Phenotypes in acute respiratory distress syndrome: moving towards precision medicine

Strategies to minimize heterogeneity and optimize clinical trials in Acute Respiratory Distress Syndrome (ARDS): Insights from mathematical modelling

Background

Mathematical modelling may aid in understanding the complex interactions between injury and immune response in critical illness.

Methods

We utilize a system biology model of COVID-19 to analyze the effect of altering baseline patient characteristics on the outcome of immunomodulatory therapies. We create example parameter sets meant to mimic diverse patient types. For each patient type, we define the optimal treatment, identify biologic programs responsible for clinical responses, and predict biomarkers of those programs.

Findings

Model states representing older and hyperinflamed patients respond better to immunomodulation than those representing obese and diabetic patients. The disparate clinical responses are driven by distinct biologic programs. Optimal treatment initiation time is determined by neutrophil recruitment, systemic cytokine expression, systemic microthrombosis and the renin-angiotensin system (RAS) in older patients, and by RAS, systemic microthrombosis and trans IL6 signalling for hyperinflamed patients. For older and hyperinflamed patients, IL6 modulating therapy is predicted to be optimal when initiated very early (<4^th day of infection) and broad immunosuppression therapy (corticosteroids) is predicted to be optimally initiated later in the disease (7^th – 9^th day of infection). We show that markers of biologic programs identified by the model correspond to clinically identified markers of disease severity.

Interpretation

We demonstrate that modelling of COVID-19 pathobiology can suggest biomarkers that predict optimal response to a given immunomodulatory treatment. Mathematical modelling thus constitutes a novel adjunct to predictive enrichment and may aid in the reduction of heterogeneity in critical care trials.

Funding

C.V. received a Marie Skłodowska Curie Actions Individual Fellowship (MSCA-IF-GF-2020-101028945). R.K.J.'s research is supported by R01-CA208205, and U01-CA 224348, R35-CA197743 and grants from the National Foundation for Cancer Research, Jane's Trust Foundation, Advanced Medical Research Foundation and Harvard Ludwig Cancer Center. No funder had a role in production or approval of this manuscript.

Six-month and 12-month patient outcomes based on inflammatory subphenotypes in sepsis-associated ARDS: secondary analysis of SAILS-ALTOS trial

BACKGROUND

Prior acute respiratory distress syndrome (ARDS) trials have identified hypoinflammatory and hyperinflammatory subphenotypes, with distinct differences in short-term outcomes. It is unknown if such differences extend beyond 90 days or are associated with physical, mental health or cognitive outcomes.

METHODS

568 patients in the multicentre Statins for Acutely Injured Lungs from Sepsis trial of rosuvastatin versus placebo were included and assigned a subphenotype. Among 6-month and 12-month survivors (N=232 and 219, respectively, representing 243 unique survivors), subphenotype status was evaluated for association with a range of patient-reported outcomes (eg, mental health symptoms, quality of life). Patient subsets also were evaluated with performance-based tests of physical function (eg, 6 min walk test) and cognition.

FINDINGS

The hyperinflammatory versus hypoinflammatory subphenotype had lower overall 12-month cumulative survival (58% vs 72%, p<0.01); however, there was no significant difference in survival beyond 90 days (86% vs 89%, p=0.70). Most survivors had impairment across the range of outcomes, with little difference between subphenotypes at 6-month and 12-month assessments. For instance, at 6 months, in comparing the hypoinflammatory versus hyperinflammatory subphenotypes, respectively, the median (IQR) patient-reported SF-36 mental health domain score was 47 (33-56) vs 44 (35-56) (p=0.99), and the per cent predicted 6 min walk distance was 66% (48%, 80%) vs 66% (49%, 79%) (p=0.76).

INTERPRETATION

Comparing the hyperinflammatory versus hypoinflammatory ARDS subphenotype, there was no significant difference in survival beyond 90 days and no consistent findings of important differences in 6-month or 12-month physical, cognitive and mental health outcomes. These findings, when considered with prior results, suggest that inflammatory subphenotypes largely reflect the acute phase of illness and its short-term impact.

Latent Class Analysis Reveals COVID-19-related Acute Respiratory Distress Syndrome Subgroups with Differential Responses to Corticosteroids

Rationale

Two distinct subphenotypes have been identified in acute respiratory distress syndrome (ARDS), but the presence of subgroups in ARDS associated with coronavirus disease (COVID-19) is unknown.

Objectives

To identify clinically relevant, novel subgroups in COVID-19–related ARDS and compare them with previously described ARDS subphenotypes.

Methods

Eligible participants were adults with COVID-19 and ARDS at Columbia University Irving Medical Center. Latent class analysis was used to identify subgroups with baseline clinical, respiratory, and laboratory data serving as partitioning variables. A previously developed machine learning model was used to classify patients as the hypoinflammatory and hyperinflammatory subphenotypes. Baseline characteristics and clinical outcomes were compared between subgroups. Heterogeneity of treatment effect for corticosteroid use in subgroups was tested.

Measurements and Main Results

From March 2, 2020, to April 30, 2020, 483 patients with COVID-19–related ARDS met study criteria. A two-class latent class analysis model best fit the population (P = 0.0075). Class 2 (23%) had higher proinflammatory markers, troponin, creatinine, and lactate, lower bicarbonate, and lower blood pressure than class 1 (77%). Ninety-day mortality was higher in class 2 versus class 1 (75% vs. 48%; P < 0.0001). Considerable overlap was observed between these subgroups and ARDS subphenotypes. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RT-PCR cycle threshold was associated with mortality in the hypoinflammatory but not the hyperinflammatory phenotype. Heterogeneity of treatment effect to corticosteroids was observed (P = 0.0295), with improved mortality in the hyperinflammatory phenotype and worse mortality in the hypoinflammatory phenotype, with the caveat that corticosteroid treatment was not randomized.

Conclusions

We identified two COVID-19–related ARDS subgroups with differential outcomes, similar to previously described ARDS subphenotypes. SARS-CoV-2 PCR cycle threshold had differential value for predicting mortality in the subphenotypes. The subphenotypes had differential treatment responses to corticosteroids.

The Inflammatory Lung Microenvironment; a Key Mediator in MSC Licensing

Recent clinical trials of mesenchymal stromal cell (MSC) therapy for various inflammatory conditions have highlighted the significant benefit to patients who respond to MSC administration. Thus, there is strong interest in investigating MSC therapy in acute inflammatory lung conditions, such as acute respiratory distress syndrome (ARDS). Unfortunately, not all patients respond, and evidence now suggests that the differential disease microenvironment present across patients and sub-phenotypes of disease or across disease severities influences MSC licensing, function and therapeutic efficacy. Here, we discuss the importance of licensing MSCs and the need to better understand how the disease microenvironment influences MSC activation and therapeutic actions, in addition to the need for a patient-stratification approach.

Neutrophil-to-lymphocyte ratio is a powerful predictor of adult patients with acute respiratory distress syndrome who might benefit from corticosteroid therapy

BACKGROUND

There is no convincing pharmacological treatment for patients withacute respiratory distress syndrome (ARDS). The efficacy of corticosteroids in ARDS patients remains controversial. Neutrophil-to-Lymphocyte Ratio (NLR) has displayed as a good biomarker for inflammation and immune status, and thus a prognostic marker in some critical patients of ARDS. In this study, we hypothesized that NLR could also serve as an indicator for the efficacy of corticosteroid therapy in ARDS patients.

METHODS

Subjects included in this retrospective cohort study with ARDS patients who were admitted to an academic hospital in Wuhan, China, from May 1st, 2020 to April 20th, 2021. Multivariable logisitic regression model was used to evaluate risk factors of 30-day in-hospital mortality and ventilator-free days. Multi-Cox regression model was used to assess the efficacy of corticosteroid treatment in terms of NLR cutoff value.

RESULTS

Among the 357 patients in our study, 89 (24.9%) had NLR≥14.35 and 268 (75.1%) had NLR<14.35. Among them, 53 patients with NLR≥14.35 (58.9%) received corticosteroids and 99 patients with NLR<14.35 (37.1%) received corticosteroids. Post-adjustment analysis (by APACHE II score and age) revealed that corticosteroid treatment was associated with a decreased risk of 30-day mortality in the NLR≥14.35 group but with an increased risk of death in the NLR<14.35 group. Use of corticosteroid in NLR≥14.35 group significantly increased ventilator-free days (7.0 vs. 13.0, P<0.001).

CONCLUSION

NLR may be used to help identify ARDS patients who may benefit from corticosteroid treatment. Large-sized randomized controlled trials are warranted to determine the optimal cutoff value of NLR.

Lung Ultrasound Assessment of Focal and Non-focal Lung Morphology in Patients With Acute Respiratory Distress Syndrome

Background: The identification of phenotypes based on lung morphology can be helpful to better target mechanical ventilation of individual patients with acute respiratory distress syndrome (ARDS). We aimed to assess the accuracy of lung ultrasound (LUS) methods for classification of lung morphology in critically ill ARDS patients under mechanical ventilation.

Methods: This was a post hoc analysis on two prospective studies that performed LUS and chest computed tomography (CT) scanning at the same time. Expert panels from the two participating centers separately developed two LUS methods for classifying lung morphology based on LUS aeration scores from a 12-region exam (Amsterdam and Lombardy method). Moreover, a previously developed LUS method based on anterior LUS scores was tested (Piedmont method). Sensitivity and specificity of all three LUS methods was assessed in the cohort of the other center(s) by using CT as the gold standard for classification of lung morphology.

Results: The Amsterdam and Lombardy cohorts consisted of 32 and 19 ARDS patients, respectively. From these patients, 23 (45%) had focal lung morphology while others had non-focal lung morphology. The Amsterdam method could classify focal lung morphology with a sensitivity of 77% and a specificity of 100%, while the Lombardy method had a sensitivity and specificity of 100 and 61%. The Piedmont method had a sensitivity and specificity of 91 and 75% when tested on both cohorts. With both the Amsterdam and Lombardy method, most patients could be classified based on the anterior regions alone.

Conclusion: LUS-based methods can accurately classify lung morphology in invasively ventilated ARDS patients compared to gold standard chest CT. The anterior LUS regions showed to be the most discriminant between focal and non-focal lung morphology, although accuracy increased moderately when lateral and posterior LUS regions were integrated in the method.

Characterizing preclinical sub-phenotypic models of acute respiratory distress syndrome: An experimental ovine study

The acute respiratory distress syndrome (ARDS) describes a heterogenous population of patients with acute severe respiratory failure. However, contemporary advances have begun to identify distinct sub-phenotypes that exist within its broader envelope. These sub-phenotypes have varied outcomes and respond differently to several previously studied interventions. A more precise understanding of their pathobiology and an ability to prospectively identify them, may allow for the development of precision therapies in ARDS. Historically, animal models have played a key role in translational research, although few studies have so far assessed either the ability of animal models to replicate these sub-phenotypes or investigated the presence of sub-phenotypes within animal models. Here, in three ovine models of ARDS, using combinations of oleic acid and intravenous, or intratracheal lipopolysaccharide, we investigated the presence of sub-phenotypes which qualitatively resemble those found in clinical cohorts. Principal Component Analysis and partitional clustering identified two clusters, differentiated by markers of shock, inflammation, and lung injury. This study provides a first exploration of ARDS phenotypes in preclinical models and suggests a methodology for investigating this phenomenon in future studies.

Pharmacologic Treatments for Acute Respiratory Distress Syndrome

Acute respiratory distress syndrome is a heterogenous syndrome with many etiologies for which there are no definitive pharmacologic treatments, despite decades of research. We explore some adjunctive pharmacologic therapies, including neuromuscular blockade, corticosteroids, and inhaled pulmonary vasodilators. Additionally, we explore some investigative therapies, including Vitamin C, beta-agonists, statins, mesenchymal stromal cells, and granulocyte-macrophage colony stimulating factor. We do discuss the potential role of steroids in acute respiratory distress syndrome with severe acute respiratory syndrome coronavirus 2 as a trigger. The standard of care, however, remains supportive care.

Electrical impedance tomography as a tool for monitoring mechanical ventilation. An introduction to the technique

Electrical impedance tomography (EIT) is a non-invasive, radiation-free method of diagnostics imaging, allowing for a bedside, real-time dynamic assessment of lung function. It stands as an alternative for other imagining methods, such as computed tomography (CT) or ultrasound. Even though the technique is rather novel, it has a wide variety of possible applications. In the era of modern mechanical ventilation, a dynamic assessment of patient's respiratory condition appears to fulfil the idea of personalized treatment. Additionally, an increasing frequency of respiratory failure among intensive care populations raises demand for improved monitoring tools. This review aims to raise awareness and presents possible implications for the use of EIT in the intensive care setting.

Identification of distinct clinical phenotypes of acute respiratory distress syndrome with differential responses to treatment

Background

Acute respiratory distress syndrome (ARDS) is a heterogeneous syndrome, and the identification of homogeneous subgroups and phenotypes is the first step toward precision critical care. We aimed to explore whether ARDS phenotypes can be identified using clinical data, are reproducible and are associated with clinical outcomes and treatment response.

Methods

This study is based on a retrospective analysis of data from the telehealth intensive care unit (eICU) collaborative research database and three ARDS randomized controlled trials (RCTs) (ALVEOLI, FACTT and SAILS trials). We derived phenotypes in the eICU by cluster analysis based on clinical data and compared the clinical characteristics and outcomes of each phenotype. The reproducibility of the derived phenotypes was tested using the data from three RCTs, and treatment effects were evaluated.

Results

Three clinical phenotypes were identified in the training cohort of 3875 ARDS patients. Of the three phenotypes identified, phenotype I (n = 1565; 40%) was associated with fewer laboratory abnormalities, less organ dysfunction and the lowest in-hospital mortality rate (8%). Phenotype II (n = 1232; 32%) was correlated with more inflammation and shock and had a higher mortality rate (18%). Phenotype III (n = 1078; 28%) was strongly correlated with renal dysfunction and acidosis and had the highest mortality rate (22%). These results were validated using the data from the validation cohort (n = 3670) and three RCTs (n = 2289) and had reproducibility. Patients with these ARDS phenotypes had different treatment responses to randomized interventions. Specifically, in the ALVEOLI cohort, the effects of ventilation strategy (high PEEP vs low PEEP) on ventilator-free days differed by phenotype (p = 0.001); in the FACTT cohort, there was a significant interaction between phenotype and fluid-management strategy for 60-day mortality (p = 0.01). The fluid-conservative strategy was associated with improved mortality in phenotype II but had the opposite effect in phenotype III.

Conclusion

Three clinical phenotypes of ARDS were identified and had different clinical characteristics and outcomes. The analysis shows evidence of a phenotype-specific treatment benefit in the ALVEOLI and FACTT trials. These findings may improve the identification of distinct subsets of ARDS patients for exploration in future RCTs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-021-03734-y.

Comparisons of Outcomes between Patients with Direct and Indirect Acute Respiratory Distress Syndrome Receiving Extracorporeal Membrane Oxygenation

Acute respiratory distress syndrome (ARDS) is a heterogeneous syndrome caused by direct (local damage to lung parenchyma) or indirect lung injury (insults from extrapulmonary sites with acute systemic inflammatory response), the clinical and biological complexity can have a profound effect on clinical outcomes. We performed a retrospective analysis of 152 severe ARDS patients receiving extracorporeal membrane oxygenation (ECMO). Our objective was to assess the differences in clinical characteristics and outcomes of direct and indirect ARDS patients receiving ECMO. Overall hospital mortality was 53.3%. A total of 118 patients were assigned to the direct ARDS group, and 34 patients were assigned to the indirect ARDS group. The 28-, 60-, and 90-day hospital mortality rates were significantly higher among indirect ARDS patients (all p < 0.05). Cox regression models demonstrated that among direct ARDS patients, diabetes mellitus, immunocompromised status, ARDS duration before ECMO, and SOFA score during the first 3 days of ECMO were independently associated with mortality. In indirect ARDS patients, SOFA score and dynamic compliance during the first 3 days of ECMO were independently associated with mortality. Our findings revealed that among patients receiving ECMO, direct and indirect subphenotypes of ARDS have distinct clinical outcomes and different predictors for mortality.

Strategies to protect surfactant and enhance its activity

The knowledge about surfactant biology is now deeper and recent research has allowed to clarify its role in several human lung disorders. The balance between surfactant production and consumption is better known and the same applies to their regulatory mechanisms. This has allowed to hypothesize and investigate several new and original strategies to protect surfactant and enhance its activity. These interventions are potentially useful for several disorders and particularly for acute respiratory distress syndrome. We here highlight the mechanisms regulating surfactant consumption, encompassing surfactant catabolism but also surfactant injury due to other mechanisms, in a physiopathology-driven fashion. We then analyze each corresponding strategy to protect surfactant and enhance its activity. Some of these strategies are more advanced in terms of research & development pathway, some others are still investigational, but all are promising and deserve a joint effort from clinical-academic researchers and the industry.

Biological Subphenotypes of Acute Respiratory Distress Syndrome Show Prognostic Enrichment in Mechanically Ventilated Patients without Acute Respiratory Distress Syndrome

Rationale: Recent studies showed that biological subphenotypes in acute respiratory distress syndrome (ARDS) provide prognostic enrichment and show potential for predictive enrichment. Objectives: To determine whether these subphenotypes and their prognostic and potential for predictive enrichment could be extended to other patients in the ICU, irrespective of fulfilling the definition of ARDS. Methods: This is a secondary analysis of a prospective observational study of adult patients admitted to the ICU. We tested the prognostic enrichment of both cluster-derived and latent-class analysis (LCA)-derived biological ARDS subphenotypes by evaluating the association with clinical outcome (ICU-day, 30-day mortality, and ventilator-free days) using logistic regression and Cox regression analysis. We performed a principal component analysis to compare blood leukocyte gene expression profiles between subphenotypes and the presence of ARDS. Measurements and Main Results: We included 2,499 mechanically ventilated patients (674 with and 1,825 without ARDS). The cluster-derived "reactive" subphenotype was, independently of ARDS, significantly associated with a higher probability of ICU mortality, higher 30-day mortality, and a lower probability of successful extubation while alive compared with the "uninflamed" subphenotype. The blood leukocyte gene expression profiles of individual subphenotypes were similar for patients with and without ARDS. LCA-derived subphenotypes also showed similar profiles. Conclusions: The prognostic and potential for predictive enrichment of biological ARDS subphenotypes may be extended to mechanically ventilated critically ill patients without ARDS. Using the concept of biological subphenotypes for splitting cohorts of critically ill patients could add to improving future precision-based trial strategies and lead to identifying treatable traits for all critically ill patients.

Plasma Metabolites in Early Sepsis Identify Distinct Clusters Defined by Plasma Lipids

Supplemental Digital Content is available in the text.

OBJECTIVES:

Unbiased global metabolomic profiling has not been used to identify distinct subclasses in patients with early sepsis and sepsis-associated acute respiratory distress syndrome. In this study, we examined whether the plasma metabolome reflects systemic illness in early sepsis and in acute respiratory distress syndrome.

DESIGN:

Plasma metabolites were measured in subjects with early sepsis.

SETTING:

Patients were admitted from the emergency department to the ICU in a plasma sample collected within 24 hours of ICU admission. Metabolic profiling of 970 metabolites was performed by Metabolon (Durham, NC). Hierarchical clustering and partial least squares discriminant clustering were used to identify distinct clusters among patients with early sepsis and sepsis-associated acute respiratory distress syndrome.

INTERVENTIONS:

None.

MEASUREMENTS AND MAIN RESULTS:

Among critically ill patients with early sepsis (n = 197), three metabolically distinct subgroups were identified, with metabolic subtype driven by plasma lipids. Group 1, with 45 subjects (23% of cohort), had increased 60-day mortality (odds ratio, 2; 95% CI, 0.99–4.0; p = 0.04 for group 1 vs all others). This group also had higher rates of vasopressor-dependent shock, acute kidney injury, and met Berlin acute respiratory distress syndrome criteria more often (all p < 0.05). Conversely, metabolic group 3, with 76 subjects (39% of cohort), had the lowest risk of 60-day mortality (odds ratio, 0.44; 95% CI, 0.22–0.86; p = 0.01) and lower rates of organ dysfunction as reflected in a lower Simplified Acute Physiology Score II (p < 0.001). In contrast, global metabolomic profiling did not separate patient with early sepsis with moderate-to-severe acute respiratory distress syndrome (n = 78) from those with sepsis without acute respiratory distress syndrome (n = 75).

CONCLUSIONS:

Plasma metabolomic profiling in patients with early sepsis identified three metabolically distinct groups that were characterized by different plasma lipid profiles, distinct clinical phenotypes, and 60-day mortality. Plasma metabolites did not distinguish patients with early sepsis who developed acute respiratory distress syndrome from those who did not.

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

Acute respiratory distress syndrome (ARDS) is a clinically heterogenous syndrome, rather than a distinct disease. This heterogeneity at least partially explains the difficulty in studying treatments for these patients and contributes to the numerous trials of therapies for the syndrome that have not shown benefit. Recent studies have identified different subphenotypes within the heterogenous patient population. These different subphenotypes likely have variable clinical responses to specific therapies, a concept known as heterogeneity of treatment effect (HTE). Recognizing different subphenotypes and HTE has important implications for the clinical management of patients with ARDS. In this review, we will present studies that have identified different subphenotypes and discuss how they can modify the effects of therapies evaluated in trials that are commonly considered to have demonstrated no overall benefit in patients with ARDS.

Acute respiratory distress syndrome phenotypes with distinct clinical outcomes in PHARLAP trial cohort

Background: The Permissive Hypercapnia, Alveolar Recruitment and Low Airway Pressure (PHARLAP) randomised controlled trial compared an open lung ventilation strategy with control ventilation, and found that open lung ventilation did not reduce the number of ventilatorfree days (VFDs) or mortality in patients with moderate-to-severe acute respiratory distress syndrome (ARDS). Parsimonious models can identify distinct phenotypes of ARDS (hypo-inflammatory and hyperinflammatory) which are associated with different outcomes and treatment responses. Objective: To test the hypothesis that a parsimonious model would identify patients with distinctly different clinical outcomes in the PHARLAP study. Design, setting and participants: Blood and lung lavage samples were collected in a subset of PHARLAP patients who were recruited in Australian and New Zealand centres. A previously validated parsimonious model (interleukin-8, soluble tumour necrosis factor receptor-1 and bicarbonate) was used to classify patients with blood samples into hypo-inflammatory and hyperinflammatory groups. Generalised linear modelling was used to examine the interaction between inflammatory phenotype and treatment group (intervention or control). Main outcome measure: The primary outcome was number of VFDs at Day 28. Results: Data for the parsimonious model were available for 56 of 115 patients (49%). Within this subset, 38 patients (68%) and 18 patients (32%) were classified as having hypo-inflammatory and hyperinflammatory phenotypes, respectively. Patients with the hypo- inflammatory phenotype had more VFDs at Day 28 when compared with those with the hyperinflammatory phenotype (median [IQR], 19.5[11-24] versus 8[0-21];P= 0.03). Patients with the hyperinflammatory phenotype had numerically fewer VFDs when managed with an open lung strategy than when managed with control "protective" ventilation (median [IQR], 0 [0-19] versus 16 [8-22]). Conclusion: In the PHARLAP trial, ARDS patients classified as having a hyperinflammatory phenotype, with a parsimonious three-variable model, had fewer VFDs at Day 28 compared with patients classified as having a hypo-inflammatory phenotype. Future clinical studies of ventilatory strategies should consider incorporating distinct ARDS phenotypes into their trial design.

Systemic and organ-specific immune-related manifestations of COVID-19

Immune-related manifestations are increasingly recognized conditions in patients with COVID-19, with around 3,000 cases reported worldwide comprising more than 70 different systemic and organ-specific disorders. Although the inflammation caused by SARS-CoV-2 infection is predominantly centred on the respiratory system, some patients can develop an abnormal inflammatory reaction involving extrapulmonary tissues. The signs and symptoms associated with this excessive immune response are very diverse and can resemble some autoimmune or inflammatory diseases, with the clinical phenotype that is seemingly influenced by epidemiological factors such as age, sex or ethnicity. The severity of the manifestations is also very varied, ranging from benign and self-limiting features to life-threatening systemic syndromes. Little is known about the pathogenesis of these manifestations, and some tend to emerge within the first 2 weeks of SARS-CoV-2 infection, whereas others tend to appear in a late post-infectious stage or even in asymptomatic patients. As the body of evidence comprises predominantly case series and uncontrolled studies, diagnostic and therapeutic decision-making is unsurprisingly often based on the scarcely reported experience and expert opinion. Additional studies are required to learn about the mechanisms involved in the development of these manifestations and apply that knowledge to achieve early diagnosis and the most suitable therapy.

Etiology-associated heterogeneity in acute respiratory distress syndrome: a retrospective cohort study

Background

Heterogeneity in acute respiratory distress syndrome (ARDS) has led to many statistically negative clinical trials. Etiology is considered an important source of pathogenesis heterogeneity in ARDS but previous studies have usually adopted a dichotomous classification, such as pulmonary versus extrapulmonary ARDS, to evaluate it. Etiology-associated heterogeneity in ARDS remains poorly described.

Methods

In this retrospective cohort study, we described etiology-associated heterogeneity in gas exchange abnormality (PaO₂/FiO₂ [P/F] and ventilatory ratios), hemodynamic instability, non-pulmonary organ dysfunction as measured by the Sequential Organ Failure Assessment (SOFA) score, biomarkers of inflammation and coagulation, and 30-day mortality. Linear regression was used to model the trajectory of P/F ratios over time. Wilcoxon rank-sum tests, Kruskal–Wallis rank tests and Chi-squared tests were used to compare between-etiology differences.

Results

From 1725 mechanically ventilated patients in the ICU, we identified 258 (15%) with ARDS. Pneumonia (48.4%) and non-pulmonary sepsis (11.6%) were the two leading causes of ARDS. Compared with pneumonia associated ARDS, extra-pulmonary sepsis associated ARDS had a greater P/F ratio recovery rate (difference = 13 mmHg/day, p = 0.01), more shock (48% versus 73%, p = 0.01), higher non-pulmonary SOFA scores (6 versus 9 points, p < 0.001), higher d-dimer levels (4.2 versus 9.7 mg/L, p = 0.02) and higher mortality (43% versus 67%, p = 0.02). In pneumonia associated ARDS, there was significant difference in proportion of shock (p = 0.005) between bacterial and non-bacterial pneumonia.

Conclusion

This study showed that there was remarkable etiology-associated heterogeneity in ARDS. Heterogeneity was also observed within pneumonia associated ARDS when bacterial pneumonia was compared with other non-bacterial pneumonia. Future studies on ARDS should consider reporting etiology-specific data and exploring possible effect modification associated with etiology.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-021-01557-9.

Changes in Plasma Soluble Receptor for Advanced Glycation End-Products Are Associated with Survival in Patients with Acute Respiratory Distress Syndrome

The plasma soluble receptor for advanced glycation end-products (sRAGE) is a marker of lung epithelial injury with prognostic value when measured at baseline in acute respiratory distress syndrome (ARDS). However, whether changes in plasma sRAGE could inform prognosis in ARDS remains unknown. In this secondary analysis of the Lung Imaging for Ventilator Setting in ARDS (LIVE) multicenter randomized controlled trial, which evaluated a personalized ventilation strategy tailored to lung morphology, plasma sRAGE was measured upon study entry (baseline) and on days one, two, three, four and six. The association between changes in plasma sRAGE over time and 90-day survival was evaluated. Higher baseline plasma sRAGE (HR per-one log increment, 1.53; 95% CI, 1.16–2.03; p = 0.003) and an increase in sRAGE over time (HR for each one-log increment in plasma sRAGE per time unit, 1.01; 95% CI, 1.01–1.02; p < 10⁻³) were both associated with increased 90-day mortality. Each 100-unit increase in the plasma sRAGE level per unit of time increased the risk of death at day 90 by 1% in joint modeling. Plasma sRAGE increased over time when a strategy of maximal alveolar recruitment was applied in patients with focal ARDS. Current findings suggest that the rate of change in plasma sRAGE over time is associated with 90-day survival and could be helpful as a surrogate outcome in ARDS.

Thrombospondin-1 Restricts Interleukin-36γ-Mediated Neutrophilic Inflammation during Pseudomonas aeruginosa Pulmonary Infection

Interleukin-36γ (IL-36γ), a member of the IL-1 cytokine superfamily, amplifies lung inflammation and impairs host defense during acute pulmonary Pseudomonas aeruginosa infection. To be fully active, IL-36γ is cleaved at its N-terminal region by proteases such as neutrophil elastase (NE) and cathepsin S (CatS). However, it remains unclear whether limiting extracellular proteolysis restrains the inflammatory cascade triggered by IL-36γ during P. aeruginosa infection. Thrombospondin-1 (TSP-1) is a matricellular protein with inhibitory activity against NE and the pathogen-secreted Pseudomonas elastase LasB-both proteases implicated in amplifying inflammation. We hypothesized that TSP-1 tempers the inflammatory response during lung P. aeruginosa infection by inhibiting the proteolytic environment required for IL-36γ activation. Compared to wild-type (WT) mice, TSP-1-deficient (Thbs1-/-) mice exhibited a hyperinflammatory response in the lungs during P. aeruginosa infection, with increased cytokine production and an unrestrained extracellular proteolytic environment characterized by higher free NE and LasB, but not CatS activity. LasB cleaved IL-36γ proximally to M19 at a cleavage site distinct from those generated by NE and CatS, which cleave IL-36γ proximally to Y16 and S18, respectively. N-terminal truncation experiments in silico predicted that the M19 and the S18 isoforms bind the IL-36R complex almost identically. IL-36γ neutralization ameliorated the hyperinflammatory response and improved lung immunity in Thbs1-/- mice during P. aeruginosa infection. Moreover, administration of cleaved IL-36γ induced cytokine production and neutrophil recruitment and activation that was accentuated in Thbs1-/- mice lungs. Collectively, our data show that TSP-1 regulates lung neutrophilic inflammation and facilitates host defense by restraining the extracellular proteolytic environment required for IL-36γ activation.IMPORTANCEPseudomonas aeruginosa pulmonary infection can lead to exaggerated neutrophilic inflammation and tissue destruction, yet host factors that regulate the neutrophilic response are not fully known. IL-36γ is a proinflammatory cytokine that dramatically increases in bioactivity following N-terminal processing by proteases. Here, we demonstrate that thrombospondin-1, a host matricellular protein, limits N-terminal processing of IL-36γ by neutrophil elastase and the Pseudomonas aeruginosa-secreted protease LasB. Thrombospondin-1-deficient mice (Thbs1-/-) exhibit a hyperinflammatory response following infection. Whereas IL-36γ neutralization reduces inflammatory cytokine production, limits neutrophil activation, and improves host defense in Thbs1-/- mice, cleaved IL-36γ administration amplifies neutrophilic inflammation in Thbs1-/- mice. Our findings indicate that thrombospondin-1 guards against feed-forward neutrophilic inflammation mediated by IL-36γ in the lung by restraining the extracellular proteolytic environment.

Haemophagocytic syndrome and COVID-19

Primary and secondary haemophagocytic lymphohistiocytosis (HLH) are hyperferritinaemic hyperinflammatory syndromes with a common terminal pathway triggered by different etiopathogenetic factors. HLH is characterised by a decreased capacity of interferon gamma production with an activated NK phenotype profile similar to other hyperinflammatory syndromes. Viruses are closely linked to the development of HLH as infectious triggers, and the break of tolerance to self-antigens is considered a critical mechanism involved in the development of immune-mediated conditions triggered by viral infections. Emerging studies in patients with COVID-19 are suggesting a key role of monocytes/macrophages in the pathogenesis of this viral infection, and there is a significant overlap between several features reported in severe COVID-19 and the features included in the HLH-2004 diagnostic criteria. Therefore, SARS-Cov-2, as other respiratory viruses, may also be considered a potential etiological trigger of HLH. The frequency of HLH in adult patients with severe COVID-19 is lower than 5%, although this figure could be underestimated considering that most reported cases lacked information about some specific criteria (mainly the histopathological criteria and the measurement of NK cell function and sCD25 levels). Because HLH is a multi-organ syndrome, the diagnostic approach in a patient with severe COVID-19 in whom HLH is suspected must be carried out in a syndromic and holistic way, and not in the light of isolated clinical or laboratory features. In COVID-19 patients presenting with persistent high fever, progressive pancytopenia, and hepatosplenic involvement, together with the characteristic triad of laboratory abnormalities (hyperferritinaemia, hypertriglyceridaemia, and hypofibrinogenaemia), the suspicion of HLH is high, and the diagnostic workup must be completed with specific immunological and histopathological studies.

Inhibition of Caspase-1 with Tetracycline Ameliorates Acute Lung Injury

Rationale: Acute respiratory distress syndrome (ARDS) is a heterogeneous syndrome with a mortality of up to 40%. Precision medicine approaches targeting patients on the basis of their molecular phenotypes of ARDS might help to identify effective pharmacotherapies. The inflammasome-caspase-1 pathway contributes to the development of ARDS via IL-1β and IL-18 production. Recent studies indicate that tetracycline can be used to treat inflammatory diseases mediated by IL-1β and IL-18, although the molecular mechanism by which tetracycline inhibits inflammasome-caspase-1 signaling remains unknown. Objectives: To identify patients with ARDS characterized by IL-1β and IL-18 expression and investigate the ability of tetracycline to inhibit inflammasome-caspase-1 signaling in ARDS. Methods: IL-1β and IL-18 concentrations were quantified in BAL fluid from patients with ARDS. Tetracycline's effects on lung injury and inflammation were assessed in two mouse models of direct (pulmonary) acute lung injury, and its effects on IL-1β and IL-18 production were assessed by alveolar leukocytes from patients with direct ARDS ex vivo. Murine macrophages were used to further characterize the effect of tetracycline on the inflammasome-caspase-1 pathway. Measurements and Main Results: BAL fluid concentrations of IL-1β and IL-18 are significantly higher in patients with direct ARDS than those with indirect (nonpulmonary) ARDS. In experimental acute lung injury, tetracycline significantly diminished lung injury and pulmonary inflammation by selectively inhibiting caspase-1-dependent IL-1β and IL-18 production, leading to improved survival. Tetracycline also reduced the production of IL-1β and IL-18 by alveolar leukocytes from patients with direct ARDS. Conclusions: Tetracycline may be effective in the treatment of direct ARDS in patients with elevated caspase-1 activity. Clinical Trial registered with www.clinicaltrials.gov (NCT04079426).

Surfactant therapies for pediatric and neonatal ARDS: ESPNIC expert consensus opinion for future research steps

Pediatric (PARDS) and neonatal (NARDS) acute respiratory distress syndrome have different age-specific characteristics and definitions. Trials on surfactant for ARDS in children and neonates have been performed well before the PARDS and NARDS definitions and yielded conflicting results. This is mainly due to heterogeneity in study design reflecting historic lack of pathobiology knowledge. We reviewed the available clinical and preclinical data to create an expert consensus aiming to inform future research steps and advance the knowledge in this area. Eight trials investigated the use of surfactant for ARDS in children and ten in neonates, respectively. There were improvements in oxygenation (7/8 trials in children, 7/10 in neonates) and mortality (3/8 trials in children, 1/10 in neonates) improved. Trials were heterogeneous for patients' characteristics, surfactant type and administration strategy. Key pathobiological concepts were missed in study design. Consensus with strong agreement was reached on four statements: 1. There are sufficient preclinical and clinical data to support targeted research on surfactant therapies for PARDS and NARDS. Studies should be performed according to the currently available definitions and considering recent pathobiology knowledge. 2. PARDS and NARDS should be considered as syndromes and should be pre-clinically studied according to key characteristics, such as direct or indirect (primary or secondary) nature, clinical severity, infectious or non-infectious origin or patients' age. 3. Explanatory should be preferred over pragmatic design for future trials on PARDS and NARDS. 4. Different clinical outcomes need to be chosen for PARDS and NARDS, according to the trial phase and design, trigger type, severity class and/or surfactant treatment policy. We advocate for further well-designed preclinical and clinical studies to investigate the use of surfactant for PARDS and NARDS following these principles.

Precision medicine in acute respiratory distress syndrome: workshop report and recommendations for future research

Acute respiratory distress syndrome (ARDS) is a devastating critical illness that can be triggered by a wide range of insults and remains associated with a high mortality of around 40%. The search for targeted treatment for ARDS has been disappointing, possibly due to the enormous heterogeneity within the syndrome. In this perspective from the European Respiratory Society research seminar on "Precision medicine in ARDS", we will summarise the current evidence for heterogeneity, explore the evidence in favour of precision medicine and provide a roadmap for further research in ARDS. There is evident variation in the presentation of ARDS on three distinct levels: 1) aetiological; 2) physiological and 3) biological, which leads us to the conclusion that there is no typical ARDS. The lack of a common presentation implies that intervention studies in patients with ARDS need to be phenotype aware and apply a precision medicine approach in order to avoid the lack of success in therapeutic trials that we faced in recent decades. Deeper phenotyping and integrative analysis of the sources of variation might result in identification of additional treatable traits that represent specific pathobiological mechanisms, or so-called endotypes.

Biomarkers in acute respiratory distress syndrome

PURPOSE OF REVIEW

This article provides an overview of protein biomarkers for acute respiratory distress syndrome (ARDS) and their potential use in future clinical trials.

RECENT FINDINGS

The protein biomarkers studied as indices of biological processes involved in the pathogenesis of ARDS may have diagnostic and/or prognostic value. Recently, they also proved useful for identifying ARDS phenotypes and assessing heterogeneity of treatment effect in retrospective analyses of completed clinical trials.

SUMMARY

This article summarizes the current research on ARDS biomarkers and provides insights into how they should be integrated as prognostic and predictive enrichment tools in future clinical trials.

Respiratory distress syndrome in preterm neonates in the era of precision medicine: A modern critical care-based approach

Respiratory distress syndrome (RDS) was recognized to be caused by primary surfactant deficiency almost 70 years ago and continuous positive airway pressure was introduced approximately 50 years ago. Since then, there have been many developments in neonatology; we know many things but others are still controversial. The more we know, the more questions arise. However, this review aims to indicate what is more needed to understand and how should be the modern approach to RDS in the era of precision medicine. The review is divided between new concepts and new tools. We will explain the interaction between steroids, CPAP and surfactant, as well as the surfactant catabolism and the diagnosis of NARDS; lung ultrasound and new tools to optimize CPAP will also be covered. How these concepts are integrated in the author's personal experience is also illustrated.

Systematic review of diagnostic methods for acute respiratory distress syndrome

Rationale

Acute respiratory distress syndrome (ARDS) is currently diagnosed by the Berlin definition, which does not include a direct measure of pulmonary oedema, endothelial permeability or pulmonary inflammation. We hypothesised that biomarkers of these processes have good diagnostic accuracy for ARDS.

Methods

Medline and Scopus were searched for original diagnostic studies using minimally invasive testing. Primary outcome was the diagnostic accuracy per test and was categorised by control group. The methodological quality was assessed with QUADAS-2 tool. Biomarkers that had an area under the receiver operating characteristic curve (AUROCC) of >0.75 and were studied with minimal bias against an unselected control group were considered to be promising.

Results

Forty-four articles were included. The median AUROCC for all evaluated tests was 0.80 (25th to 75th percentile: 0.72–0.88). The type of control group influenced the diagnostic accuracy (p=0.0095). Higher risk of bias was associated with higher diagnostic accuracy (AUROCC 0.75 for low-bias, 0.77 for intermediate-bias and 0.84 for high-bias studies; p=0.0023). Club cell protein 16 and soluble receptor for advanced glycation end-products in plasma and two panels with biomarkers of oxidative stress in breath showed good diagnostic accuracy in low-bias studies that compared ARDS patients to an unselected intensive care unit (ICU) population.

Conclusion

This systematic review revealed only four diagnostic tests fulfilling stringent criteria for a promising biomarker in a low-bias setting. For implementation into the clinical setting, prospective studies in a general unselected ICU population with good methodological quality are needed.

Accuracy of diagnosis of acute respiratory distress syndrome (ARDS) is associated with risk of bias. There is a lack of validated diagnostic tests in an unbiased setting, emphasising the need for quality driven diagnostic research in ARDS.https://bit.ly/2GfPAvf

Molecular and biophysical mechanisms behind the enhancement of lung surfactant function during controlled therapeutic hypothermia

Therapeutic hypothermia (TH) enhances pulmonary surfactant performance in vivo by molecular mechanisms still unknown. Here, the interfacial structure and the composition of lung surfactant films have been analysed in vitro under TH as well as the molecular basis of its improved performance both under physiological and inhibitory conditions. The biophysical activity of a purified porcine surfactant was tested under slow and breathing-like dynamics by constrained drop surfactometry (CDS) and in the captive bubble surfactometer (CBS) at both 33 and 37 °C. Additionally, the temperature-dependent surfactant activity was also analysed upon inhibition by plasma and subsequent restoration by further surfactant supplementation. Interfacial performance was correlated with lateral structure and lipid composition of films made of native surfactant. Lipid/protein mixtures designed as models to mimic different surfactant contexts were also studied. The capability of surfactant to drastically reduce surface tension was enhanced at 33 °C. Larger DPPC-enriched domains and lower percentages of less active lipids were detected in surfactant films exposed to TH-like conditions. Surfactant resistance to plasma inhibition was boosted and restoration therapies were more effective at 33 °C. This may explain the improved respiratory outcomes observed in cooled patients with acute respiratory distress syndrome and opens new opportunities in the treatment of acute lung injury.

Practitioner's Guide to Latent Class Analysis: Methodological Considerations and Common Pitfalls

Latent class analysis is a probabilistic modeling algorithm that allows clustering of data and statistical inference. There has been a recent upsurge in the application of latent class analysis in the fields of critical care, respiratory medicine, and beyond. In this review, we present a brief overview of the principles behind latent class analysis. Furthermore, in a stepwise manner, we outline the key processes necessary to perform latent class analysis including some of the challenges and pitfalls faced at each of these steps. The review provides a one-stop shop for investigators seeking to apply latent class analysis to their data.

Anti-inflammatory Effects of Statins in Lung Vascular Pathology: From Basic Science to Clinical Trials

HMG-CoA reductase inhibitors (or statins) are cholesterol-lowering drugs and are among the most widely prescribed medications in the United States. Statins exhibit pleiotropic effects that extend beyond cholesterol reduction including anti-atherosclerotic, antiproliferative, anti-inflammatory, and antithrombotic effects. Over the last 20 years, statins have been studied and examined in pulmonary vascular disorders, including both chronic pulmonary vascular disease such as pulmonary hypertension, and acute pulmonary vascular endothelial injury such as acute lung injury. In both research and clinical settings, statins have demonstrated promising vascular protection through modulation of the endothelium, attenuation of vascular leak, and promotion of endothelial repair following lung inflammation. This chapter provides a summary of the rapidly changing literature, summarizes the anti-inflammatory mechanism of statins on pulmonary vascular disorders, and explores clinical evidence for statins as a potential therapeutic approach to modulation of the endothelium as well as a means to broaden our understanding of pulmonary vasculopathy pathophysiology.

Lung protection in acute respiratory distress syndrome: what should we target?

PURPOSE OF REVIEW

Most clinical trials of lung-protective ventilation have tested one-size-fits-all strategies with mixed results. Data are lacking on how best to tailor mechanical ventilation to patient-specific risk of lung injury.

RECENT FINDINGS

Risk of ventilation-induced lung injury is determined by biological predisposition to biophysical lung injury and physical mechanical perturbations that concentrate stress and strain regionally within the lung. Recent investigations have identified molecular subphenotypes classified as hyperinflammatory and hypoinflammatory acute respiratory distress syndrome (ARDS), which may have dissimilar risk for ventilation-induced lung injury. Mechanically, gravity-dependent atelectasis has long been recognized to decrease total aerated lung volume available for tidal ventilation, a concept termed the 'ARDS baby lung'. Recent studies have demonstrated that the aerated baby lung also has nonuniform stress/strain distribution, with potentially injurious forces concentrated in zones of heterogeneity where aerated alveoli are adjacent to flooded or atelectatic alveoli. The preponderance of evidence also indicates that current standard-of-care tidal volume management is not universally protective in ARDS. When considering escalation of lung-protective interventions, potential benefits of the intervention should be weighed against tradeoffs of accompanying cointerventions required, for example, deeper sedation or neuromuscular blockade. A precision medicine approach to lung-protection would weigh.

SUMMARY

A precision medicine approach to lung-protective ventilation requires weighing four key factors in each patient: biological predisposition to biophysical lung injury, mechanical predisposition to biophysical injury accounting for spatial mechanical heterogeneity within the lung, anticipated benefits of escalating lung-protective interventions, and potential unintended adverse effects of mandatory cointerventions.

Phenotypes and personalized medicine in the acute respiratory distress syndrome

Although the acute respiratory distress syndrome (ARDS) is well defined by the development of acute hypoxemia, bilateral infiltrates and non-cardiogenic pulmonary edema, ARDS is heterogeneous in terms of clinical risk factors, physiology of lung injury, microbiology, and biology, potentially explaining why pharmacologic therapies have been mostly unsuccessful in treating ARDS. Identifying phenotypes of ARDS and integrating this information into patient selection for clinical trials may increase the chance for efficacy with new treatments. In this review, we focus on classifying ARDS by the associated clinical disorders, physiological data, and radiographic imaging. We consider biologic phenotypes, including plasma protein biomarkers, gene expression, and common causative microbiologic pathogens. We will also discuss the issue of focusing clinical trials on the patient's phase of lung injury, including prevention, administration of therapy during early acute lung injury, and treatment of established ARDS. A more in depth understanding of the interplay of these variables in ARDS should provide more success in designing and conducting clinical trials and achieving the goal of personalized medicine.

Machine Learning Classifier Models Can Identify Acute Respiratory Distress Syndrome Phenotypes Using Readily Available Clinical Data

Rationale: Two distinct phenotypes of acute respiratory distress syndrome (ARDS) with differential clinical outcomes and responses to randomly assigned treatment have consistently been identified in randomized controlled trial cohorts using latent class analysis. Plasma biomarkers, key components in phenotype identification, currently lack point-of-care assays and represent a barrier to the clinical implementation of phenotypes.Objectives: The objective of this study was to develop models to classify ARDS phenotypes using readily available clinical data only.Methods: Three randomized controlled trial cohorts served as the training data set (ARMA [High vs. Low Vt], ALVEOLI [Assessment of Low Vt and Elevated End-Expiratory Pressure to Obviate Lung Injury], and FACTT [Fluids and Catheter Treatment Trial]; n = 2,022), and a fourth served as the validation data set (SAILS [Statins for Acutely Injured Lungs from Sepsis]; n = 745). A gradient-boosted machine algorithm was used to develop classifier models using 24 variables (demographics, vital signs, laboratory, and respiratory variables) at enrollment. In two secondary analyses, the ALVEOLI and FACTT cohorts each, individually, served as the validation data set, and the remaining combined cohorts formed the training data set for each analysis. Model performance was evaluated against the latent class analysis-derived phenotype.Measurements and Main Results: For the primary analysis, the model accurately classified the phenotypes in the validation cohort (area under the receiver operating characteristic curve [AUC], 0.95; 95% confidence interval [CI], 0.94-0.96). Using a probability cutoff of 0.5 to assign class, inflammatory biomarkers (IL-6, IL-8, and sTNFR-1; P < 0.0001) and 90-day mortality (38% vs. 24%; P = 0.0002) were significantly higher in the hyperinflammatory phenotype as classified by the model. Model accuracy was similar when ALVEOLI (AUC, 0.94; 95% CI, 0.92-0.96) and FACTT (AUC, 0.94; 95% CI, 0.92-0.95) were used as the validation cohorts. Significant treatment interactions were observed with the clinical classifier model-assigned phenotypes in both ALVEOLI (P = 0.0113) and FACTT (P = 0.0072) cohorts.Conclusions: ARDS phenotypes can be accurately identified using machine learning models based on readily available clinical data and may enable rapid phenotype identification at the bedside.

Current and evolving standards of care for patients with ARDS

Care for patients with acute respiratory distress syndrome (ARDS) has changed considerably over the 50 years since its original description. Indeed, standards of care continue to evolve as does how this clinical entity is defined and how patients are grouped and treated in clinical practice. In this narrative review we discuss current standards – treatments that have a solid evidence base and are well established as targets for usual care – and also evolving standards – treatments that have promise and may become widely adopted in the future. We focus on three broad domains of ventilatory management, ventilation adjuncts, and pharmacotherapy. Current standards for ventilatory management include limitation of tidal volume and airway pressure and standard approaches to setting PEEP, while evolving standards might focus on limitation of driving pressure or mechanical power, individual titration of PEEP, and monitoring efforts during spontaneous breathing. Current standards in ventilation adjuncts include prone positioning in moderate-severe ARDS and veno-venous extracorporeal life support after prone positioning in patients with severe hypoxemia or who are difficult to ventilate. Pharmacotherapy current standards include corticosteroids for patients with ARDS due to COVID-19 and employing a conservative fluid strategy for patients not in shock; evolving standards may include steroids for ARDS not related to COVID-19, or specific biological agents being tested in appropriate sub-phenotypes of ARDS. While much progress has been made, certainly significant work remains to be done and we look forward to these future developments.

Can Computer Decision Support Help Us Follow Our Own Rules in Pediatric Acute Respiratory Distress Syndrome?

Computerized decision support in pediatric #ARDS may improve guideline compliance. Can #MachineLearning improve on this further? @drjonpelly and @cmhorvat discuss a new phase one clinical trial in this month’s @PedCritCareMed.

Mysteries, Epistemological Modesty, and Artificial Intelligence in Surgery

Life is filled with puzzles and mysteries, and we often fail to recognize the difference. As described by Gregory Treverton and Malcolm Gladwell, puzzles are solved by gathering and assimilating all relevant data in a logical, linear fashion, as in deciding which antibiotic to prescribe for an infection. In contrast, mysteries remain unsolved until all relevant data are analyzed and interpreted in a way that appreciates their depth and complexity, as in determining how to best modulate the host immune response to infection. When investigating mysteries, we often fail to appreciate their depth and complexity. Instead, we gather and assimilate more data, treating the mystery like a puzzle. This strategy is often unsuccessful. Traditional approaches to predictive analytics and phenotyping in surgery use this strategy.

The Inflammasome in Times of COVID-19

Coronaviruses (CoVs) are members of the genus Betacoronavirus and the Coronaviridiae family responsible for infections such as severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and more recently, coronavirus disease-2019 (COVID-19). CoV infections present mainly as respiratory infections that lead to acute respiratory distress syndrome (ARDS). However, CoVs, such as COVID-19, also present as a hyperactivation of the inflammatory response that results in increased production of inflammatory cytokines such as interleukin (IL)-1β and its downstream molecule IL-6. The inflammasome is a multiprotein complex involved in the activation of caspase-1 that leads to the activation of IL-1β in a variety of diseases and infections such as CoV infection and in different tissues such as lungs, brain, intestines and kidneys, all of which have been shown to be affected in COVID-19 patients. Here we review the literature regarding the mechanism of inflammasome activation by CoV infection, the role of the inflammasome in ARDS, ventilator-induced lung injury (VILI), and Disseminated Intravascular Coagulation (DIC) as well as the potential mechanism by which the inflammasome may contribute to the damaging effects of inflammation in the cardiac, renal, digestive, and nervous systems in COVID-19 patients.

A "Window of Therapeutic Opportunity" for Anti-Cytokine Therapy in Patients With Coronavirus Disease 2019

The effects of cytokine inhibition in the different phases of the severe coronavirus disease 2019 (COVID-19) are currently at the center of intense debate, and preliminary results from observational studies and case reports offer conflicting results thus far. The identification of the correct timing of administration of anti-cytokine therapies and other immunosuppressants in COVID-19 should take into account the intricate relationship between the viral burden, the hyperactivation of the innate immune system and the adaptive immune dysfunction. The main challenge for effective administration of anti-cytokine therapy in COVID-19 will be therefore to better define a precise "window of therapeutic opportunity." Only considering a more specific set of criteria able to integrate information on direct viral damage, the cytokine burden, and the patient's immune vulnerability, it will be possible to decide, carefully balancing both benefits and risks, the appropriateness of using immunosuppressive drugs even in patients affected primarily by an infectious disease.

Prevalence of phenotypes of acute respiratory distress syndrome in critically ill patients with COVID-19: a prospective observational study

Background

In acute respiratory distress syndrome (ARDS) unrelated to COVID-19, two phenotypes, based on the severity of systemic inflammation (hyperinflammatory and hypoinflammatory), have been described. The hyperinflammatory phenotype is known to be associated with increased multiorgan failure and mortality. In this study, we aimed to identify these phenotypes in COVID-19-related ARDS.

Methods

In this prospective observational study done at two UK intensive care units, we recruited patients with ARDS due to COVID-19. Demographic, clinical, and laboratory data were collected at baseline. Plasma samples were analysed for interleukin-6 (IL-6) and soluble tumour necrosis factor receptor superfamily member 1A (TNFR1) using a novel point-of-care assay. A parsimonious regression classifier model was used to calculate the probability for the hyperinflammatory phenotype in COVID-19 using IL-6, soluble TNFR1, and bicarbonate levels. Data from this cohort was compared with patients with ARDS due to causes other than COVID-19 recruited to a previous UK multicentre, randomised controlled trial of simvastatin (HARP-2).

Findings

Between March 17 and April 25, 2020, 39 patients were recruited to the study. Median ratio of partial pressure of arterial oxygen to fractional concentration of oxygen in inspired air (PaO₂/FiO₂) was 18 kpa (IQR 15–21) and acute physiology and chronic health evaluation II score was 12 (10–16). 17 (44%) of 39 patients had died by day 28 of the study. Compared with survivors, patients who died were older and had lower PaO₂/FiO₂. The median probability for the hyperinflammatory phenotype was 0·03 (IQR 0·01–0·2). Depending on the probability cutoff used to assign class, the prevalence of the hyperinflammatory phenotype was between four (10%) and eight (21%) of 39, which is lower than the proportion of patients with the hyperinflammatory phenotype in HARP-2 (186 [35%] of 539). Using the Youden index cutoff (0·274) to classify phenotype, five (63%) of eight patients with the hyperinflammatory phenotype and 12 (39%) of 31 with the hypoinflammatory phenotype died. Compared with matched patients recruited to HARP-2, levels of IL-6 were similar in our cohort, whereas soluble TNFR1 was significantly lower in patients with COVID-19-associated ARDS.

Interpretation

In this exploratory analysis of 39 patients, ARDS due to COVID-19 was not associated with higher systemic inflammation and was associated with a lower prevalence of the hyperinflammatory phenotype than that observed in historical ARDS data. This finding suggests that the excess mortality observed in COVID-19-related ARDS is unlikely to be due to the upregulation of inflammatory pathways described by the parsimonious model.

Funding

US National Institutes of Health, Innovate UK, and Randox.

[COVID-19, an atypical acute respiratory distress syndrome]

L’infection au nouveau coronavirus Sars-Cov2 est responsable d’une forme sévère de pneumonie, la COVID-19 pouvant évoluer vers un tableau de syndrome de détresse respiratoire aiguë. Cependant, bien que les critères d’hypoxémie soient présents, ce SDRA diffère des formes classiques, notamment en raison d’une compliance pulmonaire le plus souvent normale au stade initial. Ceci suggère des mécanismes physiopathologiques spécifiques encore mal compris, qui aboutissent à des profils de la maladie devant faire repenser la ventilation protectrice, afin de limiter la genèse des lésions pulmonaires induites par la ventilation.

Pharmacological management of adult patients with acute respiratory distress syndrome

INTRODUCTION

There is still no definite drug for acute respiratory distress syndrome (ARDS) that is capable of reducing either short-term or long-term mortality. Therefore, great efforts are being made to identify a pharmacological approach that can be really effective.

AREAS COVERED

This review focuses on current challenges and future directions in the pharmacological management of ARDS, regardless of anti-infective treatments. The authors have excluded small randomized controlled trials (RCTs) with less than 60 patients because those studies do not have statistical power for outcome data, and also anecdotal trials but have considered the last meta-analysis on any drug.

EXPERT OPINION

There has been substantial progress in our knowledge of ARDS over the past two decades and many drugs have been used in its treatment. Nevertheless, effective targeted pharmacological treatments for ARDS are still lacking. The likely reason why a pharmacological approach is beneficial for some patients, but harmful for others is that ARDS is an extremely heterogeneous syndrome. To overcome this issue, a precision approach for ARDS, whereby therapies are specifically targeted to patients most likely to benefit, has been proposed. At present, however, the application of this approach seems to be a difficult task.

Direct acute respiratory distress syndrome after gastric perforation caused by an intragastric balloon: a case report

BACKGROUND

Acute respiratory distress syndrome (ARDS) is a life-threatening condition and the identification of the underlying direct (pulmonary) or indirect (non-pulmonary) cause is mandatory for a successful treatment. Intragastric balloon (IGB) therapy is a minimal invasive and supposedly harmless option to reduce body weight for the growing number of obese people. We present a case of a young patient who developed a direct ARDS due to initially undiagnosed abdominal pathologies caused by an IGB therapy.

CASE PRESENTATION

A 23-year old woman was admitted because of a direct ARDS for extracorporeal membrane oxygenation (ECMO) therapy. Weeks before, an IGB has been removed because of abdominal pain and free intraabdominal air. Diagnostic work-up of free intraabdominal air, previous pain of the left shoulder and newly developed abscess pneumonia revealed a perforation of the posterior wall of the gastral antrum. This resulted in a left subphrenic abscess with destruction of the diaphragm, development of pneumonia per continuitatem and subsequent direct lung injury. The gastric perforation was endoscopically clipped and the ARDS was successfully treated under ECMO therapy.

CONCLUSION

This case illustrates that a patient presenting with direct ARDS may have upper abdominal pathologies caused by a rare complication of a supposedly harmless treatment.

Early Changes Over Time in the Radiographic Assessment of Lung Edema Score Are Associated With Survival in ARDS

Background

The Radiographic Assessment of Lung Edema (RALE) score is associated with the severity of ARDS, and treatments targeted at reducing pulmonary edema such as conservative fluid management cause a reduction in RALE score over time.

Research Question

Are early changes in RALE score over time associated with survival in patients with ARDS?

Study Design and Methods

Data from patients enrolled in three centers in the Lung Imaging for Ventilation sEtting in ARDS (LIVE) trial with available chest radiographs at baseline (day 0) and days 2 or 3 were used. The RALE was scored by two independent reviewers. The primary end point was death by day 90, considering RALE score both at baseline and as a time-varying covariate in a marginal Cox survival model.

Results

RALE was scored from 135, 64, and 88 radiographs on days 0, 2, and 3, respectively. Both baseline RALE (hazard ratio [HR] for each one-point increment, 1.04; 95% CI, 1.01-1.08; P = .006) and the change in RALE over time (HR for each one-point decrease per unit of time, 0.99; 95% CI, 0.99-0.99; P = .03) were associated with death by day 90, even after adjustment for age, sex, BMI, Simplified Acute Physiology Score II, vasopressor use, and total volume of fluids received since study entry.

Interpretation

The change in RALE during the first days after ARDS onset is independently associated with survival and may be useful as a surrogate end point in future clinical trials of new therapeutics in ARDS.

Therapeutic targeting of metabolic alterations in acute respiratory distress syndrome

Acute respiratory distress syndrome (ARDS) remains a significant source of mortality in critically ill patients. Characterised by acute, widespread alveolar inflammation and pulmonary oedema, its pathophysiological heterogeneity has meant that targeted treatments have remained elusive. Metabolomic analysis has made initial steps in characterising the underlying metabolic derangements of ARDS as an indicator of phenotypical class and has identified mitochondrial dysfunction as a potential therapeutic target. Mesenchymal stem cells and their derived extracellular vesicles have shown significant promise as potential therapies in delivering mitochondria in order to redivert metabolism onto physiological pathways.

External Validation of an Acute Respiratory Distress Syndrome Prediction Model Using Radiology Reports

OBJECTIVES

Acute respiratory distress syndrome is frequently under recognized and associated with increased mortality. Previously, we developed a model that used machine learning and natural language processing of text from radiology reports to identify acute respiratory distress syndrome. The model showed improved performance in diagnosing acute respiratory distress syndrome when compared to a rule-based method. In this study, our objective was to externally validate the natural language processing model in patients from an independent hospital setting.

DESIGN

Secondary analysis of data across five prospective clinical studies.

SETTING

An urban, tertiary care, academic hospital.

PATIENTS

Adult patients admitted to the medical ICU and at-risk for acute respiratory distress syndrome.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The natural language processing model was previously derived and internally validated in burn, trauma, and medical patients at Loyola University Medical Center. Two machine learning models were examined with the following text features from qualifying radiology reports: 1) word representations (n-grams) and 2) standardized clinical named entity mentions mapped from the National Library of Medicine Unified Medical Language System. The models were externally validated in a cohort of 235 patients at the University of Chicago Medicine, among which 110 (47%) were diagnosed with acute respiratory distress syndrome by expert annotation. During external validation, the n-gram model demonstrated good discrimination between acute respiratory distress syndrome and nonacute respiratory distress syndrome patients (C-statistic, 0.78; 95% CI, 0.72-0.84). The n-gram model had a higher discrimination for acute respiratory distress syndrome when compared with the standardized named entity model, although not statistically significant (C-statistic 0.78 vs 0.72; p = 0.09). The most important features in the model had good face validity for acute respiratory distress syndrome characteristics but differences in frequencies did occur between hospital settings.

CONCLUSIONS

Our computable phenotype for acute respiratory distress syndrome had good discrimination in external validation and may be used by other health systems for case-identification. Discrepancies in feature representation are likely due to differences in characteristics of the patient cohorts.