Date of Award

8-2025

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

School

Leadership and Advanced Nursing Practice

Committee Chair

Dr. Lachel Story

Committee Chair School

Leadership and Advanced Nursing Practice

Committee Member 2

Dr. Patsy Anderson

Committee Member 2 School

Leadership and Advanced Nursing Practice

Committee Member 3

Dr. LaWanda Baskin

Committee Member 3 School

Leadership and Advanced Nursing Practice

Committee Member 4

Dr. Aleise McGowan

Committee Member 4 School

Computing Sciences and Computer Engineering

Committee Member 5

Dr. Marlene Walden

Abstract

Neonatal sepsis remains one of the leading causes of global neonatal mortality. Reactionary approaches for diagnosis and treatment have dominated the tactics in addressing neonatal sepsis but clinical intuition is an untapped resource that could lead to earlier prediction of sepsis onset. Nurses and other staff with specialized training and experience who have served as routine caregivers for a specific patient are able to identify when the patient’s status is altered. This clinical intuition may be substantiated by referencing specific patient trends in non-invasive measures over time. This retrospective, exploratory study examined whether variation in non-invasive monitoring variables could serve as early indicators of sepsis in neonates.

The doctoral dissertation (the study) included 69 neonates (23 with sepsis and 46 matched controls) with 168 hours of monitoring data prior to the onset of sepsis. A combination of statistical approaches including Analysis of Variance (ANOVA), Mann-Whitney U tests, Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression, change-point analysis, and Cox proportional hazards models were employed. Nearly all non-invasive physiological variables demonstrated significant differences between septic and non-septic neonates, except for respiratory rate. LASSO regression identified variability in respiratory support, feeding intolerance, and abdominal distention as significant predictors of sepsis, with respiratory support demonstrating the strongest association. Cox models revealed that increased heart rate, respiratory rate, inspired oxygen concentration, and body temperature, along with decreased blood oxygen saturation and diastolic blood pressure, were significantly associated with an elevated hazard of sepsis. Change-point analysis detected early and significant increases in the frequency of bradycardia events, abdominal distention, and chest retractions beginning 48 to 72 hours prior to clinical recognition of sepsis in affected neonates.

These findings suggest that routine, non-invasive monitoring data can be used to identify early signs of impending sepsis, well before clinical diagnosis. The integration of these variables (heart rate, respiratory rate, inspired oxygen concentration, body temperature, blood oxygen saturation, diastolic blood pressure, respiratory support, feeding intolerance, abdominal distention, bradycardia events, and chest retractions) into a predictive decision support tool may enable earlier intervention, improve neonatal outcomes, and support more informed staffing and care prioritization strategies in neonatal intensive care units.

ORCID ID

0000-0002-2544-7111

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