The ARDS microenvironment enhances MSC-induced repair via VEGF in experimental acute lung inflammation.

Clinical trials investigating the potential of mesenchymal stromal cells (MSCs) for the treatment of inflammatory diseases, such as acute respiratory distress syndrome (ARDS), have been disappointing, with less than 50% of patients responding to treatment. Licensed MSCs show enhanced therapeutic efficacy in response to cytokine-mediated activation signals. There are two distinct sub-phenotypes of ARDS: hypo- and hyper-inflammatory. We hypothesized that pre-licensing MSCs in a hyper-inflammatory ARDS environment would enhance their therapeutic efficacy in acute lung inflammation (ALI). Serum samples from patients with ARDS were segregated into hypo- and hyper-inflammatory categories based on interleukin (IL)-6 levels. MSCs were licensed with pooled serum from patients with hypo- or hyper-inflammatory ARDS or healthy serum controls. Our findings show that hyper-inflammatory ARDS pre-licensed MSC conditioned medium (MSC-CMHyper) led to a significant enrichment in tight junction expression and enhanced barrier integrity in lung epithelial cells in vitro and in vivo in a vascular endothelial growth factor (VEGF)-dependent manner. Importantly, while both MSC-CMHypo and MSC-CMHyper significantly reduced IL-6 and tumor necrosis factor alpha (TNF-α) levels in the bronchoalveolar lavage fluid (BALF) of lipopolysaccharide (LPS)-induced ALI mice, only MSC-CMHyper significantly reduced lung permeability and overall clinical outcomes including weight loss and clinical score. Thus, the hypo- and hyper-inflammatory ARDS environments may differentially influence MSC cytoprotective and immunomodulatory functions.

Cell-based Therapies for Acute Respiratory Distress Syndrome: Where Are We Now?

There is considerable interest in the potential for cell-based therapies, particularly mesenchymal stromal cells (MSCs) and their products, as a therapy for acute respiratory distress syndrome (ARDS). MSCs exert effects via diverse mechanisms including reducing excessive inflammation by modulating neutrophil, macrophage and T-cell function, decreasing pulmonary permeability and lung edema, and promoting tissue repair. Clinical studies indicate that MSCs are safe and well tolerated, with promising therapeutic benefits in specific clinical settings, leading to regulatory approvals of MSCs for specific indications in some countries.This perspective reassesses the therapeutic potential of MSC-based therapies for ARDS given insights from recent cell therapy trials in both COVID-19 and in 'classic' ARDS, and discusses studies in graft-vs.-host disease, one of the few licensed indications for MSC therapies. We identify important unknowns in the current literature, address challenges to clinical translation, and propose an approach to facilitate assessment of the therapeutic promise of MSC-based therapies for ARDS.

Digital Twins of Acute Hypoxemic Respiratory Failure Patients Suggest a Mechanistic Basis for Success and Failure of Noninvasive Ventilation.

OBJECTIVES: To clarify the mechanistic basis for the success or failure of noninvasive ventilation (NIV) in acute hypoxemic respiratory failure (AHRF). DESIGN: We created digital twins based on mechanistic computational models of individual patients with AHRF. SETTING: Interdisciplinary Collaboration in Systems Medicine Research Network. SUBJECTS: We used individual patient data from 30 moderate-to-severe AHRF patients who had failed high-flow nasal cannula (HFNC) therapy and subsequently underwent a trial of NIV. INTERVENTIONS: Using the digital twins, we evaluated lung mechanics, quantified the separate contributions of external support and patient respiratory effort to lung injury indices, and investigated their relative impact on NIV success or failure. MEASUREMENTS AND MAIN RESULTS: In digital twins of patients who successfully completed/failed NIV, after 2 hours of the trial the mean (sd) of the change in total lung stress was -10.9 (6.2)/-0.35 (3.38) cm H2O, mechanical power -13.4 (12.2)/-1.0 (5.4) J/min, and total lung strain 0.02 (0.24)/0.16 (0.30). In the digital twins, positive end-expiratory pressure (PEEP) produced by HFNC was similar to that set during NIV. In digital twins of patients who failed NIV vs. those who succeeded, intrinsic PEEP was 3.5 (0.6) vs. 2.3 (0.8) cm H2O, inspiratory pressure support was 8.3 (5.9) vs. 22.3 (7.2) cm H2O, and tidal volume was 10.9 (1.2) vs. 9.4 (1.8) mL/kg. In digital twins, successful NIV increased respiratory system compliance +25.0 (16.4) mL/cm H2O, lowered inspiratory muscle pressure -9.7 (9.6) cm H2O, and reduced the contribution of patient spontaneous breathing to total driving pressure by 57.0%. CONCLUSIONS: In digital twins of AHRF patients, successful NIV improved lung mechanics, lowering respiratory effort and indices associated with lung injury. NIV failed in patients for whom only low levels of positive inspiratory pressure support could be applied without risking patient self-inflicted lung injury due to excessive tidal volumes.

Epidemiology, ventilation management and outcomes of COVID-19 ARDS patients versus patients with ARDS due to pneumonia in the Pre-COVID era.

BACKGROUND: Ventilation management may differ between COVID-19 ARDS (COVID-ARDS) patients and patients with pre-COVID ARDS (CLASSIC-ARDS); it is uncertain whether associations of ventilation management with outcomes for CLASSIC-ARDS also exist in COVID-ARDS. METHODS: Individual patient data analysis of COVID-ARDS and CLASSIC-ARDS patients in six observational studies of ventilation, four in the COVID-19 pandemic and two pre-pandemic. Descriptive statistics were used to compare epidemiology and ventilation characteristics. The primary endpoint were key ventilation parameters; other outcomes included mortality and ventilator-free days and alive (VFD-60) at day 60. RESULTS: This analysis included 6702 COVID-ARDS patients and 1415 CLASSIC-ARDS patients. COVID-ARDS patients received lower median VT (6.6 [6.0 to 7.4] vs 7.3 [6.4 to 8.5] ml/kg PBW; p < 0.001) and higher median PEEP (12.0 [10.0 to 14.0] vs 8.0 [6.0 to 10.0] cm H2O; p < 0.001), at lower median ΔP (13.0 [10.0 to 15.0] vs 16.0 [IQR 12.0 to 20.0] cm H2O; p < 0.001) and higher median Crs (33.5 [26.6 to 42.1] vs 28.1 [21.6 to 38.4] mL/cm H2O; p < 0.001). Following multivariable adjustment, higher ΔP had an independent association with higher 60-day mortality and less VFD-60 in both groups. Higher PEEP had an association with less VFD-60, but only in COVID-ARDS patients. CONCLUSIONS: Our findings show important differences in key ventilation parameters and associations thereof with outcomes between COVID-ARDS and CLASSIC-ARDS. TRIAL REGISTRATION: Clinicaltrials.gov (identifier NCT05650957), December 14, 2022.

Phenotyping COVID-19 respiratory failure in spontaneously breathing patients with AI on lung CT-scan.

BACKGROUND: Automated analysis of lung computed tomography (CT) scans may help characterize subphenotypes of acute respiratory illness. We integrated lung CT features measured via deep learning with clinical and laboratory data in spontaneously breathing subjects to enhance the identification of COVID-19 subphenotypes. METHODS: This is a multicenter observational cohort study in spontaneously breathing patients with COVID-19 respiratory failure exposed to early lung CT within 7 days of admission. We explored lung CT images using deep learning approaches to quantitative and qualitative analyses; latent class analysis (LCA) by using clinical, laboratory and lung CT variables; regional differences between subphenotypes following 3D spatial trajectories. RESULTS: Complete datasets were available in 559 patients. LCA identified two subphenotypes (subphenotype 1 and 2). As compared with subphenotype 2 (n = 403), subphenotype 1 patients (n = 156) were older, had higher inflammatory biomarkers, and were more hypoxemic. Lungs in subphenotype 1 had a higher density gravitational gradient with a greater proportion of consolidated lungs as compared with subphenotype 2. In contrast, subphenotype 2 had a higher density submantellar-hilar gradient with a greater proportion of ground glass opacities as compared with subphenotype 1. Subphenotype 1 showed higher prevalence of comorbidities associated with endothelial dysfunction and higher 90-day mortality than subphenotype 2, even after adjustment for clinically meaningful variables. CONCLUSIONS: Integrating lung-CT data in a LCA allowed us to identify two subphenotypes of COVID-19, with different clinical trajectories. These exploratory findings suggest a role of automated imaging characterization guided by machine learning in subphenotyping patients with respiratory failure. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04395482. Registration date: 19/05/2020.

Perfusion deficits may underlie lung and kidney injury in severe COVID-19 disease: insights from a multicenter international cohort study.

BACKGROUND: Lung perfusion defects, mainly due to endothelial and coagulation activation, are a key contributor to COVID-19 respiratory failure. COVID-19 patients may also develop acute kidney injury (AKI) because of renal perfusion deficit. We aimed to explore AKI-associated factors and the independent prediction of standardized minute ventilation (MV)-a proxy of alveolar dead space-on AKI onset and persistence in COVID-19 mechanically ventilated patients. METHODS: This is a multicenter observational cohort study. We enrolled 157 COVID-19 patients requiring mechanical ventilation and intensive care unit (ICU) admission. We collected clinical information, ventilation, and laboratory data. AKI was defined by the 2012 KDIGO guidelines and classified as transient or persistent according to serum creatinine criteria persistence within 48 h. Ordered univariate and multivariate logistic regression analyses were employed to identify variables associated with AKI onset and persistence. RESULTS: Among 157 COVID-19 patients on mechanical ventilation, 47% developed AKI: 10% had transient AKI, and 37% had persistent AKI. The degree of hypoxia was not associated with differences in AKI severity. Across increasing severity of AKI groups, despite similar levels of paCO2, we observed an increased MV and standardized MV, a robust proxy of alveolar dead space. After adjusting for other clinical and laboratory covariates, standardized MV remained an independent predictor of AKI development and persistence. D-dimer levels were higher in patients with persistent AKI. CONCLUSIONS: In critically ill COVID-19 patients with respiratory failure, increased wasted ventilation is independently associated with a greater risk of persistent AKI. These hypothesis-generating findings may suggest that perfusion derangements may link the pathophysiology of both wasted ventilation and acute kidney injury in our population.

A pilot feasibility study comparing large language models in extracting key information from ICU patient text records from an Irish population.

BACKGROUND: Artificial intelligence, through improved data management and automated summarisation, has the potential to enhance intensive care unit (ICU) care. Large language models (LLMs) can interrogate and summarise large volumes of medical notes to create succinct discharge summaries. In this study, we aim to investigate the potential of LLMs to accurately and concisely synthesise ICU discharge summaries. METHODS: Anonymised clinical notes from ICU admissions were used to train and validate a prompting structure in three separate LLMs (ChatGPT, GPT-4 API and Llama 2) to generate concise clinical summaries. Summaries were adjudicated by staff intensivists on ability to identify and appropriately order a pre-defined list of important clinical events as well as readability, organisation, succinctness, and overall rank. RESULTS: In the development phase, text from five ICU episodes was used to develop a series of prompts to best capture clinical summaries. In the testing phase, a summary produced by each LLM from an additional six ICU episodes was utilised for evaluation. Overall ability to identify a pre-defined list of important clinical events in the summary was 41.5 ± 15.2% for GPT-4 API, 19.2 ± 20.9% for ChatGPT and 16.5 ± 14.1% for Llama2 (p = 0.002). GPT-4 API followed by ChatGPT had the highest score to appropriately order a pre-defined list of important clinical events in the summary as well as readability, organisation, succinctness, and overall rank, whilst Llama2 scored lowest for all. GPT-4 API produced minor hallucinations, which were not present in the other models. CONCLUSION: Differences exist in large language model performance in readability, organisation, succinctness, and sequencing of clinical events compared to others. All encountered issues with narrative coherence and omitted key clinical data and only moderately captured all clinically meaningful data in the correct order. However, these technologies suggest future potential for creating succinct discharge summaries.

Major trauma patients and their outcomes - A retrospective observational study of critical care trauma admissions to a trauma unit with special services.

INTRODUCTION: International data describes a changing pattern to trauma over the last decade, with an increasingly comorbid population presenting challenges to trauma management and resources. In Ireland, resource provision and management of trauma is being transformed to deliver a trauma network, in line with international best practice. Our hospital plays a crucial role within this network and is designated a Trauma Unit with Specialist Services (TUSS) to distinguish it from standard trauma units. METHODS: This study aims to describe the characteristics of patients and injuries and assess trends in mortality rates. It is a retrospective observational study of adult ICU trauma admissions from August 2010 to July 2021. Primary outcome was all-cause mortality at 30-days, 90-days, and 1 year. Secondary outcomes included length of stay, disposition, and complications. Patients were categorised by age, injury severity score (ISS), and mechanism of injury. RESULTS: In all, 709 patients were identified for final analysis. Annual admissions doubled since 2010/11, with a trough of 41 admissions, increasing to peak at 95 admissions in 2017/18. Blunt trauma accounted for 97.6% of cases. Falls <2 m (45.4%) and RTAs (29.2%) were the main mechanisms of injury. Polytrauma comprised 41.9% of admissions. Traumatic brain injury accounted for 30.2% of cases; 18.8% of these patients were transferred to a neurosurgical centre. The majority of patients, 58.1%, were severely injured (ISS ≥ 16). Patients ≥ 65 years of age accounted for 45.7% of admissions, with falls <2 m their primary mechanism of injury. The primary outcome of all-cause mortality reduced with an absolute risk reduction (ARR) of 8.0% (95% CI: -8.37%, 24.36%), 12.9% (95% CI: -4.19%, 29.94%) and 8.2% (95% CI: -9.64%, 26.09%) for 30-day, 90-day and 1-year respectively. Regression analysis demonstrated a significant reduction in mortality for 30-days and 90-days post presentation to hospital (P-values of 0.018, 0.033 and 0.152 for 30-day, 90-day and 1-year respectively). CONCLUSION: The burden of major trauma in our hospital is considerable and increasing over time. Substantial changes in demographics, injury mechanism and mortality were seen, with outcomes improving over time. This is consistent with international data where trauma systems have been adopted.

Different ventilation intensities among various categories of patients ventilated for reasons other than ARDS--A pooled analysis of 4 observational studies.

PURPOSE: We investigated driving pressure (ΔP) and mechanical power (MP) and associations with clinical outcomes in critically ill patients ventilated for reasons other than ARDS. MATERIALS AND METHODS: Individual patient data analysis of a pooled database that included patients from four observational studies of ventilation. ΔP and MP were compared among invasively ventilated non-ARDS patients with sepsis, with pneumonia, and not having sepsis or pneumonia. The primary endpoint was ΔP; secondary endpoints included MP, ICU mortality and length of stay, and duration of ventilation. RESULTS: This analysis included 372 (11%) sepsis patients, 944 (28%) pneumonia patients, and 2040 (61%) patients ventilated for any other reason. On day 1, median ΔP was higher in sepsis (14 [11-18] cmH2O) and pneumonia patients (14 [11-18]cmH2O), as compared to patients not having sepsis or pneumonia (13 [10-16] cmH2O) (P < 0.001). Median MP was also higher in sepsis and pneumonia patients. ΔP, as opposed to MP, was associated with ICU mortality in sepsis and pneumonia patients. CONCLUSIONS: The intensity of ventilation differed between patients with sepsis or pneumonia and patients receiving ventilation for any other reason; ΔP was associated with higher mortality in sepsis and pneumonia patients. REGISTRATION: This post hoc analysis was not registered; the individual studies that were merged into the used database were registered at clinicaltrials.gov: NCT01268410 (ERICC), NCT02010073 (LUNG SAFE), NCT01868321 (PRoVENT), and NCT03188770 (PRoVENT-iMiC).

Personalized mechanical ventilation guided by ultrasound in patients with acute respiratory distress syndrome (PEGASUS): study protocol for an international randomized clinical trial.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a frequent cause of hypoxemic respiratory failure with a mortality rate of approximately 30%. Identifying ARDS subphenotypes based on "focal" or "non-focal" lung morphology has the potential to better target mechanical ventilation strategies of individual patients. However, classifying morphology through chest radiography or computed tomography is either inaccurate or impractical. Lung ultrasound (LUS) is a non-invasive bedside tool that can accurately distinguish "focal" from "non-focal" lung morphology. We hypothesize that LUS-guided personalized mechanical ventilation in ARDS patients leads to a reduction in 90-day mortality compared to conventional mechanical ventilation. METHODS: The Personalized Mechanical Ventilation Guided by UltraSound in Patients with Acute Respiratory Distress Syndrome (PEGASUS) study is an investigator-initiated, international, randomized clinical trial (RCT) that plans to enroll 538 invasively ventilated adult intensive care unit (ICU) patients with moderate to severe ARDS. Eligible patients will receive a LUS exam to classify lung morphology as "focal" or "non-focal". Thereafter, patients will be randomized within 12 h after ARDS diagnosis to receive standard care or personalized ventilation where the ventilation strategy is adjusted to the morphology subphenotype, i.e., higher positive end-expiratory pressure (PEEP) and recruitment maneuvers for "non-focal" ARDS and lower PEEP and prone positioning for "focal" ARDS. The primary endpoint is all-cause mortality at day 90. Secondary outcomes are mortality at day 28, ventilator-free days at day 28, ICU length of stay, ICU mortality, hospital length of stay, hospital mortality, and number of complications (ventilator-associated pneumonia, pneumothorax, and need for rescue therapy). After a pilot phase of 80 patients, the correct interpretation of LUS images and correct application of the intervention within the safe limits of mechanical ventilation will be evaluated. DISCUSSION: PEGASUS is the first RCT that compares LUS-guided personalized mechanical ventilation with conventional ventilation in invasively ventilated patients with moderate and severe ARDS. If this study demonstrates that personalized ventilation guided by LUS can improve the outcomes of ARDS patients, it has the potential to shift the existing one-size-fits-all ventilation strategy towards a more individualized approach. TRIAL REGISTRATION: The PEGASUS trial was registered before the inclusion of the first patient, https://clinicaltrials.gov/ (ID: NCT05492344).

Tracheal intubation in critically ill adults with a physiologically difficult airway. An international Delphi study.

PURPOSE: Our study aimed to provide consensus and expert clinical practice statements related to airway management in critically ill adults with a physiologically difficult airway (PDA). METHODS: An international Steering Committee involving seven intensivists and one Delphi methodology expert was convened by the Society of Critical Care Anaesthesiologists (SOCCA) Physiologically Difficult Airway Task Force. The committee selected an international panel of 35 expert clinician-researchers with expertise in airway management in critically ill adults. A Delphi process based on an iterative approach was used to obtain the final consensus statements. RESULTS: The Delphi process included seven survey rounds. A stable consensus was achieved for 53 (87%) out of 61 statements. The experts agreed that in addition to pathophysiological conditions, physiological alterations associated with pregnancy and obesity also constitute a physiologically difficult airway. They suggested having an intubation team consisting of at least three healthcare providers including two airway operators, implementing an appropriately designed checklist, and optimizing hemodynamics prior to tracheal intubation. Similarly, the experts agreed on the head elevated laryngoscopic position, routine use of videolaryngoscopy during the first attempt, preoxygenation with non-invasive ventilation, careful mask ventilation during the apneic phase, and attention to cardiorespiratory status for post-intubation care. CONCLUSION: Using a Delphi method, agreement among a panel of international experts was reached for 53 statements providing guidance to clinicians worldwide on safe tracheal intubation practices in patients with a physiologically difficult airway to help improve patient outcomes. Well-designed studies are needed to assess the effects of these practice statements and address the remaining uncertainties.