Daily Ards Research Analysis

INTRODUCTION: Spectral analysis of gastric aspirates obtained shortly after birth predicts the diagnosis of respiratory distress syndrome in neonates born <32 completed weeks gestation. We sought to determine whether this prototype point-of-care device measuring surfactant components in gastric aspirates could predict prolonged respiratory support needs in neonates ≥30 completed weeks gestation. METHODS: Gastric aspirates obtained within 30 min of birth were analyzed by spectroscopy to quantify surfactant components. These spectral data were entered into an existing algorithm to assess subjects' biochemical lung maturity. This algorithmic output was paired with clinical data to evaluate the performance of the algorithm in predicting subjects' need for respiratory support at six hours of life (prolonged respiratory support). Each element of the algorithm was adjusted via a machine learning framework to optimize predictive performance. RESULTS: Gastric aspirates from 179 subjects (median 36 weeks, range 31-41 weeks) were eligible for analysis. Spectral analysis of gastric aspirates predicted the need for prolonged respiratory support with 70% sensitivity and 92% specificity. Positive- and negative-predictive values were 86% and 82%, respectively, for the overall cohort. Among gestational age subgroups, positive prediction was highest among moderately preterm neonates (32-33 weeks), while negative prediction was highest among term neonates. DISCUSSION: Spectral analysis of surfactant components contained in the gastric fluid of neonates ≥30 completed weeks gestation predicts the need for prolonged respiratory support with good performance. Predictive performance varied according to subjects' gestational age at birth, suggesting that gestational age-specific algorithms may improve the performance of this point-of-care diagnostic test.

Endothelial glycocalyx (eGC) degradation contributes to vascular and pulmonary dysfunction in acute lung injury (ALI). This study provides a comprehensive review of the structure of the endothelial glycocalyx (eGC) and the mechanisms underlying its injury. Additionally, it evaluates biomarkers indicative of glycocalyx disruption that have been investigated for clinical use, including syndecan-1, heparan sulfate, and hyaluronan. These biomarkers have been studied in both circulating and airway compartments, with some studies reporting signal size-dependent variations in their levels. Laboratory measurement methods, specifically immunoassays and mass spectrometry, are examined with an emphasis on preanalytical variables, analytical performance, interference, and existing deficiencies in standardization, calibration, and traceability. These deficiencies contribute to the challenges in achieving comparability across different studies. Subsequently, we assessed the evidence regarding the clinical utility of risk stratification and outcome prediction in the context of ALI/ARDS and sepsis heterogeneity, focusing on cohort characteristics, sampling intervals, and sample types. In conclusion, we propose the implementation of novel glycocalyx-stabilizing treatments and future advancements, such as multi-marker panels and their integration with microvascular imaging. Generally, the standardization of protocols and establishment of reporting systems are essential prerequisites for the incorporation of these biomarkers into routine clinical laboratory and intensive care unit workflows as reliable tools.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a complex syndrome with multiple risk factors that can lead to acute respiratory failure and, in turn, high morbidity and mortality. To clarify the syndrome's underlying pathomechanisms and develop novel therapies, we have summarized and analyzed a series of chief cause-induced animal models of ARDS. AIM: Although various animal models have been developed to represent the traits of human ARDS based on clinical symptoms and the yardstick of positive clinical trials, each model has unique features that reflect only part of the characteristics modeled. In response, this review aims to investigate characteristics of ARDS in current animal models and offers new strategies and insights for developing animal models aimed at capturing the features of human ARDS. CONCLUSION: This review summarizes the physiological characteristics of animals used in models of ARDS and evaluates the advantages and disadvantages of the chief cause-induced models for modeling human ARDS in animals, for results that can inform the establishment, assessment, and experimental study of ARDS in animal models.