Predictive model using baseline characteristics at birth for INtubation-SURfactant-Extubation (INSURE) failure in preterm with respiratory distress syndrome
Keywords:
Extubation, Prognosis, Respiratory Distress Syndrome, Surfactant, Gestational Age, Birth Weight, Apgar ScoreAbstract
Background: The use of surfactant via INSURE (INtubation-Surfactant-Extubation) methods is widely employed for the treatment of respiratory distress syndrome (RDS) in preterm infants to reduce complications associated with invasive mechanical ventilation. However, if INSURE is unsuccessful, defined as requiring reintubation within 72 hours after extubation, mortality rates and rates of bronchopulmonary dysplasia increase significantly.
Objective: To develop predictive scores from baseline characteristics at birth of preterm for predicting INSURE failure.
Design, Setting, and Participants: Prognostic prediction research utilizing a retrospective observation design from 1 January 2018, to 31 December 2022, in preterm infants born before 34 weeks gestational age with RDS treated with INSURE at Phatthalung hospital, Thailand.
Methods: Retrospective data from medical records on infants and maternal characteristics associated with INSURE failure were use to develop a prediction score for INSURE failure using multivariable logistic regression, with risk scores derived from coefficients of variable in the equation.
Results: A total of 159 patients were included in the study and followed until discharge, with 26 patients (16.4%) experiencing INSURE failure. Four variables predicted INSURE failure including: 1. Maternal gestaional age, 2. Birth weight of the infants, 3. Apgar score at 1 minute, and 4. Severity of RDS in infants (with scores >16 increase the risk by 6-fold). Overall, a score >16 had a sensitivity of 80.8%, specificity of 87.2%, and AuROC of 0.86, 95%CI (0.77-0.96).
Conclusions: Creating a prediction score for INSURE failure in crucial in identifying the risks associated with this approach for treating RDS in preterm infants. This score can aid medical teams in selecting the most appropriate treatment for each infant.
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