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Published on: April 7, 2021
Risk Factors and Prediction Models for Less Invasive Surfactant Administration Failure in Preterm Infants: A
1Department of Neonatology, Institute of Postgraduate Medical education & Research and SSKM Hospital, 244 AJC Bose Road, Kolkata, West Bengal, India.
Insights
Predicting less invasive surfactant administration (LISA) failure in preterm infants with respiratory distress syndrome (RDS) is crucial. Key risk factors include higher oxygen saturation index and incomplete antenatal corticosteroids, informing treatment decisions.
Area of Science:
- Neonatal Medicine
- Pediatric Pulmonology
- Clinical Informatics
Background:
- Respiratory distress syndrome (RDS) is a common complication in preterm infants.
- Less invasive surfactant administration (LISA) is a preferred method for RDS management.
- Identifying factors predicting LISA failure is essential for optimizing care in low-resource settings.
Purpose of the Study:
- To identify risk factors for LISA failure in preterm infants with RDS in a low-and-middle income country (LMIC).
- To develop and validate prediction models for LISA failure risk.
- To inform clinical decisions regarding surfactant administration strategies.
Main Methods:
- Retrospective cohort study of 600 preterm infants receiving LISA.
- Analysis using random forest, support vector machine, and Lasso penalized logistic regression.
- Validation of prediction models on a testing set.
Main Results:
- LISA failure occurred in 30-40% of infants.
- Significant risk factors included higher oxygen saturation index (OSI), higher cord base deficit, lower birth weight, lower admission temperature, and incomplete antenatal corticosteroids (ANS).
- Random forest and SVM models showed high accuracy (92.42% and 90.91%); Lasso and random forest had high sensitivity (96.55% and 93.88%).
- LISA failure was associated with higher rates of bronchopulmonary dysplasia (BPD), retinopathy of prematurity (ROP), and mortality.
Conclusions:
- Prediction models can estimate individual risk of LISA failure.
- Identifying high-risk infants can guide decisions on alternative surfactant administration methods.
- This research has implications for improving outcomes in preterm infants with RDS in LMICs.
Objective:
This study aimed to identify risk factors associated with less invasive surfactant administration (LISA) failure in preterm infants with respiratory distress syndrome (RDS) in a low-and-middle income country (LMIC) and develop a prediction model to estimate the risk of LISA failure.
Methods:
This retrospective cohort study included 600 preterm infants who received LISA at a tertiary care neonatal unit in eastern India from January 2020 to December 2024.
Results:
LISA failure, defined as the need for intubation and mechanical ventilation within 72 h of the procedure, ranged from 30% to 40%. The most important risk factors for LISA failure identified by random forest analysis were higher oxygen saturation index (OSI), higher cord base deficit, lower birth weight, lower admission temperature, and incomplete course of antenatal corticosteroids (ANS). Various prediction models were developed and validated on the testing set, with random forest and support vector machine using radial kernel demonstrating the highest accuracy (92.42% and 90.91%, respectively). In terms of sensitivity, Lasso penalized logistic regression was the best performing model followed by the random forest (96.55% and 93.88% respectively). The incidence of bronchopulmonary dysplasia (BPD), retinopathy of prematurity (ROP) requiring treatment, mortality, median duration of respiratory support, and time to discharge were significantly higher in the LISA failure group compared to the successful LISA group.
Conclusion:
This study highlights the need for prediction models to estimate the risk of LISA failure in individual patients, which may inform decisions regarding alternative methods of surfactant administration in patients at high risk of LISA failure.
