Early identification of patients at risk of acute lung injury: evaluation of lung injury prediction score in a multicenter cohort study

Risk factors of acute respiratory distress syndrome in sepsis caused by intra-abdominal infections: A retrospective study

BACKGROUND

Intra-abdominal infections are frequently associated with acute respiratory distress syndrome, which significantly affects patient prognosis. However, little is known about the specific risk factors of acute respiratory distress syndrome in sepsis caused by intra-abdominal infections.

METHODS

This retrospective study included adult patients with intra-abdominal sepsis admitted to the intensive care unit of a tertiary teaching hospital in China between June 2017 and June 2022. Patients were categorized based on the presence or absence of acute respiratory distress syndrome. Data, including vital signs, laboratory values, and severity scores collected within 24 hours of sepsis diagnosis, as well as outcomes within 90 days, were analyzed. Multivariable logistic regression was used to identify independent risk factors associated with acute respiratory distress syndrome.

RESULTS

A total of 738 patients were included, of whom 218 (29.5%) developed acute respiratory distress syndrome. Patients with acute respiratory distress syndrome were younger, had a higher body mass index and disease severity scores, and exhibited higher proportions of septic shock and hospital-acquired intra-abdominal infections. The mortalities in the intensive care unit and at 28 and 90 days were higher in the acute respiratory distress syndrome group. In the multivariate logistic regression model, age under 65 years (odds ratio [95% confidence interval]: 1.571 [1.093-2.259]), elevated body mass index (2.070 [1.382-3.101] for overweight, 6.994 [3.207-15.255]) for obesity, septic shock (2.043 [1.400-2.980]), procalcitonin (1.009 [1.004-1.015]), hospital-acquired intra-abdominal infections (2.528[1.373-4.657]), and source of intra-abdominal infections (2.170 [1.140-4.128] for biliary tract infection, 0.443 [0.217-0.904] for gastroduodenal perforation) were independently associated with acute respiratory distress syndrome.

CONCLUSION

In patients with intra-abdominal sepsis, age under 65 years, higher body mass index and procalcitonin, septic shock, hospital-acquired intra-abdominal infections, and biliary tract infection were risk factors for acute respiratory distress syndrome.

Pulmonary drug delivery devices and nanosystems as potential treatment strategies for acute respiratory distress syndrome (ARDS)

Despite advances in drug delivery technologies, treating acute respiratory distress syndrome (ARDS) is challenging due to pathophysiological barriers such as lung injury, oedema fluid build-up, and lung inflammation. Active pharmaceutical ingredients (API) can be delivered directly to the lung site of action with the use of aerosol-based drug delivery devices, and this circumvents the hepatic first-pass effect and improves the bioavailability of drugs. This review discusses the various challenges and barriers for pulmonary drug delivery, current interventions for delivery, considerations for effective drug delivery, and the use of nanoparticle drug delivery carriers as potential strategies for delivering therapeutics in ARDS. Nanosystems have the added benefit of entrapping drugs, increase pulmonary drug bioavailability, and using biocompatible and biodegradable excipients that can facilitate targeted and/or controlled delivery. These systems provide an alternative to existing conventional systems. An effective way to deliver drugs for the treatment of ARDS can be by using colloidal systems that are aerosolized or inhaled. Drug distribution to the deeper pulmonary tissues is necessary due to the significant endothelial cell destruction that is prevalent in ARDS. The particle size of nanoparticles (<0.5 μm) makes them ideal candidates for treating ARDS as they can reach the alveoli. A look into the various potential benefits and limitations of nanosystems used for other lung disorders is also considered to indicate how they may be useful for the potential treatment of ARDS.

Smoking on the risk of acute respiratory distress syndrome: a systematic review and meta-analysis

BACKGROUND

The relationship between smoking and the risk of acute respiratory distress syndrome (ARDS) has been recognized, but the conclusions have been inconsistent. This systematic review and meta-analysis investigated the association between smoking and ARDS risk in adults.

METHODS

The PubMed, EMBASE, Cochrane Library, and Web of Science databases were searched for eligible studies published from January 1, 2000, to December 31, 2023. We enrolled adult patients exhibiting clinical risk factors for ARDS and smoking condition. Outcomes were quantified using odds ratios (ORs) for binary variables and mean differences (MDs) for continuous variables, with a standard 95% confidence interval (CI).

RESULTS

A total of 26 observational studies involving 36,995 patients were included. The meta-analysis revealed a significant association between smoking and an increased risk of ARDS (OR 1.67; 95% CI 1.33-2.08; P < 0.001). Further analysis revealed that the associations between patient-reported smoking history and ARDS occurrence were generally similar to the results of all the studies (OR 1.78; 95% CI 1.38-2.28; P < 0.001). In contrast, patients identified through the detection of tobacco metabolites (cotinine, a metabolite of nicotine, and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), a metabolite of tobacco products) showed no significant difference in ARDS risk (OR 1.19; 95% CI 0.69-2.05; P = 0.53). The smoking group was younger than the control group (MD - 7.15; 95% CI - 11.58 to - 2.72; P = 0.002). Subgroup analysis revealed that smoking notably elevated the incidence of ARDS with extrapulmonary etiologies (OR 1.85; 95% CI 1.43-2.38; P < 0.001). Publication bias did not affect the integrity of our conclusions. Sensitivity analysis further reinforced the reliability of our aggregated outcomes.

CONCLUSIONS

There is a strong association between smoking and elevated ARDS risk. This emphasizes the need for thorough assessment of patients' smoking status, urging healthcare providers to vigilantly monitor individuals with a history of smoking, especially those with additional extrapulmonary risk factors for ARDS.

Acute Respiratory Distress Syndrome: Definition, Diagnosis, and Routine Management

Acute respiratory distress syndrome (ARDS) is an acute inflammatory lung injury characterized by severe hypoxemic respiratory failure, bilateral opacities on chest imaging, and low lung compliance. ARDS is a heterogeneous syndrome that is the common end point of a wide variety of predisposing conditions, with complex pathophysiology and underlying mechanisms. Routine management of ARDS is centered on lung-protective ventilation strategies such as low tidal volume ventilation and targeting low airway pressures to avoid exacerbation of lung injury, as well as a conservative fluid management strategy.

Aspiration Pneumonia

Aspiration pneumonia is a lower respiratory tract infection that results from inhalation of foreign material, often gastric and oropharyngeal contents. It is important to distinguish this from a similar entity, aspiration with chemical pneumonitis, as treatment approaches may differ. An evolving understanding of the human microbiome has shed light on the pathogenesis of aspiration pneumonia, suggesting that dysbiosis, repetitive injury, and inflammatory responses play a role in its development. Risk factors for aspiration events involve a complex interplay of anatomical and physiological dysfunctions in the nervous, gastrointestinal, and pulmonary systems. Current treatment strategies have shifted away from anaerobic organisms as leading pathogens. Prevention of aspiration pneumonia primarily involves addressing oropharyngeal dysphagia, a significant risk factor for aspiration pneumonia, particularly among elderly individuals and those with cognitive and neurodegenerative disorders.

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.

Effect of a physician-nurse integrated lung protection care model in neurocritical patients

Background

Lung injury resulting from diffuse pulmonary interstitial and other lung-related complications is a significant contributor to poor prognosis and mortality in patients with critical neurological diseases. To enhance patient outcomes, it is essential to investigate a lung protection model that involves the collaboration of doctors, nurses, and other medical professionals.

Methods

Patients receiving different care styles were divided into two groups: routine care (RC) and lung function protection care (LFPC). The LFPC group included airway and posture management, sedation and analgesia management, positive end-expiratory pressure titration in ventilation management, and fluid volume management, among others. Statistical analysis methods, such as chi-square, were used to compare the incidence of acute lung injury (ALI), neurogenic pulmonary edema (NPE), ventilator-associated pneumonia (VAP), acute respiratory distress syndrome (ARDS), and length of stay between the RC and LFPC groups.

Results

The RC group included 68 patients (33 males; 34-74 years of age). The LFPC group included 60 patients (29 males; 37-73 years of age). Compared with the RC group, the LFPC group had lower occurrence rates of ALI (20.0 % vs. 38.2 %, P = 0.024), NPE (8.3 % vs. 23.5 %, P = 0.021), VAP (8.3 % vs. 25.0 %, P = 0.013), and ARDS (1.7 % vs. 16.2 %, P = 0.015). The length of hospital stay was shorter in the LFPC group than in the RC group (11.3 ± 3.5 vs. 14.3 ± 4.4 days, P = 0.0001).

Conclusion

The physician-nurse integrated lung protection care model proved to be effective in improving outcomes, reducing complications, and shortening the hospital stay length for neurocritical patients.

Adherence to lung protective mechanical ventilation in patients admitted to a surgical intensive care unit and the associated increased mortality

Background

The adherence rate to the lung protective ventilation (LPV) strategy, which is generally accepted as a standard practice in mechanically ventilated patients, reported in the literature is approximately 40%. This study aimed to determine the adherence rate to the LPV strategy, factors associated with this adherence, and related clinical outcomes in mechanically ventilated patients admitted to the surgical intensive care unit (SICU).

Methods

This prospective observational study was conducted in the SICU of a tertiary university-based hospital between April 2018 and February 2019. Three hundred and six adult patients admitted to the SICU who required mechanical ventilation support for more than 12 h were included. Ventilator parameters at the initiation of mechanical ventilation support in the SICU were recorded. The LPV strategy was defined as ventilation with a tidal volume of equal or less than 8 ml/kg of predicted body weight plus positive end-expiratory pressure of at least 5 cm H2O. Demographic and clinical data were recorded and analyzed.

Results

There were 306 patients included in this study. The adherence rate to the LPV strategy was 36.9%. Height was the only factor associated with adherence to the LPV strategy (odds ratio for each cm, 1.10; 95% confidence interval (CI), 1.06-1.15). Cox regression analysis showed that the LPV strategy was associated with increased 90-day mortality (hazard ratio, 1.73; 95% CI, 1.02-2.94).

Conclusion

The adherence rate to the LPV strategy among patients admitted to the SICU was modest. Further studies are warranted to explore whether the application of the LPV strategy is simply a marker of disease severity or a causative factor for increased mortality.

Gastroesophageal reflux disease and the risk of respiratory diseases: a Mendelian randomization study

BACKGROUND

Observational studies have suggested a suspected association between gastroesophageal reflux disease (GERD) and respiratory diseases, but the causality remains equivocal. The goal of this study was to evaluate the causal role of GERD in respiratory diseases by employing Mendelian randomization (MR) studies.

METHODS

We conducted Mendelian randomization analysis based on summary data of genome-wide association studies (GWASs) and three MR statistical techniques (inverse variance weighted, weighted median and MR-Egger) were employed to assess the probable causal relationship between GERD and the risk of respiratory diseases. Sensitivity analysis was also carried out to ensure more trustworthy results, which involves examining the heterogeneity, pleiotropy and leave-one-SNP-out method. We also identified 33 relevant genes and explored their distribution in 26 normal tissues.

RESULTS

In the analysis, for every unit increase in developing GERD, the odds ratio for developing COPD, bronchitis, pneumonia, lung cancer and pulmonary embolism rose by 72% (ORIVW = 1.72, 95% CI 1.50; 1.99), 19% (ORIVW = 1.19, 95% CI 1.11; 1.28), 16% (ORIVW = 1.16, 95% CI 1.07; 1.26), 0. 3% (ORIVW = 1.003, 95% CI 1.0012; 1.0043) and 33% (ORIVW = 1.33, 95% CI 1.12; 1.58), respectively, in comparison with non-GERD cases. In addition, neither heterogeneity nor pleiotropy was found in the study. This study also found that gene expression was higher in the central nervous system and brain tissue than in other normal tissues.

CONCLUSIONS

This study provided evidence that people who developed GERD had a higher risk of developing COPD, bronchitis, pneumonia, lung cancer and pulmonary embolism. Our research suggests physicians to give effective treatments for GERD on respiratory diseases. By exploring the gene expression, our study may also help to reveal the role played by the central nervous system and brain tissue in developing respiratory diseases caused by GERD.

Optimizing the Synergistic Potential of Pseudo-Labels from Radiology Notes and Annotated Ground Truth in Identifying Pulmonary Opacities on Chest Radiographs for Early Detection of Acute Respiratory Distress Syndrome

Acute Respiratory Distress Syndrome (ARDS) is a life-threatening lung injury, hallmarks of which are bilateral radiographic opacities. Studies have shown that early recognition of ARDS could reduce severity and lethal clinical sequela. A Convolutional Neural Network (CNN) model that can identify bilateral pulmonary opacities on chest x-ray (CXR) images can aid early ARDS recognition. Obtaining large datasets with ground truth labels to train CNNs is challenging, as medical image annotation requires clinical expertise and meticulous consideration. In this work, we implement a natural language processing pipeline that extracts pseudo-labels CXR images by parsing radiology notes for abnormal findings. We obtain ground-truth annotations from clinicians for the presence of pulmonary opacities for a subset of these images. A knowledge distillation-based teacher-student training framework is implemented to leverage the larger dataset with noisy pseudo-labels. Our results show an AUC of 0.93 (95%CI 0.92-0.94) for the prediction of bilateral opacities on chest radiographs.

A Sequent of Gram-Negative Co-Infectome-Induced Acute Respiratory Distress Syndrome Are Potentially Subtle Aggravators Associated to the SARS-CoV-2 Evolution of Virulence

Acute respiratory distress syndrome (ARDS) is one of the major problems in COVID-19 that is not well understood. ARDS is usually complicated by co-infections in hospitals. Although ARDS is inherited by Europeans and Africans, this is not clear for those from the Middle East. There are severe limitations in correlations made between COVID-19, ARDS, co-infectome, and patient demographics. We investigated 298 patients for associations of ARDS, coinfections, and patient demographics on COVID-19 patients' outcomes. Of the 149 patients examined for ARDS during COVID-19, 16 had an incidence with a higher case fatality rate (CFR) of 75.0% compared to those without ARDS (27.0%) (p value = 0.0001). The co-infectome association showed a CFR of 31.3% in co-infected patients; meanwhile, only 4.8% of those without co-infections (p value = 0.01) died. The major bacteria were Acinetobacter baumannii and Escherichia coli, either alone or in a mixed infection with Klebsiella pneumoniae. Kaplan-Meier survival analysis of COVID-19 patients with and without ARDS revealed a significant difference in the survival time of patients with ARDS (58.8 +/- 2.7 days) and without ARDS (41.9 +/- 1.8 days) (p value = 0.0002). These findings prove that increased hospital time was risky for co-infectome-induced SDRS later on. This also explained that while empiric therapy and lethal ventilations delayed the mortality in 75% of patients, they potentially did not help those without co-infection or ARDS who stayed for shorter times. In addition, the age of patients (n = 298) was significantly associated with ARDS (72.9 +/- 8.9) compared to those without it (56.2 +/- 15.1) and was irrespective of gender. However, there were no significant differences neither in the age of admitted patients before COVID-19 (58.5 +/- 15.3) and during COVID-19 (57.2 +/- 15.5) nor in the gender and COVID-19 fatality (p value 0.546). Thus, Gram-negative co-infectome potentially induced fatal ARDS, aggravating the COVID-19 outcome. These findings are important for the specific differential diagnosis of patients with and without ARDS and co-infections. Future vertical investigations on mechanisms of Gram-negative-induced ARDS are imperative since hypervirulent strains are rapidly circulating. This study was limited as it was a single-center study confined to Ha'il hospitals; a large-scale investigation in major national hospitals would gain more insights.

Predictive value of combination of lung injury prediction score and receptor for advanced glycation end‑products for the occurrence of acute respiratory distress syndrome

The present study evaluated the predictive value of the combination of the lung injury prediction score (LIPS) and receptor for advanced glycation end-products (RAGE) for the occurrence of acute respiratory distress syndrome (ARDS) in critically ill patients with ARDS risk factors. A total of 551 patients with risk factors of ARDS were divided into an ARDS group and a non-ARDS group. LIPS was computed within 6 h of admission into the ICU, and the plasma concentration of RAGE was detected within 24 h of admission. Multivariate analysis was performed to identify independent associations, and the predictive values for ARDS occurrence were assessed with receiver operating characteristic (ROC) curve. Within 7 days after admission into the ICU, ARDS occurred in 176 patients (31.9%). Multivariate analysis demonstrated that LIPS [odds ratio (OR), 1.282; 95% confidence interval (CI), 1.108-1.604], RAGE levels (OR, 2.359; 95% CI, 1.351-4.813) and Acute Physiology and Chronic Health Evaluation II score (OR, 1.167; 95% CI, 1.074-1.485) were independently associated with ARDS occurrence. ROC curves demonstrated that the area under curve (AUC) of LIPS, RAGE levels and their combination was 0.714 [standard error (SE), 0.023; 95% CI, 0.670-0.759], 0.709 (SE, 0.025; 95% CI, 0.660-0.758) and 0.889 (SE, 0.014; 95% CI, 0.861-0.917), respectively. The AUC of LIPS combined with RAGE levels was significantly higher compared with those of LIPS (0.889 vs. 0.714; Z=6.499; P<0.001) and RAGE (0.889 vs. 0.709; Z=6.282; P<0.001) levels alone. In conclusion, both LIPS and RAGE levels were independently associated with ARDS occurrence in critically ill patients with ARDS risk factors, and had medium predictive values for ARDS occurrence. Combination of LIPS with RAGE levels increased the predictive value for ARDS occurrence.

Inflammatory subphenotypes in patients at risk of ARDS: evidence from the LIPS-A trial

PURPOSE

Latent class analysis (LCA) has identified hyper- and non-hyper-inflammatory subphenotypes in patients with acute respiratory distress syndrome (ARDS). It is unknown how early inflammatory subphenotypes can be identified in patients at risk of ARDS. We aimed to test for inflammatory subphenotypes upon presentation to the emergency department.

METHODS

LIPS-A was a trial of aspirin to prevent ARDS in at-risk patients presenting to the emergency department. In this secondary analysis, we performed LCA using clinical, blood test, and biomarker variables.

RESULTS

Among 376 (96.4%) patients from the LIPS-A trial, two classes were identified upon presentation to the emergency department (day 0): 72 (19.1%) patients demonstrated characteristics of a hyper-inflammatory and 304 (80.9%) of a non-hyper-inflammatory subphenotype. 15.3% of patients in the hyper- and 8.2% in the non-hyper-inflammatory class developed ARDS (p = 0.07). Patients in the hyper-inflammatory class had fewer ventilator-free days (median [interquartile range, IQR] 28[23-28] versus 28[27-28]; p = 0.010), longer intensive care unit (3[2-6] versus 0[0-3] days; p < 0.001) and hospital (9[6-18] versus 5[3-9] days; p < 0.001) length of stay, and higher 1-year mortality (34.7% versus 20%; p = 0.008). Subphenotypes were identified on day 1 and 4 in a subgroup with available data (n = 244). 77.9% of patients remained in their baseline class throughout day 4. Patients with a hyper-inflammatory subphenotype throughout the study period (n = 22) were at higher risk of ARDS (36.4% versus 10.4%; p = 0.003).

CONCLUSION

Hyper- and non-hyper-inflammatory subphenotypes may precede ARDS development, remain identifiable over time, and can be identified upon presentation to the emergency department. A hyper-inflammatory subphenotype predicts worse outcomes.

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.

Postoperative acute respiratory distress syndrome in randomized controlled trials

BACKGROUND

Acute respiratory distress syndrome is a potentially fatal postoperative complication. We aimed to estimate temporal trends of the representation of patients with postoperative acute respiratory distress syndrome in clinical trials, determine their distinct clinical features, and identify predictors of mortality.

METHODS

This is a secondary analysis of 7 randomized controlled clinical trials conducted by the Acute Respiratory Distress Syndrome Network and the Clinical Trials Network for the Prevention and Early Treatment of Acute Lung Injury. Patients with acute respiratory distress syndrome were classified into a postoperative acute respiratory distress syndrome group (ie, patients who had undergone elective surgery in the immediate period before trial enrollment) and a non-postoperative acute respiratory distress syndrome group.

RESULTS

Out of 5,316 patients with acute respiratory distress syndrome, 256 (4.8%) had postoperative acute respiratory distress syndrome. Representation of postoperative acute respiratory distress syndrome in trials gradually declined from 2000 to 2011, but it remained stable afterward at 2.7%. Postoperative acute respiratory distress syndrome was associated with lower 90-day mortality (24.6% vs 30.9%, P = .032) than non-postoperative acute respiratory distress syndrome, even after adjusting for age, acute respiratory distress syndrome severity, usage of vasopressors at baseline, and the study publication year (hazard ratio 0.63, 95% confidence interval 0.49-0.82). Age (odds ratio 1.07, 95% confidence interval 1.04-1.09), immunosuppression (odds ratio 4.12, 95% confidence interval 1.43-11.86), and positive fluid balance (odds ratio 1.09, 95% confidence interval 1.04-1.14) were associated with 90-day mortality among patients with postoperative acute respiratory distress syndrome.

CONCLUSION

Representation of postoperative acute respiratory distress syndrome in trials of the Acute Respiratory Distress Syndrome Network and the Clinical Trials Network for the Prevention and Early Treatment of Acute Lung Injury gradually declined from 2000 to 2011 but remained stable afterward. Postoperative acute respiratory distress syndrome was associated with lower mortality than non-postoperative acute respiratory distress syndrome. These findings may put both temporal trends and the prognosis of postoperative acute respiratory distress syndrome in perspective. Also, positive fluid balance was associated with the mortality of patients with postoperative acute respiratory distress syndrome.

Effects of intravenous sivelestat sodium on prevention of acute respiratory distress syndrome in patients with sepsis: study protocol for a double-blind multicentre randomised controlled trial

INTRODUCTION

Sepsis is one of the most common risk factors for acute respiratory distress syndrome (ARDS). Neutrophil elastase (NE) is believed to be an important mediator of ARDS. When sepsis occurs, a large number of inflammatory factors are activated and released, which makes neutrophils migrate into the lung, eventually leading to the occurrence of ARDS. Sivelestat sodium is an NE inhibitor that can inhibit the inflammatory reaction during systemic inflammatory response syndrome and alleviate lung injury. Therefore, we hypothesise that intravenous sivelestat sodium may prevent the occurrence of ARDS in patients with sepsis.

METHODS AND ANALYSIS

This is a prospective, investigator-initiated, double-blind, adaptive, multicentre, randomised, controlled clinical trial with an adaptive 'sample size re-estimation' design. Patients meeting the inclusion criteria who were transferred into the intensive care unit will be randomly assigned to receive sivelestat sodium or placebo for up to 7 days. The primary outcome is the development of ARDS within 7 days after randomisation. A total of 238 patients will be recruited based on a 15% decrease in the incidence of ARDS in the intervention group in this study. A predefined interim analysis will be performed to ensure that the calculation is reasonable after reaching 50% (120) of the planned sample size.

ETHICS AND DISSEMINATION

The study protocol was approved by the Ethics Committee of ZhongDa Hospital affiliated to Southeast University (identifier: Clinical Ethical Approval No. 2021ZDSYLL153-P03). Results will be submitted for publication in peer-reviewed journals and presented at relevant conferences and meetings.

TRIAL REGISTRATION NUMBER

NCT04973670.

Early plasma proteomic biomarkers and prediction model of acute respiratory distress syndrome after cardiopulmonary bypass: a prospective nested cohort study

BACKGROUND

Early recognition of the risk of acute respiratory distress syndrome (ARDS) after cardiopulmonary bypass (CPB) may improve clinical outcomes. The main objective of this study was to identify proteomic biomarkers and develop an early prediction model for CPB-ARDS.

METHODS

The authors conducted three prospective nested cohort studies of all consecutive patients undergoing cardiac surgery with CPB at Union Hospital of Tongji Medical College Hospital. Plasma proteomic profiling was performed in ARDS patients and matched controls (Cohort 1, April 2021-July 2021) at multiple timepoints: before CPB (T1), at the end of CPB (T2), and 24 h after CPB (T3). Then, for Cohort 2 (August 2021-July 2022), biomarker expression was measured and verified in the plasma. Furthermore, lung ischemia/reperfusion injury (LIRI) models and sham-operation were established in 50 rats to explore the tissue-level expression of biomarkers identified in the aforementioned clinical cohort. Subsequently, a machine learning-based prediction model incorporating protein and clinical predictors from Cohort 2 for CPB-ARDS was developed and internally validated. Model performance was externally validated on Cohort 3 (January 2023-March 2023).

RESULTS

A total of 709 proteins were identified, with 9, 29, and 35 altered proteins between ARDS cases and controls at T1, T2, and T3, respectively, in Cohort 1. Following quantitative verification of several predictive proteins in Cohort 2, higher levels of thioredoxin domain containing 5 (TXNDC5), cathepsin L (CTSL), and NPC intracellular cholesterol transporter 2 (NPC2) at T2 were observed in CPB-ARDS patients. A dynamic online predictive nomogram was developed based on three proteins (TXNDC5, CTSL, and NPC2) and two clinical risk factors (CPB time and massive blood transfusion), with excellent performance (precision: 83.33%, sensitivity: 93.33%, specificity: 61.16%, and F1 score: 85.05%). The mean area under the receiver operating characteristics curve (AUC) of the model after 10-fold cross-validation was 0.839 (95% CI: 0.824-0.855). Model discrimination and calibration were maintained during external validation dataset testing, with an AUC of 0.820 (95% CI: 0.685-0.955) and a Brier Score of 0.177 (95% CI: 0.147-0.206). Moreover, the considerably overexpressed TXNDC5 and CTSL proteins identified in the plasma of patients with CPB-ARDS, exhibited a significant upregulation in the lung tissue of LIRI rats.

CONCLUSIONS

This study identified several novel predictive biomarkers, developed and validated a practical prediction tool using biomarker and clinical factor combinations for individual prediction of CPB-ARDS risk. Assessing the plasma TXNDC5, CTSL, and NPC2 levels might identify patients who warrant closer follow-up and intensified therapy for ARDS prevention following major surgery.

Reliability of the respiratory rate and oxygenation index for successful high-flow nasal cannula support in coronavirus disease pneumonia: a retrospective cohort study

BACKGROUND

High-flow nasal cannula (HFNC) therapy is an important non-invasive respiratory support in acute respiratory failure, including coronavirus disease (COVID-19) pneumonia. Although the respiratory rate and oxygenation (ROX) index is a simple and useful predictor for HFNC failure and mortality, there is limited evidence for its use in patients with COVID-19 pneumonia. We aimed to evaluate the ROX index as a predictor for HFNC failure in patients with COVID-19 pneumonia. We also evaluated the ROX index as a predictor for 28-day mortality.

METHODS

In this single-center, retrospective, cohort study, 248 patients older than 18 years of age with COVID-19 pneumonia received HFNC therapy for acute respiratory failure. The ROX index was evaluated within 4 h from the start of HFNC therapy. Past medical history, laboratory data, and the ROX index were evaluated as predictors for HFNC failure and 28-day mortality.

RESULTS

The ROX index < 4.88 showed a significantly high risk ratio for HFNC failure (2.13 [95% confidence interval [CI]: 1.47 - 3.08], p < 0.001). The ROX index < 4.88 was significantly associated with 28-day mortality (p = 0.049) in patients with COVID-19 pneumonia receiving HFNC therapy. Age, chronic hypertension, high lactate dehydrogenase level, and low ROX index showed significantly high risk ratio for HFNC failure. C-reactive protein level and low ROX index were predictors of 28-day morality.

CONCLUSION

The ROX index is a useful predictor for HFNC success and 28-day mortality in patients with COVID-19 pneumonia receiving HFNC therapy.

TRIAL REGISTRATION

An independent ethics committee approved the study (Research Ethics Review Committee of Kobe City Medical Center General Hospital [number: zn220303; date: February 21, 2022]), which was performed in accordance with the Declaration of Helsinki, Guidelines for Good Clinical Practice.

Exposure to ambient air pollutants and acute respiratory distress syndrome risk in sepsis

PURPOSE

Exposures to ambient air pollutants may prime the lung enhancing risk of acute respiratory distress syndrome (ARDS) in sepsis. Our objective was to determine the association of short-, medium-, and long-term pollutant exposures and ARDS risk in critically ill sepsis patients.

METHODS

We analyzed a prospective cohort of 1858 critically ill patients with sepsis, and estimated short- (3 days), medium- (6 weeks), and long- (5 years) term exposures to ozone, nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), particulate matter < 2.5 μm (PM2.5), and PM < 10 μm (PM10) using weighted averages of daily levels from monitors within 50 km of subjects' residences. Subjects were followed for 6 days for ARDS by the Berlin Criteria. The association between each pollutant and ARDS was determined using multivariable logistic regression adjusting for preselected confounders. In 764 subjects, we measured plasma concentrations of inflammatory proteins at presentation and tested for an association between pollutant exposure and protein concentration via linear regression.

RESULTS

ARDS developed in 754 (41%) subjects. Short- and long-term exposures to SO2, NO2, and PM2.5 were associated with ARDS risk (SO2: odds ratio (OR) for the comparison of the 75-25th long-term exposure percentile 1.43 (95% confidence interval (CI) 1.16, 1.77); p < 0.01; NO2: 1.36 (1.06, 1.74); p = 0.04, PM2.5: 1.21 (1.04, 1.41); p = 0.03). Long-term exposures to these three pollutants were also associated with plasma interleukin-1 receptor antagonist and soluble tumor necrosis factor receptor-1 concentrations.

CONCLUSION

Short and long-term exposures to ambient SO2, PM2.5, and NO2 are associated with increased ARDS risk in sepsis, representing potentially modifiable environmental risk factors for sepsis-associated ARDS.

The role of artificial neural networks in prediction of severe acute pancreatitis associated acute respiratory distress syndrome: A retrospective study

Early identification and intervention of acute respiratory distress syndrome (ARDS) are particularly important. This study aimed to construct predictive models for ARDS following severe acute pancreatitis (SAP) by artificial neural networks and logistic regression. The artificial neural networks model was constructed using clinical data from 214 SAP patients. The patient cohort was randomly divided into a training set and a test set, with 149 patients allocated to the training set and 65 patients assigned to the test set. The artificial neural networks and logistic regression models were trained by the training set, and then the performance of both models was evaluated using the test set. The sensitivity, specificity, PPV, NPV, accuracy, and AUC value of artificial neural networks model were 68.0%, 87.5%, 77.3%, 81.4%, 80.0%, 0.853 ± 0.054 (95% CI: 0.749-0.958). The sensitivity, specificity, PPV, NPV, accuracy and AUC value of logistic regression model were 48.7%, 85.3%, 65.5%, 74.4%, 72.0%, 0.799 ± 0.045 (95% CI: 0.710-0.888). There were no significant differences between the artificial neural networks and logistic regression models in predictive performance. Bedside Index of Severity in Acute Pancreatitis score, procalcitonin, prothrombin time, and serum calcium were the most important predictive variables in the artificial neural networks model. The discrimination abilities of logistic regression and artificial neural networks models in predicting SAP-related ARDS were similar. It is advisable to choose the model according to the specific research purpose.

A targeted metabolomics approach for sepsis-induced ARDS and its subphenotypes

BACKGROUND

Acute respiratory distress syndrome (ARDS) is etiologically and clinically a heterogeneous disease. Its diagnostic characteristics and subtype classification, and the application of these features to treatment, have been of considerable interest. Metabolomics is becoming important for identifying ARDS biology and distinguishing its subtypes. This study aimed to identify metabolites that could distinguish sepsis-induced ARDS patients from non-ARDS controls, using a targeted metabolomics approach, and to identify whether sepsis-induced direct and sepsis-induced indirect ARDS are metabolically distinct groups, and if so, confirm their metabolites and associated pathways.

METHODS

This study retrospectively analyzed 54 samples of ARDS patients from a sepsis registry that was prospectively collected from March 2011 to February 2018, along with 30 non-ARDS controls. The cohort was divided into direct and indirect ARDS. Metabolite concentrations of five analyte classes (energy metabolism, free fatty acids, amino acids, phospholipids, sphingolipids) were measured using liquid chromatography-tandem mass spectrometry and gas chromatography-mass spectrometry by targeted metabolomics.

RESULTS

In total, 186 metabolites were detected. Among them, 102 metabolites could differentiate sepsis-induced ARDS patients from the non-ARDS controls, while 14 metabolites could discriminate sepsis-induced ARDS subphenotypes. Using partial least-squares discriminant analysis, we showed that sepsis-induced ARDS patients were metabolically distinct from the non-ARDS controls. The main distinguishing metabolites were lysophosphatidylethanolamine (lysoPE) plasmalogen, PE plasmalogens, and phosphatidylcholines (PCs). Sepsis-induced direct and indirect ARDS were also metabolically distinct subgroups, with differences in lysoPCs. Glycerophospholipid and sphingolipid metabolism were the most significant metabolic pathways involved in sepsis-induced ARDS biology and in sepsis-induced direct/indirect ARDS, respectively.

CONCLUSION

Our study demonstrated a marked difference in metabolic patterns between sepsis-induced ARDS patients and non-ARDS controls, and between sepsis-induced direct and indirect ARDS subpheonotypes. The identified metabolites and pathways can provide clues relevant to the diagnosis and treatment of individuals with ARDS.

Respiratory Distress Complicating Falciparum Malaria Imported to Berlin, Germany: Incidence, Burden, and Risk Factors

While European healthcare systems face resource shortages as a consequence of the coronavirus pandemic, numbers of imported falciparum malaria cases increased again with re-intensifying international travel. The aim of the study was to identify malaria-specific complications associated with a prolonged intensive care unit (ICU) length of stay (ICU-LOS) in the pre-COVID-19 era and to determine targets for their prevention. This retrospective observational investigation included all the cases treated from 2001 to 2015 at the Charité University Hospital, Berlin. The association of malaria-specific complications with the ICU-LOS was assessed using a multivariate Cox proportional hazard regression. The risk factors for the individual complications were determined using a multivariate Bayesian logistic regression. Among the 536 included cases, 68 (12.7%) required intensive care and 55 (10.3%) suffered from severe malaria (SM). The median ICU-LOS was 61 h (IQR 38-91 h). Respiratory distress, which occurred in 11 individuals (2.1% of the total cases, 16.2% of the ICU patients, and 20% of the SM cases), was the only complication independently associated with ICU-LOS (adjusted hazard ratio for ICU discharge by 61 h 0.24, 95% confidence interval, 95%CI, 0.08-0.75). Shock (adjusted odds ratio, aOR, 11.5; 95%CI, 1.5-113.3), co-infections (aOR 7.5, 95%CI 1.2-62.8), and each mL/kg/h fluid intake in the first 24 treatment hours (aOR 2.2, 95%CI 1.1-5.1) were the independent risk factors for its development. Respiratory distress is not rare in severe imported falciparum malaria, and it is associated with a substantial burden. Cautious fluid management, including in shocked individuals, and the control of co-infections may help prevent its development and thereby reduce the ICU-LOS.

Factors associated with acute respiratory distress syndrome in brain-injured patients: A systematic review and meta-analysis

PURPOSE

Acute respiratory distress syndrome (ARDS) is common in patients with acute brain injury admitted to the ICU. We aimed to identify factors associated with ARDS in this population.

METHODS

We searched MEDLINE, Embase, Cochrane Central, Scopus, and Web of Science from inception to January 14, 2022. Three reviewers independently screened articles and selected English-language studies reporting risk factors for ARDS in brain-injured adult patients. Data were extracted on ARDS incidence, adjusted and unadjusted risk factors, and clinical outcomes. Risk of bias was reported using the Quality in Prognostic Studies tool. Certainty of evidence was assessed using GRADE.

RESULTS

We selected 23 studies involving 6,961,284 patients with acute brain injury. The pooled cumulative incidence of ARDS after brain injury was 17.0% (95%CI 10.7-25.8). In adjusted analysis, factors associated with ARDS included sepsis (odds ratio (OR) 4.38, 95%CI 2.37-8.10; high certainty), history of hypertension (OR 3.11, 95%CI 2.31-4.19; high certainty), pneumonia (OR 2.69, 95%CI 2.35-3.10; high certainty), acute kidney injury (OR 1.44, 95%CI 1.30-1.59; moderate certainty), admission hypoxemia (OR 1.67, 95%CI 1.29-2.17; moderate certainty), male sex (OR 1.30, 95%CI 1.06-1.58; moderate certainty), and chronic obstructive pulmonary disease (OR 1.27, 95%CI 1.13-1.44; moderate certainty). Development of ARDS was independently associated with increased odds of in-hospital mortality (OR 3.12, 95% CI 1.39-7.00).

CONCLUSIONS

Multiple risk factors are associated with ARDS in brain-injured patients. These findings could be used to develop prognostic models for ARDS or as prognostic enrichment strategies for patient enrolment in future clinical trials.

Altered Lung Heat Shock Protein-70 Expression and Severity of Sepsis-Induced Acute Lung Injury in a Chronic Kidney Disease Rat Model

Enhanced heat shock protein-70 (HSP-70) expression in the lungs is associated with attenuated acute lung injury (ALI) in a sepsis model. Chronic kidney disease (CKD) significantly contributes to the poor prognosis of patients with sepsis. This study examined the relationship between sepsis-induced ALI severity and altered lung HSP-70 expression in CKD. Experimental rats underwent a sham operation (control group) or 5/6 nephrectomy (CKD group). Sepsis was induced with cecal ligation and puncture (CLP). Laboratory tests and lung harvest were performed in the control group (without CLP and after 3, 12, 24, and 72 h of CLP) and in the CKD group (without CLP and after 72 h of CLP). ALI was the most severe after 12 h of sepsis. The mean lung injury score at 72 h after sepsis was significantly higher in the CKD group than in the control group (4.38 versus 3.30, p < 0.01). Nonetheless, enhanced lung HSP-70 expression was not observed in the CKD group. This study shows that altered lung HSP-70 expression is associated with the worsening of sepsis-induced ALI in patients with CKD. Enhancing lung HSP-70 is a novel treatment target for patients with CKD and sepsis-induced ALI.

A prediction model for predicting the risk of acute respiratory distress syndrome in sepsis patients: a retrospective cohort study

BACKGROUND

The risk of death in sepsis patients with acute respiratory distress syndrome (ARDS) was as high as 20-50%. Few studies focused on the risk identification of ARDS among sepsis patients. This study aimed to develop and validate a nomogram to predict the ARDS risk in sepsis patients based on the Medical Information Mart for Intensive Care IV database.

METHODS

A total of 16,523 sepsis patients were included and randomly divided into the training and testing sets with a ratio of 7:3 in this retrospective cohort study. The outcomes were defined as the occurrence of ARDS for ICU patients with sepsis. Univariate and multivariate logistic regression analyses were used in the training set to identify the factors that were associated with ARDS risk, which were adopted to establish the nomogram. The receiver operating characteristic and calibration curves were used to assess the predictive performance of nomogram.

RESULTS

Totally 2422 (20.66%) sepsis patients occurred ARDS, with the median follow-up time of 8.47 (5.20, 16.20) days. The results found that body mass index, respiratory rate, urine output, partial pressure of carbon dioxide, blood urea nitrogen, vasopressin, continuous renal replacement therapy, ventilation status, chronic pulmonary disease, malignant cancer, liver disease, septic shock and pancreatitis might be predictors. The area under the curve of developed model were 0.811 (95% CI 0.802-0.820) in the training set and 0.812 (95% CI 0.798-0.826) in the testing set. The calibration curve showed a good concordance between the predicted and observed ARDS among sepsis patients.

CONCLUSION

We developed a model incorporating thirteen clinical features to predict the ARDS risk in patients with sepsis. The model showed a good predictive ability by internal validation.

Intraoperative Ventilator Management of the Critically Ill Patient

Strategies for the intraoperative ventilator management of the critically ill patient focus on parameters used for lung protective ventilation with acute respiratory distress syndrome, preventing or limiting the deleterious effects of mechanical ventilation, and optimizing anesthetic and surgical conditions to limit postoperative pulmonary complications for patients at risk. Patient conditions such as obesity, sepsis, the need for laparoscopic surgery, or one-lung ventilation may benefit from intraoperative lung protective ventilation strategies. Anesthesiologists can use risk evaluation and prediction tools, monitor advanced physiologic targets, and incorporate new innovative monitoring techniques to develop an individualized approach for patients.

Postoperative Respiratory Failure and Advanced Ventilator Settings

Postoperative respiratory failure has a multifactorial etiology, of which atelectasis is the most common mechanism. Its injurious effects are magnified by surgical inflammation, high driving pressures, and postoperative pain. Chest physiotherapy and noninvasive ventilation are good options to prevent progression of respiratory failure. Acute respiratory disease syndrome is a late and severe finding, which is associated with high morbidity and mortality. If present, proning is a safe, effective, and underutilized therapy. Extracorporeal membrane oxygenation is an option only when traditional supportive measures have failed.

Predicting Persistent Acute Respiratory Failure in Acute Pancreatitis: The Accuracy of Two Lung Injury Indices

BACKGROUND/AIMS

Early and accurate identification of patients with acute pancreatitis (AP) at high risk of persistent acute respiratory failure (PARF) is crucial. We sought to determine the accuracy of simplified Lung Injury Prediction Score (sLIPS) and simplified Early Acute Lung Injury (sEALI) for predicting PARF in ward AP patients.

METHODS

Consecutive AP patients in a training cohort from West China Hospital of Sichuan University (n = 912) and a validation cohort from The First Affiliated Hospital of Nanchang University (n = 1033) were analyzed. PARF was defined as oxygen in arterial blood/fraction of inspired oxygen < 300 mmHg that lasts for > 48 h. The sLIPS was composed by shock (predisposing condition), alcohol abuse, obesity, high respiratory rate, low oxygen saturation, high oxygen requirement, hypoalbuminemia, and acidosis (risk modifiers). The sEALI was calculated from oxygen 2 to 6 L/min, oxygen > 6 L/min, and high respiratory rate. Both indices were calculated on admission.

RESULTS

PARF developed in 16% (145/912) and 22% (228/1033) (22%) of the training and validation cohorts, respectively. In these patients, sLIPS and sEALI were significantly increased. sLIPS ≥ 2 predicted PARF in the training (AUROC 0.87, 95% CI 0.84-0.89) and validation (AUROC 0.81, 95% CI 0.78-0.83) cohorts. sLIPS was significantly more accurate than sEALI and current clinical scoring systems in both cohorts (all P < 0.05).

CONCLUSIONS

Using routinely available clinical data, the sLIPS can accurately predict PARF in ward AP patients and outperforms the sEALI and current existing clinical scoring systems.

To Establish an Early Prediction Model for Acute Respiratory Distress Syndrome in Severe Acute Pancreatitis Using Machine Learning Algorithm

OBJECTIVE

To develop binary and quaternary classification prediction models in patients with severe acute pancreatitis (SAP) using machine learning methods, so that doctors can evaluate the risk of patients with acute respiratory distress syndrome (ARDS) and severe ARDS at an early stage.

METHODS

A retrospective study was conducted on SAP patients hospitalized in our hospital from August 2017 to August 2022. Logical Regression (LR), Random Forest (RF), Support Vector Machine (SVM), Decision Tree (DT), and eXtreme Gradient Boosting (XGB) were used to build the binary classification prediction model of ARDS. Shapley Additive explanations (SHAP) values were used to interpret the machine learning model, and the model was optimized according to the interpretability results of SHAP values. Combined with the optimized characteristic variables, four-class classification models, including RF, SVM, DT, XGB, and Artificial Neural Network (ANN), were constructed to predict mild, moderate, and severe ARDS, and the prediction effects of each model were compared.

RESULTS

The XGB model showed the best effect (AUC = 0.84) in the prediction of binary classification (ARDS or non-ARDS). According to SHAP values, the prediction model of ARDS severity was constructed with four characteristic variables (PaO₂/FiO₂, APACHE II, SOFA, AMY). Among them, the overall prediction accuracy of ANN is 86%, which is the best.

CONCLUSIONS

Machine learning has a good effect in predicting the occurrence and severity of ARDS in SAP patients. It can also provide a valuable tool for doctors to make clinical decisions.

Admission serum sodium and osmolarity are not associated with the occurrence or outcomes of acute respiratory distress syndrome in critically ill

BACKGROUND

Previous studies suggested that hypernatremia or hyperosmolarity may have protective effects in lung injury. We hypothesized that hypernatremia and/or hyperosmolarity would prevent ARDS.

DESIGN

Retrospective cohort study of all admissions at medical, surgical, and multidisciplinary intensive care units in Mayo Clinic, Rochester from the year of 2009 to 2019. The occurrence of ARDS was identified using a validated computerized search strategy. The association between serum sodium/osmolarity and the occurrence of ARDS was analyzed using a multivariable logistic regression model. The relationship between serum sodium/osmolarity and outcomes of ARDS was analyzed using linear and logistic regression models.

RESULTS

Among 50,498 patients, the serum sodium level on admission did not have a significant association with the occurrence of ARDS, with an adjusted odds ratio of 0.95 [95% CI (0.86, 1.05)]. There was no significant association between calculated serum osmolarity and the occurrence of ARDS, with an adjusted odds ratio of 1.03 [95% CI (1.00, 1.07)]. 1560 patients developed ARDS during the ICU stay. Their serum sodium level and osmolarity level did not have a significant association with their outcomes.

CONCLUSIONS

Admission serum sodium or serum osmolarity were not associated with the occurrence or outcomes of ARDS in ICU.

Novel models for early prediction and prevention of acute respiratory distress syndrome in patients following hepatectomy: A clinical translational study based on 1,032 patients

Background

Acute respiratory distress syndrome (ARDS) is a serious organ failure and postoperative complication. However, the incidence rate, early prediction and prevention of postoperative ARDS in patients undergoing hepatectomy remain unidentified.

Methods

A total of 1,032 patients undergoing hepatectomy between 2019 and 2020, at the Eastern Hepatobiliary Surgery Hospital were included. Patients in 2019 and 2020 were used as the development and validation cohorts, respectively. The incidence rate of ARDS was assessed. A logistic regression model and a least absolute shrinkage and selection operator (LASSO) regression model were used for constructing ARDS prediction models.

Results

The incidence of ARDS was 8.8% (43/490) in the development cohort and 5.7% (31/542) in the validation cohort. Operation time, postoperative aspartate aminotransferase (AST), and postoperative hemoglobin (Hb) were all critical predictors identified by the logistic regression model, with an area under the curve (AUC) of 0.804 in the development cohort and 0.752 in the validation cohort. Additionally, nine predictors were identified by the LASSO regression model, with an AUC of 0.848 in the development cohort and 0.786 in the validation cohort.

Conclusion

We reported the incidence of ARDS in patients undergoing hepatectomy and developed two simple and practical prediction models for early predicting postoperative ARDS in patients undergoing hepatectomy. These tools may improve clinicians' ability to early estimate the risk of postoperative ARDS and timely prevent its emergence.

Association of the C-terminal 42-peptide fragment of alpha-1 antitrypsin with the severity of ARDS: A pilot study

BACKGROUND

Acute respiratory distress syndrome is a life-threatening condition with a hospital mortality rate of up to 40%. Biomarkers related to the pathophysiology of ARDS may not only identify patients at risk but may also serve as potential therapeutic targets. This study examined the association between the proteolytic C-terminal 42-peptide fragment of alpha-1 antitrypsin and ARDS severity.

METHODS

The 42-peptide fragment and interleukin-6 levels were measured in 21 patients with mild-to-moderate ARDS and 47 patients with moderate-to-severe ARDS on days 1, 3, and 5 after diagnosis/admission to the intensive care unit. To elucidate the association between both biomarkers and the PaO₂/FiO₂ ratio, the concentrations of both biomarkers were compared between the two groups, and a multivariate regression analysis was performed.

RESULTS

The concentrations of both biomarkers were higher in patients with moderate-to-severe ARDS. While the PaO₂/FiO₂ ratio increased from day 1 to day 3, the concentrations of both biomarkers decreased. Multivariate regression analysis revealed negative associations between the PaO₂/FiO₂ ratio and both the C-terminal 42-peptide of alpha-1 antitrypsin and interleukin-6 on day 1 (beta: -0.138, p = 0.052; beta: -0.096, p = 0.004) and on day 3 (beta: -0.157, p = 0.045; beta: -0.106, p = 0.043).

INTERPRETATION

The C-terminal 42-peptide of alpha-1 antitrypsin is a new biomarker associated with ARDS severity. Its predictive value in identifying patients at risk of developing moderate-to-severe ARDS must be investigated in additional, independent prospective studies.

Prediction of acute lung injury in severe acute pancreatitis by routine clinical data

AIM

Acute lung injury (ALI) is a common complication of severe acute pancreatitis (SAP) with a high mortality. Early prediction of patients at risk in initial stage can improve the long-term survival.

METHODS

A total of 91 patients with SAP out of 1647 acute pancreatitis patients from January 2015 to December 2020 were considered. A predictive model for SAP-associated ALI was constructed based on the valuable risk factors identified from routine clinical characteristics and plasma biomarkers. The value of the model was evaluated and compared with Lung Injury Prediction Score (LIPS). A nomogram was built to visualize the model.

RESULTS

Diabetes, oxygen supplementation, neutrophil count and D-dimer were found to be associated with ALI in SAP. The predictive model based on these factors had an area under the receiver operating characteristic curve [AUC: 0.88, 95% confidence interval (CI): 0.81-0.95], which was superior to LIPS (AUC: 0.71, 95% CI: 0.60-0.83), also with the higher sensitivity (65%) and specificity (96%) than LIPS (62%, 74%, respectively). Decision curve analysis of the model showed a higher net benefit than LIPS. Visualization by a nomogram facilitated the application of the model.

CONCLUSION

Diabetes, oxygen supplementation, neutrophil count and D-dimer were risk factors for SAP-associated ALI. The combination of these routine clinical data and the model visualization by a nomogram provided a simple and effective way in predicting ALI in the early phase of SAP.

Post-Transplant and In-Hospital Risk Factors for ARDS After Hematopoietic Stem Cell Transplantation

BACKGROUND

ARDS is a serious complication of hematopoietic stem cell transplant (HSCT). Pre-transplant risk factors for developing ARDS after HSCT have been recently identified. The objective of this study was to better understand post-transplant risk factors for developing ARDS after HSCT.

METHODS

This was a nested case-control study. ARDS cases were matched to hospitalized non-ARDS controls by age, type of transplantation (allogeneic vs autologous), and time from transplantation. In a conditional logistic regression model, any potential risk factors were adjusted a priori for risk factors known to be associated with ARDS development.

RESULTS

One hundred and seventy ARDS cases were matched 1:1 to non-ARDS hospitalized controls. Pre-admission, cases were more likely to be on steroids (odds ratio [OR] 1.90 [1.13-3.19], P = .02). At time of admission, cases had lower platelet count (OR 0.95 [0.91-0.99], P = .02), lower bicarbonate (OR 0.94 [0.88-0.99], P = .035), and higher creatinine (OR 1.91 [1.23-2.94], P = .004). During the first 24 h after admission, cases were more likely to have received transfusion (OR 2.41 [1.48-3.94], P < .001), opioids (OR 2.94 [1.67-5.18], P < .001), and have greater fluid administration (OR 1.52 [1.30-1.78], P < .001). During the hospitalization, ARDS cases had higher temperature (OR 1.77 [1.34-2.33], P < .001) and higher breathing frequency (OR 1.52 [1.33-1.74], P < .001). ARDS cases were more likely to have had sepsis (OR 68.0 [15.2-301.7], P < .001), bloodstream infection (OR 4.59 [2.46-8.57], P < .001), and pneumonia (OR 9.76 [5.01-19.00], P < .001).

CONCLUSIONS

Several post-transplant predictors of ARDS development specific to the HSCT population were identified in the pre-hospital and early in-hospital domains. These findings can provide insights into causal mechanisms of ARDS development and be used to develop HSCT-specific risk prediction models.

Case Fatality of Hospitalized Patients with COVID-19 Infection Suffering from Acute Respiratory Distress Syndrome in Germany

Aims: Patients suffering from viral pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are at risk of developing acute respiratory distress syndrome (ARDS). ARDS is a serious complication of COVID-19 that requires early recognition and comprehensive management. Little is known about the concomitant prevalence of both entities in Germany. Thus, we sought to analyze predictors and regional trends of case fatality in patients with COVID-19 and ARDS in Germany. Methods: We analyzed data on the characteristics, comorbidities and in-hospital outcomes for all hospitalized patients with COVID-19 and compared those with and without ARDS in Germany in 2020. Results: Overall, 176,137 hospitalized patients with confirmed COVID-19 were included in this analysis; among these, 11,594 (6.6%) suffered from ARDS. Most patients with ARDS were treated in hospitals in urban areas (n = 6485); proportion rate of mechanical ventilation was higher (45.9%) compared to those treated in hospitals of suburban (36.1%) or rural areas (32.0%). Proportion of ARDS grew exponentially with age until the sixth decade of life. Case-fatality rate was considerably higher in COVID-19 patients with ARDS compared to those without (48.3% vs. 15.8%; p < 0.001). Independent predictors of in-hospital case fatality with an OR > 3 were age ≥ 70 years, severe ARDS, severe liver disease, acute renal failure, stroke, dialysis treatment, shock and necessity of ECMO. Conclusions: The case fatality of COVID-19 patients with ARDS is dramatically high and shows relevant regional disparities. Our findings may help to draw more attention to predictors for in-hospital case fatality in patients hospitalized with COVID-19 and suffering from ARDS.

Clinical characteristics and predictors of burn complicated with smoke inhalation injury: A retrospective analysis

Fire smoke enters the human lungs through the respiratory tract. The damage to the respiratory tract and lung tissue is known as smoke inhalation injury (SII). Fire smoke can irritate airway epithelium cells, weaken endothelial cell adhesion and lyse alveolar type II epithelia cells, leading to emphysema, decreased lung function, pneumonia and risk of acute lung injury/acute respiratory distress syndrome (ARDS). The purpose of the present study was to analyze the clinical characteristics of patients with SII and the risk factors affecting their prognosis. A total of 103 patients with SII admitted between January 2016 to December 2021 to the Burns Unit of the Characteristic Medical Center of Chinese People's Armed Police Force and 983 Hospital of the Joint Logistics Support Force of the Chinese People's Liberation Army were selected for the present study. The demographics and clinical features between different severities of SII were analyzed. Univariate/multivariate logistic regression was used to analyze the potential predictors for severity, ARDS and mortality of patients with SII. Receiver operating characteristic (ROC) curves were used to screen independent risk factors and identify their prediction accuracy. It was concluded that total body surface area (TBSA), III burn area (of total %TBSA), cases of respiratory infections, ARDS morbidity, mortality, acute physiology and chronic health evaluation II, lung injury prediction score, lactic acid, white blood cells (WBC), alanine transaminase, blood urea nitrogen, serum creatinine and uric acid were indicators that were raised with increasing severity of SII. However red blood cells, hemoglobin, platelet count, total protein, albumin, and albumin/globulin were decreased with the increasing severity of SII (P<0.05). WBC >20.91 (10⁹/l) was a reliable indicator for severe SII. Lactic acid >9.60 (mmol/l) demonstrated a high degree of accuracy in predicting ARDS development in patients with SII. Hemoglobin <83.00 (g/l) showed a high degree of accuracy in predicting mortality. In summary, the highlighted assessment parameters could be used to contribute to devising improved treatment plans to preempt worsening conditions (such as shock, ARDS, multiple organ dysfunction syndrome and death).

Effect of Uncomplicated Diabetes Mellitus on Acute Respiratory Distress Syndrome Among COVID-19 Patients in Aseer Region, Saudi Arabia

BACKGROUND

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; an ssRNA virus), which mainly affects the respiratory system but can also cause damage to other body systems. Acute respiratory distress syndrome (ARDS) is a serious complication of COVID-19 that requires early recognition and comprehensive management. ARDS is a diffuse inflammatory process that causes diffuse alveolar damage in the lung.  Aim: The study aimed to assess the effect of uncomplicated diabetes mellitus on ARDS among COVID-19 patients in the Aseer region.

METHODOLOGY

 A retrospective cohort study was conducted in Aseer Central Hospital between July 10, 2021 to Jan 15, 2022 where confirmed inpatient COVID-19 cases in the Aseer region were classified into two groups. The first group was diabetic patients without any diabetes-related complications and confirmed for COVID-19 infection (diabetes group). The second group was confirmed COVID-19 patients free from any chronic disease. Extracted data included patients' diabetes status, medical history, socio-demographic data, COVID-19 infection data and vaccination, experienced signs and symptoms, tachypnea, use of accessory muscles of respiration, nasal flaring, grunting, cyanosis, need for hospitalization, need for mechanical ventilation and ICU admission.  Results: The study included 144 patients with uncomplicated diabetes and 323 healthy patients with COVID-19 infection. The mean age of the diabetic group was 65.4 ± 12.9 years old compared to 40.2 ± 11.9 years old for the healthy group. Only one case of the diabetic group was vaccinated against COVID-19 at the study period versus two cases of the healthy group (P=.925). Also, 14 (9.7%) of the diabetic group were contacted with confirmed COVID-19 cases in comparison to 44 (13.6%) healthy cases (P=.238). A total of five (3.5%) diabetic cases needed mechanical ventilation during hospitalization compared to 23 (7.1%) healthy cases with no statistical significance (P=.125). Also, 12 (8.3%) diabetic cases admitted to ICU versus 42 (13%) of healthy cases (P=.145).  Conclusions: In conclusion, there is a great controversy regarding the effect of diabetes on the progression of COVID-19 infection to ARDS. The current study showed that there was no significant difference between diabetic and healthy COVID-19 infected cases regarding ARDS related clinical factors mainly need of ICU admission and mechanical ventilation.

Curcumin alleviated lipopolysaccharide-induced lung injury via regulating the Nrf2-ARE and NF-κB signaling pathways in ducks

BACKGROUND

Under the intensive modern poultry farming system, the lung of duck is one of the main target organs for various bacterial and viral infections. Curcumin is a kind of natural polyphenol compound for which various beneficial biological functions exist, including being an anti-inflammatory, antioxidant, and antiviral. The aim of this work was to investigate the mechanism of curcumin-alleviated lipopolysaccharide (LPS)-induced lung damage by the nuclear erythroid 2-related factor 2 (Nrf2)-antioxidant reaction element (ARE) and nuclear factor kappa B (NF-κB) signaling pathway in ducks.

RESULTS

In total, 450 one-day-old male specific pathogen-free ducks were randomly assigned into three dietary treatments: CON, basal diet; LPS, basal diet + LPS treatment; LPS + CUR, basal diet + LPS + 500 mg kg^-1 of curcumin. At the end of the experiment (21 days), ducks in LPS treatment were challenged with 5 mg LPS per kilogram of body weight and the other two treatments were injected with the same dose of phosphate-buffered saline solution. The results showed that LPS caused acute inflammation, oxidation stress, and lung injury. Dietary addition of curcumin significantly relieved the oxidation stress and inflammation parameters. Moreover, the results showed that remission may be through the signaling pathways of both Nrf2-ARE and NF-κB.

CONCLUSION

In conclusion, dietary supplementation of 500 mg kg^-1 of curcumin exhibited a lung-protective effect in ducks. This experiment broadens the mode of metabolism actions of curcumin in the target organs and provides an insight for the application of curcumin in waterfowl feed. © 2022 Society of Chemical Industry.

Deep Learning Chest CT for Clinically Precise Prediction of Sepsis-Induced Acute Respiratory Distress Syndrome: A Protocol for an Observational Ambispective Cohort Study

Background: Sepsis commonly causes acute respiratory distress syndrome (ARDS), and ARDS contributes to poor prognosis in sepsis patients. Early prediction of ARDS for sepsis patients remains a clinical challenge. This study aims to develop and validate chest computed tomography (CT) radiomic-based signatures for early prediction of ARDS and assessment of individual severity in sepsis patients. Methods: In this ambispective observational cohort study, a deep learning model, a sepsis-induced acute respiratory distress syndrome (SI-ARDS) prediction neural network, will be developed to extract radiomics features of chest CT from sepsis patients. The datasets will be collected from these retrospective and prospective cohorts, including 400 patients diagnosed with sepsis-3 definition during a period from 1 May 2015 to 30 May 2022. 160 patients of the retrospective cohort will be selected as a discovering group to reconstruct the model and 40 patients of the retrospective cohort will be selected as a testing group for internal validation. Additionally, 200 patients of the prospective cohort from two hospitals will be selected as a validating group for external validation. Data pertaining to chest CT, clinical information, immune-associated inflammatory indicators and follow-up will be collected. The primary outcome is to develop and validate the model, predicting in-hospital incidence of SI-ARDS. Finally, model performance will be evaluated using the area under the curve (AUC) of receiver operating characteristic (ROC), sensitivity and specificity, using internal and external validations. Discussion: Present studies reveal that early identification and classification of the SI-ARDS is essential to improve prognosis and disease management. Chest CT has been sought as a useful diagnostic tool to identify ARDS. However, when characteristic imaging findings were clearly presented, delays in diagnosis and treatment were impossible to avoid. In this ambispective cohort study, we hope to develop a novel model incorporating radiomic signatures and clinical signatures to provide an easy-to-use and individualized prediction of SI-ARDS occurrence and severe degree in patients at early stage.

In vivo molecular imaging stratifies rats with different susceptibilities to hyperoxic acute lung injury

99mTc-hexamethylpropyleneamine oxime (HMPAO) and 99mTc-duramycin in vivo imaging detects pulmonary oxidative stress and cell death, respectively, in rats exposed to >95% O2 (hyperoxia) as a model of acute respiratory distress syndrome (ARDS). Preexposure to hyperoxia for 48 h followed by 24 h in room air (H-T) is protective against hyperoxia-induced lung injury. This study's objective was to determine the ability of 99mTc-HMPAO and 99mTc-duramycin to track this protection and to elucidate underlying mechanisms. Rats were exposed to normoxia, hyperoxia for 60 h, H-T, or H-T followed by 60 h of hyperoxia (H-T + 60). Imaging was performed 20 min after intravenous injection of either 99mTc-HMPAO or 99mTc-duramycin. 99mTc-HMPAO and 99mTc-duramycin lung uptake was 200% and 167% greater (P < 0.01) in hyperoxia compared with normoxia rats, respectively. On the other hand, uptake of 99mTc-HMPAO in H-T + 60 was 24% greater (P < 0.01) than in H-T rats, but 99mTc-duramycin uptake was not significantly different (P = 0.09). Lung wet-to-dry weight ratio, pleural effusion, endothelial filtration coefficient, and histological indices all showed evidence of protection and paralleled imaging results. Additional results indicate higher mitochondrial complex IV activity in H-T versus normoxia rats, suggesting that mitochondria of H-T lungs may be more tolerant of oxidative stress. A pattern of increasing lung uptake of 99mTc-HMPAO and 99mTc-duramycin correlates with advancing oxidative stress and cell death and worsening injury, whereas stable or decreasing 99mTc-HMPAO and stable 99mTc-duramycin reflects hyperoxia tolerance, suggesting the potential utility of molecular imaging for identifying at-risk hosts that are more or less susceptible to progressing to ARDS.

Inhaled aviptadil for the possible treatment of COVID-19 in patients at high risk for ARDS: study protocol for a randomized, placebo-controlled, and multicenter trial

Background

Despite the fast establishment of new therapeutic agents in the management of COVID-19 and large-scale vaccination campaigns since the beginning of the SARS-CoV-2 pandemic in early 2020, severe disease courses still represent a threat, especially to patients with risk factors. This indicates the need for alternative strategies to prevent respiratory complications like acute respiratory distress syndrome (ARDS) associated with COVID-19. Aviptadil, a synthetic form of human vasoactive intestinal peptide, might be beneficial for COVID-19 patients at high risk of developing ARDS because of its ability to influence the regulation of exaggerated pro-inflammatory proteins and orchestrate the lung homeostasis. Aviptadil has recently been shown to considerably improve the prognosis of ARDS in COVID-19 when applied intravenously. An inhaled application of aviptadil has the advantages of achieving a higher concentration in the lung tissue, fast onset of activity, avoiding the hepatic first-pass metabolism, and the reduction of adverse effects. The overall objective of this project is to assess the efficacy and safety of inhaled aviptadil in patients hospitalized for COVID-19 at high risk of developing ARDS.

Methods

This multicenter, placebo-controlled, double-blinded, randomized trial with 132 adult patients hospitalized for COVID-19 and at high risk for ARDS (adapted early acute lung injury score ≥ 2 points) is conducted in five public hospitals in Europe. Key exclusion criteria are mechanical ventilation at baseline, need for intensive care at baseline, and severe hemodynamic instability. Patients are randomly allocated to either inhale 67 μg aviptadil or normal saline (three times a day for 10 days), in addition to standard care, stratified by center. The primary endpoint is time from hospitalization to clinical improvement, defined as either hospital discharge, or improvement of at least two levels on the nine-level scale for clinical status suggested by the World Health Organization.

Discussion

Treatment strategies for COVID-19 are still limited. In the context of upcoming new variants of SARS-CoV-2 and possible inefficacy of the available vaccines and antibody therapies, the investigation of alternative therapy options plays a crucial role in decreasing associated mortality and improving prognosis. Due to its unique immunomodulating properties also targeting the SARS-CoV-2 pathways, inhaled aviptadil may have the potential to prevent ARDS in COVID-19.

Trial registration

ClinicalTrials.gov, NCT04536350. Registered 02 September 2020.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-022-06723-w.

A single-center PICU present status survey of pediatric sepsis-related acute respiratory distress syndrome

BACKGROUND

To describe the incidence, clinical features, outcomes, and mortality risk factors of sepsis associated with acute respiratory distress syndrome (ARDS) in pediatric patients.

METHODS

Patients were included in the study if they met the 2005 version of the International Pediatric Sepsis Consensus Conference and met the Pediatric Acute Lung Injury Consensus Conference (PALICC) definition within 48 h of sepsis diagnosis. Patients were classified as mild, moderate, and severe by the worst oxygenation index (OI) within 72 h of sepsis-related ARDS diagnosis.

RESULTS

Between January 1, 2015 and March 13, 2020, 9836 patients were admitted to the pediatric intensive care unit (PICU) of the Children's Hospital of Chongqing Medical University and 828 (8.4%) were identified with sepsis and 203 (24.5%) met the PALICC definition with a PICU mortality rate of 24.6% (50/203) and a 90-day mortality rate of 40.9% (83/203). After adjusting for septic shock, the pediatric logistic organ dysfunction 2 (PELOD-2), high-frequency oscillation ventilation (HFOV), and continuous renal replacement therapy (CRRT), the variables that retained an independent association with increased 90-day mortality in pediatric sepsis-related ARDS included ARDS severity, the pediatric risk of mortality III (PRISM III), number of organ dysfunctions and use of vasoactive drug types during PICU stay.

CONCLUSIONS

PICU mortality in pediatric sepsis-related ARDS was high (24.6%) and severity of hypoxemia based on the worst OI value 72 h after meeting the PALICC definition accurately stratified the patient outcomes. ARDS severity, PRISM III score, comorbid multiorgan dysfunction, and use of multiple vasoactive drugs during PICU stay were independent risk factors for 90-day mortality in pediatric sepsis-related ARDS.

Exome sequencing contributes to identify comorbidities in a rare case of infant ARDS induced by the CD40LG mutation

Background

Acute respiratory distress syndrome (ARDS) causes significant mortality in young children with certain diseases. Early diagnosis and treatment can reduce infant mortality. Here, we report a rare case of exome sequencing in the early diagnosis of immunodeficiency in an infant.

Case presentation

A four-month-old full-term male infant presented with severe shortness of breath, hypoxemia, and unexplained parenchymal lung lesions. A series of examinations were performed to search for potential culprit viruses but negative results were obtained with the only exception being the rhinovirus that tested positive. The child’s family history revealed he had a brother who died of severe infection at the age of two years. We performed an exome sequencing analysis and a mutation analysis of CD40LG to obtain genetic data on the patient. Besides, we used flow cytometry to measure the CD40LG expression levels of activated T cells. A retrospective review of all the CD40LG mutant-induced X-linked hyper IgM syndromes (XHIGM) had been conducted to assess the differences between clinical and genetic molecular features. Finally, a regular intravenous immunoglobulin (IVIG) regimen led to steady breathing, the correction of hypoxemia, and a progressive improvement of lung CT scans. During follow-up, the patient received an IVIG regimen and his CT images improved. Moreover, his parents took advantage of pre-implantation genetic testing with in vitro fertilization to have a healthy twin offspring who did not carry such a mutation according to the early exome sequencing for the proband. Compared with other CD40LG mutant cases in our center, this proband displayed a normal plasma immunoglobulin level and he should be the youngest infant to have a molecular diagnosis of XHIGM.

Conclusion

Usually, XHIGM would not be suspected with a normal plasma immunoglobulin concentration. However, as we could not identify a potential comorbidity or risk factor, exome sequencing helps target this patient's real facts. Thus, this case report calls for exome sequencing to be performed in the case of unexplained infections when immunodeficiency is suspected after general immunological tests, especially for cases with a contributive family history among infants as the maternal transfused immunoglobulin might mask immune deficiency.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01303-y.

FAK mediates LPS-induced inflammatory lung injury through interacting TAK1 and activating TAK1-NFκB pathway

Acute lung injury (ALI), characterized by inflammatory damage, is a major clinical challenge. Developing specific treatment options for ALI requires the identification of novel targetable signaling pathways. Recent studies reported that endotoxin lipopolysaccharide (LPS) induced a TLR4-dependent activation of focal adhesion kinase (FAK) in colorectal adenocarcinoma cells, suggesting that FAK may be involved in LPS-induced inflammatory responses. Here, we investigated the involvement and mechanism of FAK in mediating LPS-induced inflammation and ALI. We show that LPS phosphorylates FAK in macrophages. Either FAK inhibitor, site-directly mutation, or siRNA knockdown of FAK significantly suppresses LPS-induced inflammatory cytokine production in macrophages. FAK inhibition also blocked LPS-induced activation of MAPKs and NFκB. Mechanistically, we demonstrate that activated FAK directly interacts with transforming growth factor-β-activated kinase-1 (TAK1), an upstream kinase of MAPKs and NFκB, and then phosphorylates TAK1 at Ser412. In a mouse model of LPS-induced ALI, pharmacological inhibition of FAK suppressed FAK/TAK activation and inflammatory response in lung tissues. These activities resulted in the preservation of lung tissues in LPS-challenged mice and increased survival during LPS-induced septic shock. Collectively, our results illustrate a novel FAK-TAK1-NFκB signaling axis in LPS-induced inflammation and ALI, and support FAK as a potential target for the treatment of ALI.

Risk factors for acute respiratory distress syndrome in sepsis patients: a retrospective study from a tertiary hospital in China

Background

Less is known about the risk factors for acute respiratory distress syndrome (ARDS) in sepsis patients diagnosed according to sepsis 3.0 criteria. Moreover, the risk factors for ARDS severity remain unclear.

Methods

We retrospectively collected the characteristics of sepsis patients from the intensive care unit of the First Affiliated Hospital of China Medical University from January 2017 to September 2018. Logistic regression was used in determining the risk factors.

Results

529 patients with sepsis were enrolled and 179 developed ARDS. The most common infection sites were acute abdominal infection (n = 304) and pneumonia (n = 117). Multivariate analysis showed that patients with pancreatitis with local infection (odds ratio [OR], 3.601; 95% confidence interval [CI], 1.429–9.073, P = 0.007), pneumonia (OR 3.486; 95% CI 1.890–6.430, P < 0.001), septic shock (OR 2.163; 95% CI 1.429–3.275, P < 0.001), a higher sequential organ failure assessment (SOFA) score (OR 1.241; 95% CI 1.155–1.333, P < 0.001) and non-pulmonary SOFA score (OR 2.849; 95% CI 2.113–3.841, P < 0.001) were independent risk factors for ARDS. Moreover, pneumonia is associated with increased severity of ARDS (OR 2.512; 95% CI 1.039–6.067, P = 0.041).

Conclusions

We determined five risk factors for ARDS in sepsis patients. Moreover, pneumonia is significantly associated with an increased severity of ARDS.

Effect of high-frequency oscillatory ventilation combined with prone positioning in infants with acute respiratory distress syndrome after congenital heart surgery: A prospective randomized controlled trial

Objectives

This study aimed to evaluate the effect of high-frequency oscillatory ventilation, (HFOV) combined with prone positioning, on oxygenation and pulmonary ventilation in infants with acute respiratory distress syndrome (ARDS) after congenital heart surgery.

Design

A randomized controlled trial.

Setting

A single-center study at a tertiary teaching hospital.

Participants

Patients with postoperative ARDS after congenital heart disease were divided randomly into the following 2 groups: HFOV combined with prone position (HFOV-PP), and HFOV combined with supine position (HFOV-SP).

Interventions

The primary outcomes were the PaO₂/F_IO₂ ratio and the oxygenation index after the intervention, and the secondary outcomes were respiratory variables, hemodynamics, complications, and other short-term outcomes.

Results

Sixty-five eligible infants with ARDS were randomized to either the HFOV-PP (n = 32) or HFOV-SP (n = 33) group. No significant difference in baseline data was found between the 2 groups (p > 0.05). Oxygenation was improved in both groups after HFOV intervention. Compared with the HFOV-SP group, the HFOV-PP group had significantly increased PaO₂/F_IO₂ and oxygenation index and a shorter duration of invasive ventilation and length of cardiac intensive care unit stay. No serious complications occurred in the 2 groups.

Conclusion

HFOV-PP significantly improved oxygenation in infants with ARDS after cardiac surgery and had no serious complications.

Correlation of small nucleolar RNA host gene 16 with acute respiratory distress syndrome occurrence and prognosis in sepsis patients

Background

Long noncoding RNA small nucleolar RNA host gene 16 (lnc‐SNHG16) regulates sepsis‐induced acute lung injury and inflammation, which is involved in the pathophysiology of acute respiratory distress syndrome (ARDS). The present study intended to explore the role of lnc‐SNHG16 as a potential biomarker indicating ARDS risk, disease severity, inflammation, and mortality in sepsis.

Methods

Peripheral blood mononuclear cell (PBMC) samples were collected from 160 sepsis patients within 24 hours after admission and 30 healthy controls (HCs). Then, lnc‐SNHG16 in PBMCs was detected by reverse transcription‐quantitative polymerase chain reaction. Sepsis patients were followed up until death or up to 28 days.

Results

lnc‐SNHG16 was declined in sepsis patients compared with HCs (p < 0.001). The incidence of ARDS was 27.5% among sepsis patients; meanwhile, sepsis patients with ARDS had higher mortality than those without ARDS (p < 0.001). Furthermore, lnc‐SNHG16 was declined in sepsis patients with ARDS compared to those without ARDS (p < 0.001); besides, higher lnc‐SNHG16 was independently correlated with declined ARDS occurrence in sepsis patients (p = 0.001), while primary respiratory infection and higher CRP were independently correlated with elevated ARDS occurrence in sepsis patients (both p < 0.05). Moreover, a negative correlation was found in lnc‐SNHG16 with history of diabetes, history of chronic obstructive pulmonary disease, and APACHE II and SOFA scores (all p < 0.05). Additionally, lnc‐SNHG16 was declined in sepsis deaths compared with survivors (p = 0.002), while it was not independently linked with sepsis mortality.

Conclusion

lnc‐SNHG16 correlates with lower ARDS occurrence and better prognosis in sepsis patients.

Development and external validation of models to predict acute respiratory distress syndrome related to severe acute pancreatitis

BACKGROUND

Acute respiratory distress syndrome (ARDS) is a major cause of death in patients with severe acute pancreatitis (SAP). Although a series of prediction models have been developed for early identification of such patients, the majority are complicated or lack validation. A simpler and more credible model is required for clinical practice.

AIM

To develop and validate a predictive model for SAP related ARDS.

METHODS

Patients diagnosed with AP from four hospitals located at different regions of China were retrospectively grouped into derivation and validation cohorts. Statistically significant variables were identified using the least absolute shrinkage and selection operator regression method. Predictive models with nomograms were further built using multiple logistic regression analysis with these picked predictors. The discriminatory power of new models was compared with some common models. The performance of calibration ability and clinical utility of the predictive models were evaluated.

RESULTS

Out of 597 patients with AP, 139 were diagnosed with SAP (80 in derivation cohort and 59 in validation cohort) and 99 with ARDS (62 in derivation cohort and 37 in validation cohort). Four identical variables were identified as independent risk factors for both SAP and ARDS: heart rate [odds ratio (OR) = 1.05; 95%CI: 1.04-1.07; P < 0.001; OR = 1.05, 95%CI: 1.03-1.07, P < 0.001], respiratory rate (OR = 1.08, 95%CI: 1.0-1.17, P = 0.047; OR = 1.10, 95%CI: 1.02-1.19, P = 0.014), serum calcium concentration (OR = 0.26, 95%CI: 0.09-0.73, P = 0.011; OR = 0.17, 95%CI: 0.06-0.48, P = 0.001) and blood urea nitrogen (OR = 1.15, 95%CI: 1.09-1.23, P < 0.001; OR = 1.12, 95%CI: 1.05-1.19, P < 0.001). The area under receiver operating characteristic curve was 0.879 (95%CI: 0.830-0.928) and 0.898 (95%CI: 0.848-0.949) for SAP prediction in derivation and validation cohorts, respectively. This value was 0.892 (95%CI: 0.843-0.941) and 0.833 (95%CI: 0.754-0.912) for ARDS prediction, respectively. The discriminatory power of our models was improved compared with that of other widely used models and the calibration ability and clinical utility of the prediction models performed adequately.

CONCLUSION

The present study constructed and validated a simple and accurate predictive model for SAP-related ARDS in patients with AP.