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Limited predictability of maximal muscular pressure using the difference between peak airway pressure and positive end-expiratory pressure during proportional assist ventilation (PAV)

Abstract

Background

If the proportional assist ventilation (PAV) level is known, muscular effort can be estimated from the difference between peak airway pressure and positive end-expiratory pressure (PEEP) (ΔP) during PAV. We conjectured that deducing muscle pressure from ΔP may be an interesting method to set PAV, and tested this hypothesis using the oesophageal pressure time product calculation.

Methods

Eleven mechanically ventilated patients with oesophageal pressure monitoring under PAV were enrolled. Patients were randomly assigned to seven assist levels (20–80%, PAV20 means 20% PAV gain) for 15 min. Maximal muscular pressure calculated from oesophageal pressure (Pmus, oes) and from ΔP (Pmus, aw) and inspiratory pressure time product derived from oesophageal pressure (PTPoes) and from ΔP (PTPaw) were determined from the last minute of each level. Pmus, oes and PTPoes with consideration of PEEPi were expressed as Pmus, oes, PEEPi and PTPoes, PEEPi, respectively. Pressure time product was expressed as per minute (PTPoes, PTPoes, PEEPi, PTPaw) and per breath (PTPoes, br, PTPoes, PEEPi, br, PTPaw, br).

Results

PAV significantly reduced the breathing effort of patients with increasing PAV gain (PTPoes 214.3 ± 80.0 at PAV20 vs. 83.7 ± 49.3 cmH2O•s/min at PAV80, PTPoes, PEEPi 277.3 ± 96.4 at PAV20 vs. 121.4 ± 71.6 cmH2O•s/min at PAV80, p < 0.0001). Pmus, aw overestimates Pmus, oes for low-gain PAV and underestimates Pmus, oes for moderate-gain to high-gain PAV. An optimal Pmus, aw could be achieved in 91% of cases with PAV60. When the PAV gain was adjusted to Pmus, aw of 5–10 cmH2O, there was a 93% probability of PTPoes <224 cmH2O•s/min and 88% probability of PTPoes, PEEPi < 255 cmH2O•s/min.

Conclusion

Deducing maximal muscular pressure from ΔP during PAV has limited accuracy. The extrapolated pressure time product from ΔP is usually less than the pressure time product calculated from oesophageal pressure tracing. However, when the PAV gain was adjusted to Pmus, aw of 5–10 cmH2O, there was a 90% probability of PTPoes and PTPoes, PEEPi within acceptable ranges. This information should be considered when applying ΔP to set PAV under various gains.

Background

Although mechanical ventilation is a crucial tool in decreasing the respiratory effort required by ventilated patients, diaphragmatic weakness can rapidly develop with complete diaphragmatic inactivity and mechanical ventilation [1]. This type of diaphragmatic powerlessness has been termed ventilator-induced diaphragmatic dysfunction (VIDD) [2]. Controlled mechanical ventilation is a major factor in VIDD, which may be attenuated with assisted ventilation [3, 4]. This suggests that maintaining appropriate respiratory effort may be essential to preserving diaphragm function, and the ability to monitor respiratory effort during mechanical ventilation should be an important clinical issue [5].

Pressure applied to the respiratory system is usually assumed to dissipate against resistant and elastic elements. In a mechanically ventilated patient, the applied pressure is shared between the patient and ventilator [6]. This equation is difficult to solve under conventional ventilation because it is challenging to obtain reliable values for respiratory system resistance and elastance. However, in proportional assist ventilation (PAV), obtaining reliable elastance is possible during spontaneous breathing because the end of inspiration can be determined [79].

PAV with load-adjustable gain factors (PAV+) is a ventilatory mode that delivers assistance in proportion to the instantaneous flow and volume by calculating the instantaneous pressure needed to overcome the elastic and resistive pressures; these are updated several times per minute during PAV ventilation [10]. The proportion assistance is expressed as a percentage of the total pressure assisted (i.e. gain). By using this algorithm, Carteaux et al. [11] proposed a look-up table for estimating peak muscular pressure from peak airway pressure (Paw, peak) and positive end-expiratory pressure (PEEP) difference (ΔP), thus offering a way to keep the patient in a predefined comfort zone by adjusting the PAV gain. However, this algorithm has not yet been validated [12].

The oesophageal pressure time product (PTPoes) is a standard reference to assess respiratory muscle pressure. In patients with successful weaning, inspiratory PTPoes is usually <224–255 cmH2O · s/min throughout the weaning trial [13]. In addition to possible variability in respiratory elastance and resistance measured during PAV+, respiratory muscular PTP as estimated by Carteaux’s method requires several assumptions that may limit its accuracy (e.g. a triangular muscular pressure waveform and a defined inspiratory time based on Paw, peak) [11]. Thus, the derived muscular PTP may not be equal to the PTPoes. The present study aimed to verify the applicability of Carteaux’s method with measured Pmus, oes, Pmus, oes, PEEPi, PTPoes, and PTPoes, PEEPi under different PAV gain settings.

Methods

From June 2014 to October 2014, all mechanically ventilated patients in our respiratory intensive care unit (10 beds) were screened daily for appropriateness for study inclusion. Patients had to be haemodynamically stable without inotropic agents and had to be ventilated with an inspiratory oxygen fraction <0.5 and PEEP ≤8 cmH2O. They also had to agree to oesophageal balloon placement. Exclusion criteria were pregnancy, acute coronary syndrome, aortic dissection as a cause of admission, and nasal or oropharyngeal lesions that prohibited oesophageal balloon placement. We used a single type of ventilator, the Puritan-Bennett 840 with PAV+ mode (Tyco International, Princeton, NJ, USA). The National Cheng Kung University Hospital Ethics Committee (A-BR-102-090) approved this study. The patient’s next of kin gave informed consent.

The oesophageal balloon was placed in the lower third of the oesophagus and inflated with 0.5–1 mL of air. Airflow was measured via a pneumotachograph (PN 155362, Hamilton Medical, Bonaduz, Switzerland), while the airway and oesophageal pressures were individually measured using two differential pressure transducers (P/N 113252, Model 1110A, Hans Rudolph, Shawnee, KS, USA). The flow sensor was placed between the endotracheal tube and ventilator Y-piece. Tidal volume was obtained by integration of the flow signal. All signals were sampled and digitalized at 100 Hz, and data were stored in a data-acquisition system (AcqKnowledgement, Biopac MP150, Goleta, CA, USA). All patients were assessed in a 30° supine position with endotracheal suction performed before measurement if clinically required.

For individual patients, seven PAV gain levels (percentage of assistance), namely PAV20 (20% gain), PAV30, PAV40, PAV50, PAV60, PAV70, and PAV80, were randomly applied for 15 min at each level unless the patients showed discomfort. Respiratory mechanics measured by the ventilator during PAV were recorded throughout the course. Passive respiratory mechanics were measured under constant flow at the end of this protocol by increasing the back-up mandatory ventilator rate until all the breathing efforts were suppressed [13, 14].

Physiological measurement

Validation of oesophageal pressure measurement

Appropriate oesophageal balloon placement was verified by the occlusion test [15]. The ratios of change in oesophageal pressure to the change in airway opening pressure (ΔPoes/ΔPaw) during three to five spontaneous respiratory efforts against a closed airway were determined to ensure oesophageal pressure measurement reliability.

Respiratory mechanics during PAV and passive mechanical ventilation

The respiratory mechanics (Epav and Rpav) during different PAV levels were recorded as a display on the ventilator screen. The last five Epav and five Rpav at each PAV level were used for comparison. The respiratory system mechanics under constant flow and volume-cycled passive mechanical ventilation were determined at the end of the protocol using constant flow and a rapid airway occlusion technique [16, 17].

Maximum inspiratory muscular pressure with Poes tracing (Pmus, oes) and inspiratory oesophageal pressure time product per breath (PTPoes, br)

Muscular pressure was calculated by taking into account dynamic Ecw, which was obtained as the passive volume-oesophageal pressure slope [13]. Pmus, oes was defined as the maximum difference between the passive and active Poes. The inspiratory PTPoes was calculated as the area between the Pcw and Poes tracing, starting from the onset of inspiratory effort to the end of inspiratory flow. Pcw was obtained by multiplying the tidal volume by dynamic Ecw. The onset of inspiratory effort was determined by the rapid descent point from Poes. We calculated PTPoes with and without consideration of the intrinsic PEEP (PEEPi) [13]. Because gastric pressure was not measured, exact amounts of dynamic hyperinflation and expiratory muscle activity were unknown. The PTPoes was thus presented in two forms, the upper bound PTPoes, which attributes the rapid descent of Poes before the onset of inspiratory flow solely to inspiratory muscle activity, and the lower bound PTPoes, which attributes the rapid descent of Poes solely to cessation of expiratory effort [13, 14]. PTPoes, PEEPi and PTPoes thus represent the upper and lower bounds of PTP, respectively (Fig. 1).

Fig. 1
figure1

Graphic illustration of flow, airway pressure (P aw ), and oesophageal pressure tracing (P oes ) during proportional assist ventilation. Chest wall recoil pressure (P cw ) was calculated from the product of tidal volume and dynamic chest wall elastance. Upper bound oesophageal pressure time product (PTP oes, PEEPi) was calculated as the integration of the difference between Pcw, PEEPi and Poes. Lower bound oesophageal pressure time product (PTP oes ) was calculated as the integration of the difference between Pcw and Poes. Pmus, oes and Pmus, oes, PEEPi represent the maximal difference between passive and active Poes

Maximum inspiratory pressure from ΔP and PAV gain (P mus, aw ) and inspiratory pressure time product from airway per breath (PTP aw, br )

Pmus, aw during PAV was obtained by using the formula adopted by Carteaux [11]:

$$ {\mathrm{P}}_{\mathrm{mus},\ \mathrm{aw}} = \left({\mathrm{P}}_{\mathrm{aw},\ \mathrm{peak}} - \mathrm{PEEP}\right) \times \left(100 - \mathrm{gain}\right)/\mathrm{gain}. $$

PTPaw, br was calculated under the assumption of a triangular inspiratory path with the end of inspiratory effort at Paw, peak.

Statistical analysis

The results are given as mean ± SD, unless otherwise specified. The Kruskal-Wallis test was used to compare means from different groups. Dunn’s multiple comparison test was performed over pairs of groups. Repeated measured analysis of variance (ANOVA) was used to compare the means of Epav and Rpav measured by the ventilator during various PAV gain levels. Correlatios between PTPoes, br and Pmus, oes, PTPoes, PEEPi, br and Pmus, oes, PEEPi, and PTPaw, br and Pmus, aw were analysed using the two-tailed Spearman correlation test. Linear regression between PTPoes, br and Pmus, oes, PTPoes, PEEP, br and Pmus, oes, PEEPi, and PTPaw, br and Pmus, aw was analysed with a forced regression line through the origin. Limits of agreement between Pmus, aw and Pmus, oes were examined using Bland-Altman analysis. All tests were two-sided, and a p value less than .05 was considered statistically significant. All analyses were performed using Prism version 5 (GraphPad Software, San Diego, CA, USA).

Results

The results of 18 consecutive patients who fulfilled the inclusion criteria were recorded. Two patients were excluded from further analysis because of a low ΔPoes/ΔPaw ratio. One patient was excluded because of a poor oesophageal pressure signal, and four patients were excluded because of an inadequate duration of Poes tracing secondary to the intolerance of the patients to low-gain PAV. Ultimately, 11 patients with an adequate duration of PAV recording at all stages of PAV support were analysed. The clinical demographics and respiratory mechanics of these patients are shown in Table 1. The tidal volume, Paw, peak, Epav, and Rpav under various PAV gain levels are shown in Fig. 2. Significantly higher tidal volumes were found with high PAV gains. As predicted, Ppeak increased with PAV gain. There were no significant changes in Rpav, but Epav was significantly higher with a high PAV gain (p < 0.0001).

Table 1 Patient demographics and respiratory mechanics
Fig. 2
figure2

Tidal volume, peak airway pressure (P aw, peak ) and respiratory mechanics during proportional assist ventilation (PAV) under different gains. PAV20 indicates a mean gain level of 20%. Significant differences in tidal volume were found between PAV60 vs. PAV20, PAV70 vs. PAV20, PAV70 vs. PAV30, and PAV70 vs. PAV40. Significant differences in Paw, peak were found among individual Paw, peak levels under different gains, except the Paw, peak of PAV20 vs. Paw, peak of PAV30 and Paw, peak of PAV70 vs. Paw, peak of PAV80. For PAV-based patient elastance (E pav ), significant differences were found between PAV20 vs. PAV50, PAV60, PAV70, and PAV80; PAV30 vs. PAV50, PAV60, PAV70, and PAV80; PAV40 vs. PAV50, PAV60, PAV70, and PAV80; PAV50 vs. PAV70 and PAV80; PAV60 vs. PAV80; and PAV70 vs. PAV80. No significant difference was found in PAV-based patient resistance (R pav ) among various gains. For the Epav and Rpav comparison, one patient was not included because of insufficient numbers of Epav and Rpav in PAV20 and PAV30

PTP oes , PTP oes, PEEPi , peak muscular pressure and duration of inspiration (Ti) with different PAV gains and their correlation analysis

PTPoes and PTPoes, PEEPi during various PAV gain factors are shown in Fig. 3. Progressive reductions in PTPoes and PTPoes, PEEPi were noted with increasing PAV gain levels. Significant differences were found among those with low-gain and high-gain PAV (p < 0.0001). However, no significant difference in PTPoes or PTPoes, PEEPi was found between PAV20 vs. PAV30, PAV30 vs. PAV40, PAV40 vs. PAV50, or PAV50 vs. PAV60. Pmus, aw tended to underestimate Pmus, oes or Pmus, oes, PEEPi with all levels of PAV gain except PAV20 (Fig. 4a). The minimal difference between Pmus, aw and Pmus, oes was at the level of PAV30 (Fig. 4a). The Ti, aw estimated from the onset of inspiratory effort to Paw, peak was not different from that estimated from flow tracing from PAV20 to PAV50. However, the Ti, aw was significantly shortened compared to the Ti estimated from flow tracing within PAV60 to PAV80 (data not shown, p < 0.0001). Spearman correlation analysis revealed significant correlation between Pmus, aw and PTPaw, br (r 2 = 0.9341), Pmus, oes and PTPoes, br(r 2 = 0.8751), and Pmus, oes, PEEPi and PTPoes, PEEPi, br (r 2 = 0.8862). Linear regression analysis disclosed the best-fit slope between PTPaw, br and Pmus, aw to be 0.56, between PTPoes, br and Pmus, oes to be 0.73, and between PTPoes, PEEPi, br and Pmus, oes, PEEPi to be 0.83.

Fig. 3
figure3

Inspiratory pressure time product (PTP) under different gain levels. PTP calculated from the difference between the oesophageal pressure and the relaxed chest wall elastance curve (PTP oes ) decreased progressively with increasing gain with or without intrinsic positive end-expiratory pressure (PEEPi). For PTPoes, a significant difference was found between proportional assist ventilation 20% gain (PAV20) vs. PAV40, PAV50, PAV60, PAV70, and PAV80; PAV30 vs. PAV50, PAV60, PAV70, and PAV80; PAV40 vs. PAV60, PAV70, and PAV80; PAV50 vs. PAV70 and PAV80; PAV60 vs. PAV80; and PAV70 vs. PAV80. Similar patterns were found with PTPoes, PEEPi. Values in parentheses are the number of breaths analysed in each gain level

Fig. 4
figure4

a Maximum muscular pressure (P mus ) determined using either oesophageal pressure tracing or airway pressure under different proportional assist ventilation (PAV) gains. Significant differences (p < 0.05) were observed for all gain levels. b Bland-Altman analysis plot showing bias and agreement between maximal muscular pressure calculated from ΔP and PAV gain (P mus, aw ) and maximal muscular pressure calculated from maximum difference between passive and active Poes without consideration of PEEPi (P mus, oes ). The middle dashed line is the mean difference (bias). The outer dashed line is the 95% confidence interval of the difference between Pmus, aw and Pmus, oes (±1.96 SD)

Bland-Altman analysis of Pmus between Pmus, aw and Pmus, oes and selection of optimal Pmus

There was limited agreement between Pmus, aw and Pmus, oes as determined by Bland-Altman analysis (Fig. 4b). The bias was -1.2 cmH2O. The 95% confidence interval between Pmus, aw and Pmus, oes was from -11.2 to 8.8 cmH2O. The maximal muscular pressures estimated from three different approaches under different PAV gain levels are shown in Table 2. PAV60 was associated with the highest probability (91%) of optimal Pmus according to Pmus, aw (5–10 cmH2O). However, the best PAV gain for optimal PAV assessed from Pmus, oes or Pmus, oes, PEEPi was quite diverse and was absent in two patients. The concordance rate for selection of optimal PAV gain was <50% between Pmus, aw and Pmus, oes and Pmus, aw and Pmus, oes, PEEPi.

Table 2 Maximal muscular pressures determined through airway or oesophageal pressure with and without PEEPi

Pmus,aw within 5–10 cmH2O was not present in PAV20 but was present in 11–82% of breaths in other PAV gains. Around 80% of breaths in PAV50 or PAV60 were associated with Pmus,aw within 5–10 cmH2O. PTPoes <224 cmH2O·s/min and PTPoes, PEEPi <255 cmH2O·s/min are considered admissible according to Jubran et al. [13]. Despite the limited predictability of Pmus, oes or Pmus, oes, PEEPi from Pmus, aw, patients with Pmus, aw between 5 and 10 cmH2O are had 93% probability of PTPoes <220 cmH2O·s/min and 88% probability of PTPoes, PEEPi <255 cmH2O·s/min, regardless of the PAV gain. Only two breaths were associated with PTPoes values <40 cmH2O·s/min. When Pmus,aw was achieved within 5–10 cmH2O, three PAV gain levels (PAV40, PAV50 and PAV60) were associated with >90% probability of admissible PTPoes and PTPoes, PEEPi.

Discussion

Our analyses revealed several interesting findings. First, PTPoes and PTPoes, PEEPi significantly decreased with increasing PAV gain in patients with PAV. Second, the prediction of Pmus, oes or Pmus, oes, PEEPi from airway pressure tracing had limited accuracy. Third, the deduction of PTPaw from ΔP may underestimate PTPoes or PTPoes, PEEPi. Fourth, an optimal Pmus, aw (5–10 cmH2O) could be achieved in 91% of patients with PAV60, and despite the lack of accuracy for predicting Pmus, oes or Pmus, oes, PEEPi from airway pressure tracing, maintaining Pmus, aw within 5–10 cmH2O was associated with PTPoes <224 cmH2O·s/min or PTPoes, PEEPi <255 cmH2O·s/min in approximately 90% of breaths.

The significant increase in Paw, peak but minimal difference in tidal volume with increasing gain level indicates substantial adaptation of muscular pressure during PAV [18]. The lower elastance during low assist could be explained by high respiratory drive (i.e. inspiratory muscle activity does not return to zero during the 300 ms occlusion time), which underestimates the elastic recoil pressure at end-inspiration. PEEPi is unlikely to be a cause because it did not increase with greater PAV assist in the current study [9].

The algorithm proposed by Carteaux et al. [11] is a simple bedside approach to estimate inspiratory muscular pressure (Pmus, aw) in mechanically ventilated patients under PAV. We found it to be of limited value in predicting Pmus, oes. Pmus, aw tends to overestimate Pmus, oes in PAV20 but more commonly underestimates Pmus, oes from PAV40 to PAV80. Therefore, the proportion of alleviation of respiratory muscle output was usually incompletely attained as the PAV gain intended it to be. Besides, the wide 95% confidence interval from the Bland-Altman analysis of Pmus, oes and Pmus, aw implicated that Pmus, oes could not be accurately predicted by Pmus, aw.

There are several possible explanations for these findings. First, for the unique condition where Pmus, oes is usually overestimated in PAV20, a reasonable cause could be the ventilator flow control algorithm. Because respiratory effort is maximal in PAV20, the proportional-integral-derivative algorithm of the flow control system is prone to an airway pressure overshoot by the end of inspiration, which is further exaggerated fourfold in PAV20 for the calculation of Pmus, aw [19, 20]. Second is a possible discrepancy between PAV+ and CMV measured respiratory mechanics [10]. Although the PAV+ mode was continuously updated, measured respiratory system resistance and elastance may be different from those obtained under CMV [10]. Moreover, the respiratory system resistance measured by PAV+ is not reliable in cases with severe expiratory flow limitations. Third is the presence of PEEPi. In a recently published PAV+ mode bench study [21], the assistance provided by PAV+ was approximately 25% lower than expected. PEEPi with the associated trigger delay was considered a major factor affecting PAV+ accuracy due to the lack of assist during the initial part of respiratory breath, ultimately resulting in global under-assistance.

PTPoes is a better surrogate of respiratory effort in ventilated patients. In this study, the analyses of correlation between Pmus, aw and PTPaw, Pmus, oes and PTPoes, Pmus, oes, PEEPi and PTPoes, PEEPi yielded highly significant results. However, predicting PTP from Pmus, aw and Pmus, oes differed in the best-fit slope value. The slope value was 0.56 when the linear regression was performed between Pmus, aw and PTPaw. The slope increased to 0.73 between PTPoes, br and Pmus, oes and to 0.83 between PTPoes, PEEPi, br and Pmus, oes, PEEPi. This implicates that the PTPaw should be corrected when projecting into PTPoes. We offer the following explanation for the discrepancy between PTPaw and PTPoes. First, the assumption of a triangular pressure-time product is flawed because respiratory muscle pressure generation is usually exponential [2224]. The integration area above an exponential decay curve is usually larger than the integration area above a triangular line. Second, the inspiratory time is significantly shortened in high-gain PAV. The shortened inspiratory time should result in a smaller PTPaw from the triangular algorithm. A third possible cause is the influence of PEEPi. The algorithm proposed by Cardeaux et al. is also flawed as it does not consider PEEPi. The inclusion of PEEPi led to increases in Pmus, oes, PEEPi and PTPoes, PEEPi.

The predefined range of respiratory effort by Carteaux and colleagues [11] needs critical appraisal. Target limits of Pmus, aw within 5–10 cmH2O or PTPaw between 50 and 150 cmH2O·s/min were derived mainly from a desirable inspiratory effort of PTPoes, PEEPi <125 cmH2O·s/min [14]. This recommended threshold is arbitrary, not supported by quantitative diaphragm electromyogram, and possibly well below the threshold of threatening diaphragm fatigue [14]. A wider range of PTPoes, PEEPi should be allowable with minimal risk of diaphragm fatigue [13, 25, 26]. As Pmus, aw frequently underestimates Pmus, oes in the usual levels of PAV, actual PTPoes, PEEPi values are usually higher than PTPaw. Interestingly, PTPoes, PEEPi measurements were usually <255 cmH2O·s/min when Pmus, aw were within 5–10 cmH2O. This implicates that the recommended grid table for PAV remains a helpful reference for selecting the PAV level, although the newly advocated threshold requires further study for verification.

There are several limitations to the current study. The first is the limited number of patients studied and the fact that all of the patients had started to have weaning trials as reflected by the oxygen fraction and external PEEP level. Thus, our results may not be applicable to acutely ill patients under mechanical ventilation. The second is the lack of gastric pressure measurement, which meant that we could not clarify the contribution of expiratory muscle activity during PAV. However, we did not notice evident abdominal muscle contraction during PAV except in one patient with high PEEPi. Thus, the measured Pmus, oes, PEEPi should represent the inspiratory muscle motor outputs for most of our patients.

Conclusions

In summary, our results demonstrate limited accuracy of estimating respiratory effort from airway pressure tracing during PAV. Although Pmus, oes decreases with increasing PAV gain, Pmus, oes could not be precisely predicted from ΔP under various gain factors. In addition, PTPaw also underestimated PTPoes and PTPoes, PEEPi. However, when the PAV gain was adjusted to a Pmus, aw of 5–10 cmH2O, there was approximately 90% probability of maintaining the patient within an acceptable PTP range.

Abbreviations

CMV:

continuous mandatory ventilation

Ecw :

passive chest wall elastance during CMV

Epav :

PAV-based patient elastance

Ers :

passive respiratory system elastance during CMV

PAV:

proportional assist ventilation

PAV20 to PAV80:

20 to 80% PAV gain

Paw, peak :

peak airway pressure during PAV

Pcw :

chest wall elastic pressure

PEEP:

positive end-expiratory pressure

PEEPi:

intrinsic PEEP

Pmus, aw :

maximal muscular pressure calculated from ΔP and PAV gain

Pmus, oes :

maximal muscular pressure calculated from maximum difference between passive and active Poes without consideration of PEEPi

Pmus, oes, PEEPi :

maximal muscular pressure calculated from maximum difference between passive and active Poes with consideration of PEEPi

Pmus :

respiratory muscular pressure

PTP:

inspiratory pressure time product

PTPaw, br :

inspiratory pressure time product calculated from ΔP and assuming a triangular inspiratory pressure time course per breath

PTPaw :

inspiratory pressure time product calculated from ΔP and assuming a triangular inspiratory pressure time course

PTPoes, br :

inspiratory pressure time product calculated from the difference between the oesophageal pressure and the relaxed chest wall elastance curve per breath

PTPoes :

inspiratory pressure time product calculated from the difference between the oesophageal pressure and the relaxed chest wall elastance curve

PTPoes, PEEPi, br :

inspiratory pressure time product calculated from the difference between the oesophageal pressure and the relaxed chest wall elastance curve per breath with consideration of PEEPi

PTPoes, PEEPi :

PTPoes with consideration of PEEPi

Rmax :

passive maximum inspiratory resistance during CMV

Rmin :

passive minimum (airway) inspiratory resistance during CMV

Rpav :

PAV-based patient resistance

Ti :

duration of the inspiratory time determined from flow tracing during various PAV gains without consideration of PEEPi

Ti, aw :

duration of the inspiratory time determined from the peak airway pressure during various PAV gains

VIDD:

ventilator-induced diaphragmatic dysfunction

ΔP:

peak airway pressure and PEEP difference

References

  1. 1.

    Levine S, Nguyen T, Taylor N, Friscia ME, Budak MT, Rothenberg P, Zhu J, Sachdeva R, Sonnad S, Kaiser LR, et al. Rapid disuse atrophy of diaphragm fibers in mechanically ventilated humans. N Engl J Med. 2008;358(13):1327–35.

    CAS  Article  PubMed  Google Scholar 

  2. 2.

    Vassilakopoulos T, Petrof BJ. Ventilator-induced diaphragmatic dysfunction. Am J Respir Crit Care Med. 2004;169(3):336–41.

    Article  PubMed  Google Scholar 

  3. 3.

    Sassoon CS, Zhu E, Caiozzo VJ. Assist-control mechanical ventilation attenuates ventilator-induced diaphragmatic dysfunction. Am J Respir Crit Care Med. 2004;170(6):626–32.

    Article  PubMed  Google Scholar 

  4. 4.

    Jaber S, Petrof BJ, Jung B, Chanques G, Berthet JP, Rabuel C, Bouyabrine H, Courouble P, Koechlin-Ramonatxo C, Sebbane M, et al. Rapidly progressive diaphragmatic weakness and injury during mechanical ventilation in humans. Am J Respir Crit Care Med. 2011;183(3):364–71.

    CAS  Article  PubMed  Google Scholar 

  5. 5.

    Tobin MJ, Laghi F, Jubran A. Narrative review: ventilator-induced respiratory muscle weakness. Ann Intern Med. 2010;153(4):240–5.

    Article  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Chatburn RL. Classification of ventilator modes: update and proposal for implementation. Respir Care. 2007;52(3):301–23.

    PubMed  Google Scholar 

  7. 7.

    Younes M. Proportional assist ventilation, a new approach to ventilatory support. Theory. Am Rev Respir Dis. 1992;145(1):114–20.

    CAS  Article  PubMed  Google Scholar 

  8. 8.

    Younes M, Puddy A, Roberts D, Light RB, Quesada A, Taylor K, Oppenheimer L, Cramp H. Proportional assist ventilation. Results of an initial clinical trial. Am Rev Respir Dis. 1992;145(1):121–9.

    CAS  Article  PubMed  Google Scholar 

  9. 9.

    Younes M, Webster K, Kun J, Roberts D, Masiowski B. A method for measuring passive elastance during proportional assist ventilation. Am J Respir Crit Care Med. 2001;164(1):50–60.

    CAS  Article  PubMed  Google Scholar 

  10. 10.

    Kondili E, Prinianakis G, Alexopoulou C, Vakouti E, Klimathianaki M, Georgopoulos D. Respiratory load compensation during mechanical ventilation–proportional assist ventilation with load-adjustable gain factors versus pressure support. Intensive Care Med. 2006;32(5):692–9.

    Article  PubMed  Google Scholar 

  11. 11.

    Carteaux G, Mancebo J, Mercat A, Dellamonica J, Richard JC, Aguirre-Bermeo H, Kouatchet A, Beduneau G, Thille AW, Brochard L. Bedside adjustment of proportional assist ventilation to target a predefined range of respiratory effort. Crit Care Med. 2013;41(9):2125–32.

    Article  PubMed  Google Scholar 

  12. 12.

    Manley C, Garpestad E, Hill NS. A new purpose for proportional assist ventilation? Crit Care Med. 2013;41(9):2230–1.

    Article  PubMed  Google Scholar 

  13. 13.

    Jubran A, Tobin MJ. Pathophysiologic basis of acute respiratory distress in patients who fail a trial of weaning from mechanical ventilation. Am J Respir Crit Care Med. 1997;155(3):906–15.

    CAS  Article  PubMed  Google Scholar 

  14. 14.

    Jubran A, Van de Graaff WB, Tobin MJ. Variability of patient-ventilator interaction with pressure support ventilation in patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 1995;152(1):129–36.

    CAS  Article  PubMed  Google Scholar 

  15. 15.

    Akoumianaki E, Maggiore SM, Valenza F, Bellani G, Jubran A, Loring SH, Pelosi P, Talmor D, Grasso S, Chiumello D, et al. The application of esophageal pressure measurement in patients with respiratory failure. Am J Respir Crit Care Med. 2014;189(5):520–31.

    Article  PubMed  Google Scholar 

  16. 16.

    Guttmann J, Eberhard L, Fabry B, Bertschmann W, Wolff G. Continuous calculation of intratracheal pressure in tracheally intubated patients. Anesthesiology. 1993;79(3):503–13.

    CAS  Article  PubMed  Google Scholar 

  17. 17.

    Rossi A, Gottfried SB, Higgs BD, Zocchi L, Grassino A, Milic-Emili J. Respiratory mechanics in mechanically ventilated patients with respiratory failure. J Appl Physiol. 1985;58(6):1849–58.

    CAS  PubMed  Google Scholar 

  18. 18.

    Navalesi P, Hernandez P, Wongsa A, Laporta D, Goldberg P, Gottfried SB. Proportional assist ventilation in acute respiratory failure: effects on breathing pattern and inspiratory effort. Am J Respir Crit Care Med. 1996;154(5):1330–8.

    CAS  Article  PubMed  Google Scholar 

  19. 19.

    Younes M. Why does airway pressure rise sometimes near the end of inflation during pressure support? Intensive Care Med. 2008;34(1):1–3.

    Article  PubMed  Google Scholar 

  20. 20.

    Yu CH, Su PL, Lin WC, Lin SH, Chen CW. Simulation of late inspiratory rise in airway pressure during pressure support ventilation. Respir Care. 2015;60(2):201–9.

    Article  PubMed  Google Scholar 

  21. 21.

    Beloncle F, Akoumianaki E, Rittayamai N, Lyazidi A, Brochard L. Accuracy of delivered airway pressure and work of breathing estimation during proportional assist ventilation: a bench study. Ann Intensive Care. 2016;6(1):30.

    Article  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Younes M, Riddle W. A model for the relation between respiratory neural and mechanical outputs. I. Theory. J Appl Physiol. 1981;51(4):963–78.

    CAS  PubMed  Google Scholar 

  23. 23.

    Riddle W, Younes M. A model for the relation between respiratory neural and mechanical outputs. II. Methods. J Appl Physiol. 1981;51(4):979–89.

    CAS  PubMed  Google Scholar 

  24. 24.

    Younes M, Riddle W, Polacheck J. A model for the relation between respiratory neural and mechanical outputs. III. Validation. J Appl Physiol. 1981;51(4):990–1001.

    CAS  PubMed  Google Scholar 

  25. 25.

    Jaber S, Fodil R, Carlucci A, Boussarsar M, Pigeot J, Lemaire F, Harf A, Lofaso F, Isabey D, Brochard L. Noninvasive ventilation with helium-oxygen in acute exacerbations of chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2000;161(4 Pt 1):1191–200.

    CAS  Article  PubMed  Google Scholar 

  26. 26.

    Brochard L, Harf A, Lorino H, Lemaire F. Inspiratory pressure support prevents diaphragmatic fatigue during weaning from mechanical ventilation. Am Rev Respir Dis. 1989;139(2):513–21.

    CAS  Article  PubMed  Google Scholar 

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Acknowledgements

The authors appreciate graph-plotting assistance from Lan-I-Wen.

Funding

This study was sponsored by a grant from NCKUH-10303008.

Availability of data and materials

Not applicable.

Authors’ contributions

PLS participated in the study design, collected and analysed data, and drafted the revised manuscript. PSK participated in the study, analysed data, and participated in draft revision. WCL participated in the study design and help revise the manuscript. PFS carried out statistical analysis and participated in the revised manuscript. CWC conceived of the study, participated in its design and coordination, and was involved in producing the final manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent to publication

Written informed consent was obtained from the patients/families for publication of their individual details and accompanying measurements in this manuscript. The consent forms are held by the authors and are available for review by the Editor-in-Chief.

Ethical approval and consent to participate

This study was approved by The National Cheng Kung University Hospital Ethics Committee (A-BR-102-090). Consent to participate was obtained from the patients/families.

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Correspondence to Chang-Wen Chen.

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Su, P., Kao, P., Lin, W. et al. Limited predictability of maximal muscular pressure using the difference between peak airway pressure and positive end-expiratory pressure during proportional assist ventilation (PAV). Crit Care 20, 382 (2016). https://doi.org/10.1186/s13054-016-1554-4

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Keywords

  • Pressure time product
  • Proportional assist ventilation
  • Airway pressure