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Krishnan P, Rad MG, Agarwal P, Marshall C, Yang P, Bhavani SV, Holder AL, Esper A, Kamaleswaran R. HIRA: Heart Rate Interval based Rapid Alert score to characterize autonomic dysfunction among patients with sepsis-related acute respiratory failure (ARF). Physiol Meas 2023; 44:105006. [PMID: 37652033 PMCID: PMC10571460 DOI: 10.1088/1361-6579/acf5c7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 08/14/2023] [Accepted: 08/31/2023] [Indexed: 09/02/2023]
Abstract
Objective. To examine whether heart rate interval based rapid alert (HIRA) score derived from a combination model of heart rate variability (HRV) and modified early warning score (MEWS) is a surrogate for the detection of acute respiratory failure (ARF) in critically ill sepsis patients.Approach. Retrospective HRV analysis of sepsis patients admitted to Emory healthcare intensive care unit (ICU) was performed between sepsis-related ARF and sepsis controls without ARF. HRV measures such as time domain, frequency domain, and nonlinear measures were analyzed up to 24 h after patient admission, 1 h before the onset of ARF, and a random event time in the sepsis controls. Statistical significance was computed by the Wilcoxon Rank Sum test. Machine learning algorithms such as eXtreme Gradient Boosting and logistic regression were developed to validate the HIRA score model. The performance of HIRA and early warning score models were evaluated using the area under the receiver operating characteristic (AUROC).Main Results. A total of 89 (ICU) patients with sepsis were included in this retrospective cohort study, of whom 31 (34%) developed sepsis-related ARF and 58 (65%) were sepsis controls without ARF. Time-domain HRV for Electrocardiogram (ECG) Beat-to-Beat RR intervals strongly distinguished ARF patients from controls. HRV measures for nonlinear and frequency domains were significantly altered (p< 0.05) among ARF compared to controls. The HIRA score AUC: 0.93; 95% confidence interval (CI): 0.88-0.98) showed a higher predictive ability to detect ARF when compared to MEWS (AUC: 0.71; 95% CI: 0.50-0.90).Significance. HRV was significantly impaired across patients who developed ARF when compared to controls. The HIRA score uses non-invasively derived HRV and may be used to inform diagnostic and therapeutic decisions regarding the severity of sepsis and earlier identification of the need for mechanical ventilation.
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Affiliation(s)
- Preethi Krishnan
- Department of Biomedical Engineering, Emory University, Atlanta, GA, Georgia
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, Georgia
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, Georgia
| | - Milad G Rad
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, Georgia
- Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, Georgia
| | - Palak Agarwal
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, Georgia
| | - Curtis Marshall
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, Georgia
| | - Philip Yang
- Emory Critical Care Center, Emory University School of Medicine, Atlanta, GA, Georgia
- Department of Medicine, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Emory University School of Medicine, Atlanta, GA, Georgia
| | - Sivasubramanium V Bhavani
- Emory Critical Care Center, Emory University School of Medicine, Atlanta, GA, Georgia
- Department of Medicine, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Emory University School of Medicine, Atlanta, GA, Georgia
| | - Andre L Holder
- Emory Critical Care Center, Emory University School of Medicine, Atlanta, GA, Georgia
- Department of Medicine, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Emory University School of Medicine, Atlanta, GA, Georgia
| | - Annette Esper
- Emory Critical Care Center, Emory University School of Medicine, Atlanta, GA, Georgia
- Department of Medicine, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Emory University School of Medicine, Atlanta, GA, Georgia
| | - Rishikesan Kamaleswaran
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, Georgia
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, Georgia
- Emory Critical Care Center, Emory University School of Medicine, Atlanta, GA, Georgia
- Department of Medicine, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Emory University School of Medicine, Atlanta, GA, Georgia
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Grunwell JR, Rad MG, Ripple MJ, Yehya N, Wong HR, Kamaleswaran R. Identification of a pediatric acute hypoxemic respiratory failure signature in peripheral blood leukocytes at 24 hours post-ICU admission with machine learning. Front Pediatr 2023; 11:1159473. [PMID: 37009294 PMCID: PMC10063855 DOI: 10.3389/fped.2023.1159473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 03/01/2023] [Indexed: 04/04/2023] Open
Abstract
Background There is no generalizable transcriptomics signature of pediatric acute respiratory distress syndrome. Our goal was to identify a whole blood differential gene expression signature for pediatric acute hypoxemic respiratory failure (AHRF) using transcriptomic microarrays within twenty-four hours of diagnosis. We used publicly available human whole-blood gene expression arrays of a Berlin-defined pediatric acute respiratory distress syndrome (GSE147902) cohort and a sepsis-triggered AHRF (GSE66099) cohort within twenty-four hours of diagnosis and compared those children with a PaO2/FiO2 < 200 to those with a PaO2/FiO2 ≥ 200. Results We used stability selection, a bootstrapping method of 100 simulations using logistic regression as a classifier, to select differentially expressed genes associated with a PaO2/FiO2 < 200 vs. PaO2/FiO2 ≥ 200. The top-ranked genes that contributed to the AHRF signature were selected in each dataset. Genes common to both of the top 1,500 ranked gene lists were selected for pathway analysis. Pathway and network analysis was performed using the Pathway Network Analysis Visualizer (PANEV) and Reactome was used to perform an over-representation gene network analysis of the top-ranked genes common to both cohorts. Changes in metabolic pathways involved in energy balance, fundamental cellular processes such as protein translation, mitochondrial function, oxidative stress, immune signaling, and inflammation are differentially regulated early in pediatric ARDS and sepsis-induced AHRF compared to both healthy controls and to milder acute hypoxemia. Specifically, fundamental pathways related to the severity of hypoxemia emerged and included (1) ribosomal and eukaryotic initiation of factor 2 (eIF2) regulation of protein translation and (2) the nutrient, oxygen, and energy sensing pathway, mTOR, activated via PI3K/AKT signaling. Conclusions Cellular energetics and metabolic pathways are important mechanisms to consider to further our understanding of the heterogeneity and underlying pathobiology of moderate and severe pediatric acute respiratory distress syndrome. Our findings are hypothesis generating and support the study of metabolic pathways and cellular energetics to understand heterogeneity and underlying pathobiology of moderate and severe acute hypoxemic respiratory failure in children.
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Affiliation(s)
- Jocelyn R. Grunwell
- Division of Critical Care Medicine, Children’s Healthcare of Atlanta, Atlanta, GA, United States
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, United States
- Correspondence: Jocelyn R. Grunwell
| | - Milad G. Rad
- Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States
| | - Michael J. Ripple
- Division of Critical Care Medicine, Children’s Healthcare of Atlanta, Atlanta, GA, United States
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, United States
| | - Nadir Yehya
- Department of Anesthesiology and Critical Care Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Division of Pediatric Intensive Care Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
| | - Hector R. Wong
- Division of Critical Care Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
| | - Rishikesan Kamaleswaran
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, United States
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, United States
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, United States
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Kobara S, Rad MG, Grunwell JR, Coopersmith CM, Kamaleswaran R. Bioenergetic Crisis in ICU-Acquired Weakness Gene Signatures Was Associated With Sepsis-Related Mortality: A Brief Report. Crit Care Explor 2022; 4:e0818. [PMID: 36567787 PMCID: PMC9760600 DOI: 10.1097/cce.0000000000000818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
To investigate the relationship between ICU-acquired weakness (ICUAW) signatures and sepsis-related mortality using gene expression from the blood within 24 hours of sepsis onset. DESIGN Observational study using differential gene expression analysis. SETTING Publicly available gene expression profile GSE54514, single-center medical and surgical ICU. PATIENTS Patients with primary bacteremia- and respiratory-triggered sepsis including 8 nonsurvivors and 13 survivors who were 18 years old and older and admitted to ICU. MEASUREMENTS AND MAIN RESULTS Among validated 526 ICUAW gene signatures, differential gene expression analysis controlling for age identified 38 significantly expressed genes between nonsurvivors and survivors. Functional enrichment analysis of differentially expressed ICUAW genes identified impaired cadherin binding, sarcomere formation, and energy metabolism among nonsurvivors. CONCLUSIONS Our findings demonstrated a biological association between sepsis-related mortality and ICUAW signatures in the early phase of sepsis. Defects in energy metabolism and muscle fiber formation were associated with sepsis-related mortality.
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Affiliation(s)
- Seibi Kobara
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA
| | - Milad G Rad
- Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA
| | - Jocelyn R Grunwell
- Department of Pediatrics, Division of Critical Care, Emory University School of Medicine, Atlanta, GA
- Division of Critical Care Medicine, Children's Healthcare of Atlanta, Atlanta, GA
| | - Craig M Coopersmith
- Department of Surgery and Emory Critical Care Center, Emory University School of Medicine, Atlanta, GA
| | - Rishikesan Kamaleswaran
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA
- Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA
- Department of Emergency Medicine, Emory University School of Medicine, Atlanta, GA
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Grunwell JR, Rad MG, Stephenson ST, Mohammad AF, Opolka C, Fitzpatrick AM, Kamaleswaran R. Cluster analysis and profiling of airway fluid metabolites in pediatric acute hypoxemic respiratory failure. Sci Rep 2021; 11:23019. [PMID: 34836982 PMCID: PMC8626441 DOI: 10.1038/s41598-021-02354-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 11/09/2021] [Indexed: 11/24/2022] Open
Abstract
Hierarchal clustering of amino acid metabolites may identify a metabolic signature in children with pediatric acute hypoxemic respiratory failure. Seventy-four immunocompetent children, 41 (55.4%) with pediatric acute respiratory distress syndrome (PARDS), who were between 2 days to 18 years of age and within 72 h of intubation for acute hypoxemic respiratory failure, were enrolled. We used hierarchal clustering and partial least squares-discriminant analysis to profile the tracheal aspirate airway fluid using quantitative LC–MS/MS to explore clusters of metabolites that correlated with acute hypoxemia severity and ventilator-free days. Three clusters of children that differed by severity of hypoxemia and ventilator-free days were identified. Quantitative pathway enrichment analysis showed that cysteine and methionine metabolism, selenocompound metabolism, glycine, serine and threonine metabolism, arginine biosynthesis, and valine, leucine, and isoleucine biosynthesis were the top five enriched, impactful pathways. We identified three clusters of amino acid metabolites found in the airway fluid of intubated children important to acute hypoxemia severity that correlated with ventilator-free days < 21 days. Further studies are needed to validate our findings and to test our models.
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Affiliation(s)
- Jocelyn R Grunwell
- Children's Healthcare of Atlanta, Egleston Hospital, Atlanta, GA, USA. .,Department of Pediatrics, Children's Healthcare of Atlanta at Egleston, Division of Critical Care Medicine, Emory University School of Medicine, 1405 Clifton Road NE, Atlanta, GA, 30322, USA.
| | - Milad G Rad
- Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Susan T Stephenson
- Department of Pediatrics, Children's Healthcare of Atlanta at Egleston, Division of Critical Care Medicine, Emory University School of Medicine, 1405 Clifton Road NE, Atlanta, GA, 30322, USA
| | - Ahmad F Mohammad
- Department of Pediatrics, Children's Healthcare of Atlanta at Egleston, Division of Critical Care Medicine, Emory University School of Medicine, 1405 Clifton Road NE, Atlanta, GA, 30322, USA
| | - Cydney Opolka
- Children's Healthcare of Atlanta, Egleston Hospital, Atlanta, GA, USA
| | - Anne M Fitzpatrick
- Department of Pediatrics, Children's Healthcare of Atlanta at Egleston, Division of Critical Care Medicine, Emory University School of Medicine, 1405 Clifton Road NE, Atlanta, GA, 30322, USA
| | - Rishikesan Kamaleswaran
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, USA.,Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA
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Grunwell JR, Rad MG, Stephenson ST, Mohammad AF, Opolka C, Fitzpatrick AM, Kamaleswaran R. Machine Learning-Based Discovery of a Gene Expression Signature in Pediatric Acute Respiratory Distress Syndrome. Crit Care Explor 2021; 3:e0431. [PMID: 34151274 PMCID: PMC8208445 DOI: 10.1097/cce.0000000000000431] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
OBJECTIVES To identify differentially expressed genes and networks from the airway cells within 72 hours of intubation of children with and without pediatric acute respiratory distress syndrome. To test the use of a neutrophil transcription reporter assay to identify immunogenic responses to airway fluid from children with and without pediatric acute respiratory distress syndrome. DESIGN Prospective cohort study. SETTING Thirty-six bed academic PICU. PATIENTS Fifty-four immunocompetent children, 28 with pediatric acute respiratory distress syndrome, who were between 2 days to 18 years old within 72 hours of intubation for acute hypoxemic respiratory failure. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS We applied machine learning methods to a Nanostring transcriptomics on primary airway cells and a neutrophil reporter assay to discover gene networks differentiating pediatric acute respiratory distress syndrome from no pediatric acute respiratory distress syndrome. An analysis of moderate or severe pediatric acute respiratory distress syndrome versus no or mild pediatric acute respiratory distress syndrome was performed. Pathway network visualization was used to map pathways from 62 genes selected by ElasticNet associated with pediatric acute respiratory distress syndrome. The Janus kinase/signal transducer and activator of transcription pathway emerged. Support vector machine performed best for the primary airway cells and the neutrophil reporter assay using a leave-one-out cross-validation with an area under the operating curve and 95% CI of 0.75 (0.63-0.87) and 0.80 (0.70-1.0), respectively. CONCLUSIONS We identified gene networks important to the pediatric acute respiratory distress syndrome airway immune response using semitargeted transcriptomics from primary airway cells and a neutrophil reporter assay. These pathways will drive mechanistic investigations into pediatric acute respiratory distress syndrome. Further studies are needed to validate our findings and to test our models.
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Affiliation(s)
- Jocelyn R Grunwell
- Children's Healthcare of Atlanta, Egleston Hospital, Atlanta, GA
- Emory University School of Medicine, Department of Pediatrics, Division of Critical Care Medicine, Atlanta, GA
| | - Milad G Rad
- Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA
| | - Susan T Stephenson
- Emory University School of Medicine, Department of Pediatrics, Division of Critical Care Medicine, Atlanta, GA
| | - Ahmad F Mohammad
- Emory University School of Medicine, Department of Pediatrics, Division of Critical Care Medicine, Atlanta, GA
| | - Cydney Opolka
- Children's Healthcare of Atlanta, Egleston Hospital, Atlanta, GA
| | - Anne M Fitzpatrick
- Emory University School of Medicine, Department of Pediatrics, Division of Critical Care Medicine, Atlanta, GA
| | - Rishikesan Kamaleswaran
- Emory University School of Medicine, Department of Pediatrics, Division of Critical Care Medicine, Atlanta, GA
- Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA
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