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Shook LL, Castro VM, Herzberg EM, Fourman LT, Kaimal AJ, Perlis RH, Edlow AG. Offspring cardiometabolic outcomes and postnatal growth trajectories after exposure to maternal SARS-CoV-2 infection. Obesity (Silver Spring) 2024; 32:969-978. [PMID: 38351665 PMCID: PMC11039385 DOI: 10.1002/oby.23998] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 12/12/2023] [Accepted: 01/06/2024] [Indexed: 03/13/2024]
Abstract
OBJECTIVE The objective of this study is to determine whether in utero exposure to SARS-CoV-2 is associated with increased risk for a cardiometabolic diagnosis by 18 months of age. METHODS This retrospective electronic health record (EHR)-based cohort study included the live-born offspring of all individuals who delivered during the COVID-19 pandemic (April 1, 2020-December 31, 2021) at eight hospitals in Massachusetts. Offspring exposure was defined as a positive maternal SARS-CoV-2 polymerase chain reaction test during pregnancy. The primary outcome was presence of an ICD-10 code for a cardiometabolic disorder in offspring EHR by 18 months. Weight-, length-, and BMI-for-age z scores were calculated and compared at 6-month intervals from birth to 18 months. RESULTS A total of 29,510 offspring (1599 exposed and 27,911 unexposed) were included. By 18 months, 6.7% of exposed and 4.4% of unexposed offspring had received a cardiometabolic diagnosis (crude odds ratio [OR] 1.47 [95% CI: 1.10 to 1.94], p = 0.007; adjusted OR 1.38 [1.06 to 1.77], p = 0.01). Exposed offspring had a significantly greater mean BMI-for-age z score versus unexposed offspring at 6 months (z score difference 0.19 [95% CI: 0.10 to 0.29], p < 0.001; adjusted difference 0.04 [-0.06 to 0.13], p = 0.4). CONCLUSIONS Exposure to maternal SARS-CoV-2 infection was associated with an increased risk of receiving a cardiometabolic diagnosis by 18 months preceded by greater BMI-for-age at 6 months.
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Affiliation(s)
- Lydia L. Shook
- Department of Obstetrics and Gynecology, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Victor M. Castro
- Center for Quantitative Health and Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA
- Research Information Science and Computing, Mass General Brigham, Somerville, MA
| | - Emily M. Herzberg
- Division of Neonatology and Newborn Medicine, Department of Pediatrics, Massachusetts General Hospital and Harvard Medical School
| | - Lindsay T. Fourman
- Metabolism Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Anjali J. Kaimal
- Department of Obstetrics and Gynecology, University of South Florida Morsani College of Medicine, Tampa, FL
| | - Roy H. Perlis
- Center for Quantitative Health and Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Andrea G. Edlow
- Department of Obstetrics and Gynecology, Massachusetts General Hospital and Harvard Medical School, Boston, MA
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Sunwoo J, Zavriyev AI, Kaya K, Martin A, Munster C, Steele T, Cuddyer D, Sheldon Y, Orihuela-Espina F, Herzberg EM, Inder T, Franceschini MA, El-Dib M. Diffuse correlation spectroscopy blood flow monitoring for intraventricular hemorrhage vulnerability in extremely low gestational age newborns. Sci Rep 2022; 12:12798. [PMID: 35896691 PMCID: PMC9329437 DOI: 10.1038/s41598-022-16499-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [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: 03/22/2022] [Accepted: 07/11/2022] [Indexed: 11/17/2022] Open
Abstract
In premature infants with an extremely low gestational age (ELGA, < 29 weeks GA), dysregulated changes in cerebral blood flow (CBF) are among the major pathogenic factors leading to germinal matrix/intraventricular hemorrhage (GM/IVH). Continuous monitoring of CBF can guide interventions to minimize the risk of brain injury, but there are no clinically standard techniques or tools for its measurement. We report the feasibility of the continuous monitoring of CBF, including measures of autoregulation, via diffuse correlation spectroscopy (DCS) in ELGA infants using CBF variability and correlation with scalp blood flow (SBF, served as a surrogate measure of systemic perturbations). In nineteen ELGA infants (with 9 cases of GM/IVH) monitored for 6–24 h between days 2–5 of life, we found a strong correlation between CBF and SBF in severe IVH (Grade III or IV) and IVH diagnosed within 72 h of life, while CBF variability alone was not associated with IVH. The proposed method is potentially useful at the bedside for the prompt assessment of cerebral autoregulation and early identification of infants vulnerable to GM/IVH.
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Affiliation(s)
- John Sunwoo
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | - Alexander I Zavriyev
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Kutlu Kaya
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Alyssa Martin
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Chelsea Munster
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Tina Steele
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Deborah Cuddyer
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Yvonne Sheldon
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Emily M Herzberg
- Division of Neonatology and Newborn Medicine, Department of Pediatrics, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Terrie Inder
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Maria Angela Franceschini
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Mohamed El-Dib
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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Herzberg EM, Machie M, Glass HC, Shellhaas RA, Wusthoff CJ, Chang T, Abend NS, Chu CJ, Cilio MR, Bonifacio SL, Massey SL, McCulloch CE, Soul JS. Seizure Severity and Treatment Response in Newborn Infants with Seizures Attributed to Intracranial Hemorrhage. J Pediatr 2022; 242:121-128.e1. [PMID: 34780777 DOI: 10.1016/j.jpeds.2021.11.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Revised: 11/03/2021] [Accepted: 11/04/2021] [Indexed: 11/18/2022]
Abstract
OBJECTIVE We sought to characterize intracranial hemorrhage (ICH) as a seizure etiology in infants born term and preterm. For infants born term, we sought to compare seizure severity and treatment response for multisite vs single-site ICH and hypoxic-ischemic encephalopathy (HIE) with vs without ICH. STUDY DESIGN We studied 112 newborn infants with seizures attributed to ICH and 201 infants born at term with seizures attributed to HIE, using a cohort of consecutive infants with clinically diagnosed and/or electrographic seizures prospectively enrolled in the multicenter Neonatal Seizure Registry. We compared seizure severity and treatment response among infants with complicated ICH, defined as multisite vs single-site ICH and HIE with vs without ICH. RESULTS ICH was a more common seizure etiology in infants born preterm vs term (27% vs 10%, P < .001). Most infants had subclinical seizures (74%) and an incomplete response to initial antiseizure medication (ASM) (68%). In infants born term, multisite ICH was associated with more subclinical seizures than single-site ICH (93% vs 66%, P = .05) and an incomplete response to the initial ASM (100% vs 66%, P = .02). Status epilepticus was more common in HIE with ICH vs HIE alone (38% vs 17%, P = .05). CONCLUSIONS Seizure severity was greater and treatment response was lower among infants born term with complicated ICH. These data support the use of continuous video electroencephalogram monitoring to accurately detect seizures and a multistep treatment plan that considers early use of multiple ASMs, particularly with parenchymal and high-grade intraventricular hemorrhage and complicated ICH.
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Affiliation(s)
- Emily M Herzberg
- Department of Neurology, Boston Children's Hospital, Boston, MA; Division of Newborn Medicine, Department of Pediatrics, Massachusetts General Hospital, Boston, MA
| | - Michelle Machie
- Departments of Neurology and Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX
| | - Hannah C Glass
- Department of Neurology and Weill Institute for Neuroscience, University of California, San Francisco, CA; Department of Pediatrics, Benioff Children's Hospital, University of California, San Francisco, CA; Department of Epidemiology and Biostatistics, University of California, San Francisco, CA
| | | | | | - Taeun Chang
- Department of Neurology, Children's National Hospital, George Washington University School of Medicine, Washington, DC
| | - Nicholas S Abend
- Departments of Neurology and Pediatrics, Children's Hospital of Philadelphia and Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Catherine J Chu
- Department of Neurology, Massachusetts General Hospital, Boston, MA
| | - M Roberta Cilio
- Division of Pediatric Neurology, Department of Pediatrics, Saint-Luc University Hospital, Université Catholique de Louvain, Brussels, Belgium
| | - Sonia L Bonifacio
- Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University, Palo Alto, CA
| | - Shavonne L Massey
- Departments of Neurology and Pediatrics, Children's Hospital of Philadelphia and Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Charles E McCulloch
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA
| | - Janet S Soul
- Department of Neurology, Boston Children's Hospital, Boston, MA.
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Herzberg EM, Barrero-Castillero A, Matute JD. The healing power of language: caring for patients with limited english proficiency and COVID-19. Pediatr Res 2022; 91:526-528. [PMID: 33790416 PMCID: PMC8010487 DOI: 10.1038/s41390-021-01487-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 03/08/2021] [Indexed: 11/09/2022]
Affiliation(s)
- Emily M. Herzberg
- grid.32224.350000 0004 0386 9924Division of Neonatology and Newborn Medicine, Department of Pediatrics, Massachusetts General Hospital, Boston, MA USA
| | - Alejandra Barrero-Castillero
- grid.32224.350000 0004 0386 9924Division of Neonatology and Newborn Medicine, Department of Pediatrics, Massachusetts General Hospital, Boston, MA USA ,grid.239395.70000 0000 9011 8547Division of Neonatology, Beth Israel Deaconess Medical Center, Boston, MA USA
| | - Juan D. Matute
- grid.32224.350000 0004 0386 9924Division of Neonatology and Newborn Medicine, Department of Pediatrics, Massachusetts General Hospital, Boston, MA USA
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Weiss RJ, Bates SV, Song Y, Zhang Y, Herzberg EM, Chen YC, Gong M, Chien I, Zhang L, Murphy SN, Gollub RL, Grant PE, Ou Y. Mining multi-site clinical data to develop machine learning MRI biomarkers: application to neonatal hypoxic ischemic encephalopathy. J Transl Med 2019; 17:385. [PMID: 31752923 PMCID: PMC6873573 DOI: 10.1186/s12967-019-2119-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Accepted: 10/31/2019] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Secondary and retrospective use of hospital-hosted clinical data provides a time- and cost-efficient alternative to prospective clinical trials for biomarker development. This study aims to create a retrospective clinical dataset of Magnetic Resonance Images (MRI) and clinical records of neonatal hypoxic ischemic encephalopathy (HIE), from which clinically-relevant analytic algorithms can be developed for MRI-based HIE lesion detection and outcome prediction. METHODS This retrospective study will use clinical registries and big data informatics tools to build a multi-site dataset that contains structural and diffusion MRI, clinical information including hospital course, short-term outcomes (during infancy), and long-term outcomes (~ 2 years of age) for at least 300 patients from multiple hospitals. DISCUSSION Within machine learning frameworks, we will test whether the quantified deviation from our recently-developed normative brain atlases can detect abnormal regions and predict outcomes for individual patients as accurately as, or even more accurately, than human experts. Trial Registration Not applicable. This study protocol mines existing clinical data thus does not meet the ICMJE definition of a clinical trial that requires registration.
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Affiliation(s)
- Rebecca J Weiss
- Division of Newborn Medicine, Department of Pediatrics, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Sara V Bates
- Division of Newborn Medicine, Department of Pediatrics, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Ya'nan Song
- Fetal Neonatal Neuroimaging and Developmental Science Center (FNNDSC), Boston Children's Hospital, Harvard Medical School, 401 Park Drive, Landmark Center 7022, Boston, MA, 02115, USA
| | - Yue Zhang
- Fetal Neonatal Neuroimaging and Developmental Science Center (FNNDSC), Boston Children's Hospital, Harvard Medical School, 401 Park Drive, Landmark Center 7022, Boston, MA, 02115, USA
| | - Emily M Herzberg
- Division of Newborn Medicine, Department of Pediatrics, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Yih-Chieh Chen
- Division of Newborn Medicine, Department of Pediatrics, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Maryann Gong
- Computer Science & Artificial Intelligence Lab (CSAIL), Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Isabel Chien
- Computer Science & Artificial Intelligence Lab (CSAIL), Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Lily Zhang
- Computer Science & Artificial Intelligence Lab (CSAIL), Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Shawn N Murphy
- Laboratory of Computer Science, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Randy L Gollub
- Department of Psychiatry and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - P Ellen Grant
- Fetal Neonatal Neuroimaging and Developmental Science Center (FNNDSC), Boston Children's Hospital, Harvard Medical School, 401 Park Drive, Landmark Center 7022, Boston, MA, 02115, USA.
- Neuroradiology Division, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
| | - Yangming Ou
- Fetal Neonatal Neuroimaging and Developmental Science Center (FNNDSC), Boston Children's Hospital, Harvard Medical School, 401 Park Drive, Landmark Center 7022, Boston, MA, 02115, USA.
- Neuroradiology Division, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
- Computational Health Informatics Program (CHIP), Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
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Boyd AC, Herzberg EM, Marshall MM, Lamparello NA, De Leon MA, Porter A, Evans CH, Doshi S, Shahkolahi A, Dekker D, Relf MV. Antiretroviral drug resistance among treatment-naïve HIV-1-infected persons in Washington, D.C. AIDS Patient Care STDS 2008; 22:445-8. [PMID: 18462072 DOI: 10.1089/apc.2007.0203] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Allison C. Boyd
- Department of Human Science, Georgetown University, Washington, DC
| | | | | | | | | | - Allison Porter
- Department of Human Science, Georgetown University, Washington, DC
| | - Charles H. Evans
- Department of Human Science, Georgetown University, Washington, DC
| | | | | | | | - Michael V. Relf
- Department of Nursing, Georgetown University, Washington, DC
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