Intra-cycle power: is the flow profile a neglected component of lung protection?

How to minimize mechanical power during controlled mechanical ventilation

High intrapulmonary pressures, large tidal volumes, and elevated respiratory rates during controlled mechanical ventilation can lead to barotrauma, volutrauma, and atelectrauma. Mechanical power-defined as the product of the pressure-volume integral and respiratory rate-consolidates these three risk factors into a single, intuitive parameter. Several studies have demonstrated that higher mechanical power correlates with an increased risk of lung injury and mortality, prompting the suggestion that mechanical power should be minimized. However, under the constraint of maintaining a fixed alveolar minute ventilation and positive end-expiratory pressure (PEEP), it remains unclear how to adjust respiratory rate and tidal volume to minimize mechanical power. This study provides an analytical solution to this optimization problem. Accordingly, only the elastic component of mechanical power should be targeted for minimization. Regardless of lung elastance or resistance, or the mode and settings of the ventilator, the elastic power is minimized at a tidal volume equal to twice the anatomic dead space, or approximately 4.4 ml/kg of body weight.

How to Prevent Ventilator-Induced Lung Injury in Intraoperative Mechanical Ventilation? A Randomized Prospective Study

Objective

Intraoperative mechanical ventilation practices can lead to ventilator-induced lung injury (VILI) and postoperative pulmonary complications in healthy lungs. Mechanical power (MP) has been developed as a new concept in reducing the risk of postoperative pulmonary complications as it considers all respiratory mechanics that cause VILI. The most commonly used intraoperative modes are volume control ventilation (VCV) and pressure control ventilation (PCV). In this study, VCV and PCV modes were compared in terms of respiratory mechanics in patients operated in the supine and prone positions.

Methods

The patients were divided into 4 groups (80 patients), volume control supine and prone, pressure control supine and prone with 20 patients each. MP, respiratory rate, positive end-expiratory pressure, tidal volume, peak pressure, plato pressure, driving pressure, inspiratory time, height, age, gender, body mass index, and predictive body weight data of the patients included in the groups have been obtained from "electronic data pool" with Structured Query Language queries.

Results

The supine and prone MP values of the VCV group were statistically significantly lower than the PCV group (P values were 0.010 and 0.001, respectively).

Conclusion

Supine and prone MP values of the VCV group were calculated significantly lower than the PCV group. Intraoperative PCV may be considered disadvantageous regarding the risk of VILI in the supine and prone positions.

Stress & strain in mechanically nonuniform alveoli using clinical input variables: a simple conceptual model

Clinicians currently monitor pressure and volume at the airway opening, assuming that these observations relate closely to stresses and strains at the micro level. Indeed, this assumption forms the basis of current approaches to lung protective ventilation. Nonetheless, although the airway pressure applied under static conditions may be the same everywhere in healthy lungs, the stresses within a mechanically non-uniform ARDS lung are not. Estimating actual tissue stresses and strains that occur in a mechanically non-uniform environment must account for factors beyond the measurements from the ventilator circuit of airway pressures, tidal volume, and total mechanical power. A first conceptual step for the clinician to better define the VILI hazard requires consideration of lung unit tension, stress focusing, and intracycle power concentration. With reasonable approximations, better understanding of the value and limitations of presently used general guidelines for lung protection may eventually be developed from clinical inputs measured by the caregiver. The primary purpose of the present thought exercise is to extend our published model of a uniform, spherical lung unit to characterize the amplifications of stress (tension) and strain (area change) that occur under static conditions at interface boundaries between a sphere's surface segments having differing compliances. Together with measurable ventilating power, these are incorporated into our perspective of VILI risk. This conceptual exercise brings to light how variables that are seldom considered by the clinician but are both recognizable and measurable might help gauge the hazard for VILI of applied pressure and power.

Effect of Ventilator Settings on Mechanical Power During Simulated Mechanical Ventilation of Patients With ARDS

BACKGROUND

In recent years, mechanical power (MP) has emerged as an important concept that can significantly impact outcomes from mechanical ventilation. Several individual components of ventilatory support such as tidal volume (VT), breathing frequency, and PEEP have been shown to contribute to the extent of MP delivered from a mechanical ventilator to patients in respiratory distress/failure. The aim of this study was to identify which common individual setting of mechanical ventilation is more efficient in maintaining safe and protective levels of MP using different modes of ventilation in simulated subjects with ARDS.

METHODS

We used an interactive mathematical model of ventilator output during volume control ventilation (VCV) with either constant inspiratory flow (VCV-CF) or descending ramp inspiratory flow, as well as pressure control ventilation (PCV). MP values were determined for simulated subjects with mild, moderate, and severe ARDS; and whenever MP > 17 J/min, VT, breathing frequency, or PEEP was manipulated independently to bring back MP to ≤ 17 J/min. Finally, the optimum VT-breathing frequency combinations for MP = 17 J/min were determined with all 3 modes of ventilation.

RESULTS

VCV-CF always resulted in the lowest MPs while PCV resulted in highest MPs. Reductions in VT were the most efficient for maintaining safer and protective MP. At targeted MPs of 17 J/min and maximized minute ventilation, the optimum VT-breathing frequency combinations were 250-350 mL for VT and 32-35 breaths/min for breathing frequency in mild ARDS, 200-350 mL for VT and 34-40 breaths/min for breathing frequency in moderate ARDS, and 200-300 mL for VT and 37-45 breaths/min for breathing frequency for severe ARDS.

CONCLUSIONS

VCV-CF resulted in the lowest MP. VT was the most efficient for maintaining safe and protective MP in a mathematical simulation of subjects with ARDS. In the context of maintaining low and safe MPs, ventilatory strategies with lower-than-normal VT and higher-than-normal breathing frequency will need to be implemented in patients with ARDS.

The effect of inspiratory rise time on mechanical power calculations in pressure control ventilation: dynamic approach

BACKGROUND

Mechanical power may serve as a valuable parameter for predicting ventilation-induced injury in mechanically ventilated patients. Over time, several equations have been developed to calculate power in both volume control ventilation (VCV) and pressure control ventilation (PCV). Among these equations, the linear model mechanical power equation (MPLM) closely approximates the reference method when applied in PCV. The dynamic mechanical power equation (MPdyn) computes power by utilizing the ventilatory work of breathing parameter (WOBv), which is automatically measured by the mechanical ventilator. In our study, conducted in patients with Covid-19 Acute Respiratory Distress Syndrome (C-ARDS), we calculated mechanical power using both the MPLM and MPdyn equations, employing different inspiratory rise times (Tslope) at intervals of 5%, ranging from 5 to 20% and compared the obtained results.

RESULTS

In our analysis, we used univariate linear regression at both I:E ratios of 1:2 and 1:1, considering all Tslope values. These analyses revealed that the MPdyn and MPLM equations exhibited strong correlations, with R2 values exceeding 0.96. Furthermore, our Bland-Altman analysis, which compared the power values derived from the MPdyn and MPLM equations for patient averages and all measurements, revealed a mean difference of -0.42 ± 0.41 J/min (equivalent to 2.6% ± 2.3%, p < 0.0001) and -0.39 ± 0.57 J/min (equivalent to 3.6% ± 3.5%, p < 0.0001), respectively. While there was a statistically significant difference between the equations in both absolute value and relative proportion, this difference was not considered clinically relevant. Additionally, we observed that each 5% increase in Tslope time corresponded to a decrease in mechanical power values by approximately 1 J/min.

CONCLUSIONS

The differences between mechanical power values calculated using the MPdyn and MPLM equations at various Tslope durations were determined to lack clinical significance. Consequently, for practical and continuous mechanical power estimation in Pressure-Controlled Ventilation (PCV) mode, the MPdyn equation presents itself as a viable option. It is important to note that as Tslope times increased, the calculated mechanical power exhibited a clinically relevant decrease.

Flow-controlled versus pressure-controlled ventilation in cardiac surgery with cardiopulmonary bypass - A single-center, prospective, randomized, controlled trial

STUDY OBJECTIVE

Multifactorial comparison of flow-controlled ventilation (FCV) to standard of pressure-controlled ventilation (PCV) in terms of oxygenation in cardiac surgery patients after chest closure.

DESIGN

Prospective, non-blinded, randomized, controlled trial.

SETTING

Operating theatre at an university hospital, Austria.

PATIENTS

Patients scheduled for elective, open, on-pump, cardiac surgery.

INTERVENTIONS

Participants were randomized to either individualized FCV (compliance guided end-expiratory and peak pressure setting) or control of PCV (compliance guided end-expiratory pressure setting and tidal volume of 6-8 ml/kg) for the duration of surgery.

MEASUREMENTS

The primary outcome measure was oxygenation (PaO2/FiO2) 15 min after intraoperative chest closure. Secondary endpoints included CO2-removal assessed as required minute volume to achieve normocapnia and lung tissue aeration assessed by Hounsfield unit distribution in postoperative computed tomography scans.

MAIN RESULTS

Between April 2020 and April 2021 56 patients were enrolled and 50 included in the primary analysis (mean age 70 years, 38 (76%) men). Oxygenation, assessed by PaO2/FiO2, was significantly higher in the FCV group (n = 24) compared to the control group (PCV, n = 26) (356 vs. 309, median difference (MD) 46 (95% CI 3 to 90) mmHg; p = 0.038). Additionally, the minute volume required to obtain normocapnia was significantly lower in the FCV group (4.0 vs. 6.1, MD -2.0 (95% CI -2.5 to -1.5) l/min; p < 0.001) and correlated with a significantly lower exposure to mechanical power (5.1 vs. 9.8, MD -5.1 (95% CI -6.2 to -4.0) J/min; p < 0.001). Evaluation of lung tissue aeration revealed a significantly reduced amount of non-aerated lung tissue in FCV compared to PCV (5 vs. 7, MD -3 (95% CI -4 to -1) %; p < 0.001).

CONCLUSIONS

In patients undergoing on-pump, cardiac surgery individualized FCV significantly improved oxygenation and lung tissue aeration compared to PCV. In addition, carbon dioxide removal was accomplished at a lower minute volume leading to reduced applied mechanical power.

Understanding the mechanisms of ventilator-induced lung injury using animal models

Mechanical ventilation is a life-saving therapy in several clinical situations, promoting gas exchange and providing rest to the respiratory muscles. However, mechanical ventilation may cause hemodynamic instability and pulmonary structural damage, which is known as ventilator-induced lung injury (VILI). The four main injury mechanisms associated with VILI are as follows: barotrauma/volutrauma caused by overstretching the lung tissues; atelectrauma, caused by repeated opening and closing of the alveoli resulting in shear stress; and biotrauma, the resulting biological response to tissue damage, which leads to lung and multi-organ failure. This narrative review elucidates the mechanisms underlying the pathogenesis, progression, and resolution of VILI and discusses the strategies that can mitigate VILI. Different static variables (peak, plateau, and driving pressures, positive end-expiratory pressure, and tidal volume) and dynamic variables (respiratory rate, airflow amplitude, and inspiratory time fraction) can contribute to VILI. Moreover, the potential for lung injury depends on tissue vulnerability, mechanical power (energy applied per unit of time), and the duration of that exposure. According to the current evidence based on models of acute respiratory distress syndrome and VILI, the following strategies are proposed to provide lung protection: keep the lungs partially collapsed (SaO2 > 88%), avoid opening and closing of collapsed alveoli, and gently ventilate aerated regions while keeping collapsed and consolidated areas at rest. Additional mechanisms, such as subject-ventilator asynchrony, cumulative power, and intensity, as well as the damaging threshold (stress-strain level at which tidal damage is initiated), are under experimental investigation and may enhance the understanding of VILI.

Optimized ventilation power to avoid VILI

The effort to minimize VILI risk must be multi-pronged. The need to adequately ventilate, a key determinant of hazardous power, is reduced by judicious permissive hypercapnia, reduction of innate oxygen demand, and by prone body positioning that promotes both efficient pulmonary gas exchange and homogenous distributions of local stress. Modifiable ventilator-related determinants of lung protection include reductions of tidal volume, plateau pressure, driving pressure, PEEP, inspiratory flow amplitude and profile (using longer inspiration to expiration ratios), and ventilation frequency. Underappreciated conditional cofactors of importance to modulate the impact of local specific power may include lower vascular pressures and blood flows. Employed together, these measures modulate ventilation power with the intent to avoid VILI while achieving clinically acceptable targets for pulmonary gas exchange.

Plateau Pressure and Driving Pressure in Volume- and Pressure-Controlled Ventilation: Comparison of Frictional and Viscoelastic Resistive Components in Pediatric Acute Respiratory Distress Syndrome

OBJECTIVES

To examine frictional, viscoelastic, and elastic resistive components, as well threshold pressures, during volume-controlled ventilation (VCV) and pressure-controlled ventilation (PCV) in pediatric patients with acute respiratory distress syndrome (ARDS).

DESIGN

Prospective cohort study.

SETTING

Seven-bed PICU, Hospital El Carmen de Maipú, Chile.

PATIENTS

Eighteen mechanically ventilated patients less than or equal to 15 years old undergoing neuromuscular blockade as part of management for ARDS.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

All patients were in VCV mode during measurement of pulmonary mechanics, including: the first pressure drop (P1) upon reaching zero flow during the inspiratory hold, peak inspiratory pressure (PIP), plateau pressure (P PLAT ), and total positive end-expiratory pressure (tPEEP). We calculated the components of the working pressure, as defined by the following: frictional resistive = PIP-P1; viscoelastic resistive = P1-P PLAT ; purely elastic = driving pressure (ΔP) = P PLAT -tPEEP; and threshold = intrinsic PEEP. The procedures and calculations were repeated on PCV, keeping the same tidal volume and inspiratory time. Measurements in VCV were considered the gold standard. We performed Spearman correlation and Bland-Altman analysis. The median (interquartile range [IQR]) for patient age was 5 months (2-17 mo). Tidal volume was 5.7 mL/kg (5.3-6.1 mL/kg), PIP cm H 2 O 26 (23-27 cm H 2 O), P1 23 cm H 2 O (21-26 cm H 2 O), P PLAT 19 cm H 2 O (17-22 cm H 2 O), tPEEP 9 cm H 2 O (8-9 cm H 2 O), and ΔP 11 cm H 2 O (9-13 cm H 2 O) in VCV mode at baseline. There was a robust correlation (rho > 0.8) and agreement between frictional resistive, elastic, and threshold components of working pressure in both modes but not for the viscoelastic resistive component. The purely frictional resistive component was negligible. Median peak inspiratory flow with decelerating-flow was 21 (IQR, 15-26) and squared-shaped flow was 7 L/min (IQR, 6-10 L/min) ( p < 0.001).

CONCLUSIONS

P PLAT , ΔP, and tPEEP can guide clinical decisions independent of the ventilatory mode. The modest purely frictional resistive component emphasizes the relevance of maintaining the same safety limits, regardless of the selected ventilatory mode. Therefore, peak inspiratory flow should be studied as a mechanism of ventilator-induced lung injury in pediatric ARDS.

Practical assessment of risk of VILI from ventilating power: a conceptual model

At the bedside, assessing the risk of ventilator-induced lung injury (VILI) requires parameters readily measured by the clinician. For this purpose, driving pressure (DP) and end-inspiratory static 'plateau' pressure ([Formula: see text]) of the tidal cycle are unquestionably useful but lack key information relating to associated volume changes and cumulative strain. 'Mechanical power', a clinical term which incorporates all dissipated ('non-elastic') and conserved ('elastic') energy components of inflation, has drawn considerable interest as a comprehensive 'umbrella' variable that accounts for the influence of ventilating frequency per minute as well as the energy cost per tidal cycle. Yet, like the raw values of DP and [Formula: see text], the absolute levels of energy and power by themselves may not carry sufficiently precise information to guide safe ventilatory practice. In previous work we introduced the concept of 'damaging energy per cycle'. Here we describe how-if only in concept-the bedside clinician might gauge the theoretical hazard of delivered energy using easily observed static circuit pressures ([Formula: see text] and positive end expiratory pressure) and an estimate of the maximally tolerated (threshold) non-dissipated ('elastic') airway pressure that reflects the pressure component applied to the alveolar tissues. Because its core inputs are already in use and familiar in daily practice, the simplified mathematical model we propose here for damaging energy and power may promote deeper comprehension of the key factors in play to improve lung protective ventilation.

Intracycle power distribution in a heterogeneous multi-compartmental mathematical model: possible links to strain and VILI

BACKGROUND

Repeated expenditure of energy and its generation of damaging strain are required to injure the lung by ventilation (VILI). Mathematical modeling of passively inflated, single-compartment lungs with uniform parameters for resistance and compliance indicates that standard clinical modes (flow patterns) differ impressively with respect to the timing and intensity of energy delivery-the intracycle power (ICP) that determines parenchymal stress and strain. Although measures of elastic ICP may accurately characterize instantaneous rates of global energy delivery, how the ICP component delivered to a compartment affects the VILI-linked variable of strain is determined by compartmental mechanics, compartmental size and mode of gas delivery. We extended our one-compartment model of ICP to a multi-compartment setting that varied those characteristics.

MAIN FINDINGS

The primary findings of this model/simulation indicate that: (1) the strain and strain rate experienced within a modeled compartment are nonlinear functions of delivered energy and power, respectively; (2) for a given combination of flow profile and tidal volume, resting compartmental volumes influence their resulting maximal strains in response to breath delivery; (3) flow profile is a key determinant of the maximal strain as well as maximal strain rate experienced within a multi-compartment lung. By implication, different clinician-selected flow profiles not only influence the timing of power delivery, but also spatially distribute the attendant strains of expansion among compartments with diverse mechanical properties. Importantly, the contours and magnitudes of the compartmental ICP, strain, and strain rate curves are not congruent; strain and strain rate do not necessarily follow the compartmental ICP, and the hierarchy of amplitudes among compartments for these variables may not coincide.

CONCLUSIONS

Different flow patterns impact how strain and strain rate develop as compartmental volume crests to its final value. Notably, as inflation proceeds, strain rate may rise or fall even as total strain, a monotonic function of volume, steadily (and predictably) rises. Which flow pattern serves best to minimize the maximal strain rate and VILI risk experienced within any sector, therefore, may strongly depend on the nature and heterogeneity of the mechanical properties of the injured lung.

Intracycle power and ventilation mode as potential contributors to ventilator-induced lung injury

Background

High rates of inflation energy delivery coupled with transpulmonary tidal pressures of sufficient magnitude may augment the risk of damage to vulnerable, stress-focused units within a mechanically heterogeneous lung. Apart from flow amplitude, the clinician-selected flow waveform, a relatively neglected dimension of inflation power, may distribute inflation energy of each inflation cycle non-uniformly among alveoli with different mechanical properties over the domains of time and space. In this initial step in modeling intracycle power distribution, our primary objective was to develop a mathematical model of global intracycle inflation power that uses clinician-measurable inputs to allow comparisons of instantaneous ICP profiles among the flow modes commonly encountered in clinical practice: constant, linearly decelerating, exponentially decelerating (pressure control), and spontaneous (sinusoidal).

Methods

We first tested the predictions of our mathematical model of passive inflation with the actual physical performance of a mechanical ventilator–lung system that simulated ventilation to three types of patients: normal, severe ARDS, and severe airflow obstruction. After verification, model predictions were then generated for 5000 ‘virtual ARDS patients’. Holding constant the tidal volume and inflation time between modes, the validated model then varied the flow profile and quantitated the resulting intensity and timing of potentially damaging ‘elastic’ energy and intracycle power (pressure–flow product) developed in response to random combinations of machine settings and severity levels for ARDS.

Results

Our modeling indicates that while the varied flow patterns ultimately deliver similar total amounts of alveolar energy during each breath, they differ profoundly regarding the potentially damaging pattern with which that energy distributes over time during inflation. Pressure control imposed relatively high maximal intracycle power.

Conclusions

Flow amplitude and waveform may be relatively neglected and modifiable determinants of VILI risk when ventilating ARDS.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40635-021-00420-9.