Reducing Failed Extubations in Preterm Infants Via Standardization and Real-Time Decision Support.

BACKGROUND AND OBJECTIVES: Failed extubations are associated with pulmonary morbidity in hospitalized premature newborns. The objective of this study was to use quality improvement methodology to reduce failed extubations through practice standardization and integrating a real-time extubation success calculator into the electronic medical record (EMR). METHODS: A specific, measurable, achievable, relevant, and time-bound aim was developed to reduce failed extubations (defined as reintubation <5 days from primary extubation) by 50% among infants <32 weeks' gestational age (GA) or <1500 g birth weight by December 31, 2022. Plan-do-study-act cycles were developed to standardize postextubation respiratory support and integrate the EMR-based calculator. Outcome measures included extubation failure rates. Balancing measures included days on mechanical ventilation and number of patients intubated <3 days. Process measures were followed for guideline compliance. Statistical process control charts were used to track time-ordered data and detect special cause variation. RESULTS: We observed a reduction in failed extubations from 10.3% to 2.3%, with special cause variation noted after both plan-do-study-act cycle #1 and #2. Special cause variation was detected in both GA subgroups: <28 weeks' GA (22.0%-8.6%) and ≥28 weeks' GA (4.6%-0.3%). Additionally, the average number of infants intubated <3 days increased (60.2%-73.6%), whereas average ventilator days decreased (10.8-7.0). Finally, the time from infants' extubation score reaching threshold (≥60%) to extubation decreased (14.1-6.4 days) after launching the EMR-integrated calculator. CONCLUSIONS: Practice standardization and implementation of an EMR-based real-time clinical decision support tool improved extubation success, promoted earlier extubation, and reduced ventilator days in premature newborns.

Predicting Adverse Neonatal Outcomes for Preterm Neonates with Multi-Task Learning.

Diagnosis of adverse neonatal outcomes is crucial for preterm survival since it enables doctors to provide timely treatment. Machine learning (ML) algorithms have been demonstrated to be effective in predicting adverse neonatal outcomes. However, most previous ML-based methods have only focused on predicting a single outcome, ignoring the potential correlations between different outcomes, and potentially leading to suboptimal results and overfitting issues. In this work, we first analyze the correlations between three adverse neonatal outcomes and then formulate the diagnosis of multiple neonatal outcomes as a multi-task learning (MTL) problem. We then propose an MTL framework to jointly predict multiple adverse neonatal outcomes. In particular, the MTL framework contains shared hidden layers and multiple task-specific branches. Extensive experiments have been conducted using Electronic Health Records (EHRs) from 121 preterm neonates. Empirical results demonstrate the effectiveness of the MTL framework. Furthermore, the feature importance is analyzed for each neonatal outcome, providing insights into model interpretability.

Hydrocortisone and bronchopulmonary dysplasia: variables associated with response in premature infants.

OBJECTIVE: The primary objective was to evaluate hydrocortisone's efficacy for decreasing respiratory support in premature infants with developing bronchopulmonary dysplasia (BPD). Secondary objectives included assessment of the impact of intrauterine growth restriction (IUGR), maternal history of chorioamnionitis, side effects and route of administration associated with hydrocortisone's efficacy. Dexamethasone as second-line treatment to decrease respiratory support was reviewed. METHODS: Retrospective chart review of preterm infants requiring respiratory support receiving hydrocortisone. RESULTS: A total of 48 patients were included. Successful extubation was achieved in 50% of intubated patients after hydrocortisone treatment with no major complications. In our small study, history of maternal chorioamnionitis, IUGR or route of administration did not affect the response. Rescue dexamethasone after hydrocortisone therapy was ineffective in the ten patients who failed extubation following hydrocortisone. CONCLUSION: Hydrocortisone is effective in decreasing respiratory support in patients with developing BPD without major complications. Randomized studies are warranted to confirm our findings.