ADVANCING THE UNDERSTANDING OF CLINICAL SEPSIS USING GENE EXPRESSION-DRIVEN MACHINE LEARNING TO IMPROVE PATIENT OUTCOMES.

ABSTRACT: Sepsis remains a major challenge that necessitates improved approaches to enhance patient outcomes. This study explored the potential of machine learning (ML) techniques to bridge the gap between clinical data and gene expression information to better predict and understand sepsis. We discuss the application of ML algorithms, including neural networks, deep learning, and ensemble methods, to address key evidence gaps and overcome the challenges in sepsis research. The lack of a clear definition of sepsis is highlighted as a major hurdle, but ML models offer a workaround by focusing on endpoint prediction. We emphasize the significance of gene transcript information and its use in ML models to provide insights into sepsis pathophysiology and biomarker identification. Temporal analysis and integration of gene expression data further enhance the accuracy and predictive capabilities of ML models for sepsis. Although challenges such as interpretability and bias exist, ML research offers exciting prospects for addressing critical clinical problems, improving sepsis management, and advancing precision medicine approaches. Collaborative efforts between clinicians and data scientists are essential for the successful implementation and translation of ML models into clinical practice. Machine learning has the potential to revolutionize our understanding of sepsis and significantly improve patient outcomes. Further research and collaboration between clinicians and data scientists are needed to fully understand the potential of ML in sepsis management.

Heliox with inhaled nitric oxide: a novel strategy for severe localized interstitial pulmonary emphysema in preterm neonatal ventilation.

We describe the combined use of inhaled nitric oxide and heliox (79% helium and 21% oxygen) as a rescue therapy for a critically ill infant with localized interstitial pulmonary emphysema and pulmonary hypertension. Conventional interventions were ineffective, not feasible, or unlikely to take effect in time, during this infant's acute critical illness. We added heliox based on its known pulmonary effects, and inhaled nitric oxide to improve oxygenation, after echocardiographic evidence of high right-ventricular pressure. The infant made a full recovery. To our knowledge this is the first case report of heliox and inhaled nitric oxide used simultaneously in localized interstitial pulmonary emphysema.