Establishment and Evaluation of Prenatal Prevention and Treatment Strategy for NARDS
Recruiting now · Not applicable
Conditions studied: Acute Respiratory Distress Syndrome, Respiratory Distress Syndrome, Acute
In brief
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.
Key facts
- Study ID
- NCT06188195
- Run by
- The Second Affiliated Hospital of Chongqing Medical University
- People needed
- 500
- Starts
- 2024-02-01
- Expected to finish
- 2025-12-31
- Last updated by the study team
- 2025-06-04
Who can join
Age: any. Sex: female. Healthy volunteers: not accepted.
You may qualify if…
- The pregnant women with a probability greater than 80% in the prediction model of neonatal acute respiratory distress syndrome and agreed to ACS intervention.
- Obtaining patient consent.
You may not qualify if…
- the pregnant women with a probability of less than 80% in the neonatal acute respiratory distress syndrome prediction model.
- The patient refuses.
Where it is running
- The Second Affiliated Hospital of Chongqing Medical University — Chongqing, China (enrolling)
Full record on ClinicalTrials.gov
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