Background/Case Studies: Neonatal and pediatric patients are uniquely vulnerable to transfusion-related complications. However, evidence guiding transfusion practices remains limited due to small, heterogenous cohorts and lack of robust data. Clinical decisions often rely on extrapolated adult data or institutional dogma. Investigating transfusion impact is further hindered by manual, labor-intensive chart reviews. To address this, we introduce TransfusaScope, a novel tool that integrates dynamic physiologic monitoring with transfusion event data to enable high-resolution, automated visualization, analysis, and clinical decision support.
Study
Design/Methods: TransfusaScope was developed and validated using retrospective data from a cohort of 30 pediatric inpatients who underwent transfusion during hospitalization. The system extracted and integrated data from the electronic medical record (EMR), continuous vital sign monitoring systems, and laboratory information systems. Key variables—transfusion timing, product type, lab values, and vital signs—were extracted and displayed on an interactive dashboard. The dashboard was designed with synchronized event timelines, color-coded trend overlays, interactive filtering tools for stratification, and real-time anomaly detection algorithms allowing users to explore relationships between transfusion events and physiologic data. Data accuracy and integrity were validated through manual comparison against the EMR and iterative refinement of extraction algorithms. Clinician feedback guided refinement of both the user interface and backend logic, ensuring clinical relevance and usability.
Results/Findings: Figure A illustrates the system’s functionality in a 2-month-old male with severe left-sided congenital diaphragmatic hernia (CDH) and a complex clinical course. TransfusaScope captured red blood cell transfusion volume and duration of transfusion along with trends in hemoglobin, respiratory rate, pulse, mean arterial pressure (MAP) and oxygenation (SpO2) in a comprehensive physiologic timeline.
Conclusions: TransfusaScope provides an opportunity to advance pediatric transfusion analytics by unifying multimodal, disparate data into a single, visual interface. It’s real-time EMR integration can reveal transfusion-related patterns and enhance clinical workflows, support precision medicine, and inform blood utilization strategies. For future clinical trials, it can help identify subgroups and endotypes focused on optimal timing and patient-specific transfusion thresholds. Finally, by using a unified, intuitive display with spatial encoding, dynamic highlighting, and context-aware overlays, TransfusaScope could, compared to traditional monitoring formats, promote earlier detection of transfusion-related complications and improve clinical outcomes.
