Precision Medicine and Heterogeneity of Treatment Effect in Therapies for Acute Respiratory Distress Syndrome

Heterogeneity, Bayesian thinking, and phenotyping in critical care: A primer

PURPOSE

To familiarize clinicians with the emerging concepts in critical care research of Bayesian thinking and personalized medicine through phenotyping and explain their clinical relevance by highlighting how they address the issues of frequent negative trials and heterogeneity of treatment effect.

SUMMARY

The past decades have seen many negative (effect-neutral) critical care trials of promising interventions, culminating in calls to improve the field's research through adopting Bayesian thinking and increasing personalization of critical care medicine through phenotyping. Bayesian analyses add interpretive power for clinicians as they summarize treatment effects based on probabilities of benefit or harm, contrasting with conventional frequentist statistics that either affirm or reject a null hypothesis. Critical care trials are beginning to include prospective Bayesian analyses, and many trials have undergone reanalysis with Bayesian methods. Phenotyping seeks to identify treatable traits to target interventions to patients expected to derive benefit. Phenotyping and subphenotyping have gained prominence in the most syndromic and heterogenous critical care disease states, acute respiratory distress syndrome and sepsis. Grouping of patients has been informative across a spectrum of clinically observable physiological parameters, biomarkers, and genomic data. Bayesian thinking and phenotyping are emerging as elements of adaptive clinical trials and predictive enrichment, paving the way for a new era of high-quality evidence. These concepts share a common goal, sifting through the noise of heterogeneity in critical care to increase the value of existing and future research.

CONCLUSION

The future of critical care medicine will inevitably involve modification of statistical methods through Bayesian analyses and targeted therapeutics via phenotyping. Clinicians must be familiar with these systems that support recommendations to improve decision-making in the gray areas of critical care practice.

Diagnostic accuracy of lung ultrasound in diagnosis of ARDS and identification of focal or non-focal ARDS subphenotypes: a systematic review and meta-analysis

BACKGROUND

Acute respiratory distress syndrome (ARDS) is a life-threatening respiratory condition with high mortality rates, accounting for 10% of all intensive care unit admissions. Lung ultrasound (LUS) as diagnostic tool for acute respiratory failure has garnered widespread recognition and was recently incorporated into the updated definitions of ARDS. This raised the hypothesis that LUS is a reliable method for diagnosing ARDS.

OBJECTIVES

We aimed to establish the accuracy of LUS for ARDS diagnosis and classification of focal versus non-focal ARDS subphenotypes.

METHODS

This systematic review and meta-analysis used a systematic search strategy, which was applied to PubMed, EMBASE and cochrane databases. Studies investigating the diagnostic accuracy of LUS compared to thoracic CT or chest radiography (CXR) in ARDS diagnosis or focal versus non-focal subphenotypes in adult patients were included. Quality of studies was evaluated using the QUADAS-2 tool. Statistical analyses were performed using "Mada" in Rstudio, version 4.0.3. Sensitivity and specificity with 95% confidence interval of each separate study were summarized in a Forest plot.

RESULTS

The search resulted in 2648 unique records. After selection, 11 reports were included, involving 2075 patients and 598 ARDS cases (29%). Nine studies reported on ARDS diagnosis and two reported on focal versus non-focal ARDS subphenotypes classification. Meta-analysis showed a pooled sensitivity of 0.631 (95% CI 0.450-0.782) and pooled specificity of 0.942 (95% CI 0.856-0.978) of LUS for ARDS diagnosis. In two studies, LUS could accurately differentiate between focal versus non-focal ARDS subphenotypes. Insufficient data was available to perform a meta-analysis.

CONCLUSION

This review confirms the hypothesis that LUS is a reliable method for diagnosing ARDS in adult patients. For the classification of focal or non-focal subphenotypes, LUS showed promising results, but more research is needed.

Association between sub-phenotypes identified using latent class analysis and neurological outcomes in patients with out-of-hospital cardiac arrest in Japan

BACKGROUND

In patients who experience out-of-hospital cardiac arrest (OHCA), it is important to assess the association of sub-phenotypes identified by latent class analysis (LCA) using pre-hospital prognostic factors and factors measurable immediately after hospital arrival with neurological outcomes at 30 days, which would aid in making treatment decisions.

METHODS

This study retrospectively analyzed data obtained from the Japanese OHCA registry between June 2014 and December 2019. The registry included a complete set of data on adult patients with OHCA, which was used in the LCA. The association between the sub-phenotypes and 30-day survival with favorable neurological outcomes was investigated. Furthermore, adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were estimated by multivariate logistic regression analysis using in-hospital data as covariates.

RESULTS

A total of, 22,261 adult patients who experienced OHCA were classified into three sub-phenotypes. The factor with the highest discriminative power upon patient's arrival was Glasgow Coma Scale followed by partial pressure of oxygen. Thirty-day survival with favorable neurological outcome as the primary outcome was evident in 66.0% participants in Group 1, 5.2% in Group 2, and 0.5% in Group 3. The 30-day survival rates were 80.6%, 11.8%, and 1.3% in groups 1, 2, and 3, respectively. Logistic regression analysis revealed that the ORs (95% CI) for 30-day survival with favorable neurological outcomes were 137.1 (99.4-192.2) for Group 1 and 4.59 (3.46-6.23) for Group 2 in comparison to Group 3. For 30-day survival, the ORs (95%CI) were 161.7 (124.2-212.1) for Group 1 and 5.78 (4.78-7.04) for Group 2, compared to Group 3.

CONCLUSIONS

This study identified three sub-phenotypes based on the prognostic factors available immediately after hospital arrival that could predict neurological outcomes and be useful in determining the treatment strategy of patients experiencing OHCA upon their arrival at the hospital.

Assessing the potential for precision medicine in body weight reduction with regard to type 2 diabetes mellitus therapies: A meta-regression analysis of 120 randomized controlled trials

AIMS

To assess the potential for precision medicine in type 2 diabetes by quantifying the variability of body weight as response to pharmacological treatment and to identify predictors which could explain this variability.

METHODS

We used randomized clinical trials (RCTs) comparing glucose-lowering drugs (including but not limited to sodium-glucose cotransporter-2 inhibitors, glucagon-like peptide-1 receptor agonists and thiazolidinediones) to placebo from four recent systematic reviews. RCTs reporting on body weight after treatment to allow for calculation of its logarithmic standard deviation (log[SD], i.e., treatment response heterogeneity) in verum (i.e., treatment) and placebo groups were included. Meta-regression analyses were performed with respect to variability of body weight after treatment and potential predictors.

RESULTS

A total of 120 RCTs with a total of 43 663 participants were analysed. A slightly larger treatment response heterogeneity was shown in the verum groups, with a median log(SD) of 2.83 compared to 2.79 from placebo. After full adjustment in the meta-regression model, the difference in body weight log(SD) was -0.026 (95% confidence interval -0.044; 0.008), with greater variability in the placebo groups. Scatterplots did not show any slope divergence (i.e., interaction) between clinical predictors and the respective treatment (verum or placebo).

CONCLUSIONS

We found no major treatment response heterogeneity in RCTs of glucose-lowering drugs for body weight reduction in type 2 diabetes. The precision medicine approach may thus be of limited value in this setting.

Heterogeneity of immune cells and their communications unveiled by transcriptome profiling in acute inflammatory lung injury

Background

Acute Respiratory Distress Syndrome (ARDS) or its earlier stage Acute lung injury (ALI), is a worldwide health concern that jeopardizes human well-being. Currently, the treatment strategies to mitigate the incidence and mortality of ARDS are severely restricted. This limitation can be attributed, at least in part, to the substantial variations in immunity observed in individuals with this syndrome.

Methods

Bulk and single cell RNA sequencing from ALI mice and single cell RNA sequencing from ARDS patients were analyzed. We utilized the Seurat program package in R and cellmarker 2.0 to cluster and annotate the data. The differential, enrichment, protein interaction, and cell-cell communication analysis were conducted.

Results

The mice with ALI caused by pulmonary and extrapulmonary factors demonstrated differential expression including Clec4e, Retnlg, S100a9, Coro1a, and Lars2. We have determined that inflammatory factors have a greater significance in extrapulmonary ALI, while multiple pathways collaborate in the development of pulmonary ALI. Clustering analysis revealed significant heterogeneity in the relative abundance of immune cells in different ALI models. The autocrine action of neutrophils plays a crucial role in pulmonary ALI. Additionally, there was a significant increase in signaling intensity between B cells and M1 macrophages, NKT cells and M1 macrophages in extrapulmonary ALI. The CXCL, CSF3 and MIF, TGFβ signaling pathways play a vital role in pulmonary and extrapulmonary ALI, respectively. Moreover, the analysis of human single-cell revealed DCs signaling to monocytes and neutrophils in COVID-19-associated ARDS is stronger compared to sepsis-related ARDS. In sepsis-related ARDS, CD8+ T and Th cells exhibit more prominent signaling to B-cell nucleated DCs. Meanwhile, both MIF and CXCL signaling pathways are specific to sepsis-related ARDS.

Conclusion

This study has identified specific gene signatures and signaling pathways in animal models and human samples that facilitate the interaction between immune cells, which could be targeted therapeutically in ARDS patients of various etiologies.

Consensus statements on the utility of defining ARDS and the utility of past and current definitions of ARDS-protocol for a Delphi study

INTRODUCTION

Acute respiratory distress syndrome (ARDS), marked by acute hypoxemia and bilateral pulmonary infiltrates, has been defined in multiple ways since its first description. This Delphi study aims to collect global opinions on the conceptual framework of ARDS, assess the usefulness of components within current and past definitions and investigate the role of subphenotyping. The varied expertise of the panel will provide valuable insights for refining future ARDS definitions and improving clinical management.

METHODS

A diverse panel of 35-40 experts will be selected based on predefined criteria. Multiple choice questions (MCQs) or 7-point Likert-scale statements will be used in the iterative Delphi rounds to achieve consensus on key aspects related to the utility of definitions and subphenotyping. The Delphi rounds will be continued until a stable agreement or disagreement is achieved for all statements.

ANALYSIS

Consensus will be considered as reached when a choice in MCQs or Likert-scale statement achieved ≥80% of votes for agreement or disagreement. The stability will be checked by non-parametric χ2 tests or Kruskal Wallis test starting from the second round of Delphi process. A p-value ≥0.05 will be used to define stability.

ETHICS AND DISSEMINATION

The study will be conducted in full concordance with the principles of the Declaration of Helsinki and will be reported according to CREDES guidance. This study has been granted an ethical approval waiver by the NMC Healthcare Regional Research Ethics Committee, Dubai (NMCHC/CR/DXB/REC/APP/002), owing to the nature of the research. Informed consent will be obtained from all panellists before the start of the Delphi process. The study will be published in a peer-review journal with the authorship agreed as per ICMJE requirements.

TRIAL REGISTRATION NUMBER

NCT06159465.

The Relationship Between Metabolic Syndrome and Mortality Among Patients With Acute Respiratory Distress Syndrome in Acute Respiratory Distress Syndrome Network and Prevention and Early Treatment of Acute Lung Injury Network Trials

OBJECTIVES

Metabolic syndrome is known to predict outcomes in COVID-19 acute respiratory distress syndrome (ARDS) but has never been studied in non-COVID-19 ARDS. We therefore aimed to determine the association of metabolic syndrome with mortality among ARDS trial subjects.

DESIGN

Retrospective cohort study of ARDS trials' data.

SETTING

An ancillary analysis was conducted using data from seven ARDS Network and Prevention and Early Treatment of Acute Lung Injury Network randomized trials within the Biologic Specimen and Data Repository Information Coordinating Center database.

PATIENTS

Hospitalized patients with ARDS and metabolic syndrome (defined by obesity, diabetes, and hypertension) were compared with similar patients without metabolic syndrome (those with less than three criteria).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The primary outcome was 28-day mortality. Among 4288 ARDS trial participants, 454 (10.6%) with metabolic syndrome were compared with 3834 controls (89.4%). In adjusted analyses, the metabolic syndrome group was associated with lower 28-day and 90-day mortality when compared with control (adjusted odds ratio [aOR], 0.70 [95% CI, 0.55-0.89] and 0.75 [95% CI, 0.60-0.95], respectively). With each additional metabolic criterion from 0 to 3, adjusted 28-day mortality was reduced by 18%, 22%, and 40%, respectively. In subgroup analyses stratifying by ARDS etiology, mortality was lower for metabolic syndrome vs. control in ARDS caused by sepsis or pneumonia (at 28 d, aOR 0.64 [95% CI, 0.48-0.84] and 90 d, aOR 0.69 [95% CI, 0.53-0.89]), but not in ARDS from noninfectious causes (at 28 d, aOR 1.18 [95% CI, 0.70-1.99] and 90 d, aOR 1.26 [95% CI, 0.77-2.06]). Interaction p = 0.04 and p = 0.02 for 28- and 90-day comparisons, respectively.

CONCLUSIONS

Metabolic syndrome in ARDS was associated with a lower risk of mortality in non-COVID-19 ARDS. The relationship between metabolic inflammation and ARDS may provide a novel biological pathway to be explored in precision medicine-based trials.

Elevated ferritin, mediated by IL-18 is associated with systemic inflammation and mortality in acute respiratory distress syndrome (ARDS)

BACKGROUND

Inflammatory subphenotypes have been identified in acute respiratory distress syndrome (ARDS). Hyperferritinaemia in sepsis is associated with hyperinflammation, worse clinical outcomes, and may predict benefit with immunomodulation. Our aim was to determine if raised ferritin identified a subphenotype in patients with ARDS.

METHODS

Baseline plasma ferritin concentrations were measured in patients with ARDS from two randomised controlled trials of simvastatin (Hydroxymethylglutaryl-CoA Reductase Inhibition with Simvastatin in Acute Lung Injury to Reduce Pulmonary Dysfunction-2 (HARP-2); discovery cohort, UK) and neuromuscular blockade (ROSE; validation cohort, USA). Results were analysed using a logistic regression model with restricted cubic splines, to determine the ferritin threshold associated with 28-day mortality.

RESULTS

Ferritin was measured in 511 patients from HARP-2 (95% of patients enrolled) and 847 patients (84% of patients enrolled) from ROSE. Ferritin was consistently associated with 28-day mortality in both studies and following a meta-analysis, a log-fold increase in ferritin was associated with an OR 1.71 (95% CI 1.01 to 2.90) for 28-day mortality. Patients with ferritin >1380 ng/mL (HARP-2 28%, ROSE 24%) had a significantly higher 28-day mortality and fewer ventilator-free days in both studies. Mediation analysis, including confounders (acute physiology and chronic health evaluation-II score and ARDS aetiology) demonstrated a statistically significant contribution of interleukin (IL)-18 as an intermediate pathway between ferritin and mortality.

CONCLUSIONS

Ferritin is a clinically useful biomarker in ARDS and is associated with worse patient outcomes. These results provide support for prospective interventional trials of immunomodulatory agents targeting IL-18 in this hyperferritinaemic subgroup of patients with ARDS.

Early growth response 1/Krüppel-like factor 5 pathway inhibitor alleviates lipopolysaccharide-induced lung injury by promoting autophagy

Early transcription factors play critical roles in the development of acute lung injury/acute respiratory distress syndrome (ALI/ARDS). Early growth response 1 (EGR1) is a transcription factor essential for various biological processes, including regulation of metabolism, differentiation, and inflammation. However, its role in ALI has been poorly reported. In this study, we aimed to determine the effect of EGR1 on ALI to gain insights into the theoretical basis for further treatment of ALI. By employing concerted molecular biology techniques, we showed that EGR1 protein was upregulated in mice. EGR1 protein was upregulated in mice and human lung epithelial cells in response to lipopolysaccharide (LPS) stimulation. EGR1 knockdown promoted autophagy and reduced LPS-induced pro-inflammatory mediator production. EGR1 was preferentially bound to the GCGTGGGCG motif region and EGR1-binding peak-related genes were mainly enriched in autophagy and injury stress-related pathways. Additionally, EGR1 promoted Krüppel-like factor 5 (KLF5) transcription by binding to the KLF5 promoter region, and KLF5 knockdown significantly decreased inflammatory damage, suggesting that EGR1 promotes ALI progression by regulating KLF5 expression. Furthermore, ML264, an inhibitor of the EGR1/KLF5 pathway axis, displayed a protective role in ALI to reduce inflammation. In conclusion, our findings demonstrate the potential of EGR1 knockdown to inhibit KLF5 and promote autophagy, further reducing the inflammatory response to mitigate ALI/ARDS. The EGR1/KLF5 pathway axis may be a valuable therapeutic target for the treatment of ALI/ARDS.

Signaling pathways and potential therapeutic targets in acute respiratory distress syndrome (ARDS)

Acute respiratory distress syndrome (ARDS) is a common condition associated with critically ill patients, characterized by bilateral chest radiographical opacities with refractory hypoxemia due to noncardiogenic pulmonary edema. Despite significant advances, the mortality of ARDS remains unacceptably high, and there are still no effective targeted pharmacotherapeutic agents. With the outbreak of coronavirus disease 19 worldwide, the mortality of ARDS has increased correspondingly. Comprehending the pathophysiology and the underlying molecular mechanisms of ARDS may thus be essential to developing effective therapeutic strategies and reducing mortality. To facilitate further understanding of its pathogenesis and exploring novel therapeutics, this review provides comprehensive information of ARDS from pathophysiology to molecular mechanisms and presents targeted therapeutics. We first describe the pathogenesis and pathophysiology of ARDS that involve dysregulated inflammation, alveolar-capillary barrier dysfunction, impaired alveolar fluid clearance and oxidative stress. Next, we summarize the molecular mechanisms and signaling pathways related to the above four aspects of ARDS pathophysiology, along with the latest research progress. Finally, we discuss the emerging therapeutic strategies that show exciting promise in ARDS, including several pharmacologic therapies, microRNA-based therapies and mesenchymal stromal cell therapies, highlighting the pathophysiological basis and the influences on signal transduction pathways for their use.

Integrating Multi-Omics Data With EHR for Precision Medicine Using Advanced Artificial Intelligence

With the recent advancement of novel biomedical technologies such as high-throughput sequencing and wearable devices, multi-modal biomedical data ranging from multi-omics molecular data to real-time continuous bio-signals are generated at an unprecedented speed and scale every day. For the first time, these multi-modal biomedical data are able to make precision medicine close to a reality. However, due to data volume and the complexity, making good use of these multi-modal biomedical data requires major effort. Researchers and clinicians are actively developing artificial intelligence (AI) approaches for data-driven knowledge discovery and causal inference using a variety of biomedical data modalities. These AI-based approaches have demonstrated promising results in various biomedical and healthcare applications. In this review paper, we summarize the state-of-the-art AI models for integrating multi-omics data and electronic health records (EHRs) for precision medicine. We discuss the challenges and opportunities in integrating multi-omics data with EHRs and future directions. We hope this review can inspire future research and developing in integrating multi-omics data with EHRs for precision medicine.

An Update on Management of Adult Patients with Acute Respiratory Distress Syndrome: An Official American Thoracic Society Clinical Practice Guideline

Background: This document updates previously published Clinical Practice Guidelines for the management of patients with acute respiratory distress syndrome (ARDS), incorporating new evidence addressing the use of corticosteroids, venovenous extracorporeal membrane oxygenation, neuromuscular blocking agents, and positive end-expiratory pressure (PEEP). Methods: We summarized evidence addressing four "PICO questions" (patient, intervention, comparison, and outcome). A multidisciplinary panel with expertise in ARDS used the Grading of Recommendations, Assessment, Development, and Evaluation framework to develop clinical recommendations. Results: We suggest the use of: 1) corticosteroids for patients with ARDS (conditional recommendation, moderate certainty of evidence), 2) venovenous extracorporeal membrane oxygenation in selected patients with severe ARDS (conditional recommendation, low certainty of evidence), 3) neuromuscular blockers in patients with early severe ARDS (conditional recommendation, low certainty of evidence), and 4) higher PEEP without lung recruitment maneuvers as opposed to lower PEEP in patients with moderate to severe ARDS (conditional recommendation, low to moderate certainty), and 5) we recommend against using prolonged lung recruitment maneuvers in patients with moderate to severe ARDS (strong recommendation, moderate certainty). Conclusions: We provide updated evidence-based recommendations for the management of ARDS. Individual patient and illness characteristics should be factored into clinical decision making and implementation of these recommendations while additional evidence is generated from much-needed clinical trials.

Acute respiratory distress syndrome heterogeneity and the septic ARDS subgroup

Acute respiratory distress syndrome (ARDS) is an acute diffuse inflammatory lung injury characterized by the damage of alveolar epithelial cells and pulmonary capillary endothelial cells. It is mainly manifested by non-cardiogenic pulmonary edema, resulting from intrapulmonary and extrapulmonary risk factors. ARDS is often accompanied by immune system disturbance, both locally in the lungs and systemically. As a common heterogeneous disease in critical care medicine, researchers are often faced with the failure of clinical trials. Latent class analysis had been used to compensate for poor outcomes and found that targeted treatment after subgrouping contribute to ARDS therapy. The subphenotype of ARDS caused by sepsis has garnered attention due to its refractory nature and detrimental consequences. Sepsis stands as the most predominant extrapulmonary cause of ARDS, accounting for approximately 32% of ARDS cases. Studies indicate that sepsis-induced ARDS tends to be more severe than ARDS caused by other factors, leading to poorer prognosis and higher mortality rate. This comprehensive review delves into the immunological mechanisms of sepsis-ARDS, the heterogeneity of ARDS and existing research on targeted treatments, aiming to providing mechanism understanding and exploring ideas for accurate treatment of ARDS or sepsis-ARDS.

Intensive glucose control in critically ill adults: a protocol for a systematic review and individual patient data meta-analysis

OBJECTIVE

The optimal target for blood glucose concentration in critically ill patients is unclear. We will perform a systematic review and meta-analysis with aggregated and individual patient data from randomized controlled trials, comparing intensive glucose control with liberal glucose control in critically ill adults.

DATA SOURCES

MEDLINE®, Embase, the Cochrane Central Register of Clinical Trials, and clinical trials registries (World Health Organization, clinical trials.gov). The authors of eligible trials will be invited to provide individual patient data. Published trial-level data from eligible trials that are not at high risk of bias will be included in an aggregated data meta-analysis if individual patient data are not available.

METHODS

Inclusion criteria: randomized controlled trials that recruited adult patients, targeting a blood glucose of ≤ 120mg/dL (≤ 6.6mmol/L) compared to a higher blood glucose concentration target using intravenous insulin in both groups. Excluded studies: those with an upper limit blood glucose target in the intervention group of > 120mg/dL (> 6.6mmol/L), or where intensive glucose control was only performed in the intraoperative period, and those where loss to follow-up exceeded 10% by hospital discharge.

PRIMARY ENDPOINT

In-hospital mortality during index hospital admission. Secondary endpoints: mortality and survival at other timepoints, duration of invasive mechanical ventilation, vasoactive agents, and renal replacement therapy. A random effect Bayesian meta-analysis and hierarchical Bayesian models for individual patient data will be used.

DISCUSSION

This systematic review with aggregate and individual patient data will address the clinical question, 'what is the best blood glucose target for critically ill patients overall?'Protocol version 0.4 - 06/26/2023PROSPERO registration:CRD42021278869.

American Association for the Surgery of Trauma/American College of Surgeons Committee on Trauma clinical protocol for management of acute respiratory distress syndrome and severe hypoxemia

LEVEL OF EVIDENCE

Therapeutic/Care Management: Level V.

Leveraging Data Science and Novel Technologies to Develop and Implement Precision Medicine Strategies in Critical Care

Precision medicine aims to identify treatments that are most likely to result in favorable outcomes for subgroups of patients with similar clinical and biological characteristics. The gaps for the development and implementation of precision medicine strategies in the critical care setting are many, but the advent of data science and multi-omics approaches, combined with the rich data ecosystem in the intensive care unit, offer unprecedented opportunities to realize the promise of precision critical care. In this article, the authors review the data-driven and technology-based approaches being leveraged to discover and implement precision medicine strategies in the critical care setting.

How Electronic Medical Record Integration Can Support More Efficient Critical Care Clinical Trials

Large volumes of data are collected on critically ill patients, and using data science to extract information from the electronic medical record (EMR) and to inform the design of clinical trials represents a new opportunity in critical care research. Using improved methods of phenotyping critical illnesses, subject identification and enrollment, and targeted treatment group assignment alongside newer trial designs such as adaptive platform trials can increase efficiency while lowering costs. Some tools such as the EMR to automate data collection are already in use. Refinement of data science approaches in critical illness research will allow for better clinical trials and, ultimately, improved patient outcomes.

WNT9A Affects Late-Onset Acute Respiratory Distress Syndrome and 28-Day Survival: Evidence from a Three-Step Multiomics Study

Late-onset (more than 48 h after ICU admission) acute respiratory distress syndrome (ARDS) is associated with shorter survival time and higher mortality; however, the underlying molecular targets remain unclear. As the WNT gene family is known to drive inflammation, immunity, and tissue fibrosis, all of which are closely related to the pathogenesis and prognosis of ARDS, we aim to investigate the associations of the WNT family with late-onset ARDS and 28-day survival. Genetic (n = 380), epigenetic (n = 185), transcriptional (n = 160), and protein (n = 300) data of patients with ARDS were extracted from the MEARDS (Molecular Epidemiology of ARDS) cohort. We used sure independence screening to identify late onset-related genetic biomarkers and constructed a genetic score on the basis of eight SNPs, which was associated with risk for late-onset ARDS (odds ratio [OR], 2.72; P = 3.81 × 10-14) and survival (hazard ratio [HR], 1.28; P = 0.008). The associations were further externally validated in the iSPAAR (Identification of SNPs Predisposing to Altered Acute Lung Injury Risk) (ORlate onset, 2.49 [P = 0.006]; HRsurvival, 1.87 [P = 0.045]) and MESSI (Molecular Epidemiology of Severe Sepsis in the ICU) (ORlate onset, 4.12 [P = 0.026]; HRsurvival, 1.45 [P = 0.036]) cohorts. Furthermore, we functionally interrogated the six mapped genes of eight SNPs in the multiomics data and noted associations of WNT9A (WNT family member 9A) in epigenetic (ORlate onset, 2.95 [P = 9.91 × 10-4]; HRsurvival, 1.53 [P = 0.011]) and protein (ORlate onset, 1.42 [P = 0.035]; HRsurvival, 1.38 [P = 0.011]) data. The mediation analysis indicated that the effects of WNT9A on ARDS survival were mediated by late onset (HRindirect, 1.12 [P = 0.014] for genetic data; HRindirect, 1.05 [P = 0.030] for protein data). The essential roles of WNT9A in immunity and fibrosis may explain the different trajectories of recovery and dysfunction between early- and late-onset ARDS, providing clues for ARDS treatment.

Differential roles of regulatory T cells in acute respiratory infections

Acute respiratory infections trigger an inflammatory immune response with the goal of pathogen clearance; however, overexuberant inflammation causes tissue damage and impairs pulmonary function. CD4+FOXP3+ regulatory T cells (Tregs) interact with cells of both the innate and the adaptive immune system to limit acute pulmonary inflammation and promote its resolution. Tregs also provide tissue protection and coordinate lung tissue repair, facilitating a return to homeostatic pulmonary function. Here, we review Treg-mediated modulation of the host response to respiratory pathogens, focusing on mechanisms underlying how Tregs promote resolution of inflammation and repair of acute lung injury. We also discuss potential strategies to harness and optimize Tregs as a cellular therapy for patients with severe acute respiratory infection and discuss open questions in the field.

Cardiovascular Subphenotypes in ARDS: Diagnostic and Therapeutic Implications and Overlap with Other ARDS Subphenotypes

Acute respiratory distress syndrome (ARDS) is a highly heterogeneous clinical condition. Shock is a poor prognostic sign in ARDS, and heterogeneity in its pathophysiology may be a barrier to its effective treatment. Although right ventricular dysfunction is commonly implicated, there is no consensus definition for its diagnosis, and left ventricular function is neglected. There is a need to identify the homogenous subgroups within ARDS, that have a similar pathobiology, which can then be treated with targeted therapies. Haemodynamic clustering analyses in patients with ARDS have identified two subphenotypes of increasingly severe right ventricular injury, and a further subphenotype of hyperdynamic left ventricular function. In this review, we discuss how phenotyping the cardiovascular system in ARDS may align with haemodynamic pathophysiology, can aid in optimally defining right ventricular dysfunction and can identify tailored therapeutic targets for shock in ARDS. Additionally, clustering analyses of inflammatory, clinical and radiographic data describe other subphenotypes in ARDS. We detail the potential overlap between these and the cardiovascular phenotypes.

Pulmonary drug delivery for acute respiratory distress syndrome

The acute respiratory distress syndrome (ARDS) is a life-threatening condition that causes respiratory failure. Despite numerous clinical trials, there are no molecularly targeted pharmacologic therapies to prevent or treat ARDS. Drug delivery during ARDS is challenging due to the heterogenous nature of lung injury and occlusion of lung units by edema fluid and inflammation. Pulmonary drug delivery during ARDS offers several potential advantages including limiting the off-target and off-organ effects and directly targeting the damaged and inflamed lung regions. In this review we summarize recent ARDS clinical trials using both systemic and pulmonary drug delivery. We then discuss the advantages of pulmonary drug delivery and potential challenges to its implementation. Finally, we discuss the use of nanoparticle drug delivery and surfactant-based drug carriers as potential strategies for delivering therapeutics to the injured lung in ARDS.

Heterogeneous treatment effects analysis for social scientists: A review

Social scientists have long been interested in the varying responses to a specific intervention, motivating the enterprise of heterogeneous treatment effects (HTE) analysis. Over the past five decades, the rapid development of HTE methods, from conventional multiplicative interactions in linear models to explorations based on machine learning techniques, has been witnessed. This article presents a systematic review of major HTE methods, including multiplicative interaction modeling, generalized additive modeling, propensity-score-based methods, marginal treatment effect, separate LASSO constraints, causal trees, causal forests, Bayesian additive regression trees, and meta-learners (i.e., the S-learner, T-learner, X-learner, and R-learner). These methods, as described roughly in a chronological order to emphasize methodological developments, are addressed to highlight their respective strengths and limitations. Following an illustrative example, this article reflects on future methodological developments.

Comparison of Clinical Characteristics and Predictors of Mortality between Direct and Indirect ARDS

Background and Objectives: Acute Respiratory Distress Syndrome (ARDS) is a heterogeneous syndrome that encompasses lung injury from a direct pulmonary or indirect systemic insult. Studies have shown that direct and indirect ARDS differ in their pathophysiologic process. In this study, we aimed to compare the different clinical characteristics and predictors of 28-day mortality between direct and indirect ARDS. Materials and Methods: The data of 1291 ARDS patients from September 2012 to December 2021 at the Second Affiliated Hospital of Chongqing Medical University were reviewed. We enrolled 451 ARDS patients in our study through inclusion and exclusion criteria. According to the risk factors, each patient was divided into direct (n = 239) or indirect (n = 212) ARDS groups. The primary outcome was 28-day mortality. Results: The patients with direct ARDS were more likely to be older (p < 0.001) and male (p = 0.009) and have more comorbidity (p < 0.05) and higher 28-day mortality (p < 0.001) than those with indirect ARDS. Age and multiple organ dysfunction syndrome (MODS) were predictors of 28-day mortality in the direct ARDS group, while age, MODS, creatinine, prothrombin time (PT), and oxygenation index (OI) were independent predictors of 28-day mortality in the indirect ARDS group. Creatinine, PT, and OI have interactions with ARDS types (all p < 0.01). Conclusions: The patients with direct ARDS were more likely to be older and male and have worse conditions and prognoses than those with indirect ARDS. Creatinine, PT, and OI were predictors of 28-day mortality only in the indirect ARDS group. The differences between direct and indirect ARDS suggest the need for different management strategies of ARDS.

Acute respiratory distress syndrome after in-hospital cardiac arrest

OBJECTIVE

Acute respiratory distress syndrome (ARDS) after out-of-hospital cardiac arrest is common and associated with worse outcomes. In the hospital setting, there are many potential risk factors for post-arrest ARDS, such as aspiration, sepsis, and shock. ARDS after in-hospital cardiac arrest (IHCA) has not been characterized.

METHODS

We performed a single-center retrospective study of adult patients admitted to the hospital between 2014-2018 who suffered an IHCA, achieved return of spontaneous circulation (ROSC), and were either already intubated at the time of arrest or within 2 hours of ROSC. Post-IHCA ARDS was defined as meeting the Berlin criteria in the first 3 days following ROSC. Outcomes included alive-and-ventilator free days across 28 days, hospital length-of-stay, hospital mortality, and hospital disposition.

RESULTS

Of 203 patients included, 146 (71.9%) developed ARDS. In unadjusted analysis, patients with ARDS had fewer alive-and-ventilator-free days over 28 days with a median of 1 (IQR: 0, 21) day, compared to 18 (IQR: 0, 25) days in patients without ARDS (p = 0.03). However, this association was not significant after multivariate adjustment. There was also a non-significant longer hospital length-of-stay (15 [IQR: 7, 26] vs 10 [IQR: 7, 22] days, p = 0.25; median adjusted increase in ARDS patients: 3 [95% CI: -2 to 8] days, p = 0.27) and higher hospital mortality (53% vs 44%, p = 0.26; aOR 1.6 [95% CI: 0.8-2.9], p = 0.17) in the ARDS group.

CONCLUSION

Among IHCA patients, almost three-quarters developed ARDS within 3 days of ROSC. As in out of hospital cardiac arrest, post-IHCA ARDS is common.

Lung Mechanics Over the Century: From Bench to Bedside and Back to Bench

Lung physiology research advanced significantly over the last 100 years. Respiratory mechanics applied to animal models of lung disease extended the knowledge of the workings of respiratory system. In human research, a better understanding of respiratory mechanics has contributed to development of mechanical ventilators. In this review, we explore the use of respiratory mechanics in basic science to investigate asthma and chronic obstructive pulmonary disease (COPD). We also discuss the use of lung mechanics in clinical care and its role on the development of modern mechanical ventilators. Additionally, we analyse some bench-developed technologies that are not in widespread use in the present but can become part of the clinical arsenal in the future. Finally, we explore some of the difficult questions that intensive care doctors still face when managing respiratory failure. Bringing back these questions to bench can help to solve them. Interaction between basic and translational science and human subject investigation can be very rewarding, as in the conceptualization of “Lung Protective Ventilation” principles. We expect this interaction to expand further generating new treatments and managing strategies for patients with respiratory disease.