MUC5AC concentrations in lung lavage fluids are associated with acute lung injury after cardiac surgery.

Heart surgery may be complicated by acute lung injury and adult respiratory distress syndrome. Expression and release of mucins MUC5AC and MUC5B in the lungs has been reported to be increased in acute lung injury. The aim of our study was to [1] investigate the perioperative changes of MUC5AC, MUC5B and other biomarkers in mini-bronchoalveolar lavage (minBAL), and [2] relate these to clinical outcomes after cardiac surgery. In this prospective cohort study in 49 adult cardiac surgery patients pre- and post-surgery non-fiberscopic miniBAL fluids were analysed for MUC5AC, MUC5B, IL-8, human neutrophil elastase, and neutrophils. All measured biomarkers increased after surgery. Perioperative MUC5AC-change showed a significant negative association with postoperative P/F ratio (p = 0.018), and a positive association with ICU stay (p = 0.027). In conclusion, development of lung injury after cardiac surgery and prolonged ICU stay are associated with an early increase of MUC5AC as detected in mini-BAL.

Comprehensive profiling of amino acids and derivatives in biological samples: A robust UHPLC-MS/MS method for investigating acute lung injury.

The severe respiratory dysfunctions associated with acute lung injury (ALI) and its sequelae have a high morbidity and mortality rate, are multifactorial, and lack a viable treatment. Considering the critical function that amino acids and derivatives play in the genesis of illnesses and the regulation of metabolic processes, monitoring the levels of metabolites associated with amino acids in biological matrices is necessary and interesting to study their pathological mechanisms. Exploring the dynamics of amino acids and derivatives level and searching for biomarkers provides improved clinical ideas for the diagnosis and treatment of ALI. Therefore, we developed an ultra-high-performance liquid chromatography-electrospray tandem mass spectrometry (UHPLC-MS/MS) method that can simultaneously determine the amino acid and derivatives metabolic levels to study amino acid profiles in different biological samples to facilitate clinical research of ALI. In this study, 48 amino acids and derivatives, including neurotransmitters, polyamines, purines, and other types, were quantified simultaneously in a fast, high-throughput, sensitive, and reliable manner within a 15-minute run time without derivatization. No relevant studies have been reported to quantify these 48 amino acid metabolites in three biological samples simultaneously. Satisfactory linearity (R > 0.995), inter-day and intra-day accuracy (85.17-112.67 % and 85.29-111.60 %, respectively), inter-day and intra-day precision (RSD < 13.80 % and RSD < 12.01 %, respectively), matrix effects (81.00 %-118.00 %), recovery (85.09 %-114.65 %) and stability (RSD < 14.72 %) were all demonstrated by the optimized method's successful validation for all analytes. In addition, the suggested method was effectively implemented in plasma, urine, and lung tissue from normal mice and mice with ALI, with the aim of finding potential biomarkers associated with ALI. Potential biomarkers were screened through multivariate statistical analysis and volcanic map analysis, and the changes of markers in ALI were again identified through heat map analysis and correlation analysis with biochemical indicators, which provided ideas and references for subsequent mechanism studies. Here, the technique created in this work offers a quick and dependable way to perform an integrated analysis of amino acids in a variety of biological materials, which can provide research ideas for understanding the physiopathological state of various diseases.

sTREM2 in the prognostic evaluation of acute lung injury after cardiac surgery in infants.

BACKGROUND: Previous studies have shown that TREM2 plays a protective role in acute lung injury (ALI). This prospective study aimed to investigate the role of sTREM2 as a forecasting factor for ALI in infants after pediatric cardiac surgery undergoing cardiopulmonary bypass (CPB). METHODS: Seventy-five consecutive patients younger than 1 year who underwent cardiac surgery were enrolled in this study. Sixty-one fulfilled the inclusion criteria and had been divided into ALI and non-ALI groups. Children's demographic characteristics and clinical data were collected. Perioperative sTREM2 levels were analyzed at five timepoints. RESULTS: In this study, children in the ALI group were younger, lighter, with higher RACHS-1 scores and underwent significantly longer CPB time. Post-CPB ALI had an impact on clinical outcomes, which contributed to a longer duration of mechanical ventilation, ICU and hospital stay than non-ALI group. Significant differences were manifested off-CPB, 1 h/6 h after CPB, and day 1 after surgery between the two groups. Binary logistic models revealed that off-CPB sTREM2 was significantly associated with the incidence of post-CPB ALI after adjustment. ROC analysis showed that the AUC of off-CPB sTREM2 level was 0.791, and the optimal cutoff value was 788.6 pg/ml. CONCLUSIONS: The off-CPB sTREM2 level was an independent prognostic factor for post-CPB ALI in infants. IMPACT: Plasma sTREM2 works together with downstream TREM2 to regulate inflammation response by binding the receptor to other cells. Previous studies have shown that TREM2 plays a protective role in ischemia-reperfusion and has anti-inflammatory effects on acute lung injury (ALI). This study analyzed the risk factors of post-cardiopulmonary bypass (CPB) ALI. We found that weight and off-CPB sTREM2 level were independent prognostic factors for post-CPB ALI. Plasma sTREM2 may serve as an early biomarker in the prognostic evaluation of acute lung injury after cardiac surgery in infants.

Biomarkers, signaling pathways, and programmed cell death in acute lung injury and its treatment with Traditional Chinese Medicine: a narrative review.

Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) are common life-threatening, high-mortality lung diseases associated with acute and severe inflammation of the lungs. However, research on diagnostic markers and signaling pathways associated with ALI/ARDS is lacking, and no specific drug therapy is available for ALI/ARDS. Therefore, in this study, biomarkers and signaling pathways associated with ALI/ARDS were summarized to provide a reference for future clinical and research work. A review of Traditional Chinese Medicine for the treatment or prevention of ALI/ARDS is also presented to provide a reference for further development of Traditional Chinese Medicine. In summary, this review will help raise awareness of ALI/ARDS and provide insight into the future exploitation of Traditional Chinese Medicine.

A diagnostic model for sepsis-induced acute lung injury using a consensus machine learning approach and its therapeutic implications.

BACKGROUND: A significant proportion of septic patients with acute lung injury (ALI) are recognized late due to the absence of an efficient diagnostic test, leading to the postponed treatments and consequently higher mortality. Identifying diagnostic biomarkers may improve screening to identify septic patients at high risk of ALI earlier and provide the potential effective therapeutic drugs. Machine learning represents a powerful approach for making sense of complex gene expression data to find robust ALI diagnostic biomarkers. METHODS: The datasets were obtained from GEO and ArrayExpress databases. Following quality control and normalization, the datasets (GSE66890, GSE10474 and GSE32707) were merged as the training set, and four machine learning feature selection methods (Elastic net, SVM, random forest and XGBoost) were applied to construct the diagnostic model. The other datasets were considered as the validation sets. To further evaluate the performance and predictive value of diagnostic model, nomogram, Decision Curve Analysis (DCA) and Clinical Impact Curve (CIC) were constructed. Finally, the potential small molecular compounds interacting with selected features were explored from the CTD database. RESULTS: The results of GSEA showed that immune response and metabolism might play an important role in the pathogenesis of sepsis-induced ALI. Then, 52 genes were identified as putative biomarkers by consensus feature selection from all four methods. Among them, 5 genes (ARHGDIB, ALDH1A1, TACR3, TREM1 and PI3) were selected by all methods and used to predict ALI diagnosis with high accuracy. The external datasets (E-MTAB-5273 and E-MTAB-5274) demonstrated that the diagnostic model had great accuracy with AUC value of 0.725 and 0.833, respectively. In addition, the nomogram, DCA and CIC showed that the diagnostic model had great performance and predictive value. Finally, the small molecular compounds (Curcumin, Tretinoin, Acetaminophen, Estradiol and Dexamethasone) were screened as the potential therapeutic agents for sepsis-induced ALI. CONCLUSION: This consensus of multiple machine learning algorithms identified 5 genes that were able to distinguish ALI from septic patients. The diagnostic model could identify septic patients at high risk of ALI, and provide potential therapeutic targets for sepsis-induced ALI.

Identification of biomarkers associated with diagnosis of acute lung injury based on bioinformatics and machine learning.

BACKGROUND: Acute lung injury (ALI) is an acute inflammatory disease characterized by excess production of inflammatory factors in lung tissue and has a high mortality. This research was designed for the identification of novel diagnostic biomarkers for ALI and analyzing the possible association between critical genes and infiltrated immune cells. METHODS: The study used 2 datasets (GSE2411 and GSE18341) to identify differentially expressed genes (DEGs) between 2 groups. Then we performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses to identify the functions of these DEGs. The study also used SVM-recursive feature elimination analysis and least absolute shrinkage and selection operator regression model to screen possible markers. The study further analyzed immune cell infiltration via CIBERSORT. Gene Set Enrichment Analysis was used to explore the molecular mechanism of the critical genes. RESULTS: DEGs were identified between 2 groups. In total, 690 DEGs were obtained: 527 genes were upregulated and 163 genes were downregulated. We identified PDZK1IP1, CCKAR, and CXCL2 as critical genes. And we then found that these critical genes correlated with Mast Cells, Neutrophil Cells, M1 Macrophage, dendritic cell Actived, Eosinophil Cells, B Cells Naive, Mast Cells, and dendritic cell Immature. Furthermore, we investigated the specific signaling pathways involved in key genes and derived some potential molecular mechanisms by which key genes affect disease progression by use of Gene Set Enrichment Analysis. Moreover, we predict transcription factors. Also, we obtained critical gene-related microRNAs through the targetscan database, and visualized the microRNA network of the genes. CONCLUSION: Our findings might provide some novel clue for the exploration of novel markers for ALI diagnosis. The critical genes and their associations with immune infiltration may offer new insight into understanding ALI developments.

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.

Interrater Reliability of the 2015 Pediatric Acute Lung Injury Consensus Conference Criteria for Pediatric ARDS.

BACKGROUND: Diagnostic guidelines for pediatric ARDS (PARDS) were developed at the 2015 Pediatric Acute Lung Injury Consensus Conference (PALICC). Although this was an improvement in creating pediatric-specific diagnostic criteria, there remains potential for variability in identification of PARDS. RESEARCH QUESTION: What is the interrater reliability of the 2015 PALICC criteria for diagnosing moderate to severe PARDS? What clinical criteria and patient factors are associated with diagnostic disagreements? STUDY DESIGN AND METHODS: Patients with acute hypoxic respiratory failure admitted from 2016 to 2021 who received invasive mechanical ventilation were retrospectively reviewed by two pediatric ICU physicians. Reviewers evaluated whether the patient met the 2015 PALICC definition of moderate to severe PARDS and rated their diagnostic confidence. Interrater reliability was measured using Gwet's agreement coefficient. RESULTS: Thirty-seven of 191 encounters had a diagnostic disagreement. Interrater reliability was substantial (Gwet's agreement coefficient, 0.74; 95% CI, 0.65-0.83). Disagreements were caused by different interpretations of chest radiographs (56.8%), ambiguity in origin of pulmonary edema (37.8%), or lack of clarity if patient's current condition was significantly different from baseline (27.0%). Disagreement was more likely in patients who were chronically ventilated (OR, 4.66; 95% CI, 2.16-10.08; P < .001), had a primary cardiac admission diagnosis (OR, 3.36; 95% CI, 1.18-9.53; P = .02), or underwent cardiothoracic surgery during the admission (OR, 4.90; 95% CI, 1.60-15.00; P = .005). Reviewers were at least moderately confident in their decision 73% of the time; however, they were less likely to be confident if the patient had cardiac disease or chronic respiratory failure. INTERPRETATION: The interrater reliability of the 2015 PALICC criteria for diagnosing moderate to severe PARDS in this cohort was substantial, with diagnostic disagreements commonly caused by differences in chest radiograph interpretations. Patients with cardiac disease or chronic respiratory failure were more vulnerable to diagnostic disagreements. More guidance is needed on interpreting chest radiographs and diagnosing PARDS in these subgroups.

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.

Pathobiology, Severity, and Risk Stratification of Pediatric Acute Respiratory Distress Syndrome: From the Second Pediatric Acute Lung Injury Consensus Conference.

OBJECTIVES: To review the literature for studies published in children on the pathobiology, severity, and risk stratification of pediatric acute respiratory distress syndrome (PARDS) with the intent of guiding current medical practice and identifying important areas for future research related to severity and risk stratification. DATA SOURCES: Electronic searches of PubMed and Embase were conducted from 2013 to March 2022 by using a combination of medical subject heading terms and text words to capture the pathobiology, severity, and comorbidities of PARDS. STUDY SELECTION: We included studies of critically ill patients with PARDS that related to the severity and risk stratification of PARDS using characteristics other than the oxygenation defect. Studies using animal models, adult only, and studies with 10 or fewer children were excluded from our review. DATA EXTRACTION: Title/abstract review, full-text review, and data extraction using a standardized data collection form. DATA SYNTHESIS: The Grading of Recommendations Assessment, Development, and Evaluation approach was used to identify and summarize relevant evidence and develop recommendations for clinical practice. There were 192 studies identified for full-text extraction to address the relevant Patient/Intervention/Comparator/Outcome questions. One clinical recommendation was generated related to the use of dead space fraction for risk stratification. In addition, six research statements were generated about the impact of age on acute respiratory distress syndrome pathobiology and outcomes, addressing PARDS heterogeneity using biomarkers to identify subphenotypes and endotypes, and use of standardized ventilator, physiologic, and nonpulmonary organ failure measurements for future research. CONCLUSIONS: Based on an extensive literature review, we propose clinical management and research recommendations related to characterization and risk stratification of PARDS severity.

Definition, Incidence, and Epidemiology of Pediatric Acute Respiratory Distress Syndrome: From the Second Pediatric Acute Lung Injury Consensus Conference.

OBJECTIVES: In 2015, the Pediatric Acute Lung Injury Consensus Conference (PALICC) provided the first pediatric-specific definitions for acute respiratory distress syndrome (pediatric acute respiratory distress syndrome [PARDS]). These definitions have since been operationalized in cohort and interventional PARDS studies. As substantial data have accrued since 2015, we have an opportunity to assess the construct validity and utility of the initial PALICC definitions. Therefore, the Second PALICC (PALICC-2) brought together multiple PARDS experts and aimed to identify and summarize relevant evidence related to the definition and epidemiology of PARDS and create modifications to the definition of PARDS. DATA SOURCES: MEDLINE (Ovid), Embase (Elsevier), and CINAHL Complete (EBSCOhost). STUDY SELECTION: We included studies of subjects with PARDS, or at risk for PARDS, excluding studies pertaining primarily to adults except as specified for identifying age-specific cutoffs. DATA EXTRACTION: Title/abstract review, full-text review, and data extraction using a standardized data collection form. DATA SYNTHESIS: The Grading of Recommendations Assessment, Development, and Evaluation approach was used to identify and summarize evidence and develop recommendations. A total of 97 studies were identified for full-text extraction addressing distinct aspects of the PARDS definition, including age, timing, imaging, oxygenation, modes of respiratory support, and specific coexisting conditions. Data were assessed in a Patient/Intervention/Comparator/Outcome format when possible, and formally summarized for effect size, risk, benefit, feasibility of implementation, and equity. A total of 17 consensus-based definition statements were made that update the definition of PARDS, as well as the related diagnoses of "Possible PARDS" and "At-Risk for PARDS." These statements are presented alongside a summary of the relevant epidemiology. CONCLUSIONS: We present updated, data-informed consensus statements on the definition for PARDS and the related diagnoses of "Possible PARDS" and "At-Risk for PARDS."

Methodology of the Second Pediatric Acute Lung Injury Consensus Conference.

OBJECTIVES: This article describes the methodology used for The Second Pediatric Acute Lung Injury Consensus Conference (PALICC-2). The PALLIC-2 sought to develop evidence-based clinical recommendations and when evidence was lacking, expert-based consensus statements and research priorities for the diagnosis and management of pediatric acute respiratory distress syndrome (PARDS). DATA SOURCES: Electronic searches were conducted using PubMed, Embase, and Cochrane Library (CENTRAL) databases from 2012 to March 2022. STUDY SELECTION: Content was divided into 11 sections related to PARDS, with abstract and full text screening followed by data extraction for studies which met inclusion with no exclusion criteria. DATA EXTRACTION: We used a standardized data extraction form to construct evidence tables, grade the evidence, and formulate recommendations or statements using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. DATA SYNTHESIS: This consensus conference was comprised of a multidisciplinary group of international experts in pediatric critical care, pulmonology, respiratory care, and implementation science which followed standards set by the Institute of Medicine, using the GRADE system and Research And Development/University of California, Los Angeles appropriateness method, modeled after PALICC 2015. The panel of 52 content and four methodology experts had several web-based meetings over the course of 2 years. We conducted seven systematic reviews and four scoping reviews to cover the 11 topic areas. Dissemination was via primary publication listing all statements and separate supplemental publications for each subtopic that include supporting arguments for each recommendation and statement. CONCLUSIONS: A consensus conference of experts from around the world developed recommendations and consensus statements for the definition and management of PARDS and identified evidence gaps which need further research.

Monitoring in Pediatric Acute Respiratory Distress Syndrome: From the Second Pediatric Acute Lung Injury Consensus Conference.

OBJECTIVES: Monitoring is essential to assess changes in the lung condition, to identify heart-lung interactions, and to personalize and improve respiratory support and adjuvant therapies in pediatric acute respiratory distress syndrome (PARDS). The objective of this article is to report the rationale of the revised recommendations/statements on monitoring from the Second Pediatric Acute Lung Injury Consensus Conference (PALICC-2). DATA SOURCES: MEDLINE (Ovid), Embase (Elsevier), and CINAHL Complete (EBSCOhost). STUDY SELECTION: We included studies focused on respiratory or cardiovascular monitoring of children less than 18 years old with a diagnosis of PARDS. We excluded studies focused on neonates. DATA EXTRACTION: Title/abstract review, full-text review, and data extraction using a standardized data collection form. DATA SYNTHESIS: The Grading of Recommendations Assessment, Development and Evaluation approach was used to identify and summarize evidence and develop recommendations. We identified 342 studies for full-text review. Seventeen good practice statements were generated related to respiratory and cardiovascular monitoring. Four research statements were generated related to respiratory mechanics and imaging monitoring, hemodynamics monitoring, and extubation readiness monitoring. CONCLUSIONS: PALICC-2 monitoring good practice and research statements were developed to improve the care of patients with PARDS and were based on new knowledge generated in recent years in patients with PARDS, specifically in topics of general monitoring, respiratory system mechanics, gas exchange, weaning considerations, lung imaging, and hemodynamic monitoring.

Identification of biomarkers and candidate small-molecule drugs in lipopolysaccharide (LPS)-induced acute lung injury by bioinformatics analysis

Background/objective: Acute lung injury (ALI) is a critical clinical syndrome with high rates of incidence and mortality. However, its molecular mechanism remains unclear. The current work aimed to explore the molecular mechanisms of ALI by identifying different expression genes (DEGs) and candidate drugs using a combination of chip analysis and experimental validation. Methods: Three microarray datasets were downloaded from Gene Expression Omnibus (GEO) database to obtain DEGs. We conducted a Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway-enrichment analyses of overlapping DEGs among three databases. The expression level of key gene was verified by Western blotting analysis in LPS-treated ALI cell models. Finally, we predicted the candidate drugs targeting the key gene that might be effective for ALI treatment, and the role of candidate drug in treating ALI was verified by investigation. Results: A total 29 overlapping DEGs were up-regulated in LPS-induced ALI groups. They were enriched in inflammation and inflammation-related pathways. Serpin family A member 3 (SERPINA3) was defined as a key gene because it was associated with inflammation pathway and up-regulated in microarray datasets in LPS-induced ALI. In LPS-induced human bronchial epithelial cells transformed with Ad12-SV40-2B (BEAS-2B) cells, SERPINA3 was enhanced. Pyridoxal phosphate as an upstream drug of SERPINA3 could improve cell viability and reduce expression inflammatory factors in LPS-treated BEAS-2B cells. Conclusion: Our study suggested that pyridoxal phosphate could be a candidate drug targeting SERPINA3 gene in LPS-induced ALI. It has protective and anti-inflammatory effects in BEAS-2B cells, and may become a potential novel treatment for ALI (AU)

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.

Preterm sepsis is associated with acute lung injury as measured by pulmonary severity score.

BACKGROUND: Sepsis related acute lung injury (ALI) is established in adults but has not been investigated in premature infants. Herein, we used pulmonary severity score (PSS) trajectories and C-reactive protein (CRP) to examine the relation between sepsis and ALI in premature infants. METHODS: This retrospective study identified 211 sepsis and 123 rule out (RO) events in 443 infants born <31 weeks and <1500 grams. The PSS was calculated prior to, at the time of, and up to 1 week after each event. Initial and peak CRP values were collected for each event. RESULTS: PSS significantly increased at 0 h from baseline (-72h) and remained increased at all subsequent time points (all p < 0.002) in sepsis events. Mean PSS in sepsis episodes were also higher compared to RO events at +24 h, +48 h, +72 h, and +168 h (all p < 0.004). A positive correlation was noted between peak CRP values in sepsis events and PSS at 0 h, +24 h, +48 h, and +72 h. CONCLUSIONS: The temporal PSS trends and correlation with CRP levels observed in sepsis but not in RO events supports the hypothesis that neonatal sepsis is associated with ALI and contributes to the accumulating evidence that neonatal ARDS occurs. IMPACT: To evaluate pulmonary severity scores and c-reactive protein values over time to establish an association between preterm neonatal sepsis and acute lung injury (ALI). Though sepsis is well established as the most common indirect cause of ALI leading to acute respiratory distress syndrome (ARDS) in adults and pediatrics, this phenomenon remains undefined in neonates. This study validates the proposal by the Neonatal ARDS Project that ARDS also occurs in neonates by demonstrating acute and sustained changes in markers of pulmonary injury temporally related to a diagnosis of neonatal sepsis in preterm infants.

The CHARTER-Ireland trial: can nebulised heparin reduce acute lung injury in patients with SARS-CoV-2 requiring advanced respiratory support in Ireland: a study protocol and statistical analysis plan for a randomised control trial.

BACKGROUND: COVID-19 pneumonia is associated with the development of acute respiratory distress syndrome (ARDS) displaying some typical histological features. These include diffuse alveolar damage with extensive pulmonary coagulation activation. This results in fibrin deposition in the microvasculature, leading to the formation of hyaline membranes in the air sacs. Well-conducted clinical trials have found that nebulised heparin limits pulmonary fibrin deposition, attenuates progression of ARDS, hastens recovery and is safe in non-COVID ARDS. Unfractionated heparin also inactivates the SARS-CoV-2 virus and prevents entry into mammalian cells. Nebulisation of heparin may therefore limit fibrin-mediated lung injury and inhibit pulmonary infection by SARS-CoV-2. Based on these findings, we designed the CHARTER-Ireland Study, a phase 1b/2a randomised controlled study of nebulised heparin in patients requiring advanced respiratory support for COVID-19 pneumonia. METHODS: This is a multi-centre, phase 1b/IIa, randomised, parallel-group, open-label study. The study will randomise 40 SARs-CoV-2-positive patients receiving advanced respiratory support in a critical care area. Randomisation will be via 1:1 allocation to usual care plus nebulised unfractionated heparin 6 hourly to day 10 while receiving advanced respiratory support or usual care only. The study aims to evaluate whether unfractionated heparin will decrease the procoagulant response associated with ARDS up to day 10. The study will also assess safety and tolerability of nebulised heparin as defined by number of severe adverse events; oxygen index and respiratory oxygenation index of intubated and unintubated, respectively; ventilatory ratio; and plasma concentration of interleukin (IL)-1ß, IL6, IL-8, IL-10 and soluble tumour necrosis factor receptor 1, C-reactive protein, procalcitonin, ferritin, fibrinogen and lactate dehydrogenase as well as the ratios of IL-1ß/IL-10 and IL-6/IL-10. These parameters will be assessed on days 1, 3, 5 and 10; time to separation from advanced respiratory support, time to discharge from the intensive care unit and number tracheostomised to day 28; and survival to days 28 and 60 and to hospital discharge, censored at day 60. Some clinical outcome data from our study will be included in the international meta-trials, CHARTER and INHALE-HEP. DISCUSSION: This trial aims to provide evidence of potential therapeutic benefit while establishing safety of nebulised heparin in the management of ARDS associated with SARs-CoV-2 infection. TRIAL REGISTRATION: ClinicalTrials.gov NCT04511923 . Registered on 13 August 2020. Protocol version 8, 22/12/2021 Protocol identifier: NUIG-2020-003 EudraCT registration number: 2020-003349-12 9 October 2020.

Preoperative acute lung injury and oxygenation impairment occurred in the patients with acute aortic dissection.

Acute lung injury (ALI) and oxygenation impairment (OI) frequently occur in the patients with acute aortic dissection (AAD), which may necessitate mechanical ventilation and result in adverse outcomes. This paper aims to increase clinicians' awareness of the severe respiratory complications in the patients with AAD, and provide the overview of the epidemiology, adverse outcomes, pathogenesis, predictive markers and therapeutic modalities of the concurrent conditions. Currently, it is considered that inflammatory response plays a great role in the pathogenesis of ALI and OI in the patients with AAD, but the definite pathogenesis remains unclear. Given the great importance of the prediction of the occurrence of the severe respiratory complication at a very early stage, some inflammatory biomarkers have been investigated to predict the occurrence of ALI and OI in several studies. C-reactive protein was found to have a significant predictive effect for the development of ALI and OI. Early use of beta-blockers and the use of bindarit could prevent the occurrence of OI and ALI. Ulinastatin could also improve oxygenation in the patients with type-A AAD. Prevention and management of ALI and OI in AAD remain a great challenge. The definite pathogenesis should be clearly clarified and further studies should be performed to look for potential effective way to predict and manage the severe respiratory conditions.