining in the airways at end-expiration produces positive pressure, or auto-PEEP.)

Figure 9
Figure 9:
Flow-volume loop of pressure ventilation with a descending ramp flow patternInspiration is represented by the curve above the baseline and expiration by the curve below the baseline.

Recognizing trouble

Now that you know about the shapes of normal waveforms, let's look at how you can use this noninvasive bedside tool to monitor patient response to ventilatory support.15,18

  • Identifying auto-PEEP. Inspect the patient's flow-time curve: If the expiratory portion of the curve fails to return to the baseline before the next inspiration, the patient has auto-PEEP (Figure 10).1,4,19 On a FV loop, auto-PEEP may be the culprit if the expiratory curve doesn't return to the starting point to complete the loop (Figure 11).16,19
Figure 10
Figure 10:
Auto-PEEP on a flow-time curveWhen the expiratory curve doesn't return to baseline before the next inspiration, the patient has auto-PEEP.
Figure 11
Figure 11:
Auto-PEEP on an FV loopA flow-volume loop that doesn't close on the inspiratory curve indicates auto-PEEP.

The common causes of auto-PEEP include inadequate expiratory time and increasing airway resistance. An inadequate expiratory time may be caused by a rapid respiratory rate or a prolonged inspiratory time due to a slow inspiratory flow. Increasing airway resistance may result from bronchospasm, respiratory inflammation, respiratory secretions, or early collapse of alveoli or small airways during exhalation. Auto-PEEP reduces venous return, decreases cardiac output and increases work of breathing. Work with the clinician to adjust ventilator settings as necessary, administer bronchodilators and anti-inflammatory drugs, and suction the patient as needed to reduce airway resistance.

  • Recognizing patient-ventilator dyssynchrony. This occurs when ventilatory support doesn't meet a patient's requirement or doesn't synchronize with a patient's respiratory drive. For instance, pain or agitation may increase the patient's respiratory drive significantly, causing patient-ventilator dyssynchrony.15,20 Patient-related factors in patient-ventilator dyssynchrony include the respiratory drive and lung mechanics. Ventilator factors include the sensitivity setting, flow delivery, cycle-off criteria, mode of ventilation, and degree of ventilatory support.21–23

The three major types of patient-ventilator dyssynchrony are flow, trigger, and cycle. Identifying patient-ventilator dyssynchrony as early as possible is crucial because dyssynchrony increases work of breathing and patient discomfort and reduces the effectiveness of ventilatory support.15,20,23 Like auto-PEEP and air trapping, patient-ventilator dyssynchrony can be identified on ventilator waveforms.

Flow dyssynchrony (also called flow starvation) means the patient isn't getting enough air to meet metabolic demands. On a pressure-time curve, the normally convex shape of the inspiratory limb will appear punched down or concave, and you'll also see a drop in airway pressure (Figure 12).4,5,22,23 The degree of concavity depends on the set flow rate and the patient's demand. On a PV loop, look for a concave section in the inspiratory curve or the appearance of the “figure eight”—this suggests an active patient effort to draw more air flow during inspiration (Figures 13 and 14).5,7,19,24

Figure 12
Figure 12:
Flow dyssynchrony on a pressure-time curveCompare the convex inspiratory curve representing normal, adequate flow (A) to the concave inspiratory curve with a drop in airway pressure (B) indicating flow dyssynchrony (also called flow starvation).
Figure 13
Figure 13:
Flow dyssynchrony on a PV loopThe concavity in the inspiratory curve suggests that airflow isn't adequate to meet patient demand.
Figure 14
Figure 14:
Flow dyssynchrony on a PV loopIn this example, the figure-eight appearance of the loop suggests flow dyssynchrony.

Intervene by increasing the flow rate or changing from volume ventilation to pressure ventilation, which will provide additional flow to satisfy the patient's inspiratory requirements.4,16

Trigger dyssynchrony occurs when a patient's breathing effort isn't enough to trigger ventilatory support. Common causes are a low or an insensitive sensitivity setting and auto-PEEP, which makes it harder for patients to trigger the ventilator (Figures 15 and 16). On a pressure-time curve, you'll see that because of an inappropriate sensitivity setting, the negative deflection representing the patient's inspiratory effort isn't followed by a rise in positive pressure above the baseline (Figure 15). Adjust the sensitivity to be more responsive to the patient's effort.22–24 If air trapping or auto-PEEP is the problem, obtain an order to adjust PEEPe to reduce the work of breathing so that the patient can trigger the ventilator.23–25 (Remember that applying high PEEPe may increase auto-PEEP.)

Figure 15
Figure 15:
Trigger dyssynchrony on a pressure-time curveNote the negative deflection (the patient's breathing effort), which isn't followed by a rise in positive pressure above the baseline because of an insensitive sensitivity setting.
Figure 16
Figure 16:
Trigger dyssynchrony on a flow-time curveBecause of auto-PEEP, the patient's effort can't trigger the ventilator.

Cycle dyssynchrony occurs when the ventilator's inspiratory flow stops prematurely or continues into the patient's neural expiratory time. Figure 17 shows a pressure spike at the end of inspiration, indicating that the patient started to exhale before the ventilator cycled to expiration.5,15,22,24 Pressure support ventilation usually is flow cycled, so shortening the inspiratory time by adjusting the flow cycle criterion or lowering the pressure support level may solve this problem.15,22,23

Figure 17
Figure 17:
Cycle dyssynchrony during pressure support ventilationThe pressure spike (A) at the end of inspiration on a pressure-time curve indicates that the patient started exhaling before the ventilator cycled to expiration. Shortening the inspiratory time by adjusting the cycling criteria (B) eliminated the pressure spike.
  • Identifying problems with sen sitivity settings. If you see an increase in the depth of negative deflection on a pressure-time curve (Figure 18) or a large “trigger-tail” on a PV loop (Figure 19) at the beginning of inspiration, the sensitivity setting may be insensitive. This increases the patient's work of breathing and compromises the effectiveness of ventilatory support.15,19,26 On the other hand, an oversensitive setting may result in autotriggering (Figure 20), or a ventilator breath that's triggered without patient effort. Other causes of autotriggering are cardiac oscillation (vibration produced by heart beats, which can affect ventilator flow delivery and airway pressure), a ventilator circuit leak, or excessive water in the ventilator circuit.18,23,27,28 By inspecting the ventilator waveforms, you'll be able to identify the most appropriate sensitivity settings for your patients.
  • Detecting an air leak. If the expiratory portion of a volume-time curve doesn't return to the baseline, suspect an air leak from the expiratory limb of the ventilator circuit or auto-PEEP (Figure 4).7,24 A decrease in peak expiratory flow rate (PEFR) on a flow-time curve may be caused by an air leak from the expiratory limb of the ventilator circuit or increasing airway resistance (Figure 21).5,16
Figure 18
Figure 18:
Adjusting sensitivity settingsCompare the negative deflections indicating patient effort: Minor patient effort is needed to trigger a mandatory breath (A), an ineffective effort elicits no ventilator response (B), and increased patient effort is needed to trigger a mandatory breath because of an insensitive sensitivity setting (C).
Figure 19
Figure 19:
An insensitive sensitivity setting on a PV loopAn increase in the size of the “trigger tail” means that the patient must make a greater effort to trigger the ventilator because of an insensitive setting.
Figure 20
Figure 20:
AutotriggeringIn this waveform, A and C are spontaneous breaths; B is the ventilator being triggered without patient effort. The mode is pressure-support ventilation at 10 cm H2O.
Figure 21
Figure 21:
Air leak or increasing airway resistanceA decrease in PEFR on a flow-time curve suggests an air leak from the ventilator circuit's expiratory limb, or increasing airway resistance.

An air leak from the inspiratory limb of the ventilator circuit or a decrease in airway resistance appears on the ventilator waveform as a decrease in PIP (Figure 22). An air leak from the ventilator's inspiratory limb also can appear as delivered tidal volume that's less than the set tidal volume (Figure 23).3,5

Figure 22
Figure 22:
Air leak on a pressure-time curveIn this waveform, the decrease in PIP suggests an air leak from the ventilator's inspiratory limb, or a decrease in airway resistance.
Figure 23
Figure 23:
Air leak on a volume-time curve of volume-control ventilationDelivered tidal volume less than set tidal volume indicates an air leak from the ventilator's inspiratory limb.

On ventilator loops, an incomplete loop indicates an air leak, as shown in Figures 24 (a PV loop) and Figure 25 (an FV loop). Look at the end point of the loop to estimate the quantity of the air leak in milliliters.5,16

Figure 24
Figure 24:
Air leak on a PV loopThe expiratory curve on this loop doesn't return to the starting point, suggesting an air leak of 100 mL.
Figure 25
Figure 25:
Air leak on an FV loopThe same 100-mL expiratory air leak on an FV loop, again indicated by the expiratory portion of the loop not closing at the zero point.
  • Identifying other problems related to mechanical ventilation. Expiratory tidal volume that exceeds inspiratory tidal volume can be caused by active patient exhalation (for example, because of auto-PEEP as in Figure 26) or inaccurate calibration of the ventilator's flow transducer.16,24 If active exhalation is the problem, the patient may need to be sedated so his respiratory muscles can rest. A ventilator with calibration problems will need to be serviced.
  • Evaluating the effect of bronchodilators. Effective bronchodilator therapy reduces airway resistance. You'll see this as reduced PIP on a pressure-time waveform, increased PEFR and less profound auto-PEEP on a flow-time waveform, and shortened expiratory time on flow-time and volume-time curves (Figure 27).5,16,19
Figure 26
Figure 26:
Active exhalationAuto-PEEP that causes active patient exhalation is shown as a negative deflection on the volume-time curve because the exhaled volume exceeds the inspired volume.
Figure 27
Figure 27:
Evaluating the effect of bronchodilatorsBefore-and-after waveforms showing how effective bronchodilator therapy reduces airway resistance. In the pressure-time curve (top), PIP falls. In the flow-time curve (middle), PEFR rises and auto-PEEP is decreased. Expiratory time is reduced in the flow-time and volume-time curves (bottom).

On an FV loop, increasing airway resistance is seen as decreased PEFR on the expiratory curve and a non-linear return to the starting point. Figure 28 shows how effective bronchodilator therapy increases PEFR and leads to more linear return of the expiratory curve.5,19

Figure 28
Figure 28:
Changing airway resistanceThe dashed line shows decreased PEFR on an FV loop, indicating increased airway resistance. Effective bronchodilator therapy increases PEFR and restores the expiratory curve to a more linear shape (solid line).
  • Determining the level of neuromuscular blockade. A patient-initiated breath by a patient on neuromuscular blockade is called “breakthrough breathing,” and indicates an inadequate level of muscle relaxants or the tapering off of muscle relaxants. In Figure 29, you can see the negative deflection indicating a patient-initiated breath on the pressure-time curve. This is a simple and reliable way to determine if the level of neuromuscular blockade is adequate.4,5
  • Monitoring respiratory resistance and compliance. Changes in airway resistance and chest wall and lung compliance can be identified by reviewing PV or FV loops. For instance, a widening or increase in the bowing of a PV loop suggests increased airway resistance (Figure 30).4,5,7
Figure 29
Figure 29:
Assessing the level of neuromuscular blockadeA patient-initiated breath (breakthrough breathing) at the 4-second mark on this waveform indicates that neuromuscular blockage is inadequate or is tapering off. The mode is volume-control ventilation.
Figure 30
Figure 30:
Change in airway resistanceThe normal PV loop, shown as a solid line, widens or bows (dashed line) when the patient's airway resistance increases.

The slope of PV loops is primarily affected by the patient's chest wall and lung compliance. Decreasing compliance lowers the slope of a PV loop and moves it toward the right. Improving compliance elevates the slope and moves it toward the left (Figure 31).4,5,16,17 For example, if chest compliance is compromised by ascites or obesity, place the patient in high Fowler's position to improve chest compliance and ventilation. The changes in ventilator waveforms should be obvious after this intervention.

Figure 31
Figure 31:
Change in lung complianceDecreasing lung compliance reduces the slope of a PV loop (dashed line); improving compliance increases the slope (solid line).

Both PV and FV loops can be used to estimate respiratory resistance. Changes in lung compliance may be monitored by examining changes in PV loops. See Figures 28, 30, and 31 for the dynamic trend of respiratory resistance and compliance.5,7,17

  • Setting up optimal PEEP and tidal volume. With PV loops, the low inflection point (LIP) is considered the point of pressure where most alveolar recruitment begins. Alveoli can be filled and opened rapidly when pressure is increased above this point (Figure 32). Alveolar overdistension occurs at the upper inflection point (UIP). A small increase in tidal volume beyond this will increase pressure significantly and lead to alveolar overdistension, putting patients at high risk of VILI (Figures 32 and 33).2,12,17,29
Figure 32
Figure 32:
Setting up optimal PEEPeSome clinicians recommend setting PEEPe above the low inflection point and keeping plateau pressure below the upper inflection point, if these points can be identified on a PV loop.
Figure 33
Figure 33:
Setting up optimal tidal volumeA tidal volume of 600 mL (solid line) produces a “beak” on the end of inspiration on the PV loop, indicating alveolar overdistension. Reducing the tidal volume to 500 mL (dashed line) eliminates the “beak”.

How to set the optimal PEEPe for patients with ARDS is controversial.29 Inadequate PEEPe lets unstable alveoli and small airways collapse. Repeated opening and closing of alveoli with each ventilator cycle increases shearing forces and causes VILI. Excessive PEEPe also causes VILI and hypotension, decreases cardiac output, and leads to reduced oxygen delivery. Some clinicians recommend setting PEEPe at 2 to 4 cm H2O higher than the LIP to prevent alveolar and small airway collapse, and keeping plateau pressure below the UIP to prevent lung injury.12,30–32

However, the LIP is influenced by many factors, such as the flow rate, PIP, patient respiratory activity, and patient chest wall and abdominal compliance. Neither inflection point can be determined from dynamic PV loops under normal conditions. Short-term sedation and neuromuscular blockade as well as zero PEEPe are often required to locate the LIP. Also there's no standard method to determine the precise location of the LIP. As a result, the clinical application of the inflection points is significantly limited, and most clinicians prescribe PEEPe and tidal volume based on experience and preference.1,2,12,33–36

Another use for PV loops is in setting up an optimal tidal volume. A “beak” on the end of inspiration of the PV loop indicates alveolar overdistension (Figure 33). With volume-control ventilation, the preset tidal volume should be reduced to avoid lung injury.1,2,24 Fenstermacher and Hong9 recommend that optimal tidal volume be set at a point that is 2 cm H2O below the UIP. Others recommend that the tidal volume be set at a level that maintains plateau pressure below the upper inflection point.32,36

Riding the wave

Ventilator graphics are widely available and a valuable bedside monitoring tool. By understanding the usefulness of this graphical information, you'll be able to identify and respond to problems promptly and appropriately. By understanding how to interpret and apply ventilator waveforms, you'll be able to enhance the effectiveness of mechanical ventilation and optimize patient care.

REFERENCE

1. Branson RD, Davis K, Campbell RS. Monitoring graphic displays of pressure, volume and flow: the usefulness of ventilator waveforms. World Federation J Crit Care. 2004;1(1):8–12.
2. Pruitt WC. Ventilator graphics made easy. RT. 2002;15(1):23–24,50.
3. Zahodnic RJ. Ventilation for life. Ventilator waveforms: an example of a structured approach to analysis. AARC Times. 2000;24(4):10–14.
4. Burns SM. Working with respiratory waveforms: how to use bedside graphics. AACN Clin Issues Adv Pract Acute Crit Care. 2003;14(2):133–144.
5. Shortall SP, Perkins LA. Ventilator graphics and waveform analysis. In: Pierce LNB, ed. Management of the Mechanically Ventilated Patient. 2nd ed. Elsevier Saunders; 2007.
6. Hess DR. Ventilator waveforms and the physiology of pressure support ventilation. Respir Care. 2005;50(2):166–186.
7. Puritan Bennett. Ventilator waveforms: Graphical presentation of ventilatory data. Pleasanton, CA, Tyco Healthcare, 2003.
8. Yang SC, Yang SP. Effects of inspiratory flow waveforms on lung mechanics, gas exchange, and respiratory metabolism in COPD patients during mechanical ventilation. Chest. 2002;12(6):2096–2104.
9. Fenstermacher D, Hong D. Mechanical ventilation: What have we learned? Crit Care Nurs Q. 2004;27(3):258–294.
10. Pilbeam SP. Initial ventilator settings. In: Pilbeam SP, Cairo JM, eds. Mechanical Ventilation: Physiological and Clinical Application, 4th ed. Elsevier; 2006.
11. Pierce LNB. Mechanical ventilation: indications, ventilator performance of the respiratory cycle, and initiation. In: Pierce LNB, ed. Management of the Mechanically Ventilated Patient. 2nd ed. Elsevier; 2007.
12. Donahoe M. Basic ventilator management: lung protective strategies. Surg Clin North Am. 2006;86(6):1389–1408.
13. Barbas CSV, De Matos GFJ, Pincelli MP, et al. Mechanical ventilation in acute respiratory failure: recruitment and high positive end-expiratory pressure are necessary. Curr Opin Crit Care. 2005;11(1):18–28.
14. Corbridge SJ, Corbridge TC. Severe exacerbations of asthma. Crit Care Nurs Q. 2004;27(3):207–230.
15. Nilsestuen JO, Hargett KD. Using ventilator graphics to identify patient-ventilator asynchrony. Respir Care. 2005;50(2):202–232.
16. Pilbeam SP. Ventilator graphics. In: Pilbeam SP, Cairo JM, eds. Mechanical Ventilation: Physiological and Clinical Applications. 4th ed. Elsevier Mosby; 2006.
17. Lucangelo U, Bernabe F, Blanch L. Respiratory mechanics derived from signals in the ventilator circuit. Respir Care. 2005;50(1):55–65.
18. Georgopoulos D, Prinianakis G, Kondili E. Bedside waveforms interpretation as a tool to identify patient-ventilator asynchronies. Intensive Care Med. 2006;32(1):34–47.
19. Dhand R. Ventilator graphics and respiratory mechanics in the patient with obstructive lung disease. Respir Care. 2005;50(2):246–259.
20. Hess DR, Thompson BT. Patient-ventilator dyssynchrony during lung protective ventilation: What's a clinician to do? Crit Care Med. 2006;34(1):231–233.
21. Kondili E, Xirouchaki N, Georgopoulos D. Modulation and treatment of patient-ventilator dyssynchrony. Curr Opin Crit Care. 2007;13(1):84–89.
22. Epstein SK. Optimizing patient-ventilator synchrony. Semin Respir Crit Care Med. 2001;22(2):137–152.
23. Thille AW, Brochard L. Promoting patient-ventilator synchrony. Clin Pulm Med. 2007;14(6):350–359.
24. McArthur C. Ventilation for life. Ventilator graphics: improving patient care. AARC Times. 2005;29(4):13–14,16,18,20.
25. Blanch L, Bernabe F, Lucangelo U. Measurement of air trapping, intrinsic positive end-expiratory pressure, and dynamic hyperinflation in mechanically ventilated patients. Respir Care. 2005;50(1):110–124.
26. Pruitt WC. Ventilation for life. Patient waveforms: more than just ventilator graphics. AARC Times. 2003;27(8):6,8,10–12.
27. Lucangelo U, Bernabe F, Blanch L. Lung mechanics at the bedside: make it simple. Curr Opin Crit Care. 2007;13(1):64–72.
28. Imanaka H, Nishimura M, Takeuchi M, Kimball WR, Yahagi N, Kumon K. Autotriggering caused by cardiogenic oscillation during flow-triggered mechanical ventilation. Crit Care Med. 2000;28(2):402–407.
29. Levy MM. Optimal PEEP in ARDS: Changing concepts and current controversies. Crit Care Clin. 2002;18(1):15–33.
30. Villar J, Kacmarek RM, Perez-Mendez L, Aguirre-Jaime A. A high positive end-expiratory pressure, low tidal volume ventilatory strategy improves outcome in persistent acute respiratory distress syndrome: a randomized, controlled trial. Crit Care Med. 2006;34(5):1311–1318.
31. Pilbeam SP. Improving oxygenation and management of ARDS. In: Pilbeam SP, Cairo JM, eds. Mechanical Ventilation: Physiological and Clinical Applications. 4th ed. Elsevier Mosby; 2006.
32. Lee WL, Stewart TE, MacDonald R, et al. Safety of pressure-volume curve measurement in acute lung injury and ARDS using a syringe technique. Chest. 2002;121(5):1595–1601.
33. Blanch L, Lopez-Aguilar J, Villagra A. Bedside evaluation of pressure-volume curves in patients with acute respiratory distress syndrome. Curr Opin Crit Care. 2007;13(3):332–337.
34. Nishida T, Suchodolski K, Schettino GPP, et al. Peak volume history and peak pressure-volume curve pressures independently affect the shape of the pressure-volume curve of the respiratory system. Crit Care Med. 2004;32(6):1358–1364.
35. Hickling KG. Reinterpreting the pressure-volume curve in patients with acute respiratory distress syndrome. Curr Opin Crit Care. 2002;8(1):32–38.
36. Richard J-CM, Mercat A, Maggiore SM, Bonmarchand G. Method and interpretation of the pressure volume curve in patients with acute respiratory distress syndrome. Clin Pulm Med. 2005;12(6):352–358.
© 2009 Lippincott Williams & Wilkins, Inc.