Flow starvation during square-flow assisted ventilation detected by supervised deep learning techniques.

BACKGROUND: Flow starvation is a type of patient-ventilator asynchrony that occurs when gas delivery does not fully meet the patients' ventilatory demand due to an insufficient airflow and/or a high inspiratory effort, and it is usually identified by visual inspection of airway pressure waveform. Clinical diagnosis is cumbersome and prone to underdiagnosis, being an opportunity for artificial intelligence. Our objective is to develop a supervised artificial intelligence algorithm for identifying airway pressure deformation during square-flow assisted ventilation and patient-triggered breaths. METHODS: Multicenter, observational study. Adult critically ill patients under mechanical ventilation > 24 h on square-flow assisted ventilation were included. As the reference, 5 intensive care experts classified airway pressure deformation severity. Convolutional neural network and recurrent neural network models were trained and evaluated using accuracy, precision, recall and F1 score. In a subgroup of patients with esophageal pressure measurement (ΔPes), we analyzed the association between the intensity of the inspiratory effort and the airway pressure deformation. RESULTS: 6428 breaths from 28 patients were analyzed, 42% were classified as having normal-mild, 23% moderate, and 34% severe airway pressure deformation. The accuracy of recurrent neural network algorithm and convolutional neural network were 87.9% [87.6-88.3], and 86.8% [86.6-87.4], respectively. Double triggering appeared in 8.8% of breaths, always in the presence of severe airway pressure deformation. The subgroup analysis demonstrated that 74.4% of breaths classified as severe airway pressure deformation had a ΔPes > 10 cmH2O and 37.2% a ΔPes > 15 cmH2O. CONCLUSIONS: Recurrent neural network model appears excellent to identify airway pressure deformation due to flow starvation. It could be used as a real-time, 24-h bedside monitoring tool to minimize unrecognized periods of inappropriate patient-ventilator interaction.

Linking Acute Physiology to Outcomes in the ICU: Challenges and Solutions for Research.

ICU clinicians rely on bedside physiological measurements to inform many routine clinical decisions. Because deranged physiology is usually associated with poor clinical outcomes, it is tempting to hypothesize that manipulating and intervening on physiological parameters might improve outcomes for patients. However, testing these hypotheses through mathematical models of the relationship between physiology and outcomes presents a number of important methodological challenges. These models reflect the theories of the researcher and can therefore be heavily influenced by one's assumptions and background beliefs. Model building must therefore be approached with great care and forethought, because failure to consider relevant sources of measurement error, confounding, coupling, and time dependency or failure to assess the direction of causality for associations of interest before modeling may give rise to spurious results. This paper outlines the main challenges in analyzing and interpreting these models and offers potential solutions to address these challenges.

Objective and subjective cognition in survivors of COVID-19 one year after ICU discharge: the role of demographic, clinical, and emotional factors.

BACKGROUND: Intensive Care Unit (ICU) COVID-19 survivors may present long-term cognitive and emotional difficulties after hospital discharge. This study aims to characterize the neuropsychological dysfunction of COVID-19 survivors 12 months after ICU discharge, and to study whether the use of a measure of perceived cognitive deficit allows the detection of objective cognitive impairment. We also explore the relationship between demographic, clinical and emotional factors, and both objective and subjective cognitive deficits. METHODS: Critically ill COVID-19 survivors from two medical ICUs underwent cognitive and emotional assessment one year after discharge. The perception of cognitive deficit and emotional state was screened through self-rated questionnaires (Perceived Deficits Questionnaire, Hospital Anxiety and Depression Scale and Davidson Trauma Scale), and a comprehensive neuropsychological evaluation was carried out. Demographic and clinical data from ICU admission were collected retrospectively. RESULTS: Out of eighty participants included in the final analysis, 31.3% were women, 61.3% received mechanical ventilation and the median age of patients was 60.73 years. Objective cognitive impairment was observed in 30% of COVID-19 survivors. The worst performance was detected in executive functions, processing speed and recognition memory. Almost one in three patients manifested cognitive complaints, and 22.5%, 26.3% and 27.5% reported anxiety, depression and post-traumatic stress disorder (PTSD) symptoms, respectively. No significant differences were found in the perception of cognitive deficit between patients with and without objective cognitive impairment. Gender and PTSD symptomatology were significantly associated with perceived cognitive deficit, and cognitive reserve with objective cognitive impairment. CONCLUSIONS: One-third of COVID-19 survivors suffered objective cognitive impairment with a frontal-subcortical dysfunction 12 months after ICU discharge. Emotional disturbances and perceived cognitive deficits were common. Female gender and PTSD symptoms emerged as predictive factors for perceiving worse cognitive performance. Cognitive reserve emerged as a protective factor for objective cognitive functioning. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04422444; June 9, 2021.

The Effect of Clusters of Double Triggering and Ineffective Efforts in Critically Ill Patients.

OBJECTIVES: To characterize clusters of double triggering and ineffective inspiratory efforts throughout mechanical ventilation and investigate their associations with mortality and duration of ICU stay and mechanical ventilation. DESIGN: Registry-based, real-world study. BACKGROUND: Asynchronies during invasive mechanical ventilation can occur as isolated events or in clusters and might be related to clinical outcomes. SUBJECTS: Adults requiring mechanical ventilation greater than 24 hours for whom greater than or equal to 70% of ventilator waveforms were available. INTERVENTIONS: We identified clusters of double triggering and ineffective inspiratory efforts and determined their power and duration. We used Fine-Gray's competing risk model to analyze their effects on mortality and generalized linear models to analyze their effects on duration of mechanical ventilation and ICU stay. MEASUREMENTS AND MAIN RESULTS: We analyzed 58,625,796 breaths from 180 patients. All patients had clusters (mean/d, 8.2 [5.4-10.6]; mean power, 54.5 [29.6-111.4]; mean duration, 20.3 min [12.2-34.9 min]). Clusters were less frequent during the first 48 hours (5.5 [2.5-10] vs 7.6 [4.4-9.9] in the remaining period [p = 0.027]). Total number of clusters/d was positively associated with the probability of being discharged alive considering the total period of mechanical ventilation (p = 0.001). Power and duration were similar in the two periods. Power was associated with the probability of being discharged dead (p = 0.03), longer mechanical ventilation (p < 0.001), and longer ICU stay (p = 0.035); cluster duration was associated with longer ICU stay (p = 0.027). CONCLUSIONS: Clusters of double triggering and ineffective inspiratory efforts are common. Although higher numbers of clusters might indicate better chances of survival, clusters with greater power and duration indicate a risk of worse clinical outcomes.

Clusters of Double Triggering Impact Clinical Outcomes: Insights From the EPIdemiology of Patient-Ventilator aSYNChrony (EPISYNC) Cohort Study.

OBJECTIVES: To measure the impact of clusters of double triggering on clinical outcomes. DESIGN: Prospective cohort study. SETTING: Respiratory ICU in Brazil. PATIENTS: Adult patients under recent mechanical ventilation and with expectation of mechanical ventilation for more than 24 hours after enrollment. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We used a dedicated software to analyze ventilator waveforms throughout the entire period of mechanical ventilation and detect double triggering. We defined a cluster of double triggering as a period of time containing at least six double triggering events in a 3-minute period. Patients were followed until hospital discharge. We addressed the association between the presence and the duration of clusters with clinical outcomes. A total of 103 patients were enrolled in the study and 90 (87%) had at least one cluster of double triggering. The median number of clusters per patient was 19 (interquartile range, 6-41), with a median duration of 8 minutes (6-12 min). Compared with patients who had no clusters, patients with at least one cluster had longer duration of mechanical ventilation (7 d [4-11 d] vs 2 d [2-3 d]) and ICU length of stay (9 d [7-16 d] vs 13 d [2-8 d]). Thirty-three patients had high cumulative duration of clusters of double triggering (≥ 12 hr), and it was associated with longer duration of mechanical ventilation, fewer ventilator-free days, and longer ICU length of stay. Adjusted by duration of mechanical ventilation and severity of illness, high cumulative duration of clusters was associated with shorter survival at 28 days (hazard ratio, 2.09 d; 95% CI, 1.04-4.19 d). CONCLUSIONS: Clusters of double triggering are common and were associated with worse clinical outcomes. Patients who had a high cumulative duration of clusters had fewer ventilator-free days, longer duration of mechanical ventilation, longer ICU length of stay, and shorter survival than patients with low cumulative duration of cluster.

Dead space estimates may not be independently associated with 28-day mortality in COVID-19 ARDS.

BACKGROUND: Estimates for dead space ventilation have been shown to be independently associated with an increased risk of mortality in the acute respiratory distress syndrome and small case series of COVID-19-related ARDS. METHODS: Secondary analysis from the PRoVENT-COVID study. The PRoVENT-COVID is a national, multicenter, retrospective observational study done at 22 intensive care units in the Netherlands. Consecutive patients aged at least 18 years were eligible for participation if they had received invasive ventilation for COVID-19 at a participating ICU during the first month of the national outbreak in the Netherlands. The aim was to quantify the dynamics and determine the prognostic value of surrogate markers of wasted ventilation in patients with COVID-19-related ARDS. RESULTS: A total of 927 consecutive patients admitted with COVID-19-related ARDS were included in this study. Estimations of wasted ventilation such as the estimated dead space fraction (by Harris-Benedict and direct method) and ventilatory ratio were significantly higher in non-survivors than survivors at baseline and during the following days of mechanical ventilation (p < 0.001). The end-tidal-to-arterial PCO2 ratio was lower in non-survivors than in survivors (p < 0.001). As ARDS severity increased, mortality increased with successive tertiles of dead space fraction by Harris-Benedict and by direct estimation, and with an increase in the VR. The same trend was observed with decreased levels in the tertiles for the end-tidal-to-arterial PCO2 ratio. After adjustment for a base risk model that included chronic comorbidities and ventilation- and oxygenation-parameters, none of the dead space estimates measured at the start of ventilation or the following days were significantly associated with 28-day mortality. CONCLUSIONS: There is significant impairment of ventilation in the early course of COVID-19-related ARDS but quantification of this impairment does not add prognostic information when added to a baseline risk model. TRIAL REGISTRATION: ISRCTN04346342. Registered 15 April 2020. Retrospectively registered.

Automated detection and quantification of reverse triggering effort under mechanical ventilation.

BACKGROUND: Reverse triggering (RT) is a dyssynchrony defined by a respiratory muscle contraction following a passive mechanical insufflation. It is potentially harmful for the lung and the diaphragm, but its detection is challenging. Magnitude of effort generated by RT is currently unknown. Our objective was to validate supervised methods for automatic detection of RT using only airway pressure (Paw) and flow. A secondary objective was to describe the magnitude of the efforts generated during RT. METHODS: We developed algorithms for detection of RT using Paw and flow waveforms. Experts having Paw, flow and esophageal pressure (Pes) assessed automatic detection accuracy by comparison against visual assessment. Muscular pressure (Pmus) was measured from Pes during RT, triggered breaths and ineffective efforts. RESULTS: Tracings from 20 hypoxemic patients were used (mean age 65 ± 12 years, 65% male, ICU survival 75%). RT was present in 24% of the breaths ranging from 0 (patients paralyzed or in pressure support ventilation) to 93.3%. Automatic detection accuracy was 95.5%: sensitivity 83.1%, specificity 99.4%, positive predictive value 97.6%, negative predictive value 95.0% and kappa index of 0.87. Pmus of RT ranged from 1.3 to 36.8 cmH20, with a median of 8.7 cmH20. RT with breath stacking had the highest levels of Pmus, and RTs with no breath stacking were of similar magnitude than pressure support breaths. CONCLUSION: An automated detection tool using airway pressure and flow can diagnose reverse triggering with excellent accuracy. RT generates a median Pmus of 9 cmH2O with important variability between and within patients. TRIAL REGISTRATION: BEARDS, NCT03447288.

The central nervous system during lung injury and mechanical ventilation: a narrative review.

Mechanical ventilation induces a number of systemic responses for which the brain plays an essential role. During the last decade, substantial evidence has emerged showing that the brain modifies pulmonary responses to physical and biological stimuli by various mechanisms, including the modulation of neuroinflammatory reflexes and the onset of abnormal breathing patterns. Afferent signals and circulating factors from injured peripheral tissues, including the lung, can induce neuronal reprogramming, potentially contributing to neurocognitive dysfunction and psychological alterations seen in critically ill patients. These impairments are ubiquitous in the presence of positive pressure ventilation. This narrative review summarises current evidence of lung-brain crosstalk in patients receiving mechanical ventilation and describes the clinical implications of this crosstalk. Further, it proposes directions for future research ranging from identifying mechanisms of multiorgan failure to mitigating long-term sequelae after critical illness.

An effective pressure-flow characterization of respiratory asynchronies in mechanical ventilation.

Ineffective effort during expiration (IEE) occurs when there is a mismatch between the demand of a mechanically ventilated patient and the support delivered by a Mechanical ventilator during the expiration. This work presents a pressure-flow characterization for respiratory asynchronies and validates a machine-learning method, based on the presented characterization, to identify IEEs. 1500 breaths produced by 8 mechanically-ventilated patients were considered: 500 of them were included into the training set and the remaining 1000 into the test set. Each of them was evaluated by 3 experts and classified as either normal, artefact, or containing inspiratory, expiratory, or cycling-off asynchronies. A software implementing the proposed method was trained by using the experts' evaluations of the training set and used to identify IEEs in the test set. The outcomes were compared with a consensus of three expert evaluations. The software classified IEEs with sensitivity 0.904, specificity 0.995, accuracy 0.983, positive and negative predictive value 0.963 and 0.986, respectively. The Cohen's kappa is 0.983 (with 95% confidence interval (CI): [0.884, 0.962]). The pressure-flow characterization of respiratory cycles and the monitoring technique proposed in this work automatically identified IEEs in real-time in close agreement with the experts.

Methotrexate Ameliorates Systemic Inflammation and Septic Associated-Lung Damage in a Cecal Ligation and Puncture Septic Rat Model.

BACKGROUND: Sepsis is a serious, heterogeneous clinical entity produced by a severe and systemic host inflammatory response to infection. Methotrexate (MTX) is a folate-antagonist that induces the generation of adenosine and also inhibits JAK/STAT pathway; MTX it is widely used as an anti-inflammatory drug to control the immune system. OBJECTIVE: The aim of this study was to assess the beneficial effects of a single and low dose of MTX in the systemic response and acute lung injury (ALI) induced by sepsis. As in the clinics, we treated our animals with antibiotics and fluids and performed the source control to mimic the current clinic treatment. METHODS AND MAIN RESULTS: Sepsis was induced in rats by a cecal ligation puncture (CLP) procedure. Six hours after induction of sepsis, we proceeded to the source control; fluids and antibiotics were administered at 6 h and 24 h after CLP. MTX (2.5 mg/Kg) was administered 6 h after the first surgery in one CLP experimental group and to one Sham group. A protective effect of MTX was observed through a significant reduction of pro-inflammatory cytokines and a decrease infiltration of inflammatory cells in the lung. In addition, we found a regulation in adenosine receptor A2aR and the metalloproteinases by MTX. CONCLUSION: A single, low dose of MTX attenuates sepsis lung-associated damage by decreasing pro-inflammatory response, infiltration of pro-inflammatory cells and avoiding defective tissue lung remodeling.

Cognitive phenotypes 1 month after ICU discharge in mechanically ventilated patients: a prospective observational cohort study.

BACKGROUND: ICU patients undergoing invasive mechanical ventilation experience cognitive decline associated with their critical illness and its management. The early detection of different cognitive phenotypes might reveal the involvement of diverse pathophysiological mechanisms and help to clarify the role of the precipitating and predisposing factors. Our main objective is to identify cognitive phenotypes in critically ill survivors 1 month after ICU discharge using an unsupervised machine learning method, and to contrast them with the classical approach of cognitive impairment assessment. For descriptive purposes, precipitating and predisposing factors for cognitive impairment were explored. METHODS: A total of 156 mechanically ventilated critically ill patients from two medical/surgical ICUs were prospectively studied. Patients with previous cognitive impairment, neurological or psychiatric diagnosis were excluded. Clinical variables were registered during ICU stay, and 100 patients were cognitively assessed 1 month after ICU discharge. The unsupervised machine learning K-means clustering algorithm was applied to detect cognitive phenotypes. Exploratory analyses were used to study precipitating and predisposing factors for cognitive impairment. RESULTS: K-means testing identified three clusters (K) of patients with different cognitive phenotypes: K1 (n = 13), severe cognitive impairment in speed of processing (92%) and executive function (85%); K2 (n = 33), moderate-to-severe deficits in learning-memory (55%), memory retrieval (67%), speed of processing (36.4%) and executive function (33.3%); and K3 (n = 46), normal cognitive profile in 89% of patients. Using the classical approach, moderate-to-severe cognitive decline was recorded in 47% of patients, while the K-means method accurately classified 85.9%. The descriptive analysis showed significant differences in days (p = 0.016) and doses (p = 0.039) with opioid treatment in K1 vs. K2 and K3. In K2, there were more women, patients were older and had more comorbidities (p = 0.001) than in K1 or K3. Cognitive reserve was significantly (p = 0.001) higher in K3 than in K1 or K2. CONCLUSION: One month after ICU discharge, three groups of patients with different cognitive phenotypes were identified through an unsupervised machine learning method. This novel approach improved the classical classification of cognitive impairment in ICU survivors. In the exploratory analysis, gender, age and the level of cognitive reserve emerged as relevant predisposing factors for cognitive impairment in ICU patients. TRIAL REGISTRATION: ClinicalTrials.gov Identifier:NCT02390024; March 17,2015.

Integrated 3D printing solution to mitigate shortages of airway consumables and personal protective equipment during the COVID-19 pandemic.

BACKGROUND: To cope with shortages of equipment during the COVID-19 pandemic, we established a nonprofit end-to-end system to identify, validate, regulate, manufacture, and distribute 3D-printed medical equipment. Here we describe the local and global impact of this system. METHODS: Together with critical care experts, we identified potentially lacking medical equipment and proposed solutions based on 3D printing. Validation was based on the ISO 13485 quality standard for the manufacturing of customized medical devices. We posted the design files for each device on our website together with their technical and printing specifications and created a supply chain so that hospitals from our region could request them. We analyzed the number/type of items, petitioners, manufacturers, and catalogue views. RESULTS: Among 33 devices analyzed, 26 (78·8%) were validated. Of these, 23 (88·5%) were airway consumables and 3 (11·5%) were personal protective equipment. Orders came from 19 (76%) hospitals and 6 (24%) other healthcare institutions. Peak production was reached 10 days after the catalogue was published. A total of 22,135 items were manufactured by 59 companies in 18 sectors; 19,212 items were distributed to requesting sites during the busiest days of the pandemic. Our online catalogue was also viewed by 27,861 individuals from 113 countries. CONCLUSIONS: 3D printing helped mitigate shortages of medical devices due to problems in the global supply chain.

Effects of sedatives and opioids on trigger and cycling asynchronies throughout mechanical ventilation: an observational study in a large dataset from critically ill patients.

BACKGROUND: In critically ill patients, poor patient-ventilator interaction may worsen outcomes. Although sedatives are often administered to improve comfort and facilitate ventilation, they can be deleterious. Whether opioids improve asynchronies with fewer negative effects is unknown. We hypothesized that opioids alone would improve asynchronies and result in more wakeful patients than sedatives alone or sedatives-plus-opioids. METHODS: This prospective multicenter observational trial enrolled critically ill adults mechanically ventilated (MV) > 24 h. We compared asynchronies and sedation depth in patients receiving sedatives, opioids, or both. We recorded sedation level and doses of sedatives and opioids. BetterCare™ software continuously registered ineffective inspiratory efforts during expiration (IEE), double cycling (DC), and asynchrony index (AI) as well as MV modes. All variables were averaged per day. We used linear mixed-effects models to analyze the relationships between asynchronies, sedation level, and sedative and opioid doses. RESULTS: In 79 patients, 14,166,469 breaths were recorded during 579 days of MV. Overall asynchronies were not significantly different in days classified as sedatives-only, opioids-only, and sedatives-plus-opioids and were more prevalent in days classified as no-drugs than in those classified as sedatives-plus-opioids, irrespective of the ventilatory mode. Sedative doses were associated with sedation level and with reduced DC (p < 0.0001) in sedatives-only days. However, on days classified as sedatives-plus-opioids, higher sedative doses and deeper sedation had more IEE (p < 0.0001) and higher AI (p = 0.0004). Opioid dosing was inversely associated with overall asynchronies (p < 0.001) without worsening sedation levels into morbid ranges. CONCLUSIONS: Sedatives, whether alone or combined with opioids, do not result in better patient-ventilator interaction than opioids alone, in any ventilatory mode. Higher opioid dose (alone or with sedatives) was associated with lower AI without depressing consciousness. Higher sedative doses administered alone were associated only with less DC. TRIAL REGISTRATION: ClinicalTrial.gov, NCT03451461.

Double Cycling During Mechanical Ventilation: Frequency, Mechanisms, and Physiologic Implications.

OBJECTIVES: Double cycling generates larger than expected tidal volumes that contribute to lung injury. We analyzed the incidence, mechanisms, and physiologic implications of double cycling during volume- and pressure-targeted mechanical ventilation in critically ill patients. DESIGN: Prospective, observational study. SETTING: Three general ICUs in Spain. PATIENTS: Sixty-seven continuously monitored adult patients undergoing volume control-continuous mandatory ventilation with constant flow, volume control-continuous mandatory ventilation with decelerated flow, or pressure control-continuous mandatory mechanical ventilation for longer than 24 hours. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We analyzed 9,251 hours of mechanical ventilation corresponding to 9,694,573 breaths. Double cycling occurred in 0.6%. All patients had double cycling; however, the distribution of double cycling varied over time. The mean percentage (95% CI) of double cycling was higher in pressure control-continuous mandatory ventilation 0.54 (0.34-0.87) than in volume control-continuous mandatory ventilation with constant flow 0.27 (0.19-0.38) or volume control-continuous mandatory ventilation with decelerated flow 0.11 (0.06-0.20). Tidal volume in double-cycled breaths was higher in volume control-continuous mandatory ventilation with constant flow and volume control-continuous mandatory ventilation with decelerated flow than in pressure control-continuous mandatory ventilation. Double-cycled breaths were patient triggered in 65.4% and reverse triggered (diaphragmatic contraction stimulated by a previous passive ventilator breath) in 34.6% of cases; the difference was largest in volume control-continuous mandatory ventilation with decelerated flow (80.7% patient triggered and 19.3% reverse triggered). Peak pressure of the second stacked breath was highest in volume control-continuous mandatory ventilation with constant flow regardless of trigger type. Various physiologic factors, none mutually exclusive, were associated with double cycling. CONCLUSIONS: Double cycling is uncommon but occurs in all patients. Periods without double cycling alternate with periods with clusters of double cycling. The volume of the stacked breaths can double the set tidal volume in volume control-continuous mandatory ventilation with constant flow. Gas delivery must be tailored to neuroventilatory demand because interdependent ventilator setting-related physiologic factors can contribute to double cycling. One third of double-cycled breaths were reverse triggered, suggesting that repeated respiratory muscle activation after time-initiated ventilator breaths occurs more often than expected.

A Quantile Analysis of Plateau and Driving Pressures: Effects on Mortality in Patients With Acute Respiratory Distress Syndrome Receiving Lung-Protective Ventilation.

OBJECTIVES: The driving pressure (plateau pressure minus positive end-expiratory pressure) has been suggested as the major determinant for the beneficial effects of lung-protective ventilation. We tested whether driving pressure was superior to the variables that define it in predicting outcome in patients with acute respiratory distress syndrome. DESIGN: A secondary analysis of existing data from previously reported observational studies. SETTING: A network of ICUs. PATIENTS: We studied 778 patients with moderate to severe acute respiratory distress syndrome. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We assessed the risk of hospital death based on quantiles of tidal volume, positive end-expiratory pressure, plateau pressure, and driving pressure evaluated at 24 hours after acute respiratory distress syndrome diagnosis while ventilated with standardized lung-protective ventilation. We derived our model using individual data from 478 acute respiratory distress syndrome patients and assessed its replicability in a separate cohort of 300 acute respiratory distress syndrome patients. Tidal volume and positive end-expiratory pressure had no impact on mortality. We identified a plateau pressure cut-off value of 29 cm H2O, above which an ordinal increment was accompanied by an increment of risk of death. We identified a driving pressure cut-off value of 19 cm H2O where an ordinal increment was accompanied by an increment of risk of death. When we cross tabulated patients with plateau pressure less than 30 and plateau pressure greater than or equal to 30 with those with driving pressure less than 19 and driving pressure greater than or equal to 19, plateau pressure provided a slightly better prediction of outcome than driving pressure in both the derivation and validation cohorts (p < 0.0000001). CONCLUSIONS: Plateau pressure was slightly better than driving pressure in predicting hospital death in patients managed with lung-protective ventilation evaluated on standardized ventilator settings 24 hours after acute respiratory distress syndrome onset.

Role of heparin in pulmonary cell populations in an in-vitro model of acute lung injury.

BACKGROUND: In the early stages of acute respiratory distress syndrome (ARDS), pro-inflammatory mediators inhibit natural anticoagulant factors and initiate an increase in procoagulant activity. Previous studies proved the beneficial effects of heparin in pulmonary coagulopathy, which derive from its anticoagulant and anti-inflammatory activities, although it is uncertain whether heparin works. Understanding the specific effect of unfractioned heparin on cell lung populations would be of interest to increase our knowledge about heparin pathways and to treat ARDS. METHODS: In the current study, the effect of heparin was assessed in primary human alveolar macrophages (hAM), alveolar type II cells (hATII), and fibroblasts (hF) that had been injured with LPS. RESULTS: Heparin did not produce any changes in the Smad/TGFß pathway, in any of the cell types evaluated. Heparin reduced the expression of pro-inflammatory markers (TNF-α and IL-6) in hAM and deactivated the NF-kß pathway in hATII, diminishing the expression of IRAK1 and MyD88 and their effectors, IL-6, MCP-1 and IL-8. CONCLUSIONS: The current study demonstrated that heparin significantly ameliorated the cells lung injury induced by LPS through the inhibition of pro-inflammatory cytokine expression in macrophages and the NF-kß pathway in alveolar cells. Our results suggested that a local pulmonary administration of heparin through nebulization may be able to reduce inflammation in the lung; however, further studies are needed to confirm this hypothesis.

Bayesian joint modeling of bivariate longitudinal and competing risks data: An application to study patient-ventilator asynchronies in critical care patients.

Mechanical ventilation is a common procedure of life support in intensive care. Patient-ventilator asynchronies (PVAs) occur when the timing of the ventilator cycle is not simultaneous with the timing of the patient respiratory cycle. The association between severity markers and the events death or alive discharge has been acknowledged before, however, little is known about the addition of PVAs data to the analyses. We used an index of asynchronies (AI) to measure PVAs and the SOFA (sequential organ failure assessment) score to assess overall severity. To investigate the added value of including the AI, we propose a Bayesian joint model of bivariate longitudinal and competing risks data. The longitudinal process includes a mixed effects model for the SOFA score and a mixed effects beta regression model for the AI. The survival process is defined in terms of a cause-specific hazards model for the competing risks death or alive discharge. Our model indicates that the SOFA score is strongly related to vital status. PVAs are positively associated with alive discharge but there is not enough evidence that PVAs provide a more accurate indication of death prognosis than the SOFA score alone.

Impact of Recruitment on Static and Dynamic Lung Strain in Acute Respiratory Distress Syndrome.

BACKGROUND: Lung strain, defined as the ratio between end-inspiratory volume and functional residual capacity, is a marker of the mechanical load during ventilation. However, changes in lung volumes in response to pressures may occur in injured lungs and modify strain values. The objective of this study was to clarify the role of recruitment in strain measurements. METHODS: Six oleic acid-injured pigs were ventilated at positive end-expiratory pressure (PEEP) 0 and 10 cm H2O before and after a recruitment maneuver (PEEP = 20 cm H2O). Lung volumes were measured by helium dilution and inductance plethysmography. In addition, six patients with moderate-to-severe acute respiratory distress syndrome were ventilated with three strategies (peak inspiratory pressure/PEEP: 20/8, 32/8, and 32/20 cm H2O). Lung volumes were measured in computed tomography slices acquired at end-expiration and end-inspiration. From both series, recruited volume and lung strain (total, dynamic, and static) were computed. RESULTS: In the animal model, recruitment caused a significant decrease in dynamic strain (from [mean ± SD] 0.4 ± 0.12 to 0.25 ± 0.07, P < 0.01), while increasing the static component. In patients, total strain remained constant for the three ventilatory settings (0.35 ± 0.1, 0.37 ± 0.11, and 0.32 ± 0.1, respectively). Increases in tidal volume had no significant effects. Increasing PEEP constantly decreased dynamic strain (0.35 ± 0.1, 0.32 ± 0.1, and 0.04+0.03, P < 0.05) and increased static strain (0, 0.06 ± 0.06, and 0.28 ± 0.11, P < 0.05). The changes in dynamic and total strain among patients were correlated to the amount of recruited volume. An analysis restricted to the changes in normally aerated lung yielded similar results. CONCLUSION: Recruitment causes a shift from dynamic to static strain in early acute respiratory distress syndrome.