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Citarella BW, Kartsonaki C, Ibáñez-Prada ED, Gonçalves BP, Baruch J, Escher M, Pritchard MG, Wei J, Philippy F, Dagens A, Hall M, Lee J, Kutsogiannis DJ, Wils EJ, Fernandes MA, Tirupakuzhi Vijayaraghavan BK, Panda PK, Martin-Loeches I, Ohshimo S, Fatoni AZ, Horby P, Dunning J, Rello J, Merson L, Rojek A, Vaillant M, Olliaro P, Reyes LF. Characteristics and outcomes of COVID-19 patients admitted to hospital with and without respiratory symptoms. Heliyon 2024; 10:e29591. [PMID: 38779000 PMCID: PMC11109728 DOI: 10.1016/j.heliyon.2024.e29591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Revised: 03/21/2024] [Accepted: 04/10/2024] [Indexed: 05/25/2024] Open
Abstract
Background COVID-19 is primarily known as a respiratory illness; however, many patients present to hospital without respiratory symptoms. The association between non-respiratory presentations of COVID-19 and outcomes remains unclear. We investigated risk factors and clinical outcomes in patients with no respiratory symptoms (NRS) and respiratory symptoms (RS) at hospital admission. Methods This study describes clinical features, physiological parameters, and outcomes of hospitalised COVID-19 patients, stratified by the presence or absence of respiratory symptoms at hospital admission. RS patients had one or more of: cough, shortness of breath, sore throat, runny nose or wheezing; while NRS patients did not. Results Of 178,640 patients in the study, 86.4 % presented with RS, while 13.6 % had NRS. NRS patients were older (median age: NRS: 74 vs RS: 65) and less likely to be admitted to the ICU (NRS: 36.7 % vs RS: 37.5 %). NRS patients had a higher crude in-hospital case-fatality ratio (NRS 41.1 % vs. RS 32.0 %), but a lower risk of death after adjusting for confounders (HR 0.88 [0.83-0.93]). Conclusion Approximately one in seven COVID-19 patients presented at hospital admission without respiratory symptoms. These patients were older, had lower ICU admission rates, and had a lower risk of in-hospital mortality after adjusting for confounders.
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Affiliation(s)
| | - Christiana Kartsonaki
- MRC Population Health Research Unit, Clinical Trials Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Elsa D. Ibáñez-Prada
- Universidad de La Sabana, Chía, Colombia
- Clínica Universidad de La Sabana, Chía, Colombia
| | | | - Joaquin Baruch
- ISARIC, Pandemic Sciences Institute, University of Oxford, Oxford, UK
| | - Martina Escher
- ISARIC, Pandemic Sciences Institute, University of Oxford, Oxford, UK
| | - Mark G. Pritchard
- ISARIC, Pandemic Sciences Institute, University of Oxford, Oxford, UK
| | - Jia Wei
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Fred Philippy
- Competence Centre for Methodology and Statistics, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Andrew Dagens
- ISARIC, Pandemic Sciences Institute, University of Oxford, Oxford, UK
| | - Matthew Hall
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - James Lee
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Demetrios James Kutsogiannis
- Department of Critical Care Medicine, Faculty of Medicine and Dentistry, The University of Alberta, Edmonton, Alberta, Canada
| | - Evert-Jan Wils
- Department of Intensive Care, Franciscus Gasthuis & Vlietland, Rotterdam, the Netherlands
| | - Marília Andreia Fernandes
- Department of Internal Medicine, Hospital Curry Cabral, Centro Hospitalar Universitário de Lisboa Central, Lisbon, Portugal
| | | | | | - Ignacio Martin-Loeches
- Department of Intensive Care Medicine, Multidisciplinary Intensive Care Research Organization (MICRO), St James' Hospital, Dublin, Ireland
| | - Shinichiro Ohshimo
- Department of Emergency and Critical Care Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Arie Zainul Fatoni
- Department of Anesthesiology and Intensive Therapy, Saiful Anwar General Hospital, Brawijaya University, Malang, East Java, Indonesia
| | - Peter Horby
- ISARIC, Pandemic Sciences Institute, University of Oxford, Oxford, UK
| | - Jake Dunning
- ISARIC, Pandemic Sciences Institute, University of Oxford, Oxford, UK
| | - Jordi Rello
- Vall d'Hebrón Institute Research, Barcelona, Spain
- CHU Nîmes, Nîmes, France
| | - Laura Merson
- ISARIC, Pandemic Sciences Institute, University of Oxford, Oxford, UK
| | - Amanda Rojek
- ISARIC, Pandemic Sciences Institute, University of Oxford, Oxford, UK
- Royal Melbourne Hospital, Melbourne, Australia
| | - Michel Vaillant
- Competence Centre for Methodology and Statistics, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Piero Olliaro
- ISARIC, Pandemic Sciences Institute, University of Oxford, Oxford, UK
| | - Luis Felipe Reyes
- ISARIC, Pandemic Sciences Institute, University of Oxford, Oxford, UK
- Universidad de La Sabana, Chía, Colombia
- Clínica Universidad de La Sabana, Chía, Colombia
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Hurtado JI, López-Radcenco A, Izquierdo-García JL, Rodríguez F, Moyna G, Greif G, Nin N. A comparative NMR-based metabolomics study of lung parenchyma of severe COVID-19 patients. Front Mol Biosci 2023; 10:1295216. [PMID: 38033387 PMCID: PMC10684917 DOI: 10.3389/fmolb.2023.1295216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 10/30/2023] [Indexed: 12/02/2023] Open
Abstract
COVID-19 was the most significant infectious-agent-related cause of death in the 2020-2021 period. On average, over 60% of those admitted to ICU facilities with this disease died across the globe. In severe cases, COVID-19 leads to respiratory and systemic compromise, including pneumonia-like symptoms, acute respiratory distress syndrome, and multiorgan failure. While the upper respiratory tract and lungs are the principal sites of infection and injury, most studies on the metabolic signatures in COVID-19 patients have been carried out on serum and plasma samples. In this report we attempt to characterize the metabolome of lung parenchyma extracts from fatal COVID-19 cases and compare them with that from other respiratory diseases. Our findings indicate that the metabolomic profiles from fatal COVID-19 and non-COVID-19 cases are markedly different, with the former being the result of increased lactate and amino acid metabolism, altered energy pathways, oxidative stress, and inflammatory response. Overall, these findings provide additional insights into the pathophysiology of COVID-19 that could lead to the development of targeted therapies for the treatment of severe cases of the disease, and further highlight the potential of metabolomic approaches in COVID-19 research.
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Affiliation(s)
- Joaquín I. Hurtado
- Laboratorio de Interacción Hospedero Patógeno, Unidad de Biología Molecular, Institut Pasteur de Montevideo, Montevideo, Uruguay
| | | | - José Luis Izquierdo-García
- Grupo de Resonancia Magnética Nuclear e Imagen en Biomedicina, Instituto Pluridisciplinar, Universidad Complutense de Madrid, Madrid, Spain
- Departamento de Química en Ciencias Farmacéuticas, Facultad de Farmacia, Universidad Complutense de Madrid, Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III, Madrid, Spain
| | - Fernando Rodríguez
- Centro de Referencia COVID 1, Hospital Español, Administración de Servicios de Salud del Estado, Montevideo, Uruguay
| | - Guillermo Moyna
- Departamento de Química del Litoral, Universidad de la República, Paysandú, Uruguay
| | - Gonzalo Greif
- Laboratorio de Interacción Hospedero Patógeno, Unidad de Biología Molecular, Institut Pasteur de Montevideo, Montevideo, Uruguay
| | - Nicolás Nin
- Centro de Referencia COVID 1, Hospital Español, Administración de Servicios de Salud del Estado, Montevideo, Uruguay
- Centro de Referencia COVID 2, Instituto Nacional de Ortopedia y Traumatología, Administración de Servicios de Salud del Estado, Montevideo, Uruguay
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Lolobali MC, Widnyana IMG, Wulansari NMA, Wibhuti IBR, Wiryana M, Sedono R, Heriwardito A. Contributing Factors to Increased Left Ventricular End-Diastolic Volume in COVID-19 ICU Patients in Sanglah Hospital: A Study on Galectin-3. Open Access Maced J Med Sci 2022. [DOI: 10.3889/oamjms.2022.10591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND: Coronavirus disease 2019 (COVID-19) is a respiratory disease that has become the largest pandemic and also could put the heart at risk of dysfunction. Galectin-3 is involved in the inflammatory process that continues with remodeling and eventually fibrosis. Using galectin-3 examination, we could predict the possible worsening of heart function and evaluate data on influencing factors for increased left ventricular end-diastolic volume (LVEDV) which could later progress to heart failure.
METHODS: This is an observational prospective analytic study in the COVID-19 ICU of Sanglah Hospital, Bali, Indonesia. The study was conducted from June to October 2021. All research subjects had their blood samples taken for galectin-3 levels examination using enzyme-linked immunosorbent assay (ELISA). Subjects were also evaluated for left ventricular end-diastolic volume (LVEDV) with echocardiography, SOFA scores, and troponin I levels. Subjects were treated with COVID-19 standard protocol established by the Ministry of Health. After 72 h post-admission, subjects were re-examined for galectin-3 levels and LVEDV. Data were analyzed using STATA™.
RESULTS: A total of 45 research subjects were analyzed. Bivariate analysis of the difference of galectin-3 and LVEDV was shown to be insignificant (r = 0.08), no correlation was found between galectin-3 level and LVEDV on ICU admission (r = 0.191), and no correlation found between galectin-3 level and LVEDV after 72 h of hospitalization (r=0.197). Multivariate analysis also showed that none of the variables, namely, difference of galectin-3 level, age, gender, troponin I, SOFA, and Charlson scores had statistically significant correlation with LVEDV (p < 0.05).
CONCLUSION: No significant correlation was found between galectin-3 level and an increase in LVEDV.
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Hayakawa K, Morioka S, Asai Y, Tsuzuki S, Yamada G, Suzuki S, Matsunaga N, Ohmagari N. Predictors of silent hypoxia in hospitalized patients with COVID-19 in Japan. J Infect Chemother 2022; 28:1436-1438. [PMID: 35725530 PMCID: PMC9189118 DOI: 10.1016/j.jiac.2022.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 05/19/2022] [Accepted: 06/02/2022] [Indexed: 11/30/2022]
Abstract
INTRODUCTION Silent hypoxia (SH) is common in patients with coronavirus disease (COVID-19) in Japan and other countries. Early identification of SH is important as more treatment options for COVID-19 have become available. This study aimed to identify predictors of SH using a nationwide COVID-19 registry of hospitalized patients. METHODS Adult patients who were admitted to hospital with COVID-19 between January 2020 and June 2021 and who were hypoxic on admission (SpO2: 70-93%), not transferred from another facility, and who did not have disturbance of consciousness, confusion, or dementia, were included. SH was defined as hypoxia in the absence of shortness of breath/dyspnea upon admission. Predictors of SH were identified using univariable and multivariable logistic regression. RESULTS The study included 1904 patients, of whom 990 (52%) satisfied the criteria for SH. Compared to patients without SH, patients with SH were older, more likely to be female, and had a slightly higher SpO2 on admission. Compared to patients without SH, patients with SH had a lower prevalence of chronic lung disease (CLD) other than chronic obstructive pulmonary disease (COPD), asthma, and obesity. Multivariable analysis revealed that the independent predictors of SH were older age, a shorter interval from symptom onset to admission, higher SpO2, and an absence of CLD or COPD. CONCLUSIONS The absence of underlying lung disease and older age were important predictors of SH. The results of this study, which is the largest such study reported to date in Japan, may help clarify the mechanism of SH.
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Affiliation(s)
- Kayoko Hayakawa
- Disease Control and Prevention Center, National Center for Global Health and Medicine, Tokyo, Japan; AMR Clinical Reference Center, National Center for Global Health and Medicine, Tokyo, Japan.
| | - Shinichiro Morioka
- Disease Control and Prevention Center, National Center for Global Health and Medicine, Tokyo, Japan; AMR Clinical Reference Center, National Center for Global Health and Medicine, Tokyo, Japan; Emerging and Reemerging Infectious Diseases, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Yusuke Asai
- AMR Clinical Reference Center, National Center for Global Health and Medicine, Tokyo, Japan
| | - Shinya Tsuzuki
- Disease Control and Prevention Center, National Center for Global Health and Medicine, Tokyo, Japan; AMR Clinical Reference Center, National Center for Global Health and Medicine, Tokyo, Japan; Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Gen Yamada
- Disease Control and Prevention Center, National Center for Global Health and Medicine, Tokyo, Japan
| | - Setsuko Suzuki
- Disease Control and Prevention Center, National Center for Global Health and Medicine, Tokyo, Japan
| | - Nobuaki Matsunaga
- AMR Clinical Reference Center, National Center for Global Health and Medicine, Tokyo, Japan
| | - Norio Ohmagari
- Disease Control and Prevention Center, National Center for Global Health and Medicine, Tokyo, Japan; AMR Clinical Reference Center, National Center for Global Health and Medicine, Tokyo, Japan
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