Evaluation of the Kinetics of Pancreatic Stone Protein as a Predictor of Ventilator-Associated Pneumonia

BACKGROUND

Ventilator-associated pneumonia (VAP) is a severe condition. Early and adequate antibiotic treatment is the most important strategy for improving prognosis. Pancreatic Stone Protein (PSP) has been described as a biomarker that increases values 3-4 days before the clinical diagnosis of nosocomial sepsis in different clinical settings. We hypothesized that serial measures of PSP and its kinetics allow for an early diagnosis of VAP.

METHODS

The BioVAP study was a prospective observational study designed to evaluate the role of biomarker dynamics in the diagnosis of VAP. To determine the association between repeatedly measured PSP and the risk of VAP, we used joint models for longitudinal and time-to-event data.

RESULTS

Of 209 patients, 43 (20.6%) patients developed VAP, with a median time of 4 days. Multivariate joint models with PSP, CRP, and PCT did not show an association between biomarkers and VAP for the daily absolute value, with a hazard ratio (HR) for PSP of 1.01 (95% credible interval: 0.97 to 1.05), for CRP of 1.00 (0.83 to 1.22), and for PCT of 0.95 (0.82 to 1.08). The daily change of biomarkers provided similar results, with an HR for PSP of 1.15 (0.94 to 1.41), for CRP of 0.76 (0.35 to 1.58), and for PCT of 0.77 (0.40 to 1.45).

CONCLUSION

Neither absolute PSP values nor PSP kinetics alone nor in combination with other biomarkers were useful in improving the prediction diagnosis accuracy in patients with VAP.

CLINICAL TRIAL REGISTRATION

Registered retrospectively on August 3rd, 2012. NCT02078999.

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.

Effect of postextubation noninvasive ventilation with active humidification vs high-flow nasal cannula on reintubation in patients at very high risk for extubation failure: a randomized trial

PURPOSE

High-flow nasal cannula (HFNC) oxygen therapy was noninferior to noninvasive ventilation (NIV) for preventing reintubation in a heterogeneous population at high-risk for extubation failure. However, outcomes might differ in certain subgroups of patients. Thus, we aimed to determine whether NIV with active humidification is superior to HFNC in preventing reintubation in patients with ≥ 4 risk factors (very high risk for extubation failure).

METHODS

Randomized controlled trial in two intensive care units in Spain (June 2020‒June 2021). Patients ready for planned extubation with ≥ 4 of the following risk factors for reintubation were included: age > 65 years, Acute Physiology and Chronic Health Evaluation II score > 12 on extubation day, body mass index > 30, inadequate secretions management, difficult or prolonged weaning, ≥ 2 comorbidities, acute heart failure indicating mechanical ventilation, moderate-to-severe chronic obstructive pulmonary disease, airway patency problems, prolonged mechanical ventilation, or hypercapnia on finishing the spontaneous breathing trial. Patients were randomized to undergo NIV with active humidification or HFNC for 48 h after extubation. The primary outcome was reintubation rate within 7 days after extubation. Secondary outcomes included postextubation respiratory failure, respiratory infection, sepsis, multiorgan failure, length of stay, mortality, adverse events, and time to reintubation.

RESULTS

Of 182 patients (mean age, 60 [standard deviation (SD), 15] years; 117 [64%] men), 92 received NIV and 90 HFNC. Reintubation was required in 21 (23.3%) patients receiving NIV vs 35 (38.8%) of those receiving HFNC (difference -15.5%; 95% confidence interval (CI) -28.3 to -1%). Hospital length of stay was lower in those patients treated with NIV (20 [12‒36.7] days vs 26.5 [15‒45] days, difference 6.5 [95%CI 0.5-21.1]). No additional differences in the other secondary outcomes were observed.

CONCLUSIONS

Among adult critically ill patients at very high-risk for extubation failure, NIV with active humidification was superior to HFNC for preventing reintubation.

Effects of IFIH1 rs1990760 variants on systemic inflammation and outcome in critically ill COVID-19 patients in an observational translational study

Background:

Variants in IFIH1, a gene coding the cytoplasmatic RNA sensor MDA5, regulate the response to viral infections. We hypothesized that IFIH1 rs199076 variants would modulate host response and outcome after severe COVID-19.

Methods:

Patients admitted to an intensive care unit (ICU) with confirmed COVID-19 were prospectively studied and rs1990760 variants determined. Peripheral blood gene expression, cell populations, and immune mediators were measured. Peripheral blood mononuclear cells from healthy volunteers were exposed to an MDA5 agonist and dexamethasone ex-vivo, and changes in gene expression assessed. ICU discharge and hospital death were modeled using rs1990760 variants and dexamethasone as factors in this cohort and in-silico clinical trials.

Results:

About 227 patients were studied. Patients with the IFIH1 rs1990760 TT variant showed a lower expression of inflammation-related pathways, an anti-inflammatory cell profile, and lower concentrations of pro-inflammatory mediators. Cells with TT variant exposed to an MDA5 agonist showed an increase in IL6 expression after dexamethasone treatment. All patients with the TT variant not treated with steroids survived their ICU stay (hazard ratio [HR]: 2.49, 95% confidence interval [CI]: 1.29–4.79). Patients with a TT variant treated with dexamethasone showed an increased hospital mortality (HR: 2.19, 95% CI: 1.01–4.87) and serum IL-6. In-silico clinical trials supported these findings.

Conclusions:

COVID-19 patients with the IFIH1 rs1990760 TT variant show an attenuated inflammatory response and better outcomes. Dexamethasone may reverse this anti-inflammatory phenotype.

Funding:

Centro de Investigación Biomédica en Red (CB17/06/00021), Instituto de Salud Carlos III (PI19/00184 and PI20/01360), and Fundació La Marató de TV3 (413/C/2021).

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.

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.

Monitoring Asynchrony During Invasive Mechanical Ventilation

Mechanical ventilation in critically ill patients must effectively unload inspiratory muscles and provide safe ventilation (ie, enhancing gas exchange, protect the lungs and the diaphragm). To do that, the ventilator should be in synchrony with patient's respiratory rhythm. The complexity of such interplay leads to several concerning issues that clinicians should be able to recognize. Asynchrony between the patient and the ventilator may induce several deleterious effects that require a proper physiological understanding to recognize and manage them. Different tools have been developed and proposed beyond the careful analysis of the ventilator waveforms to help clinicians in the decision-making process. Moreover, appropriate handling of asynchrony requires clinical skills, physiological knowledge, and suitable medication management. New technologies and devices are changing our daily practice, from automated real-time recognition of asynchronies and their distribution during mechanical ventilation, to smart alarms and artificial intelligence algorithms based on physiological big data and personalized medicine. Our goal as clinicians is to provide care of patients based on the most accurate and current knowledge, and to incorporate new technological methods to facilitate and improve the care of the critically ill.

Comparison of direct and indirect models of early induced acute lung injury

Background

The animal experimental counterpart of human acute respiratory distress syndrome (ARDS) is acute lung injury (ALI). Most models of ALI involve reproducing the clinical risk factors associated with human ARDS, such as sepsis or acid aspiration; however, none of these models fully replicates human ARDS.

Aim

To compare different experimental animal models of ALI, based on direct or indirect mechanisms of lung injury, to characterize a model which more closely could reproduce the acute phase of human ARDS.

Materials and methods

Adult male Sprague-Dawley rats were subjected to intratracheal instillations of (1) HCl to mimic aspiration of gastric contents; (2) lipopolysaccharide (LPS) to mimic bacterial infection; (3) HCl followed by LPS to mimic aspiration of gastric contents with bacterial superinfection; or (4) cecal ligation and puncture (CLP) to induce peritonitis and mimic sepsis. Rats were sacrificed 24 h after instillations or 24 h after CLP.

Results

At 24 h, rats instilled with LPS or HCl-LPS had increased lung permeability, alveolar neutrophilic recruitment and inflammatory markers (GRO/KC, TNF-α, MCP-1, IL-1β, IL-6). Rats receiving only HCl or subjected to CLP had no evidence of lung injury.

Conclusions

Rat models of ALI induced directly by LPS or HCl-LPS more closely reproduced the acute phase of human ARDS than the CLP model of indirectly induced ALI.

Pretreatment with adalimumab reduces ventilator-induced lung injury in an experimental model

Objective

To determine whether adalimumab administration before mechanical ventilation reduces ventilator-induced lung injury (VILI).

Methods

Eighteen rats randomized into 3 groups underwent mechanical ventilation for 3 hours with a fraction of inspired oxygen = 0.40% including a low tidal volume group (n = 6), where tidal volume = 8mL/kg and positive end-expiratory pressure = 5cmH2O; a high tidal volume group (n = 6), where tidal volume = 35mL/kg and positive end-expiratory pressure = 0; and a pretreated + high tidal volume group (n = 6) where adalimumab (100ug/kg) was administered intraperitoneally 24 hours before mechanical ventilation + tidal volume = 35mL/kg and positive end-expiratory pressure = 0. ANOVA was used to compare histological damage (ATS 2010 Lung Injury Scoring System), pulmonary edema, lung compliance, arterial partial pressure of oxygen, and mean arterial pressure among the groups.

Results

After 3 hours of ventilation, the mean histological lung injury score was higher in the high tidal volume group than in the low tidal volume group (0.030 versus 0.0051, respectively, p = 0.003). The high tidal volume group showed diminished lung compliance at 3 hours (p = 0.04) and hypoxemia (p = 0,018 versus control). Pretreated HVt group had an improved histological score, mainly due to a significant reduction in leukocyte infiltration (p = 0.003).

Conclusion

Histological examination after 3 hours of injurious ventilation revealed ventilator-induced lung injury in the absence of measurable changes in lung mechanics or oxygenation; administering adalimumab before mechanical ventilation reduced lung edema and histological damage.

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.

EPISYNC study: predictors of patient-ventilator asynchrony in a prospective cohort of patients under invasive mechanical ventilation - study protocol

INTRODUCTION

Patient-ventilator asynchrony is common during the entire period of invasive mechanical ventilation (MV) and is associated with worse clinical outcomes. However, risk factors associated with asynchrony are not completely understood. The main objectives of this study are to estimate the incidence of asynchrony during invasive MV and its association with respiratory mechanics and other baseline patient characteristics.

METHODS AND ANALYSIS

We designed a prospective cohort study of patients admitted to the intensive care unit (ICU) of a university hospital. Inclusion criteria are adult patients under invasive MV initiated for less than 72 hours, and with expectation of remaining under MV for more than 24 hours. Exclusion criteria are high flow bronchopleural fistula, inability to measure respiratory mechanics and previous tracheostomy. Baseline assessment includes clinical characteristics of patients at ICU admission, including severity of illness, reason for initiation of MV, and measurement of static mechanics of the respiratory system. We will capture ventilator waveforms during the entire MV period that will be analysed with dedicated software (Better Care, Barcelona, Spain), which automatically identifies several types of asynchrony and calculates the asynchrony index (AI). We will use a linear regression model to identify risk factors associated with AI. To assess the relationship between survival and AI we will use Kaplan-Meier curves, log rank tests and Cox regression. The calculated sample size is 103 patients. The statistical analysis will be performed by the software R Programming (www.R-project.org) and will be considered statistically significant if the p value is less than 0.05.

ETHICS AND DISSEMINATION

The study was approved by the Ethics Committee of Instituto do Coração, School of Medicine, University of São Paulo, Brazil, and informed consent was waived due to the observational nature of the study. We aim to disseminate the study findings through peer-reviewed publications and national and international conference presentations.

TRIAL REGISTRATION NUMBER

NCT02687802; Pre-results.

Predicting Patient-ventilator Asynchronies with Hidden Markov Models

In mechanical ventilation, it is paramount to ensure the patient's ventilatory demand is met while minimizing asynchronies. We aimed to develop a model to predict the likelihood of asynchronies occurring. We analyzed 10,409,357 breaths from 51 critically ill patients who underwent mechanical ventilation >24 h. Patients were continuously monitored and common asynchronies were identified and regularly indexed. Based on discrete time-series data representing the total count of asynchronies, we defined four states or levels of risk of asynchronies, z1 (very-low-risk) - z4 (very-high-risk). A Poisson hidden Markov model was used to predict the probability of each level of risk occurring in the next period. Long periods with very few asynchronous events, and consequently very-low-risk, were more likely than periods with many events (state z4). States were persistent; large shifts of states were uncommon and most switches were to neighbouring states. Thus, patients entering states with a high number of asynchronies were very likely to continue in that state, which may have serious implications. This novel approach to dealing with patient-ventilator asynchrony is a first step in developing smart alarms to alert professionals to patients entering high-risk states so they can consider actions to improve patient-ventilator interaction.

Dead space in acute respiratory distress syndrome

Dead space is the portion of each tidal volume that does not take part in gas exchange and represents a good global index of the efficiency of the lung function. Dead space is not routinely measured in critical care practice, because the difficulties in in interpreting capnograms and the different methods of calculations. Different dead space indices can provide useful information in acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) patients, where changes in microvasculature are the main determinants for the increase in dead space and consequently a worsening of the outcome. Lung recruitment is a dynamic process that combines recruitment manoeuvres (RMs) with positive end expiratory pressure (PEEP) and low Vt to recruit collapsed alveoli. Dead space guided recruitment allows avoiding regional overdistension or reduction in cardiac output in critical care patients with ALI or ARDS. Different patterns of ventilation affect also CO₂ elimination; in fact, end-inspiratory pause prolongation reduces dead space, increasing respiratory system compliance; plateau pressure and consequently driving pressure increase accordingly. Dead space measurement is a reliable method that provides important clinical and prognostic information. Different capnographic indices can be useful to evaluate therapeutic interventions or setting mechanical ventilation.

Validation of the ICU-DaMa tool for automatically extracting variables for minimum dataset and quality indicators: The importance of data quality assessment

BACKGROUND

Big data analytics promise insights into healthcare processes and management, improving outcomes while reducing costs. However, data quality is a major challenge for reliable results. Business process discovery techniques and an associated data model were used to develop data management tool, ICU-DaMa, for extracting variables essential for overseeing the quality of care in the intensive care unit (ICU).

OBJECTIVE

To determine the feasibility of using ICU-DaMa to automatically extract variables for the minimum dataset and ICU quality indicators from the clinical information system (CIS).

METHODS

The Wilcoxon signed-rank test and Fisher's exact test were used to compare the values extracted from the CIS with ICU-DaMa for 25 variables from all patients attended in a polyvalent ICU during a two-month period against the gold standard of values manually extracted by two trained physicians. Discrepancies with the gold standard were classified into plausibility, conformance, and completeness errors.

RESULTS

Data from 149 patients were included. Although there were no significant differences between the automatic method and the manual method, we detected differences in values for five variables, including one plausibility error and two conformance and completeness errors. Plausibility: 1) Sex, ICU-DaMa incorrectly classified one male patient as female (error generated by the Hospital's Admissions Department). Conformance: 2) Reason for isolation, ICU-DaMa failed to detect a human error in which a professional misclassified a patient's isolation. 3) Brain death, ICU-DaMa failed to detect another human error in which a professional likely entered two mutually exclusive values related to the death of the patient (brain death and controlled donation after circulatory death). Completeness: 4) Destination at ICU discharge, ICU-DaMa incorrectly classified two patients due to a professional failing to fill out the patient discharge form when thepatients died. 5) Length of continuous renal replacement therapy, data were missing for one patient because the CRRT device was not connected to the CIS.

CONCLUSIONS

Automatic generation of minimum dataset and ICU quality indicators using ICU-DaMa is feasible. The discrepancies were identified and can be corrected by improving CIS ergonomics, training healthcare professionals in the culture of the quality of information, and using tools for detecting and correcting data errors.

Nebulized Heparin Attenuates Pulmonary Coagulopathy and Inflammation through Alveolar Macrophages in a Rat Model of Acute Lung Injury

Objective  Alveolar macrophages play a key role in the development and resolution of acute respiratory distress syndrome (ARDS), modulating the inflammatory response and the coagulation cascade in lungs. Anti-coagulants may be helpful in the treatment of ARDS. This study investigated the effects of nebulized heparin on the role of alveolar macrophages in limiting lung coagulation and inflammatory response in an animal model of acute lung injury (ALI).

Methods  Rats were randomized to four experimental groups. In three groups, ALI was induced by intratracheal instillation of lipopolysaccharide (LPS) and heparin was nebulized at constant oxygen flow: the LPS/Hep group received nebulized heparin 4 and 8 hours after injury; the Hep/LPS/Hep group received nebulized heparin 30 minutes before and 4 and 8 hours after LPS-induced injury; the LPS/Sal group received nebulized saline 4 and 8 hours after injury. The control group received only saline. Animals were exsanguinated 24 hours after LPS instillation. Lung tissue, bronchoalveolar lavage fluid (BALF) and alveolar macrophages isolated from BALF were analysed.

Results  LPS increased protein concentration, oedema and neutrophils in BALF as well as procoagulant and proinflammatory mediators in lung tissue and alveolar macrophages. In lung tissue, nebulized heparin attenuated ALI through decreasing procoagulant (tissue factor, thrombin–anti-thrombin complexes, fibrin degradation products) and proinflammatory (interleukin 6, tumour necrosis factor alpha) pathways. In alveolar macrophages, nebulized heparin reduced expression of procoagulant genes and the effectors of transforming growth factor beta (Smad 2, Smad 3) and nuclear factor kappa B (p-selectin, CCL-2). Pre-treatment resulted in more pronounced attenuation.

Conclusion  Nebulized heparin reduced pulmonary coagulopathy and inflammation without producing systemic bleeding, partly by modulating alveolar macrophages.

Do sedation and analgesia contribute to long-term cognitive dysfunction in critical care survivors?

Deep sedation during stay in the Intensive Care Unit (ICU) may have deleterious effects upon the clinical and cognitive outcomes of critically ill patients undergoing mechanical ventilation. Over the last decade a vast body of literature has been generated regarding different sedation strategies, with the aim of reducing the levels of sedation in critically ill patients. There has also been a growing interest in acute brain dysfunction, or delirium, in the ICU. However, the effect of sedation during ICU stay upon long-term cognitive deficits in ICU survivors remains unclear. Strategies for reducing sedation levels in the ICU do not seem to be associated with worse cognitive and psychological status among ICU survivors. Sedation strategy and management efforts therefore should seek to secure the best possible state in the mechanically ventilated patient and lower the prevalence of delirium, in order to prevent long-term cognitive alterations.

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.

The intensive care medicine research agenda for airways, invasive and noninvasive mechanical ventilation

In an important sense, support of the respiratory system has been a defining characteristic of intensive care since its inception. The pace of basic and clinical research in this field has escalated over the past two decades, resulting in palpable improvement at the bedside as measured by both efficacy and outcome. As in all medical research, however, novel ideas built upon observations are continually proposed, tested, and either retained or discarded on the basis of the persuasiveness of the evidence. What follows are concise descriptions of the current standards of management practice in respiratory support, the areas of present-day uncertainty, and our suggested agenda for the near future of research aimed at testing current assumptions, probing uncertainties, and solidifying the foundation on which to base our progress to the next level.

A new experimental model of acid- and endotoxin-induced acute lung injury in rats

The majority of the animal models of acute lung injury (ALI) are focused on the acute phase. This limits the studies of the mechanisms involved in later phases and the effects of long-term treatments. Thus the goal of this study was to develop an experimental ALI model of aspiration pneumonia, in which diffuse alveolar damage continues for 72 h. Rats were intratracheally instilled with one dose of HCl (0.1 mol/l) followed by another instillation of one dose of LPS (0, 10, 20, 30, or 40 μg/g body weight) 2 h later, which models aspiration of gastric contents that progresses to secondary lung injury from bacteria or bacterial products. The rats were euthanized at 24, 48, and 72 h after the last instillation. The results showed that HCl and LPS at all doses caused activation of inflammatory responses, increased protein permeability and apoptosis, and induced mild hypoxemia in rat lungs at 24 h postinstillation. However, this lung damage was present at 72 h only in rats receiving HCl and LPS at the doses of 30 and 40 μg/g body wt. Mortality (∼50%) occurred in the first 48 h and only in the rats treated with HCl and LPS at the highest dose (40 μg/g body wt). In conclusion, intratracheal instillation of HCl followed by LPS at the dose of 30 μg/g body wt results in severe diffuse alveolar damage that continues at least 72 h. This rat model of aspiration pneumonia-induced ALI will be useful for testing long-term effects of new therapeutic strategies in ALI.

Brain injury requires lung protection

The paper entitled "The high-mobility group protein B1-Receptor for advanced glycation endproducts (HMGB1-RAGE) axis mediates traumatic brain injury (TBI)-induced pulmonary dysfunction in lung transplantation" published recently in Science Translational Medicine links lung failure after transplantation with alterations in the axis HMGB1-RAGE after TBI, opening a new field for exploring indicators for the early detection of patients at risk of developing acute lung injury (ALI). The lung is one of the organs most vulnerable to the inflammatory cascade triggered by TBI. HMGB1 is an alarm in that can be released from activated immune cells in response to tissue injury. Increased systemic HMGB1 concentration correlates with poor lung function before and after lung transplant, confirming its role in acute ALI after TBI. HMGB1 exerts its influence by interacting with several receptors, including the RAGE receptor. RAGE also plays an important role in the onset of innate immune inflammatory responses, and systemic levels of RAGE are strongly associated with ALI and clinical outcomes in ventilator-induced lung injury. RAGE ligation to HMGB1 triggers the amplification of the inflammatory cascade involving nuclear factor-κB (NF-κB) activation. Identifying early biomarkers that mediate pulmonary dysfunction will improve outcomes not only in lung transplantation, but also in other scenarios. These novel findings show that upregulation of the HMGB1-RAGE axis plays an important role in brain-lung crosstalk.

Assessment of PaO₂/FiO₂ for stratification of patients with moderate and severe acute respiratory distress syndrome

OBJECTIVES

A recent update of the definition of acute respiratory distress syndrome (ARDS) proposed an empirical classification based on ratio of arterial partial pressure of oxygen to fraction of inspired oxygen (PaO₂/FiO₂) at ARDS onset. Since the proposal did not mandate PaO₂/FiO₂ calculation under standardised ventilator settings (SVS), we hypothesised that a stratification based on baseline PaO₂/FiOv would not provide accurate assessment of lung injury severity.

DESIGN

A prospective, multicentre, observational study.

SETTING

A network of teaching hospitals.

PARTICIPANTS

478 patients with eligible criteria for moderate (100<PaO₂/FiO₂≤200) and severe (PaO₂/FiO₂≤100) ARDS and followed until hospital discharge.

INTERVENTIONS

We examined physiological and ventilator parameters in association with the PaO₂/FiO₂ at ARDS onset, after 24 h of usual care and at 24 h under a SVS. At 24 h, patients were reclassified as severe, moderate, mild (200<PaO₂/FiO₂≤300) ARDS and non-ARDS (PaO₂/FiO₂>300).

PRIMARY AND SECONDARY OUTCOMES

Group severity and hospital mortality.

RESULTS

At ARDS onset, 173 patients had a PaO₂/FiO₂≤100 but only 38.7% met criteria for severe ARDS at 24 h under SVS. When assessed under SVS, 61.3% of patients with severe ARDS were reclassified as moderate, mild and non-ARDS, while lung severity and hospital mortality changed markedly with every PaO₂/FiO₂ category (p<0.000001). Our model of risk stratification outperformed the stratification using baseline PaO₂/FiO₂ and non-standardised PaO₂/FiO₂ at 24 h, when analysed by the predictive receiver operating characteristic (ROC) curve: area under the ROC curve for stratification at baseline was 0.583 (95% CI 0.525 to 0.636), 0.605 (95% CI 0.552 to 0.658) at 24 h without SVS and 0.693 (95% CI 0.645 to 0.742) at 24 h under SVS (p<0.000001).

CONCLUSIONS

Our findings support the need for patient assessment under SVS at 24 h after ARDS onset to assess disease severity, and have implications for the diagnosis and management of ARDS patients.

TRIAL REGISTRATION NUMBERS

NCT00435110 and NCT00736892.

Innovation and technology transfer in the health sciences: a cross-sectional perspective

This article is based on the strategic reflection and discussion that took place on occasion of the first conference on innovation and technology transfer in the health sciences organized by the REGIC-ENS-FENIN-SEMICYUC and held in Madrid in the Instituto de Salud Carlos III on May 7th, 2013, with the aim of promoting the transfer of technological innovation in medicine and health care beyond the European program "Horizon 2020". The presentations dealt with key issues such as evaluation of the use of new technologies, the need to impregnate the decisions related to adoption and innovation with the concepts of value and sustainability, and the implication of knowledge networks in the need to strengthen their influence upon the creation of a "culture of innovation" among health professionals. But above all, emphasis was placed on the latent innovation potential of hospitals, and the fact that these, being the large companies that they are, should seriously consider that much of their future sustainability may depend on proper management of their ability to generate innovation, which is not only the generation of ideas but also their transformation into products or processes that create value and economic returns.

Patient-ventilator dyssynchrony during assisted invasive mechanical ventilation

Patient-ventilator dyssynchrony is common during mechanical ventilation. Dyssynchrony decreases comfort, prolongs mechanical ventilation and intensive care unit stays, and might lead to worse outcome. Dyssynchrony can occur during the triggering of the ventilator, the inspiration period after triggering, the transition from inspiration to expiration, and the expiratory phase. The most common dyssynchronies are delayed triggering, autotriggering, ineffective inspiratory efforts (which can occur at any point in the respiratory cycle), mismatch between the patient's and ventilator's inspiratory times, and double triggering. At present, the detection of dyssynchronies usually depends on healthcare staff observing ventilator waveforms; however, performance is suboptimal and many events go undetected. To date, technological complexity has made it impossible to evaluate patient-ventilator synchrony throughout the course of mechanical ventilation. Studies have shown that a high index of dyssynchrony may increase the duration of mechanical ventilation. Better training, better ventilatory modes, and/or computerized systems that permit better synchronization of patients' demands and ventilator outputs are necessary to improve patient-ventilator synchrony.