Vulnerable infants: Prediction and diagnosis of respiratory outcomes

Polavarapu, Mounika

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https://hdl.handle.net/2142/105176 Copy

Description

Title

Vulnerable infants: Prediction and diagnosis of respiratory outcomes

Author(s)

Polavarapu, Mounika

Issue Date

2019-04-12

Director of Research (if dissertation) or Advisor (if thesis)

Klonoff-Cohen, Hillary S.

Doctoral Committee Chair(s)

Klonoff-Cohen, Hillary S.

Committee Member(s)

• An, Ruopeng
• Joshi, Divya
• Kumar, Praveen
• Rosenblatt, Karin

Department of Study

Kinesiology & Community Health

Discipline

Community Health

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

bronchopulmonary dysplasia, prediction, diagnosis, childhood asthma, serum eosinophil cationic protein, SIDS, risk score

Abstract

The overall aim of my dissertation is to explore and develop prediction and diagnostic approaches to three health outcomes in vulnerable infants associated with respiratory system disorders: (i) Bronchopulmonary Dysplasia, the most common adverse outcome in premature infants, (ii) Childhood Asthma, the most common chronic condition among children, and (iii) Sudden Infant Death Syndrome, the third leading cause of death among all infants in the US. Project 1: Bronchopulmonary dysplasia (BPD) is a form of chronic lung disease that affects primarily premature newborns and infants. The objective of this project was to develop a clinical prediction model for bronchopulmonary dysplasia (BPD) in a setting where non-invasive ventilation is the primary choice of ventilatory support. The goal was to have the ability to predict the risk of BPD at an early stage of life on days 1, 7, and 21 of postnatal age to determine which infants will benefit most from interventions that may reduce the risk of developing BPD (primary prevention) and its progression. Early administration of caffeine (within 48 hours), antenatal steroids, and maximum FiO2 levels were found to add significant predictive value to the adverse outcome of BPD and its severity. The c-statistics for the prediction model on day 1 was 0.9062, on day 7 was 0.9270, and on day 21 was 0.9434. This model reflects improvements/decisions in clinical treatment advances and may enable clinicians and parents to make more optimal decisions on prophylactic treatment options to prevent bronchopulmonary dysplasia among infants. Project 2: Childhood asthma is an enormous challenge for clinicians because it lacks standardized diagnostic criteria. An inflammatory biomarker could represent a critical factor in developing tools that reliably predict the development of asthma in young children in daily clinical practice. A systematic review and meta-analysis of existing literature were conducted to evaluate the efficacy of an airway inflammatory marker, serum eosinophil cationic protein, in diagnosing asthma among children up to 5 years of age. Although a definitive role for serum eosinophil cationic protein in the diagnosis of asthma in young children <5 years was not established in this study because of the small number of research articles, it may be a valuable biomarker if measured in a larger group of younger asthmatic patients, stratified by age at the critical time for lung development. A multicentric population-based prospective study with longer follow-up periods are necessary to confirm the role of serum eosinophil cationic protein in diagnosing childhood asthma among children less than 5 years of age. Project 3: This project aimed to develop a SIDS risk scoring system to identify the cumulative effects of maternal, infant and environmental factors that may be predictive of SIDS risk. A risk scoring system ranging from 0-6 was developed based on the risk factors, maternal age, birth weight of the infant, exposure to passive, and the duration of breastfeeding. Factors making infants vulnerable to SIDS (low birth weight, young maternal age) in combination with the effect of exogenous stressors (passive smoking, breastfeeding) during the critical developmental period predicted the risk of SIDS in our model. The highest risk score of 6 had a sensitivity of 100% and a positive predictive value of 80.33%. For a cuff off criterion of score 1 and lower for low-risk, the calculated risk score had a specificity of 100% and a negative predictive value of 92.68%. Identifying infants at high risk of SIDS enables parents and clinicians to be more vigilant about how to possibly prevent these infant deaths. Furthermore, preventing SIDS in low-risk infants will also relieve some anxiety among parents.

Graduation Semester

2019-05

Type of Resource

text

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http://hdl.handle.net/2142/105176

Copyright and License Information

Copyright 2019 Mounika Polavarapu

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