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Yuan R, Chen H, Yi L, Li X, Hu X, Li X, Zhang H, Zhou P, Liang C, Lin H, Zeng L, Zhuang X, Ruan Q, Chen Y, Deng Y, Liu Z, Lu J, Xiao J, Chen L, Xiao X, Li J, Li B, Li Y, He J, Sun J. Enhanced immunity against SARS-CoV-2 in returning Chinese individuals. Hum Vaccin Immunother 2024; 20:2300208. [PMID: 38191194 DOI: 10.1080/21645515.2023.2300208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 12/26/2023] [Indexed: 01/10/2024] Open
Abstract
Global COVID-19 vaccination programs effectively contained the fast spread of SARS-CoV-2. Characterizing the immunity status of returned populations will favor understanding the achievement of herd immunity and long-term management of COVID-19 in China. Individuals were recruited from 7 quarantine stations in Guangzhou, China. Blood and throat swab specimens were collected from participants, and their immunity status was determined through competitive ELISA, microneutralization assay and enzyme-linked FluoroSpot assay. A total of 272 subjects were involved in the questionnaire survey, of whom 235 (86.4%) were returning Chinese individuals and 37 (13.6%) were foreigners. Blood and throat swab specimens were collected from 108 returning Chinese individuals. Neutralizing antibodies against SARS-CoV-2 were detected in ~90% of returning Chinese individuals, either in the primary or the homologous and heterologous booster vaccination group. The serum NAb titers were significantly decreased against SARS-CoV-2 Omicron BA.5, BF.7, BQ.1 and XBB.1 compared with the prototype virus. However, memory T-cell responses, including specific IFN-γ and IL-2 responses, were not different in either group. Smoking, alcohol consumption, SARS-CoV-2 infection, COVID-19 vaccination, and the time interval between last vaccination and sampling were independent influencing factors for NAb titers against prototype SARS-CoV-2 and variants of concern. The vaccine dose was the unique common influencing factor for Omicron subvariants. Enhanced immunity against SARS-CoV-2 was established in returning Chinese individuals who were exposed to reinfection and vaccination. Domestic residents will benefit from booster homologous or heterologous COVID-19 vaccination after reopening of China, which is also useful against breakthrough infection.
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Affiliation(s)
- Runyu Yuan
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Huimin Chen
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Lina Yi
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Xinxin Li
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Ximing Hu
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
- School of Public Health, Southern Medical University, Guangzhou, China
| | - Xing Li
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Huan Zhang
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Pingping Zhou
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Chumin Liang
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Huifang Lin
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Lilian Zeng
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Xue Zhuang
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - QianQian Ruan
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
- School of Public Health, Sun Yat-Sen University, Guangzhou, China
| | - Yueling Chen
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
- School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China
| | - Yingyin Deng
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
- School of Public Health, Southern Medical University, Guangzhou, China
| | - Zhe Liu
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Jing Lu
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Jianpeng Xiao
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Liang Chen
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Xincai Xiao
- Guangzhou Chest Hospital, Guangzhou Medical University, Guangzhou, China
| | - Jing Li
- Quality Control Department, Sinovac Life Sciences Co. Ltd., Beijing, China
| | - Baisheng Li
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Yan Li
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Jianfeng He
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Jiufeng Sun
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- School of Public Health, Southern Medical University, Guangzhou, China
- School of Public Health, Sun Yat-Sen University, Guangzhou, China
- School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China
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2
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Khan RS, Ordog T, Hong SD, Schmitz AH, Thattaliyath B, Sharathkumar AA. Evolution of Cardiovascular Findings in Multisystem Inflammatory Syndrome in Children (MIS-C) Across COVID-19 Variants: Common Trends and Unusual Presentations. Pediatr Cardiol 2024; 45:552-559. [PMID: 38261062 DOI: 10.1007/s00246-023-03397-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 12/25/2023] [Indexed: 01/24/2024]
Abstract
Multisystem inflammatory syndrome in children (MIS-C) is a rare condition following COVID-19 infection. Cardiac involvement is common and includes left ventricular systolic dysfunction, cardiac marker elevation, electrocardiogram (ECG) changes, and coronary artery dilation. This single-center retrospective cohort study compares cardiovascular disease between three major SARS-CoV-2 variants and describes the evolution of findings in medium-term follow-up. Of 69 total children (mean age 9.2 years, 58% male), 60 (87%) had cardiovascular involvement with the most common features being troponin elevation in 33 (47%) and left ventricular dysfunction in 22 (32%). Based on presumed infection timing, 61 patients were sorted into variant cohorts of Alpha, Delta, and Omicron. Hospitalization was longer for the Delta group (7.7 days) vs Alpha (5.1 days, p = 0.0065) and Omicron (4.9 days, p = 0.012). Troponin elevation was more common in Delta compared to Alpha (13/20 vs 7/25, p = 0.18), and cumulative evidence of cardiac injury (echocardiographic abnormality and/or troponin elevation) was more common in Delta (17/20) compared with Alpha (12/25, p = 0.013) or Omicron (8/16, p = 0.034). Forty-nine (77%) of the original cohort (n = 69) had no cardiac symptoms or findings beyond 3 months post-hospitalization. Cardiac MRI was performed in 28 patients (between 3 and 6 months post-hospitalization) and was normal in 25 patients (89%). The differences in the variant cohorts may be due to alteration of the immune landscape with higher severity of COVID-19 infection. Despite overall reassuring cardiac outcomes, it is important to note the variability of presentation and remain vigilant with future variants.
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Affiliation(s)
- Rabia S Khan
- Division of Pediatric Cardiology, Department of Pediatrics, UCLA Health Sciences, Los Angeles, CA, USA.
| | | | - Sandy D Hong
- Division of Pediatric Rheumatology, Department of Pediatrics, University of Iowa Hospitals and Clinics, Iowa City, IA, USA
| | - Anna H Schmitz
- Division of Hospital Medicine, Department of Pediatrics, University of Iowa Hospitals and Clinics, Iowa City, IA, USA
| | - Bijoy Thattaliyath
- Division of Pediatric Cardiology, Department of Pediatrics, University of Iowa Hospitals and Clinics, Iowa City, IA, USA
| | - Anjali A Sharathkumar
- Division of Pediatric Hematology, Department of Pediatrics, University of Iowa Hospitals and Clinics, Iowa City, IA, USA
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Moreno Rojas AF, Bainto E, Harvey H, Tremoulet AH, Burns JC, Dummer KB. SARS-CoV-2 variants are associated with different clinical courses in children with MIS-C. World J Pediatr 2024; 20:143-152. [PMID: 38133726 PMCID: PMC10884140 DOI: 10.1007/s12519-023-00778-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 11/05/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND Recent infection with SARS‑CoV‑2 in children has been associated with multisystem inflammatory syndrome in children (MIS-C). SARS‑CoV‑2 has undergone different mutations. Few publications exist about specific variants and their correlation with the severity of MIS-C. METHODS This was a single-center, retrospective study including all patients admitted with MIS-C at Rady Children's Hospital-San Diego between May 2020 and March 2022. Local epidemiologic data, including viral genomic information, were obtained from public records. Demographics, clinical presentation, laboratory values, and outcomes were obtained from electronic medical records. RESULTS The analysis included 104 pediatric patients. Four MIS-C waves were identified. Circulating variants in San Diego during the first wave included clades 20A to C. During the second wave, there were variants from clades 20A to C, 20G, 21C (Epsilon), 20I (Alpha), and 20J (Gamma). The third wave had Delta strains (clades 21A, 21I, and 21J), and the fourth had Omicron variants (clades 21K, 21L, and 22C). MIS-C presented with similar symptoms and laboratory findings across all waves. More patients were admitted to the pediatric intensive care unit (PICU) (74%) and required inotropic support (63%) during the second wave. None of the patients required mechanical circulatory support, and only two required invasive ventilatory support. There was no mortality. CONCLUSIONS The various strains of SARS-CoV-2 triggered MIS-C with differing severities, with the second wave having a more severe clinical course. Whether the differences in disease severity across variants were due to changes in the virus or other factors remains unknown.
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Affiliation(s)
- Andres F Moreno Rojas
- Department of Pediatrics, Division of Pediatric Cardiology, University of California San Diego, and Rady Children's Hospital, 3020 Children's Way MC 5004, San Diego, CA, 92123, USA
| | | | - Helen Harvey
- Department of Pediatrics, Division of Pediatric Critical Care, University of California San Diego, and Rady Children's Hospital, San Diego, CA, USA
| | - Adriana H Tremoulet
- Kawasaki Disease Research Center, La Jolla, CA, USA
- Department of Pediatrics, University of California San Diego, and Rady Children's Hospital, San Diego, CA, USA
| | - Jane C Burns
- Kawasaki Disease Research Center, La Jolla, CA, USA
- Department of Pediatrics, University of California San Diego, and Rady Children's Hospital, San Diego, CA, USA
| | - Kirsten B Dummer
- Department of Pediatrics, Division of Pediatric Cardiology, University of California San Diego, and Rady Children's Hospital, 3020 Children's Way MC 5004, San Diego, CA, 92123, USA.
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Sperotto F, Gutiérrez-Sacristán A, Makwana S, Li X, Rofeberg VN, Cai T, Bourgeois FT, Omenn GS, Hanauer DA, Sáez C, Bonzel CL, Bucholz E, Dionne A, Elias MD, García-Barrio N, González TG, Issitt RW, Kernan KF, Laird-Gion J, Maidlow SE, Mandl KD, Ahooyi TM, Moraleda C, Morris M, Moshal KL, Pedrera-Jiménez M, Shah MA, South AM, Spiridou A, Taylor DM, Verdy G, Visweswaran S, Wang X, Xia Z, Zachariasse JM, Newburger JW, Avillach P. Clinical phenotypes and outcomes in children with multisystem inflammatory syndrome across SARS-CoV-2 variant eras: a multinational study from the 4CE consortium. EClinicalMedicine 2023; 64:102212. [PMID: 37745025 PMCID: PMC10511777 DOI: 10.1016/j.eclinm.2023.102212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 08/22/2023] [Accepted: 08/29/2023] [Indexed: 09/26/2023] Open
Abstract
Background Multisystem inflammatory syndrome in children (MIS-C) is a severe complication of SARS-CoV-2 infection. It remains unclear how MIS-C phenotypes vary across SARS-CoV-2 variants. We aimed to investigate clinical characteristics and outcomes of MIS-C across SARS-CoV-2 eras. Methods We performed a multicentre observational retrospective study including seven paediatric hospitals in four countries (France, Spain, U.K., and U.S.). All consecutive confirmed patients with MIS-C hospitalised between February 1st, 2020, and May 31st, 2022, were included. Electronic Health Records (EHR) data were used to calculate pooled risk differences (RD) and effect sizes (ES) at site level, using Alpha as reference. Meta-analysis was used to pool data across sites. Findings Of 598 patients with MIS-C (61% male, 39% female; mean age 9.7 years [SD 4.5]), 383 (64%) were admitted in the Alpha era, 111 (19%) in the Delta era, and 104 (17%) in the Omicron era. Compared with patients admitted in the Alpha era, those admitted in the Delta era were younger (ES -1.18 years [95% CI -2.05, -0.32]), had fewer respiratory symptoms (RD -0.15 [95% CI -0.33, -0.04]), less frequent non-cardiogenic shock or systemic inflammatory response syndrome (SIRS) (RD -0.35 [95% CI -0.64, -0.07]), lower lymphocyte count (ES -0.16 × 109/uL [95% CI -0.30, -0.01]), lower C-reactive protein (ES -28.5 mg/L [95% CI -46.3, -10.7]), and lower troponin (ES -0.14 ng/mL [95% CI -0.26, -0.03]). Patients admitted in the Omicron versus Alpha eras were younger (ES -1.6 years [95% CI -2.5, -0.8]), had less frequent SIRS (RD -0.18 [95% CI -0.30, -0.05]), lower lymphocyte count (ES -0.39 × 109/uL [95% CI -0.52, -0.25]), lower troponin (ES -0.16 ng/mL [95% CI -0.30, -0.01]) and less frequently received anticoagulation therapy (RD -0.19 [95% CI -0.37, -0.04]). Length of hospitalization was shorter in the Delta versus Alpha eras (-1.3 days [95% CI -2.3, -0.4]). Interpretation Our study suggested that MIS-C clinical phenotypes varied across SARS-CoV-2 eras, with patients in Delta and Omicron eras being younger and less sick. EHR data can be effectively leveraged to identify rare complications of pandemic diseases and their variation over time. Funding None.
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Affiliation(s)
- Francesca Sperotto
- Department of Cardiology, Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States
| | - Alba Gutiérrez-Sacristán
- Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, United States
| | - Simran Makwana
- Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, United States
| | - Xiudi Li
- Department of Biostatistics, Harvard School of Public Health, 677 Huntington Ave, Boston, MA 02115, United States
| | - Valerie N. Rofeberg
- Department of Cardiology, Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States
| | - Tianxi Cai
- Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, United States
| | - Florence T. Bourgeois
- Department of Pediatrics, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States
| | - Gilbert S. Omenn
- Dept of Computational Medicine & Bioinformatics, Internal Medicine, Human Genetics, & Public Health, University of Michigan, 2017 Palmer Commons, Ann Arbor, MI 48109-2218, United States
| | - David A. Hanauer
- Department of Learning Health Sciences, University of Michigan Medical School, 100-107 NCRC, 2800 Plymouth Road, Ann Arbor, MI 48109, United States
| | - Carlos Sáez
- Biomedical Data Science Lab, Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politécnica de Valéncia, Camino de Vera S/N, Valencia 46022, Spain
| | - Clara-Lea Bonzel
- Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, United States
| | - Emily Bucholz
- Department of Cardiology, Children's Hospital Colorado, University of Colorado Anschutz, 13123 E. 16th Ave, Aurora, CO 80045, United States
| | - Audrey Dionne
- Department of Cardiology, Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States
| | - Matthew D. Elias
- Division of Cardiology, The Children's Hospital of Philadelphia, 3401 Civic Center Boulevard, Philadelphia, PA 19104, United States
| | - Noelia García-Barrio
- Health Informatics, Hospital Universitario 12 de Octubre, Av. de Córdoba, s/n, Madrid 28041, Spain
| | - Tomás González González
- Health Informatics, Hospital Universitario 12 de Octubre, Av. de Córdoba, s/n, Madrid 28041, Spain
| | - Richard W. Issitt
- Digital Research, Informatics and Virtual Environments (DRIVE), Great Ormond Street Hospital for Children, Great Ormond Street, London WC1N 3JH, United Kingdom
| | - Kate F. Kernan
- Department of Critical Care Medicine, University of Pittsburgh, 3550 Terrace Street, Pittsburgh, PA 15213, United States
| | - Jessica Laird-Gion
- Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States
| | - Sarah E. Maidlow
- Michigan Institute for Clinical and Health Research (MICHR) Informatics, University of Michigan, NCRC Bldg 400, 2800 Plymouth Road, Ann Arbor, MI 48109, United States
| | - Kenneth D. Mandl
- Computational Health Informatics Program, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, United States
| | - Taha Mohseni Ahooyi
- Department of Biomedical Health Informatics, The Children's Hospital of Philadelphia, Roberts Building, 734 Schuylkill Ave, Philadelphia, PA 19146, United States
| | - Cinta Moraleda
- Pediatric Infectious Disease Department, Hospital Universitario 12 de Octubre, Av. de Córdoba, s/n, Madrid 28041, Spain
| | - Michele Morris
- Department of Biomedical Informatics, University of Pittsburgh, 5607 Baum Blvd, Pittsburgh, PA 15206, United States
| | - Karyn L. Moshal
- Department of Infectious Diseases, Great Ormond Street Hospital for Children, Great Ormond Street, London WC1N 3JH, United Kingdom
| | - Miguel Pedrera-Jiménez
- Health Informatics, Hospital Universitario 12 de Octubre, Av. de Córdoba, s/n, Madrid 28041, Spain
| | - Mohsin A. Shah
- Digital Research, Informatics and Virtual Environments (DRIVE), Great Ormond Street Hospital for Children, DRIVE, 40 Bernard St, London WC1N 1LE, United Kingdom
| | - Andrew M. South
- Department of Pediatrics-Section of Nephrology, Brenner Children’s, Wake Forest University School of Medicine, Medical Center Boulevard, Winston Salem, NC 27157, United States
| | - Anastasia Spiridou
- Data Research, Innovation and Virtual Environments, Great Ormond Street Hospital for Children, DRIVE, 40 Bernard St, London WC1N 1LE, United Kingdom
| | - Deanne M. Taylor
- Department of Biomedical Health Informatics, The Children's Hospital of Philadelphia, United States
- The Department of Pediatrics, University of Pennsylvania Perelman Medical School, 3601 Civic Center Blvd, 6032 Colket, Philadelphia, PA 19104, United States
| | - Guillaume Verdy
- IAM Unit, Bordeaux University Hospital, Place amélie rabat Léon, Bordeaux 33076, France
| | - Shyam Visweswaran
- Department of Biomedical Informatics, University of Pittsburgh, 5607 Baum Blvd, Pittsburgh, PA 15206, United States
| | - Xuan Wang
- Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, United States
| | - Zongqi Xia
- Department of Neurology, University of Pittsburgh, 3501 5th Avenue, BST-3 Suite 7014, Pittsburgh, PA 15260, United States
| | - Joany M. Zachariasse
- Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, United States
| | - Jane W. Newburger
- Department of Cardiology, Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States
| | - Paul Avillach
- Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, United States
- Computational Health Informatics Program, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, United States
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Dalal N, Pfaff M, Silver L, Glater-Welt L, Sethna C, Singer P, Castellanos-Reyes L, Basalely A. The prevalence and outcomes of hyponatremia in children with COVID-19 and multisystem inflammatory syndrome in children (MIS-C). Front Pediatr 2023; 11:1209587. [PMID: 37744432 PMCID: PMC10513389 DOI: 10.3389/fped.2023.1209587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 07/24/2023] [Indexed: 09/26/2023] Open
Abstract
Introduction To assess the prevalence of hyponatremia among pediatric patients with coronavirus disease 2019 (COVID-19) and Multisystem Inflammatory Syndrome in Children (MIS-C) and determine if pediatric hyponatremia was associated with an increased length of stay, higher rates of mechanical ventilation, and/or elevated inflammatory markers on admission as compared to eunatremic patients. Methods Electronic health records were retrospectively analyzed for 168 children less than 18 years old with COVID-19 or MIS-C who were admitted to pediatric units within the Northwell Health system. The primary exposure was hyponatremic status (serum sodium <135 mEq/L) and the primary outcomes were length of stay, mechanical ventilation usage and increased inflammatory markers. Results Of the 168 children in the study cohort, 95 (56%) were admitted for COVID-19 and 73 (43.5%) for MIS-C. Overall, 60 (35.7%) patients presented with hyponatremia on admission. Patients with hyponatremia had higher rates of intensive care unit admission when compared to eunatremic patients (32/60 [53.3%] vs. 39/108 [36.1%], p = 0.030). In regression models, hyponatremia was not significantly associated with increased length of stay or mechanical ventilation rates. After adjustment for relevant confounders, hyponatremia remained associated with an increased square root CRP (β = 1.79: 95% CI: 0.22-3.36) and lower albumin levels (β = -0.22: 95% CI: -0.42--0.01). Conclusion Hyponatremia is common in pediatric COVID-19 and MIS-C. Hyponatremia was associated with a lower albumin and higher square root CRP levels. This may suggest an association of inflammation with lower serum sodium levels.
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Affiliation(s)
- Neal Dalal
- Division of Nephrology, Department of Pediatrics, Cohen Children’s Medical Center of New York, New Hyde Park, NY, United States
| | - Mairead Pfaff
- Division of Nephrology, Department of Pediatrics, Cohen Children’s Medical Center of New York, New Hyde Park, NY, United States
| | - Layne Silver
- Division of Critical Care, Department of Pediatrics, Cohen Children’s Medical Center of New York, New Hyde Park, NY, United States
| | - Lily Glater-Welt
- Division of Critical Care, Department of Pediatrics, Cohen Children’s Medical Center of New York, New Hyde Park, NY, United States
| | - Christine Sethna
- Division of Nephrology, Department of Pediatrics, Cohen Children’s Medical Center of New York, New Hyde Park, NY, United States
- Department of Pediatrics, Zucker School of Medicine at Hofstra/Northwell, Uniondale, NY, United States
| | - Pamela Singer
- Division of Nephrology, Department of Pediatrics, Cohen Children’s Medical Center of New York, New Hyde Park, NY, United States
| | - Laura Castellanos-Reyes
- Division of Nephrology, Department of Pediatrics, Cohen Children’s Medical Center of New York, New Hyde Park, NY, United States
| | - Abby Basalely
- Division of Nephrology, Department of Pediatrics, Cohen Children’s Medical Center of New York, New Hyde Park, NY, United States
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Wakiguchi H, Kaneko U, Sato S, Imagawa T, Narazaki H, Miyamae T. Clinical Features of COVID-19 in Pediatric Rheumatic Diseases: 2020-2022 Survey of the Pediatric Rheumatology Association of Japan. Viruses 2023; 15:v15051205. [PMID: 37243292 DOI: 10.3390/v15051205] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 05/15/2023] [Accepted: 05/18/2023] [Indexed: 05/28/2023] Open
Abstract
Coronavirus disease 2019 (COVID-19) in children can be compounded by concurrent diseases and immunosuppressants. For the first time, we aimed to report the clinical features of concurrent COVID-19 and pediatric rheumatic disease (PRD) in Japan. Pediatric Rheumatology Association of Japan members were surveyed between 1 April 2020 and 31 August 2022. Outcome measurements included the clinical features of concurrent PRD and COVID-19. Questionnaire responses were obtained from 38 hospitals. Thirty-one hospitals (82%) had children with PRD and COVID-19. The female-to-male ratio in these children (n = 156) was 7:3, with half aged 11-15 years. The highest proportion of children with PRD and COVID-19 was accounted for by juvenile idiopathic arthritis (52%), followed by systemic lupus erythematosus (24%), juvenile dermatomyositis (5%), scleroderma (4%), and Takayasu arteritis (3%). Of children with PRD, a significant majority (97%) were found to be asymptomatic (10%) or presented with mild symptoms (87%) of the COVID-19 infection. No severe cases or deaths were observed. Regarding the use of glucocorticoids, immunosuppressants, or biologics for PRD treatment before COVID-19, no significant difference was found between asymptomatic/mild and moderate COVID-19 in children with PRD. Therefore, COVID-19 is not a threat to children with PRD in Japan.
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Affiliation(s)
- Hiroyuki Wakiguchi
- Department of Pediatrics, Yamaguchi University Graduate School of Medicine, Ube 755-8505, Japan
| | - Utako Kaneko
- Department of Pediatrics, Niigata University Graduate School of Medical and Dental Sciences, Niigata 951-8510, Japan
| | - Satoshi Sato
- Department of Infectious Diseases and Immunology, Saitama Children's Medical Center, Saitama 330-8777, Japan
| | - Tomoyuki Imagawa
- Department of Infection and Immunology, Kanagawa Children's Medical Center, Yokohama 232-0066, Japan
| | - Hidehiko Narazaki
- Department of Pediatrics, Nippon Medical School, Tokyo 113-8602, Japan
| | - Takako Miyamae
- Department of Pediatric Rheumatology, Institute of Rheumatology, Tokyo Women's Medical University Hospital, Tokyo 162-8666, Japan
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