Respiratory Distress Syndrome, Acute

GEn1E-1124-002 is a two-part Phase 2 study to evaluate the safety and tolerability of GEn-1124 in subjects with ARDS. Treatment with IV infusion dosing as early as possible after ARDS diagnosis. Subjects will be given a second dose approximately 8 hours after the first dose and will continue with twice daily dosing (BID regimen) for 5 days.

1. A predictive model for NARDS was established based on perinatal risk factors. Multivariate Logistic regression analysis was used to screen the independent prenatal risk factors for NARDS. A Logistic regression model was constructed using the above independent risk factors and quantified in a nomogram to construct a visualization model for prenatal prediction of NARDS. 2. The role of ACS in the prevention and treatment of ARDS in near-term/full-term infants. For neonates with a probability greater than 80% in the prediction model of ARDS, at least one ACS was given before the termination of pregnancy. The GC level of cord blood (taken at birth) and the mRNA levels of α-ENaC, Na-K-atpase and SGK1 in nasal epithelium were measured within 2 hours and 1 day after birth in the ACS intervention group and the control group. The occurrence and severity of pulmonary edema, the occurrence and severity of ARDS, and the mortality rate of NARDS were evaluated by lung ultrasound. The indexes of the two groups were compared horizontally and longitudinally.

The goal of this observational study is to integrate existing clinical cohorts from the research team to establish dedicated cohorts for ARDS and high-risk ARDS patients (primarily SCAP patients), then systematically collect comprehensive clinical data and multi-omics biological samples to construct a high-quality multimodal ARDS database. Building upon this foundation, the research will develop an ARDS-specific large-scale disease model to assist clinical decision-making in early warning, diagnosis, and prognosis prediction. The main question it seeks to address is: Can the establishment of specialized ARDS cohorts and multimodal databases, combined with the development of an ARDS-specific large-scale disease model, effectively improve ARDS prediction rates, diagnostic accuracy, and reduce mortality rates, thereby enhancing overall clinical management standards?