Highly comparative time series analysis of oxygen saturation and heart rate to predict respiratory outcomes in extremely preterm infants
Year: 2024
Type: article
Abstract: Objective Highly comparative time series analysis (HCTSA) is a novel approach involving massive feature extraction using publicly available code from many disciplines. The Prematurity-Related Ventilatory Control (Pre-Vent) observational multicenter prospective study collected bedside monitor data from > 700 extremely preterm infants to identify physiologic features that predict respiratory outcomes. We calculated a subset of 33 HCTSA features on > 7 M 10-minute windows of oxygen saturation (SPO2) and heart rate (HR) from the Pre-Vent cohort to quantify predictive performance. This subset included representatives previously identified using unsupervised clustering on > 3500 HCTSA algorithms. Performance of each feature was measured by individual area under the receiver operating curve (AUC) at various days of life and binary respiratory outcomes. These were compared to optimal PreVent physiologic predictor IH90 DPE, the duration per event of intermittent hypoxemia events with threshold of 90%. Main Results The top HCTSA features were from a cluster of algorithms associated with the autocorrelation of SPO2 time series and identified low frequency patterns of desaturation as high risk. These features had comparable performance to and were highly correlated with IH90 DPE but perhaps measure the physiologic status of an infant in a more robust way that warrants further investigation. The top HR HCTSA features were symbolic transformation measures that had previously been identified as strong predictors of neonatal mortality. HR metrics were only important predictors at early days of life which was likely due to the larger proportion of infants whose outcome was death by any cause. A simple HCTSA model using 3 top features outperformed IH90 DPE at day of life 7 (.778 versus .729) but was essentially equivalent at day of life 28 (.849 versus .850). These results validated the utility of a representative HCTSA approach but also provides additional evidence supporting IH90 DPE as an optimal predictor of respiratory outcomes.
Source: Physiological Measurement
Authors: Jiaxing Qiu, Juliann M Di Fiore, Narayanan Krishnamurthi, Premananda Indic, John L Carroll, Nelson Claure, James S Kemp, Phyllis A Dennery, Namasivayam Ambalavanan, Debra E Weese-Mayer, Anna Maria Hibbs, Richard J Martin, Eduardo Bancalari, Aaron Hamvas, J Randall Moorman, Douglas E Lake, Pre-Vent Investigators, Katy N Krahn, Amanda M Zimmet, Bradley S Hopkins, Erin K Lonergan, Casey M Rand, Arlene Zadell, Arie Nakhmani, Waldemar A Carlo, Deborah Laney, Colm P Travers, Silvia Vanbuskirk, Carmen D’Ugard, Ana Cecilia Aguilar, Alini Schott, Julie Hoffmann, Laura Linneman
Institutions: University of Virginia Medical Center, University of Virginia, Rainbow Babies & Children's Hospital, Case Western Reserve University, Northwestern University, The University of Texas at Tyler, Arkansas Children's Hospital, University of Arkansas for Medical Sciences, University of Miami, Washington University in St. Louis, Brown University, University of Alabama at Birmingham, UAB Medicine, Lurie Children's Hospital, University Hospitals of Cleveland, University Hospitals Cleveland Medical Center, Jackson Memorial Hospital
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,165
Funders: U.S. Department of Health and Human Services, University of Miami, Northwestern University, Johns Hopkins University, University of Virginia, Children’s Hospital of Wisconsin Research Institute, National Institutes of Health, Leonard M. Miller School of Medicine, Washington University School of Medicine in St. Louis, National Heart, Lung, and Blood Institute, National Institute of Neurological Disorders and Stroke, Eunice Kennedy Shriver National Institute of Child Health and Human Development
Awards: Hibbs -Association Between Intermittent Hypoxia and Later Respiratory Morbidity, G2570087217, Integrated analysis of autonomic biomarkers in prematurity-related ventilatory control: Determination of neurorespiratory maturation and predictors of co-morbidity risk, Oxygenation instability and maturation of control of breathing in evolving BPD., Integrated physiomarker, biomarker and clinical predictive analytics for early warning of sepsis and necrotizing enterocolitis in very low birth weight infants., G4823492396, Prematurity-Related Ventilatory Control: Leadership Data and Coordination Center (LDCC), PHYSIOLOGIC BIOMARKERS PREDICTING VENTILATORY INSTABILITY AND HYPOXEMIA IN PREMATURE INFANTS, Racial Disparities in Preterm Brain Injury Are Driven by Differences in Cerebral Autoregulation, Pre-Vent Apnea, Non-invasive oscillometry to measure lung mechanics, response to treatments, and predict longer-term pulmonary outcomes among preterm infants: a prospective cohort study
OpenAlex ID: W4398159262