Why Reduced Inspiratory Pressure Could Determine Success of Non-Invasive Ventilation in Acute Hypoxic Respiratory Failure.

The magnitude of inspiratory effort relief within the first 2 hours of non-invasive ventilation for hypoxic respiratory failure was shown in a recent exploratory clinical study to be an early and accurate predictor of outcome at 24 hours. We simulated the application of non-invasive ventilation to three patients whose physiological and clinical characteristics match the data in that study. Reductions in inspiratory effort corresponding to reductions of esophageal pressure swing greater than 10 cmH2O more than halved the values of total lung stress, driving pressure, power and transpulmonary pressure swing. In the absence of significant reductions in inspiratory pressure, multiple indicators of lung injury increased after application of non-invasive ventilation. Clinical Relevance- We show using computer simulation that reduced inspiratory pressure after application of noninvasive ventilation translates directly into large reductions in multiple well-established indicators of lung injury, providing a potential physiological explanation for recent clinical findings.

A computational cardiopulmonary physiology simulator accurately predicts individual patient responses to changes in mechanical ventilator settings.

We present new results validating the capability of a high-fidelity computational simulator to accurately predict the responses of individual patients with acute respiratory distress syndrome to changes in mechanical ventilator settings. 26 pairs of data-points comprising arterial blood gasses collected before and after changes in inspiratory pressure, PEEP, FiO2, and I:E ratio from six mechanically ventilated patients were used for this study. Parallelized global optimization algorithms running on a high-performance computing cluster were used to match the simulator to each initial data point. Mean absolute percentage errors between the simulator predicted values of PaO2 and PaCO2 and the patient data after changing ventilator parameters were 10.3% and 12.6%, respectively. Decreasing the complexity of the simulator by reducing the number of independent alveolar compartments reduced the accuracy of its predictions. Clinical Relevance- These results provide further evidence that our computational simulator can accurately reproduce patient responses to mechanical ventilation, highlighting its usefulness as a clinical research tool.

Validation of at-the-bedside formulae for estimating ventilator driving pressure during airway pressure release ventilation using computer simulation.

BACKGROUND: Airway pressure release ventilation (APRV) is widely available on mechanical ventilators and has been proposed as an early intervention to prevent lung injury or as a rescue therapy in the management of refractory hypoxemia. Driving pressure ([Formula: see text]) has been identified in numerous studies as a key indicator of ventilator-induced-lung-injury that needs to be carefully controlled. [Formula: see text] delivered by the ventilator in APRV is not directly measurable in dynamic conditions, and there is no "gold standard" method for its estimation. METHODS: We used a computational simulator matched to data from 90 patients with acute respiratory distress syndrome (ARDS) to evaluate the accuracy of three "at-the-bedside" methods for estimating ventilator [Formula: see text] during APRV. RESULTS: Levels of [Formula: see text] delivered by the ventilator in APRV were generally within safe limits, but in some cases exceeded levels specified by protective ventilation strategies. A formula based on estimating the intrinsic positive end expiratory pressure present at the end of the APRV release provided the most accurate estimates of [Formula: see text]. A second formula based on assuming that expiratory flow, volume and pressure decay mono-exponentially, and a third method that requires temporarily switching to volume-controlled ventilation, also provided accurate estimates of true [Formula: see text]. CONCLUSIONS: Levels of [Formula: see text] delivered by the ventilator during APRV can potentially exceed levels specified by standard protective ventilation strategies, highlighting the need for careful monitoring. Our results show that [Formula: see text] delivered by the ventilator during APRV can be accurately estimated at the bedside using simple formulae that are based on readily available measurements.

Optimising respiratory support for early COVID-19 pneumonia: a computational modelling study.

BACKGROUND: Optimal respiratory support in early COVID-19 pneumonia is controversial and remains unclear. Using computational modelling, we examined whether lung injury might be exacerbated in early COVID-19 by assessing the impact of conventional oxygen therapy (COT), high-flow nasal oxygen therapy (HFNOT), continuous positive airway pressure (CPAP), and noninvasive ventilation (NIV). METHODS: Using an established multi-compartmental cardiopulmonary simulator, we first modelled COT at a fixed FiO2 (0.6) with elevated respiratory effort for 30 min in 120 spontaneously breathing patients, before initiating HFNOT, CPAP, or NIV. Respiratory effort was then reduced progressively over 30-min intervals. Oxygenation, respiratory effort, and lung stress/strain were quantified. Lung-protective mechanical ventilation was also simulated in the same cohort. RESULTS: HFNOT, CPAP, and NIV improved oxygenation compared with conventional therapy, but also initially increased total lung stress and strain. Improved oxygenation with CPAP reduced respiratory effort but lung stress/strain remained elevated for CPAP >5 cm H2O. With reduced respiratory effort, HFNOT maintained better oxygenation and reduced total lung stress, with no increase in total lung strain. Compared with 10 cm H2O PEEP, 4 cm H2O PEEP in NIV reduced total lung stress, but high total lung strain persisted even with less respiratory effort. Lung-protective mechanical ventilation improved oxygenation while minimising lung injury. CONCLUSIONS: The failure of noninvasive ventilatory support to reduce respiratory effort may exacerbate pulmonary injury in patients with early COVID-19 pneumonia. HFNOT reduces lung strain and achieves similar oxygenation to CPAP/NIV. Invasive mechanical ventilation may be less injurious than noninvasive support in patients with high respiratory effort.

High risk of patient self-inflicted lung injury in COVID-19 with frequently encountered spontaneous breathing patterns: a computational modelling study.

BACKGROUND: There is on-going controversy regarding the potential for increased respiratory effort to generate patient self-inflicted lung injury (P-SILI) in spontaneously breathing patients with COVID-19 acute hypoxaemic respiratory failure. However, direct clinical evidence linking increased inspiratory effort to lung injury is scarce. We adapted a computational simulator of cardiopulmonary pathophysiology to quantify the mechanical forces that could lead to P-SILI at different levels of respiratory effort. In accordance with recent data, the simulator parameters were manually adjusted to generate a population of 10 patients that recapitulate clinical features exhibited by certain COVID-19 patients, i.e., severe hypoxaemia combined with relatively well-preserved lung mechanics, being treated with supplemental oxygen. RESULTS: Simulations were conducted at tidal volumes (VT) and respiratory rates (RR) of 7 ml/kg and 14 breaths/min (representing normal respiratory effort) and at VT/RR of 7/20, 7/30, 10/14, 10/20 and 10/30 ml/kg / breaths/min. While oxygenation improved with higher respiratory efforts, significant increases in multiple indicators of the potential for lung injury were observed at all higher VT/RR combinations tested. Pleural pressure swing increased from 12.0 ± 0.3 cmH2O at baseline to 33.8 ± 0.4 cmH2O at VT/RR of 7 ml/kg/30 breaths/min and to 46.2 ± 0.5 cmH2O at 10 ml/kg/30 breaths/min. Transpulmonary pressure swing increased from 4.7 ± 0.1 cmH2O at baseline to 17.9 ± 0.3 cmH2O at VT/RR of 7 ml/kg/30 breaths/min and to 24.2 ± 0.3 cmH2O at 10 ml/kg/30 breaths/min. Total lung strain increased from 0.29 ± 0.006 at baseline to 0.65 ± 0.016 at 10 ml/kg/30 breaths/min. Mechanical power increased from 1.6 ± 0.1 J/min at baseline to 12.9 ± 0.2 J/min at VT/RR of 7 ml/kg/30 breaths/min, and to 24.9 ± 0.3 J/min at 10 ml/kg/30 breaths/min. Driving pressure increased from 7.7 ± 0.2 cmH2O at baseline to 19.6 ± 0.2 cmH2O at VT/RR of 7 ml/kg/30 breaths/min, and to 26.9 ± 0.3 cmH2O at 10 ml/kg/30 breaths/min. CONCLUSIONS: Our results suggest that the forces generated by increased inspiratory effort commonly seen in COVID-19 acute hypoxaemic respiratory failure are comparable with those that have been associated with ventilator-induced lung injury during mechanical ventilation. Respiratory efforts in these patients should be carefully monitored and controlled to minimise the risk of lung injury.

In Silico Modeling of Coronavirus Disease 2019 Acute Respiratory Distress Syndrome: Pathophysiologic Insights and Potential Management Implications.

OBJECTIVES: Patients with coronavirus disease 2019 acute respiratory distress syndrome appear to present with at least two distinct phenotypes: severe hypoxemia with relatively well-preserved lung compliance and lung gas volumes (type 1) and a more conventional acute respiratory distress syndrome phenotype, displaying the typical characteristics of the "baby lung" (type 2). We aimed to test plausible hypotheses regarding the pathophysiologic mechanisms underlying coronavirus disease 2019 acute respiratory distress syndrome and to evaluate the resulting implications for ventilatory management. DESIGN: We adapted a high-fidelity computational simulator, previously validated in several studies of acute respiratory distress syndrome, to: 1) develop quantitative insights into the key pathophysiologic differences between the coronavirus disease 2019 acute respiratory distress syndrome and the conventional acute respiratory distress syndrome and 2) assess the impact of different positive end-expiratory pressure, Fio2, and tidal volume settings. SETTING: Interdisciplinary Collaboration in Systems Medicine Research Network. SUBJECTS: The simulator was calibrated to represent coronavirus disease 2019 acute respiratory distress syndrome patients with both normal and elevated body mass indices undergoing invasive mechanical ventilation. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: An acute respiratory distress syndrome model implementing disruption of hypoxic pulmonary vasoconstriction and vasodilation leading to hyperperfusion of collapsed lung regions failed to replicate clinical data on type 1 coronavirus disease 2019 acute respiratory distress syndrome patients. Adding mechanisms to reflect disruption of alveolar gas-exchange due to the effects of pneumonitis and heightened vascular resistance due to the emergence of microthrombi produced levels of ventilation perfusion mismatch and hypoxemia consistent with data from type 1 coronavirus disease 2019 acute respiratory distress syndrome patients, while preserving close-to-normal lung compliance and gas volumes. Atypical responses to positive end-expiratory pressure increments between 5 and 15 cm H2O were observed for this type 1 coronavirus disease 2019 acute respiratory distress syndrome model across a range of measures: increasing positive end-expiratory pressure resulted in reduced lung compliance and no improvement in oxygenation, whereas mechanical power, driving pressure, and plateau pressure all increased. Fio2 settings based on acute respiratory distress syndrome network protocols at different positive end-expiratory pressure levels were insufficient to achieve adequate oxygenation. Incrementing tidal volumes from 5 to 10 mL/kg produced similar increases in multiple indicators of ventilator-induced lung injury in the type 1 coronavirus disease 2019 acute respiratory distress syndrome model to those seen in a conventional acute respiratory distress syndrome model. CONCLUSIONS: Our model suggests that use of standard positive end-expiratory pressure/Fio2 tables, higher positive end-expiratory pressure strategies, and higher tidal volumes may all be potentially deleterious in type 1 coronavirus disease 2019 acute respiratory distress syndrome patients, and that a highly personalized approach to treatment is advisable.

Airway clearance techniques and use of mucoactive agents for adult critically ill patients with acute respiratory failure: a qualitative study exploring UK physiotherapy practice.

OBJECTIVES: To explore and describe current UK physiotherapy practice relating to airway clearance techniques and mucoactive agents in critically ill adult patients with acute respiratory failure in the intensive care unit. DESIGN: A descriptive, qualitative study using focus group interviews. Focus groups were audio-recorded, independently transcribed, and data analysed thematically. Participants Senior, experienced physiotherapists, clinically active in critical care. RESULTS: Fifteen physiotherapists participated in four interview sessions. Five themes emerged describing airway clearance techniques: 'Repertoire of airway clearance techniques', 'Staffing and skillset', 'Commencing respiratory physiotherapy', 'Technique selection', and 'Determining effectiveness' were themes related to airway clearance techniques. Five themes were also identified in relation to mucoactive agents: 'Use in clinical practice', 'Decision to commence', 'Selection of agent', 'Stopping mucoactive agents', and 'Determining effectiveness'. A summary of key features of standard practice was developed. CONCLUSIONS: Standard UK physiotherapy practice of airway clearance techniques is variable, but patient-centred and targeted to individual need, with adjunctive use of mucoactive agents to enhance and optimise patient management if required. Based on this study, key features of airway clearance techniques have been summarised to help capture standard care, which could be used in future trials involving ACT as part of usual care.

Mucoactive agent use in adult UK Critical Care Units: a survey of health care professionals' perception, pharmacists' description of practice, and point prevalence of mucoactive use in invasively mechanically ventilated patients.

BACKGROUND: Mechanical ventilation for acute respiratory failure is one of the most common indications for admission to intensive care units (ICUs). Airway mucus clearance is impaired in these patients medication, impaired mucociliary motility, increased mucus production etc. and mucoactive agents have the potential to improve outcomes. However, studies to date have provided inconclusive results. Despite this uncertainty, mucoactives are used in adult ICUs, although the extent of use and perceptions about place in therapy are not known. AIMS AND OBJECTIVES: We aim to describe the use of mucoactive agents in mechanically ventilated patients in UK adult critical care units. Specifically, our objectives are to describe clinicians perceptions about the use of mucoactive agents, understand the indications and anticipated benefits, and describe the prevalence and type of mucoactive agents in use. METHODS: We conducted three surveys. Firstly, a practitioner-level survey aimed at nurses, physiotherapists and doctors to elucidate individual practitioners perceptions about the use of mucoactive agents. Secondly, a critical care unit-level survey aimed at pharmacists to understand how these perceptions translate into practice. Thirdly, a point prevalence survey to describe the extent of prescribing and range of products in use. The practitioner-level survey was disseminated through the UK Intensive Care Society for completion by a multi-professional membership. The unit-level and point prevalence surveys were disseminated cthrough the UK Clinical Pharmacy Association for completion by pharmacists. RESULTS: The individual practitioners survey ranked 'thick secretions' as the main reason for commencing mucoactive agents determined using clinical assessment. The highest ranked perceived benefit for patient centred outcomes was the duration of ventilation. Of these respondents, 79% stated that further research was important and 87% expressed support for a clinical trial. The unit-level survey found that mucoactive agents were used in 83% of units. The most highly ranked indication was again 'thick secretions' and the most highly ranked expected patient centred clinical benefit being improved gas exchange and reduced ventilation time. Only five critical care units provided guidelines to direct the use of mucoactive agents (4%). In the point prevalence survey, 411/993 (41%) of mechanically ventilated patients received at least one mucoactive agent. The most commonly administered mucoactives were inhaled sodium chloride 0.9% (235/993, 24%), systemic carbocisteine (161/993, 16%) and inhaled hypertonic sodium cloride (127/993, 13%). CONCLUSIONS: Mucoactive agents are used extensively in mechanically ventilated adult patients in UK ICUs to manage 'thick secretions', with a key aim to reduce the duration of ventilation. There is widespread support for clinical trials to determine the optimal use of mucoactive agent therapy in this patient population.

Predicting 30-day mortality in patients with sepsis: An exploratory analysis of process of care and patient characteristics.

BACKGROUND: Sepsis represents a significant public health burden, costing the NHS £2.5 billion annually, with 35% mortality in 2006. The aim of this exploratory study was to investigate risk factors predictive of 30-day mortality amongst patients with sepsis in Nottingham. METHODS: Data were collected prospectively from adult patients with sepsis in Nottingham University Hospitals NHS Trust as part of an on-going quality improvement project between November 2011 and March 2014. Patients admitted to critical care with the diagnosis of sepsis were included in the study. In all, 97 separate variables were investigated for their association with 30-day mortality. Variables included patient demographics, symptoms of systemic inflammatory response syndrome, organ dysfunction or tissue hypoperfusion, locations of early care, source of sepsis and time to interventions. RESULTS: A total of 455 patients were included in the study. Increased age (adjOR = 1.05 95%CI = 1.03-1.07 p < 0.001), thrombocytopenia (adjOR = 3.10 95%CI = 1.23-7.82 p = 0.016), hospital-acquired sepsis (adjOR = 3.34 95%CI = 1.78-6.27 p < 0.001), increased lactate concentration (adjOR = 1.16 95%CI = 1.06-1.27 p = 0.001), remaining hypotensive after vasopressors (adjOR = 3.89 95%CI = 1.26-11.95 p = 0.02) and mottling (adjOR = 3.80 95%CI = 1.06-13.55 p = 0.04) increased 30-day mortality odds. Conversely, fever (adjOR = 0.46 95%CI = 0.28-0.75 p = 0.002), fluid refractory hypotension (adjOR = 0.29 95%CI = 0.10-0.87 p = 0.027) and being diagnosed in surgical wards (adjOR = 0.35 95%CI = 0.15-0.81 p = 0.015) were protective. Treatment timeliness were not significant factors. CONCLUSION: Several important predictors of 30-day mortality were found by this research. Retrospective analysis of our sepsis data has revealed mortality predictors that appear to be more patient-related than intervention-specific. With this information, care can be improved for those identified most at risk of death.

Investigating the effect of cardiac oscillations and deadspace gas mixing during apnea using computer simulation.

Gaseous mixing in the anatomical deadspace with stimulation of respiratory ventilation through cardiogenic oscillations is an important physiological mechanism at the onset of apnea, which has been credited with various beneficial effects, e.g. reduction of hypercapnia during the use of low flow ventilation techniques. In this paper, a novel method is proposed to investigate the effect of these mechanisms in silico. An existing computational model of cardio-pulmonary physiology is extended to include the apneic state, gas mixing within the anatomical deadspace, insufflation into the trachea and cardiogenic oscillations. The new model is validated against data published in an experimental animal (dog) study that reported an increase in arterial partial pressure of carbon dioxide (PaCO2) during apnea. Computational simulations confirm that the model outputs accurately reproduce the available experimental data. This new model can be used to investigate the physiological mechanisms underlying clearance of carbon dioxide during apnea, and hence to develop more effective ventilation strategies for apneic patients.

Hemodynamic effects of lung recruitment maneuvers in acute respiratory distress syndrome.

BACKGROUND: Clinical trials have, so far, failed to establish clear beneficial outcomes of recruitment maneuvers (RMs) on patient mortality in acute respiratory distress syndrome (ARDS), and the effects of RMs on the cardiovascular system remain poorly understood. METHODS: A computational model with highly integrated pulmonary and cardiovascular systems was configured to replicate static and dynamic cardio-pulmonary data from clinical trials. Recruitment maneuvers (RMs) were executed in 23 individual in-silico patients with varying levels of ARDS severity and initial cardiac output. Multiple clinical variables were recorded and analyzed, including arterial oxygenation, cardiac output, peripheral oxygen delivery and alveolar strain. RESULTS: The maximal recruitment strategy (MRS) maneuver, which implements gradual increments of positive end expiratory pressure (PEEP) followed by PEEP titration, produced improvements in PF ratio, carbon dioxide elimination and dynamic strain in all 23 in-silico patients considered. Reduced cardiac output in the moderate and mild in silico ARDS patients produced significant drops in oxygen delivery during the RM (average decrease of 423 ml min-1 and 526 ml min-1, respectively). In the in-silico patients with severe ARDS, however, significantly improved gas-exchange led to an average increase of 89 ml min-1 in oxygen delivery during the RM, despite a simultaneous fall in cardiac output of more than 3 l min-1 on average. Post RM increases in oxygen delivery were observed only for the in silico patients with severe ARDS. In patients with high baseline cardiac outputs (>6.5 l min-1), oxygen delivery never fell below 700 ml min-1. CONCLUSIONS: Our results support the hypothesis that patients with severe ARDS and significant numbers of alveolar units available for recruitment may benefit more from RMs. Our results also indicate that a higher than normal initial cardiac output may provide protection against the potentially negative effects of high intrathoracic pressures associated with RMs on cardiac function. Results from in silico patients with mild or moderate ARDS suggest that the detrimental effects of RMs on cardiac output can potentially outweigh the positive effects of alveolar recruitment on oxygenation, resulting in overall reductions in tissue oxygen delivery.

Creating virtual ARDS patients.

This paper presents the methodology used in patient-specific calibration of a novel highly integrated model of the cardiovascular and pulmonary pathophysiology associated with Acute Respiratory Distress Syndrome (ARDS). We focus on data from previously published clinical trials on the static and dynamic cardio-pulmonary responses of three ARDS patients to changes in ventilator settings. From this data, the parameters of the integrated model were identified using an optimization-based methodology in multiple stages. Computational simulations confirm that the resulting model outputs accurately reproduce the available clinical data. Our results open up the possibility of creating in silico a biobank of virtual ARDS patients that could be used to evaluate current, and investigate novel, therapeutic strategies.

Computational simulation indicates that moderately high-frequency ventilation can allow safe reduction of tidal volumes and airway pressures in ARDS patients.

BACKGROUND: A recent prospective trial using porcine models of severe acute respiratory distress syndrome (ARDS) indicated that positive-pressure ventilation delivered by a conventional intensive care ventilator at a moderately high frequency allows safe reduction of tidal volume below 6 ml/kg, leading to more protective ventilation. We aimed to explore whether these results would be replicated when implementing similar ventilation strategies in a high-fidelity computational simulator, tuned to match data on the responses of a number of human ARDS patients to different ventilator inputs. METHODS: We evaluated three different strategies for managing the trade-off between increasing respiratory rate and reducing tidal volume while attempting to maintain the partial pressure of carbon dioxide in arterial blood (PaCO2) constant on a computational simulator configured with ARDS patient datasets. RESULTS: For a fixed sequence of stepwise increases in the respiratory rate, corresponding decreases in tidal volume to keep the alveolar minute ventilation and inspiratory flow constant were calculated according to standard formulae. When applied on the simulator, however, these sequences of ventilator settings failed to maintain PaCO2 adequately in the virtual patients considered. In contrast, an approach based on combining numerical optimisation methods with computational simulation allowed a sequence of tidal volume reductions to be computed for each virtual patient that maintained PaCO2 levels while significantly reducing peak airway pressures and dynamic alveolar strain in all patients. CONCLUSIONS: Our study supports the proposition that moderately high-frequency respiratory rates can allow more protective ventilation of ARDS patients and highlights the potential role of high-fidelity simulators in computing optimised and personalised ventilator settings for individual patients using this approach.

Evaluation of lung recruitment maneuvers in acute respiratory distress syndrome using computer simulation.

INTRODUCTION: Direct comparison of the relative efficacy of different recruitment maneuvers (RMs) for patients with acute respiratory distress syndrome (ARDS) via clinical trials is difficult, due to the heterogeneity of patient populations and disease states, as well as a variety of practical issues. There is also significant uncertainty regarding the minimum values of positive end-expiratory pressure (PEEP) required to ensure maintenance of effective lung recruitment using RMs. We used patient-specific computational simulation to analyze how three different RMs act to improve physiological responses, and investigate how different levels of PEEP contribute to maintaining effective lung recruitment. METHODS: We conducted experiments on five 'virtual' ARDS patients using a computational simulator that reproduces static and dynamic features of a multivariable clinical dataset on the responses of individual ARDS patients to a range of ventilator inputs. Three recruitment maneuvers (sustained inflation (SI), maximal recruitment strategy (MRS) followed by a titrated PEEP, and prolonged recruitment maneuver (PRM)) were implemented and evaluated for a range of different pressure settings. RESULTS: All maneuvers demonstrated improvements in gas exchange, but the extent and duration of improvement varied significantly, as did the observed mechanism of operation. Maintaining adequate post-RM levels of PEEP was seen to be crucial in avoiding cliff-edge type re-collapse of alveolar units for all maneuvers. For all five patients, the MRS exhibited the most prolonged improvement in oxygenation, and we found that a PEEP setting of 35 cm H2O with a fixed driving pressure of 15 cm H2O (above PEEP) was sufficient to achieve 95% recruitment. Subsequently, we found that PEEP titrated to a value of 16 cm H2O was able to maintain 95% recruitment in all five patients. CONCLUSIONS: There appears to be significant scope for reducing the peak levels of PEEP originally specified in the MRS and hence to avoid exposing the lung to unnecessarily high pressures. More generally, our study highlights the huge potential of computer simulation to assist in evaluating the efficacy of different recruitment maneuvers, in understanding their modes of operation, in optimizing RMs for individual patients, and in supporting clinicians in the rational design of improved treatment strategies.

Development of an integrated model of cardiovascular and pulmonary physiology for the evaluation of mechanical ventilation strategies.

We describe the development of an integrated cardiovascular and pulmonary model for use in the investigation of novel mechanical ventilation strategies in the intensive care unit. The cardiac model includes the cardiac chambers, the pulmonary circulation and the systemic circulation. The modeling of complex mechanisms for vascular segments, time varying elastance functions of cardiovascular components and the effect of vascular resistances, in health and disease under the influence of mechanical ventilation is investigated. The resulting biomedical simulator can aid in understanding the underlying pathophysiology of critically-ill patients and facilitate the development of more effective therapeutic strategies for evaluation in clinical trials.

Can computer simulators accurately represent the pathophysiology of individual COPD patients?

BACKGROUND: Computer simulation models could play a key role in developing novel therapeutic strategies for patients with chronic obstructive pulmonary disease (COPD) if they can be shown to accurately represent the pathophysiological characteristics of individual patients. METHODS: We evaluated the capability of a computational simulator to reproduce the heterogeneous effects of COPD on alveolar mechanics as captured in a number of different patient datasets. RESULTS: Our results show that accurately representing the pathophysiology of individual COPD patients necessitates the use of simulation models with large numbers (up to 200) of compartments for gas exchange. The tuning of such complex simulation models 'by hand' to match patient data is not feasible, and thus we present an automated approach based on the use of global optimization algorithms and high-performance computing. Using this approach, we are able to achieve extremely close matches between the simulator and a range of patient data including PaO2, PaCO2, pulmonary deadspace fraction, pulmonary shunt fraction, and ventilation/perfusion (/Q) curves. Using the simulator, we computed combinations of ventilator settings that optimally manage the trade-off between ensuring adequate gas exchange and minimizing the risk of ventilator-associated lung injury for an individual COPD patient. CONCLUSIONS: Our results significantly strengthen the credibility of computer simulation models as research tools for the development of novel management protocols in COPD and other pulmonary disease states.