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Integration of inspiratory and expiratory intraabdominal pressure: a novel concept looking at mean intraabdominal pressure
Annals of Intensive Care volume 2, Article number: S18 (2012)
Abstract
Background
The intraabdominal pressure (IAP) is an important clinical parameter that can significantly change during respiration. Currently, IAP is recorded at endexpiration (IAP_{ee}), while continuous IAP changes during respiration (ΔIAP) are ignored. Herein, a novel concept of considering continuous IAP changes during respiration is presented.
Methods
Based on the geometric mean of the IAP waveform (MIAP), a mathematical model was developed for calculating respiratoryintegrated MIAP (i.e. \mathsf{\text{MIA}}{\mathsf{\text{P}}}_{\mathsf{\text{ri}}}=\mathsf{\text{IA}}{\mathsf{\text{P}}}_{\mathsf{\text{ee}}}+i\cdot \mathrm{\Delta}\mathsf{\text{IAP}}), where 'i' is the decimal fraction of the inspiratory time, and where ΔIAP can be calculated as the difference between the IAP at endinspiration (IAP_{ei}) minus IAP_{ee}. The effect of various parameters on IAP_{ee} and MIAP_{ri} was evaluated with a mathematical model and validated afterwards in six mechanically ventilated patients. The MIAP of the patients was also calculated using a CiMON monitor (Pulsion Medical Systems, Munich, Germany). Several other parameters were recorded and used for comparison.
Results
The human study confirmed the mathematical modelling, showing that MIAP_{ri} correlates well with MIAP (R^{2} = 0.99); MIAP_{ri} was significantly higher than IAP_{ee} under all conditions that were used to examine the effects of changes in IAP_{ee}, the inspiratory/expiratory (I:E) ratio, and ΔIAP (P < 0.001). Univariate Pearson regression analysis showed significant correlations between MIAP_{ri} and IAP_{ei} (R = 0.99), IAP_{ee} (R = 0.99), and ΔIAP (R = 0.78) (P < 0.001); multivariate regression analysis confirmed that IAP_{ee} (mainly affected by the level of positive endexpiratory pressure, PEEP), ΔIAP, and the I:E ratio are independent variables (P < 0.001) determining MIAP. According to the results of a regression analysis, MIAP can also be calculated as
Conclusions
We believe that the novel concept of MIAP is a better representation of IAP (especially in mechanically ventilated patients) because MIAP takes into account the IAP changes during respiration. The MIAP can be estimated by the MIAP_{ri} equation. Since MIAP_{ri} is almost always greater than the classic IAP, this may have implications on endorgan function during intraabdominal hypertension. Further clinical studies are necessary to evaluate the physiological effects of MIAP.
Introduction
The intraabdominal pressure (IAP) is an important clinical parameter with major prognostic impact [1, 2]. An unrecognised pathological increase in IAP eventually leads to intraabdominal hypertension (IAH) and abdominal compartment syndrome (ACS) [3, 4], which result in significant morbidity and mortality [5]. Thus, recognition and reliable measurement of IAP are the first important steps for prevention and management of IAH and ACS in critically ill patients [6].
Assuming no respiratory movement, the IAP would be relatively constant and primarily determined by body posture and anthropomorphy (e.g. body mass index) [3, 7]. The IAP may be affected by conditions influencing intraabdominal volume and abdominal compliance (C _{ab}) [3, 8, 9]. Further, the complex interaction between intraabdominal volume and C _{ab} during respiration (Figure 1) may significantly [10] and frequently (12 to 40 changes per minute) change the IAP (Figure 2), with more intense effects during positivepressure mechanical ventilation or the presence of positive endexpiratory pressure (PEEP) [10–12].
According to the current consensus definitions of the World Society of the Abdominal Compartment Syndrome (WSACS), the IAP should be measured at endexpiration (IAP_{ee}) [13], referred to as the 'classic IAP' throughout the text. However, the IAP_{ee} is only a single component of an everchanging trend and thus does not incorporate a considerable portion of this IAP trend (Figure 2). The objectives of this study were to develop and validate a novel IAP measurement concept to consider IAP changes during respiration and to identify independent variables influencing IAP within this novel concept.
Methods
Part A: mathematical model
A set of numerous IAP values occurs for a patient during a single respiratory cycle. The central tendency of a set of values can be calculated by the mathematical function of the 'mean'. In determining the mean IAP, the arithmetic mean for IAP_{ee} and the endinspiratory IAP (IAP_{ei}) was described previously [14], calculated by dividing the sum of the values by the number of values. However, employing the arithmetic mean for the IAP waveform is mathematically incorrect. Instead, the mean of a waveform can be calculated by the 'geometric mean' function. The geometric mean is calculated by dividing the area under the waveform in a definite interval (i.e. the definite integral of the waveform) by the value of the definite interval [15]. Therefore, the mean IAP (MIAP) for a sample IAP waveform between the times (T _{0}) and (T) in Figure 2 can be calculated as follows:
where 'MIAP_{ri}' is the respiratoryintegrated MIAP, 'T−T _{0}' is the time interval for a full respiratory cycle, and 'IAP (t) dt' is the IAP at each time point (t). The result would be a timeweighted mean for the IAP waveform. This is closely analogous with the critically important cardiovascular concept of mean arterial blood pressure [16–18], which is the geometric mean of the arterial blood pressure waveform [19, 20]. Equation 1 may be simplified as follows (see the addendum)[21]:
where 'i' is the decimal fraction of the inspiratory time in a respiratory cycle and can be calculated from the inspiratory/expiratory (I:E) ratio (i = I /(I + E); 0 <i < 1) and ΔIAP = IAP_{ei} − IAP_{ee}. Since IAP_{ee}, i, and ΔIAP can be assumed to be independent, a computerised iteration can be used for a set of values for each parameter to determine their effect on MIAP_{ri} and to compare the MIAP_{ri} with the classic IAP.
The effects of IAP_{ee} on MIAP_{ri} and the classic IAP were examined through a gradual increase of IAP_{ee} from 12 to 25 mmHg, with steps of 1 mmHg (Figure 3). For each IAP_{ee}, a range of possible MIAP_{ri} values was calculated according to Equation 2 with an I:E ratio of 4:1 and an ΔIAP of 8.16 mmHg for the maximum MIAP_{ri}, and an I:E ratio of 1:4 and an ΔIAP of 1 mmHg for the minimum MIAP_{ri}. Because previous studies have shown a correlation between ΔIAP and IAP_{ee}, the ΔIAP was increased 10% for each 1 mmHg increase in the IAP_{ee}.
The effects of the I:E ratio on MIAP_{ri} and the classic IAP were examined by a gradual increase in the I:E ratio from 1:4 to 4:1 with steps of 0.5 (Figure 4). The amount of IAP_{ee} was held constant (19 mmHg). For each I:E ratio, a range of possible MIAP_{ri} values was calculated with an ΔIAP of 7 mmHg for the maximum MIAP_{ri} and an ΔIAP of 2 mmHg for the minimum MIAP_{ri}.
The effects of ΔIAP on MIAP_{ri} and the classic IAP were examined by a gradual increase in ΔIAP from 1 to 5 mmHg, with steps of 0.5 mmHg (Figure 5). The amount of IAP_{ee} was held constant (19 mmHg). For each ΔIAP, a range of possible MIAP_{ri} values was calculated with an I:E ratio of 4:1 for the maximum MIAP_{ri} and an I:E ratio of 1:4 for the minimum MIAP_{ri}.
Each of the abovementioned data sets was assumed to be a unique case, and the values shown in Figures 3,4,5 should not be considered as a trend in changes that can be obtained in a single patient.
Part B: human pilot study
In six ICU patients that were mechanically ventilated with Evita XL ventilators (Draeger, Lubeck, Germany), the mean IAP was automatically calculated as the geometrical mean (MIAP) via a balloontipped nasogastric tube connected to a CiMON monitor (Pulsion Medical Systems, Munich, Germany). The MIAP_{ri} was also calculated according to Equation 2. Data were collected on respiratory settings, plateau and mean alveolar pressures (P _{plat}, P _{mean}), PEEP, and dynamic compliance (calculated as the tidal volume (TV) divided by (P _{plat}  PEEP)). The C _{ab} was calculated as TV divided by ΔIAP. The thoracoabdominal index of transmission (TAI) was calculated as ΔP _{alv} (= P _{plat} − PEEP) divided by ΔIAP, in which P _{alv} is the alveolar pressure.
The effects of IAP_{ee} on MIAP_{ri} were examined by a gradual increase in PEEP from 0 to 15 cmH_{2}O, with steps of 5 cmH_{2}O during a bestPEEP manoeuvre (20 measurements at each PEEP level in five patients, resulting in 80 measurements). The effects of ΔIAP on MIAP_{ri} were examined by a gradual increase in TV from 250 to 1,000 ml, with steps of 250 ml during a lowflow pressurevolume loop (20 measurements at each TV level in five patients, resulting in 80 measurements). The effects of I:E ratio on MIAP_{ri} were examined by a gradual increase in the I:E ratio from 1:2 to 2:1, with steps of 0.5 during a recruitment manoeuvre (9 measurements at each I:E ratio in one patient, resulting in 45 measurements).
Statistical analysis was performed using SPSS software. Pearson correlation analysis and Bland and Altman analysis were performed. For comparisons between MIAP_{ri} and IAP_{ee} at different levels of IAP_{ee} (PEEP), TV, and I:E ratio, a twotailed paired Student's ttest was performed. Data are expressed as the mean with the standard deviation (SD), unless specified otherwise. A P value below 0.05 was considered statistically significant. The local EC and IRB approved the study, and informed consent was obtained from next of kin.
Results
Part A: mathematical modelling
According to Equation 2, three major independent parameters determine the MIAP_{ri}: IAP_{ee}, I:E ratio, and ΔIAP. Therefore, for each IAP_{ee}, the MIAP_{ri} depends on two other factors (Figure 3). For IAP_{ee} values between 16 and 20 mmHg, the classic IAP remained below the ACS threshold (dashed line in Figure 3); however, the MIAP_{ri} was able to exceed the ACS threshold. Furthermore, as seen in Figures 4 and 5, the classic IAP was continuously below the ACS threshold, but different ranges of probable MIAP_{ri} values were above the ACS threshold. By changing the I:E ratio, the MIAP_{ri} values changed with dissimilar intensities (e.g. when the I:E ratio decreased from 4:1 to 3.5:1, the intensity of changes in the MIAP_{ri} values was less than that when the I:E ratio decreased from 1.5:1 to 1:1; Figure 4). Furthermore, for a constant IAP_{ee}, higher values for either the I:E ratio or ΔIAP were found to be capable of causing a wider range of possible MIAP_{ri} values (Figures 4 and 5). Mathematically, for all instances in which the ΔIAP was greater than 0 mmHg, the MIAP_{ri} was larger than the classic IAP (see the addendum) [21].
Part B: human pilot study
Six mechanically ventilated patients (three severely burned patients and three surgical ICU patients) were studied. The maletofemale ratio was 2:1. Table 1 summarises the baseline patient demographics.
Regression analysis and Bland and Altman analysis
In total, 205 paired MIAP and MIAP_{ri} measurements were performed with an identical statistical mean of 12.2 ± 3.8 mmHg. Figure 6A shows an excellent correlation between the MIAP and MIAP_{ri} (R^{2} = 0.99, P < 0.001). Analysis according to Bland and Altman showed a bias and precision of 0 and 0.2 mmHg, respectively, with small limits of agreement ranging from −0.4 to 0.5 mmHg (Figure 6B). The percentage error was 3.5%.
Effect of IAP_{ee}, I:E ratio, and ΔIAP on MIAP_{ri}
Gradually increasing PEEP from 0 to 15 cmH_{2}O resulted in an increase in MIAP_{ri} from 11.7 ± 4.1 to 13.1 ± 4.2 mmHg (P < 0.001). Meanwhile, IAP_{ee} increased from 9.9 ± 3.4 to 11.9 ± 3.7 mmHg (P < 0.001). Moreover, a gradual increase in the I:E ratio from 0.5 (1:2) to 2 (2:1) caused an increase in MIAP_{ri} from 10.8 ± 2.6 to 12.9 ± 2.9 mmHg (P < 0.001), while IAP_{ee} increased from 9.7 ± 2.3 to 10.4 ± 2.5 mmHg (P < 0.001). In addition, gradually increasing TV from 250 to 1,000 ml led to an increase in ΔIAP from 2.1 ± 1.1 to 5.7 ± 2.3 (P < 0.001). This increase in ΔIAP resulted in an increase in MIAP_{ri} from 11.6 ± 4 to 13.1 ± 4.3 mmHg (P < 0.001), while IAP_{ee} increased from 10.7 ± 3.6 to 10.9 ± 3.5 mmHg (P = NS). The MIAP_{ri} was significantly higher than IAP_{ee} at each PEEP level, I:E ratio, and TV (Figure 7A,B,C; P < 0.001).
The classic IAP of patients was below the IAH grade I threshold; however, the MIAP_{ri} significantly exceeded the threshold in several instances (P < 0.001; Figure 7).
Univariate analysis
Univariate Pearson regression analysis showed significant correlations between MIAP_{ri} and IAP_{ei} (R = 0.99), IAP_{ee} (R = 0.99), ΔIAP (R = 0.78), and C _{ab} (R = −0.74); between IAP_{ei} and IAP_{ee} (R = 0.96), ΔIAP (R = 0.86), and C _{ab} (R = −0.73); between IAP_{ee} and ΔIAP (R = 0.7) and C _{ab} (R = −0.73); between ΔIAP and ΔP _{alv} (R = 0.79) and C _{ab} (R = −0.58); and finally between TAI and C _{ab} (R = −0.8) (P < 0.001). Figure 8A,B,C shows some regression plots.
Multivariate regression analysis
Analyses showed that the IAP_{ee} (mainly affected by PEEP), ΔIAP, and I:E ratio were independent variables defining the MIAP (Table 2). According to the regression analysis in our sample population, the MIAP can also be calculated from the following simplified formula (P < 0.001), in which 'I' and 'E' are elements of the I:E ratio:
Discussion
A novel concept of IAP measurement based on the geometric mean of the IAP waveform was presented. The independent parameters determining the IAP in this concept were defined. The human pilot study validated the mathematical modelling with an excellent correlation. A significant difference was observed between the classic IAP and the MIAP_{ri} in our clinical study.
The human study confirmed that MIAP_{ri} is as accurate as an automated geometric MIAP calculation by a CiMON monitor. More importantly, the higher the MIAP or IAP_{ee}, the higher the ΔIAP since ΔIAP acts as an indirect marker of C _{ab}. The ΔIAP is correlated with ΔP _{alv} or is thus inversely correlated with dynamic compliance. As well, the higher the C _{ab}, the lower the TAI. The human study confirmed the predictions of the mathematical modelling in which IAP_{ee} (affected by different PEEP settings), ΔIAP, and I:E ratio were recognised as the major independent determinants of MIAP_{ri}. We also showed that in patients with IAH and under mechanical ventilation, the IAP may be influenced by ventilator settings.
The critical difference between the MIAP_{ri} and the classic IAP near the ACS threshold in our mathematical modelling, as well as the significantly higher MIAP_{ri} than the IAP_{ee} around the IAH threshold in our human study, calls for future studies. The dissimilar intensity in MIAP_{ri} changes under changes in the I:E ratio in Figure 4 may implicate the existence of critical points in the I:E ratio, wherein changing this ratio may cause a more intense change in the MIAP_{ri}. Furthermore, since MIAP_{ri} seems to be almost always larger than the classic IAP, relying only on the classic IAP may place some patients at risk of silent IAH or ACS. Although the aim of the current study was not to address these implications clinically, these findings indicate that further investigations should be performed on respiratory manoeuvres to manage IAH in mechanically ventilated patients (e.g. decreasing the I:E ratio and/or the ΔIAP, or maintaining the I:E ratio in a predefined range).
A limitation of our study was the lack of data to evaluate the physiological difference between the MIAP_{ri} and the classic IAP. However, this study only aimed to prove the concept and to set the stage for further studies. Therefore, we believe that the lack of physiological data does not limit our findings. Nonetheless, further studies on the clinical effects of this concept are necessary before it can be introduced in clinical practice.
Conclusions
A novel concept MIAP_{ri} was presented to consider the IAP changes during respiration and was based on the geometric mean (MIAP) of the IAP waveform. An excellent correlation was observed between the results of the mathematical modelling and those obtained in real patients. Substantial differences were observed between the two IAP methods (the classic IAP measured at end expiration and the novel MIAP). Based on our findings, we believe that the novel concept of MIAP_{ri} may be a better representation for the pressure concealed within the abdominal cavity. Further clinical studies are necessary to reveal the physiological effects of this novel concept.
Authors' information
SA is aveterinary surgeon (DVM, DVSc) and a medical research consultant in laboratory animal researches in the field of trauma, haemorrhage, critical care, and anaesthesia. MLNGM is a former president and treasurer of the World Society of the Abdominal Compartment Syndrome and is the ICU and High Care Burn Unit Director of the Department of Intensive Care in Ziekenhuis Netwerk Antwerpen Stuivenberg.
Addendum
See additional file 1.
Abbreviations
 ACS:

abdominal compartment syndrome
 C _{ab} :

abdominal compliance
 IAH:

intraabdominal hypertension
 IAP:

intraabdominal pressure
 IAP_{ee} :

endexpiratory IAP
 IAP_{ei} :

endinspiratory IAP
 MIAP:

mean intraabdominal pressure (geometrical mean)
 MIAP_{ri} :

respiratoryintegrated mean intraabdominal pressure
 P _{alv} :

alveolar pressure
 P _{mean} :

mean airway pressure
 P _{plat} :

plateau airway pressure
 PEEP:

positive endexpiratory pressure
 TAI:

thoracoabdominal index of transmission
 TV:

tidal volume
 WSACS:

World Society of the Abdominal Compartment Syndrome.
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Acknowledgements
This article has been published as part of Annals of Intensive Care Volume 2 Supplement 1, 2012: Diagnosis and management of intraabdominal hypertension and abdominal compartment syndrome. The full contents of the supplement are available online at http://www.annalsofintensivecare.com/supplements/2/S1.
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MLNGM is a member of the medical advisory board of Pulsion Medical Systems, Munich, Germany.
Authors' contributions
SA and MLNGM planned the study and were responsible for the design, coordination, and drafting the manuscript. SA developed the mathematical model for MIAP calculation and performed the theoretical analyses. MLNGM performed the data collection and statistical analysis for the human pilot study. Both authors read and approved the final manuscript.
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AhmadiNoorbakhsh, S., Malbrain, M.L. Integration of inspiratory and expiratory intraabdominal pressure: a novel concept looking at mean intraabdominal pressure. Ann. Intensive Care 2, S18 (2012). https://doi.org/10.1186/211058202S1S18
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DOI: https://doi.org/10.1186/211058202S1S18
Keywords
 Tidal Volume
 Abdominal Compartment Syndrome
 Peep Level
 Dynamic Compliance
 Pulsion Medical System