Lilliam Ambroggio (United States of America)

Children's Hospital Colorado Pediatrics
Lilliam Ambroggio, PhD, is an Associate Professor of Pediatrics, and serves as the Associate Director of Research for the Section of Emergency Medicine, and the Director of Research for the Section of Hospital Medicine at the University of Colorado and the Children’s Hospital Colorado. Her federally-funded research program focuses on improving outcomes for children with common, serious respiratory infections by developing methods to improve diagnostic accuracy, implementing these methods into clinical practice, and improving the overall management of children with these infections across acute care settings. Previous studies have focused on antibiotic resistance, empiric antibiotic choice, using -omics technology to develop more accurate diagnostics, and imaging modality in managing pneumonia in children. Dr. Ambroggio enjoys mentoring the next generation of physician-scientists from all trainee levels in a wide variety of fields from firearm injury in the ED to transcriptomics of ventilator associated pneumonia for critically ill children.

Author Of 2 Presentations

DISCRIMINATION OF VIRAL FROM BACTERIAL COMMUNITY ACQUIRED PNEUMONIA IN CHILDREN USING URINE METABOLOMICS

Date
Fri, 13.05.2022
Session Time
10:00 - 11:30
Session Type
Oral Presentations Session
Room
MC 2 HALL
Lecture Time
10:52 - 11:02

Abstract

Backgrounds:

Differentiating bacterial from viral etiologies of pediatric community-acquired pneumonia (CAP) is critical to guiding appropriate therapy. However, current tests are insensitive, invasive, or impractical in children. The objective of this study is to identify candidate metabolomic biomarkers that differentiate bacteria from viral CAP.

Methods

We studied a cohort of children, 3 months-18 years old, with suspected CAP in the emergency department. Patients with chronic medical conditions or who were hospitalized 14 days prior were excluded. Viral and Mycoplasma pneumoniae (Mp) were detected by PCR of nasopharyngeal swabs. Suspected Streptococcus pneumoniae (Sp) was defined as presence of pneumococcal autolysin (lytA) and a procalcitonin of ≥1.5 ng/mL. Urine samples were collected at time of presentation and metabolites were identified and quantified by nuclear magnetic resonance spectroscopy. Metabolomics data were standardized using specific gravity. Demographic and clinical characteristics by patient status ( MP, Sp and viral) were compared using chi-square tests and ANOVA, as applicable. Random forest (RF) was used to determine the most important metabolites and clinical factors to discriminate viral etiology from Mp and Sp.

Results:

Of 160 children, 28 (17.5%) had Mp, 13 (8.1%) had Sp, and 119 (74.4%) had a virus detected by PCR (Table). Most (87%) were between 1-12 years old. The most important variables identified by RF included age, prior history of reactive airways disease, 1-methylnicotinamide, hypoxanthine, tryptophan, quinolinate, valine, trimethylamine-N-oxide, ascorbate, and 4-hydroxybenzoate.

aim 2b table_page_1.jpg

Conclusions/Learning Points:

Metabolites related to inflammatory pathways (e.g., tryptophan, quniolinate) and microbial metabolism (e.g., trimethylamine-N-oxide, 4-hydroxybenzoate) differentiated viral from typical and atypical bacterial CAP in children. Urine metabolomics can identify novel biomarkers to differentiate bacterial from viral CAP in children.

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PREDICTING SEVERE PNEUMONIA IN THE EMERGENCY DEPARTMENT: A GLOBAL STUDY OF THE PEDIATRIC EMERGENCY RESEARCH NETWORK (PERN)

Date
Thu, 12.05.2022
Session Time
08:00 - 09:30
Session Type
Parallel Symposium
Room
DIMITRIS MITROPOULOS HALL
Lecture Time
09:07 - 09:17

Abstract

Backgrounds:

Pneumonia is a frequent and costly cause of emergency department (ED) visits and hospitalizations in children. No validated tools exist to assist with management decisions for children presenting to the ED with community-acquired pneumonia (CAP). Our objective was to develop prediction models to accurately risk stratify children with CAP across a global network of pediatric EDs.

Methods

Prospective study of children 3 months to <14 years old with CAP at 69 EDs in the Pediatric Emergency Research Network. We excluded children with recent hospitalizations, chronic conditions, or critically ill. The primary outcome was an ordinal composite of CAP severity occurring within 7 days: mild (discharged), moderate (hospitalized but not severe), and severe (empyema/effusion requiring drainage, ICU>48 hours, respiratory failure requiring positive-pressure ventilation, septic shock, vasoactive infusions, extracorporeal membrane oxygenation, or death). Multivariable logistic regression was used to develop risk models for moderate/severe disease (vs. mild) and for severe disease (vs. mild or moderate).

Results:

Of 2518 children, 1314 (52.2%) had mild CAP, 1094 (43.4%) moderate, and 110 (4.4%) severe (Table 1). Vomiting, elevated heart rate, elevated respiratory rate, oxygen saturation <90%, altered mental status, retractions, prolonged capillary refill, and pleural effusion were associated with development of moderate/severe CAP (Table 2). Elevated heart rate, asymmetric breath sounds, retractions, and pleural effusion were associated with severe CAP. The AUC for the moderate/severe model was 0.844 (95% CI, 0.828, 0.860) and for the severe model was 0.827 (95% CI, 0.792, 0.862).

pern table 1 pas 2022.png

pern table 2 pas 2022.png

Conclusions/Learning Points:

We prospectively derived risk prediction models for pediatric CAP with features easily available at ED presentation in a global cohort of pediatric EDs. Both demonstrated excellent ability to predict moderate/severe disease warranting hospitalization, and severe disease for which intensive care should be considered.

Hide

Presenter Of 2 Presentations

DISCRIMINATION OF VIRAL FROM BACTERIAL COMMUNITY ACQUIRED PNEUMONIA IN CHILDREN USING URINE METABOLOMICS

Date
Fri, 13.05.2022
Session Time
10:00 - 11:30
Session Type
Oral Presentations Session
Room
MC 2 HALL
Lecture Time
10:52 - 11:02

Abstract

Backgrounds:

Differentiating bacterial from viral etiologies of pediatric community-acquired pneumonia (CAP) is critical to guiding appropriate therapy. However, current tests are insensitive, invasive, or impractical in children. The objective of this study is to identify candidate metabolomic biomarkers that differentiate bacteria from viral CAP.

Methods

We studied a cohort of children, 3 months-18 years old, with suspected CAP in the emergency department. Patients with chronic medical conditions or who were hospitalized 14 days prior were excluded. Viral and Mycoplasma pneumoniae (Mp) were detected by PCR of nasopharyngeal swabs. Suspected Streptococcus pneumoniae (Sp) was defined as presence of pneumococcal autolysin (lytA) and a procalcitonin of ≥1.5 ng/mL. Urine samples were collected at time of presentation and metabolites were identified and quantified by nuclear magnetic resonance spectroscopy. Metabolomics data were standardized using specific gravity. Demographic and clinical characteristics by patient status ( MP, Sp and viral) were compared using chi-square tests and ANOVA, as applicable. Random forest (RF) was used to determine the most important metabolites and clinical factors to discriminate viral etiology from Mp and Sp.

Results:

Of 160 children, 28 (17.5%) had Mp, 13 (8.1%) had Sp, and 119 (74.4%) had a virus detected by PCR (Table). Most (87%) were between 1-12 years old. The most important variables identified by RF included age, prior history of reactive airways disease, 1-methylnicotinamide, hypoxanthine, tryptophan, quinolinate, valine, trimethylamine-N-oxide, ascorbate, and 4-hydroxybenzoate.

aim 2b table_page_1.jpg

Conclusions/Learning Points:

Metabolites related to inflammatory pathways (e.g., tryptophan, quniolinate) and microbial metabolism (e.g., trimethylamine-N-oxide, 4-hydroxybenzoate) differentiated viral from typical and atypical bacterial CAP in children. Urine metabolomics can identify novel biomarkers to differentiate bacterial from viral CAP in children.

Hide

PREDICTING SEVERE PNEUMONIA IN THE EMERGENCY DEPARTMENT: A GLOBAL STUDY OF THE PEDIATRIC EMERGENCY RESEARCH NETWORK (PERN)

Date
Thu, 12.05.2022
Session Time
08:00 - 09:30
Session Type
Parallel Symposium
Room
DIMITRIS MITROPOULOS HALL
Lecture Time
09:07 - 09:17

Abstract

Backgrounds:

Pneumonia is a frequent and costly cause of emergency department (ED) visits and hospitalizations in children. No validated tools exist to assist with management decisions for children presenting to the ED with community-acquired pneumonia (CAP). Our objective was to develop prediction models to accurately risk stratify children with CAP across a global network of pediatric EDs.

Methods

Prospective study of children 3 months to <14 years old with CAP at 69 EDs in the Pediatric Emergency Research Network. We excluded children with recent hospitalizations, chronic conditions, or critically ill. The primary outcome was an ordinal composite of CAP severity occurring within 7 days: mild (discharged), moderate (hospitalized but not severe), and severe (empyema/effusion requiring drainage, ICU>48 hours, respiratory failure requiring positive-pressure ventilation, septic shock, vasoactive infusions, extracorporeal membrane oxygenation, or death). Multivariable logistic regression was used to develop risk models for moderate/severe disease (vs. mild) and for severe disease (vs. mild or moderate).

Results:

Of 2518 children, 1314 (52.2%) had mild CAP, 1094 (43.4%) moderate, and 110 (4.4%) severe (Table 1). Vomiting, elevated heart rate, elevated respiratory rate, oxygen saturation <90%, altered mental status, retractions, prolonged capillary refill, and pleural effusion were associated with development of moderate/severe CAP (Table 2). Elevated heart rate, asymmetric breath sounds, retractions, and pleural effusion were associated with severe CAP. The AUC for the moderate/severe model was 0.844 (95% CI, 0.828, 0.860) and for the severe model was 0.827 (95% CI, 0.792, 0.862).

pern table 1 pas 2022.png

pern table 2 pas 2022.png

Conclusions/Learning Points:

We prospectively derived risk prediction models for pediatric CAP with features easily available at ED presentation in a global cohort of pediatric EDs. Both demonstrated excellent ability to predict moderate/severe disease warranting hospitalization, and severe disease for which intensive care should be considered.

Hide