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Predicting Failure of Non-invasive Ventilation in Children with Risk Stratification Score
Start Date: 8/31/2023Start Time: 10:00 AM
End Date: 8/31/2023End Time: 12:00 PM

Event Description
BIOMED PhD Research Proposal

Predicting Failure of Non-invasive Ventilation in Children with Risk Stratification Score

Natalie Napolitano, PhD Candidate
School of Biomedical Engineering, Science and Health Systems
Drexel University

Amy Throckmorton, PhD
School of Biomedical Engineering, Science and Health Systems
Drexel University

Akira Nishisaki, MD, MSCE
Department of Anesthesiology and Critical Care Medicine
Children's Hospital of Philadelphia (CHOP)
Associate Professor of Anesthesiology and Critical Care
Perelman School of Medicine
University of Pennsylvania

Non-invasive mechanical ventilation (NIV) support for children with acute respiratory distress has become a recognized clinical standard of care. It is well reported as a viable clinical treatment strategy for a wide range of pediatric respiratory conditions, such as asthma, bronchiolitis, pneumonia, and acute respiratory distress syndrome (ARDS). Investigations of NIV to-date are, however, limited to retrospective cohorts with small sample sizes on specific respiratory diseases and do not demonstrate the full scope of NIV use including risks and clinical outcomes of failure. Further, there are inadequate studies of NIV in general that examine patient outcomes, optimal settings, and timing of determining therapy failure in children. NIV failure requires transition to invasive mechanical ventilation (IV), which is well known to experience high-risk adverse events, such as severe oxygen desaturation and cardiac arrest. The clinical decision-making process, including the timing of transition to IV is complex, multi-factorial, and associated with decision delays, thus contributing to mortality in high-risk children. The transition from NIV to IV at the appropriate time during clinical management improves patient outcomes, but there is an inadequate understanding of the optimal transition timing to achieve the best clinical results. Current clinical data fall short of analyzing the trends and identifying predictors of NIV failure; thus, this clinically motivates the use of evidence-based decision-making tools and approaches for these high-risk and vulnerable pediatric patients.

To-date, research studies have identified and evaluated clinically relevant parameters, such as heart rate, respiratory rate, and oxygen requirement, that demonstrate correlation in prediction of NIV failure and thus supporting subsequent transition to IV therapy. However, the timing to transition to IV is not protocolized and is dependent on clinician’s individual assessment; thus, use of NIV failure defined with only the single metric of intubation, without considering long-term outcomes, as an outcome is not a scientifically robust approach. Further, these studies only examined the impact of each individual parameter separately, as opposed to an interrelated, interdependent combination of parameters that lead to a clinical treatment decision. The analysis of each clinically relevant parameter only and its impact separately is insufficient and inadequate to support clinical decision making, whereby a multitude of data are considered to determine the most effective treatment pathway. This clinically motivates the need for assessing the clinical interplay and interdependency among those critical parameters that are employed in the prediction of NIV failure in high-risk patients.

Thus, to further our knowledge of NIV failure in pediatric patients, my proposal focuses on the following specific aims:
(1) Characterize the timing, intensity, and duration of NIV use in pediatric patients. This will be accomplished by analyzing pre-specified clinically important outcomes (ICU mortality, length of time requiring respiratory support, necessity of intubation, and relevant adverse events/major desaturation SpO2<70% during TI) among critically ill children through a combined retrospective dataset of individualized clinical data.

(2) Investigate feasibility of a non-invasive scoring system from clinical parameters. This will be accomplished by evaluating currently employed clinical parameters to identify those parameters with significant contributions to decision-making. The goal is to determine the optimal timing to transition from NIV to IV using the score as an independent variable and the occurrence of the patient-centered outcome as a dichotomous outcome. The score will be developed by identifying the clinical variables that are available and are clinically relevant to the therapy failure.

(3) Determine the non-invasive score and timeline threshold that would predict failure. Here I will establish the optimal timing to transition from NIV to IV. The newly developed scoring system will have robust prediction characteristics as determined by a robust mathematically modeling construct based on the Area Under the Curve (AUC) of the Receiver Operating Characteristics (ROC) Curve and Precision-Recall Curve analyses.
Contact Information:
Name: Natalia Broz
Email: njb33@drexel.edu
Natalie Napolitano
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