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Pilati Campos IM, Marques M, Peiter GC, Brandalize APC, dos Santos MB, de Melo FF, Teixeira KN. Temporal pattern of humoral immune response in mild cases of COVID-19. World J Biol Chem 2023; 14:40-51. [PMID: 37034134 PMCID: PMC10080547 DOI: 10.4331/wjbc.v14.i2.40] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 12/08/2022] [Accepted: 02/02/2023] [Indexed: 03/24/2023] Open
Abstract
BACKGROUND Understanding the humoral response pattern of coronavirus disease 2019 (COVID-19) is one of the essential factors to better characterize the immune memory of patients, which allows understanding the temporality of reinfection, provides answers about the efficacy and durability of protection against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and consequently helps in global public health and vaccination strategy. Among the patients who became infected with SARS-CoV-2, the majority who did not progress to death were those who developed the mild COVID-19, so understanding the pattern and temporality of the antibody response of these patients is certainly relevant.
AIM To investigate the temporal pattern of humoral response of specific immunoglobulin G (IgG) in mild cases of COVID-19.
METHODS Blood samples from 191 COVID-19 real-time reverse transcriptase-polymerase chain reaction (RT-qPCR)-positive volunteers from the municipality of Toledo/ Paraná/Brazil, underwent two distinct serological tests, enzyme-linked immunosorbent assay, and detection of anti-nucleocapsid IgG. Blood samples and clinicoepidemiological data of the volunteers were collected between November 2020 and February 2021. All assays were performed in duplicate and the manufacturers' recommendations were strictly followed. The data were statistically analyzed using multiple logistic regression; the variables were selected by applying the P < 0.05 criterion.
RESULTS Serological tests to detect specific IgG were performed on serum samples from volunteers who were diagnosed as being positive by RT-qPCR for COVID-19 or had disease onset in the time interval from less than 1 mo to 7 mo. The time periods when the highest number of participants with detectable IgG was observed were 1, 2 and 3 mo. It was observed that 9.42% of participants no longer had detectable IgG antibodies 1 mo only after being infected with SARS-CoV-2 and 1.57% were also IgG negative at less than 1 mo. At 5 mo, 3.14% of volunteers were IgG negative, and at 6 or 7 mo, 1 volunteer (0.52%) had no detectable IgG. During the period between diagnosis by RT-qPCR/symptoms onset and the date of collection for the study, no statistical significance was observed for any association analyzed. Moreover, considering the age category between 31 and 59 years as the exposed group, the P value was 0.11 for the category 31 to 59 years and 0.32 for the category 60 years or older, showing that in both age categories there was no association between the pair of variables analyzed. Regarding chronic disease, the exposure group consisted of the participants without any comorbidity, so the P value of 0.07 for the category of those with at least one chronic disease showed no association between the two variables.
CONCLUSION A temporal pattern of IgG response was not observed, but it is suggested that immunological memory is weak and there is no association between IgG production and age or chronic disease in mild COVID-19.
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Affiliation(s)
| | - Milena Marques
- Campus Toledo, Universidade Federal do Paraná, Toledo 85.919-899, Paraná, Brazil
| | | | | | | | - Fabrício Freire de Melo
- Campus Anísio Teixeira, Universidade Federal da Bahia, Vitória da Conquista 45029-094, Bahia, Brazil
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Mandal SK, Tare M, Deepa PR. COVID-19 infection and metabolic comorbidities: Mitigating role of nutritional sufficiency and drug - nutraceutical combinations of vitamin D. HUMAN NUTRITION & METABOLISM 2023; 31:200179. [PMID: 38620788 PMCID: PMC9762046 DOI: 10.1016/j.hnm.2022.200179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 12/12/2022] [Accepted: 12/14/2022] [Indexed: 12/24/2022]
Abstract
The vulnerability of human health is amplified in recent times with global increase in non-communicable diseases (due to lifestyle changes and environmental insults) and infectious diseases (caused by newer pathogens and drug-resistance strains). Clinical management of diseases is further complicated by disease severity caused by other comorbid factors. Drug-based therapy may not be the sole approach, particularly in scenarios like the COVID-19 pandemic, where there is no specific drug against SARS-CoV-2. Nutritional interventions are significant in armouring human populations in disease prevention, and as adjunctive therapy for disease alleviation. Amidst ongoing clinical trials to determine the efficacy of Vit. D against infections and associated complications, this review examines the pleiotropic benefits of nutritional adequacy of vitamin D (Vit. D) in combating viral infections (COVID-19), its severity and complications due to co-morbidities (obesity, diabetes, stroke and Kawasaki disease), based on research findings and clinical studies. Supplements of Vit. D in combination with other nutrients, and drugs, are suggested as promising preventive-health and adjunct-treatment strategies in the clinical management of viral infections with metabolic comorbidities.
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Affiliation(s)
- Sumit Kumar Mandal
- Department of Biological Sciences, Birla Institute of Technology and Science, Pilani, Pilani Campus, Rajasthan, India
| | - Meghana Tare
- Department of Biological Sciences, Birla Institute of Technology and Science, Pilani, Pilani Campus, Rajasthan, India
| | - P R Deepa
- Department of Biological Sciences, Birla Institute of Technology and Science, Pilani, Pilani Campus, Rajasthan, India
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Akkanti B, Suarez EE, O'Neil ER, Rali AS, Hussain R, Dinh K, Tuazon DM, MacGillivray TE, Diaz-Gomez JL, Simpson L, George JK, Kar B, Herlihy JP, Shafii AE, Gregoric ID, Masud F, Chatterjee S. Extracorporeal Membrane Oxygenation for COVID-19: Collaborative Experience From the Texas Medical Center in Houston With 2 Years Follow-Up. ASAIO J 2022; 68:1443-1449. [PMID: 36150083 DOI: 10.1097/mat.0000000000001791] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
Patients with severe refractory hypoxemic respiratory failure may benefit from extracorporeal membrane oxygenation (ECMO) for salvage therapy. The Coronavirus disease 2019 (COVID-19) pandemic offered three high-volume independent ECMO programs at a large medical center the chance to collaborate to optimize ECMO care at the beginning of the pandemic in Spring 2020. Between March 15, 2020, and May 30, 2020, 3,615 inpatients with COVID-19 were treated at the Texas Medical Center. During this time, 35 COVID-19 patients were cannulated for ECMO, all but one in a veno-venous configuration. At hospital discharge, 23 (66%) of the 35 patients were alive. Twelve patients died of vasodilatory shock (n = 9), intracranial hemorrhage (n = 2), and cannulation-related bleeding and multiorgan dysfunction (n = 1). The average duration of ECMO was 13.6 days in survivors and 25.0 days in nonsurvivors ( p < 0.04). At 1 year follow-up, all 23 discharged patients were still alive, making the 1 year survival rate 66% (23/35). At 2 years follow-up, the overall rate of survival was 63% (22/35). Of those patients who survived 2 years, all were at home and alive and well at follow-up.
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Affiliation(s)
- Bindu Akkanti
- From the Divisions of Pulmonary, Critical Care, and Sleep Medicine, Department of Internal Medicine, University of Texas McGovern Medical School, University of Texas Health Sciences Center-Houston, Houston, Texas
- The Center for Advanced Heart Failure, Department of Advanced Cardiopulmonary Therapies and Transplantation, University of Texas McGovern Medical School, University of Texas Health Sciences Center-Houston, Houston, Texas
| | - Erik E Suarez
- DeBakey Heart and Vascular Center, Houston Methodist Hospital, Houston, Texas
| | - Erika R O'Neil
- Section of Critical Care Medicine, Department of Pediatrics, Baylor College of Medicine, Houston, Texas
- Department of Critical Care, Texas Children's Hospital, Houston, Texas
| | - Aniket S Rali
- Section of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Rahat Hussain
- From the Divisions of Pulmonary, Critical Care, and Sleep Medicine, Department of Internal Medicine, University of Texas McGovern Medical School, University of Texas Health Sciences Center-Houston, Houston, Texas
- The Center for Advanced Heart Failure, Department of Advanced Cardiopulmonary Therapies and Transplantation, University of Texas McGovern Medical School, University of Texas Health Sciences Center-Houston, Houston, Texas
| | - Kha Dinh
- From the Divisions of Pulmonary, Critical Care, and Sleep Medicine, Department of Internal Medicine, University of Texas McGovern Medical School, University of Texas Health Sciences Center-Houston, Houston, Texas
- The Center for Advanced Heart Failure, Department of Advanced Cardiopulmonary Therapies and Transplantation, University of Texas McGovern Medical School, University of Texas Health Sciences Center-Houston, Houston, Texas
| | - Divina M Tuazon
- Department of Anesthesiology and Critical Care, Houston Methodist Hospital, Houston, Texas
| | | | - Jose L Diaz-Gomez
- Department of Anesthesia, Division of CV Anesthesia & Critical Care Medicine, Baylor College of Medicine, Houston, Texas
| | - Leo Simpson
- Division of Cardiology, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Joggy K George
- Department of Cardiology, Texas Heart Institute, Houston, Texas
| | - Biswajit Kar
- The Center for Advanced Heart Failure, Department of Advanced Cardiopulmonary Therapies and Transplantation, University of Texas McGovern Medical School, University of Texas Health Sciences Center-Houston, Houston, Texas
| | - J Patrick Herlihy
- Section of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Alexis E Shafii
- Department of Cardiovascular Surgery, Baylor St. Luke's Medical Center-Texas Medical Center, Houston, Texas
| | - Igor D Gregoric
- Division of Cardiothoracic Transplantation and Circulatory Support, Department of Surgery, Baylor College of Medicine, Houston, Texas
| | - Faisal Masud
- Department of Anesthesiology and Critical Care, Houston Methodist Hospital, Houston, Texas
| | - Subhasis Chatterjee
- Department of Cardiovascular Surgery, Baylor St. Luke's Medical Center-Texas Medical Center, Houston, Texas
- Department of Cardiovascular Surgery, Texas Heart Institute, Houston, Texas
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Zheng W, Wang T, Wu P, Yan Q, Liu C, Wu H, Zhan S, Liu X, Jiang Y, Zhuang H. Host Factor Interaction Networks Identified by Integrative Bioinformatics Analysis Reveals Therapeutic Implications in COPD Patients With COVID-19. Front Pharmacol 2021; 12:718874. [PMID: 35002688 PMCID: PMC8733735 DOI: 10.3389/fphar.2021.718874] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 11/11/2021] [Indexed: 01/08/2023] Open
Abstract
Background: The COVID-19 pandemic poses an imminent threat to humanity, especially for those who have comorbidities. Evidence of COVID-19 and COPD comorbidities is accumulating. However, data revealing the molecular mechanism of COVID-19 and COPD comorbid diseases is limited. Methods: We got COVID-19/COPD -related genes from different databases by restricted screening conditions (top500), respectively, and then supplemented with COVID-19/COPD-associated genes (FDR<0.05, |LogFC|≥1) from clinical sample data sets. By taking the intersection, 42 co-morbid host factors for COVID-19 and COPD were finally obtained. On the basis of shared host factors, we conducted a series of bioinformatics analysis, including protein-protein interaction analysis, gene ontology and pathway enrichment analysis, transcription factor-gene interaction network analysis, gene-microRNA co-regulatory network analysis, tissue-specific enrichment analysis and candidate drug prediction. Results: We revealed the comorbidity mechanism of COVID-19 and COPD from the perspective of host factor interaction, obtained the top ten gene and 3 modules with different biological functions. Furthermore, we have obtained the signaling pathways and concluded that dexamethasone, estradiol, progesterone, and nitric oxide shows effective interventions. Conclusion: This study revealed host factor interaction networks for COVID-19 and COPD, which could confirm the potential drugs for treating the comorbidity, ultimately, enhancing the management of the respiratory disease.
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Affiliation(s)
- Wenjiang Zheng
- The First Clinical Medical School, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Ting Wang
- The First Clinical Medical School, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Peng Wu
- The First Clinical Medical School, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Qian Yan
- The First Clinical Medical School, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Chengxin Liu
- The First Clinical Medical School, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Hui Wu
- The First Clinical Medical School, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Shaofeng Zhan
- The First Affiliated Hospital of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Xiaohong Liu
- The First Affiliated Hospital of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yong Jiang
- Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Shenzhen, China
| | - Hongfa Zhuang
- The First Affiliated Hospital of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China
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Igarashi Y, Nishimura K, Ogawa K, Miyake N, Mizobuchi T, Shigeta K, Obinata H, Takayama Y, Tagami T, Seike M, Ohwada H, Yokobori S. Machine Learning Prediction for Supplemental Oxygen Requirement in Patients with COVID-19. J NIPPON MED SCH 2021; 89:161-168. [PMID: 34526457 DOI: 10.1272/jnms.jnms.2022_89-210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND The coronavirus disease (COVID-19) poses an urgent threat to global public health and is characterized by rapid disease progression even in mild cases. In this study, we investigated whether machine learning can be used to predict which patients will have a deteriorated condition and require oxygenation in asymptomatic or mild cases of COVID-19. METHODS This single-center, retrospective, observational study included COVID-19 patients admitted to the hospital from February 1, 2020, to May 31, 2020, and who were either asymptomatic or presented with mild symptoms and did not require oxygen support on admission. Data on patient characteristics and vital signs were collected upon admission. We used seven machine learning algorithms, assessed their capability to predict exacerbation, and analyzed important influencing features using the best algorithm. RESULTS In total, 210 patients were included in the study. Among them, 43 (19%) required oxygen therapy. Of all the models, the logistic regression model had the highest accuracy and precision. Logistic regression analysis showed that the model had an accuracy of 0.900, precision of 0.893, and recall of 0.605. The most important parameter for predictive capability was SpO2, followed by age, respiratory rate, and systolic blood pressure. CONCLUSION In this study, we developed a machine learning model that can be used as a triage tool by clinicians to detect high-risk patients and disease progression earlier. Prospective validation studies are needed to verify the application of the tool in clinical practice.
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Affiliation(s)
- Yutaka Igarashi
- Department of Emergency and Critical Care Medicine, Nippon Medical School
| | - Kan Nishimura
- Department of Industrial Administration, Tokyo University of Science
| | - Kei Ogawa
- Department of Industrial Administration, Tokyo University of Science
| | - Nodoka Miyake
- Department of Emergency and Critical Care Medicine, Nippon Medical School
| | - Taiki Mizobuchi
- Department of Emergency and Critical Care Medicine, Nippon Medical School
| | - Kenta Shigeta
- Department of Emergency and Critical Care Medicine, Nippon Medical School
| | - Hirofumi Obinata
- Department of Emergency and Critical Care Medicine, Nippon Medical School.,Department of Anesthesiology, Self-Defense Forces Central Hospital
| | - Yasuhiro Takayama
- Department of Emergency and Critical Care Medicine, Nippon Medical School.,Emergency Department, Flowers and Forest Tokyo Hospital
| | - Takashi Tagami
- Department of Emergency and Critical Care Medicine, Nippon Medical School.,Department of Emergency and Critical Care Medicine, Nippon Medical School Musashi Kosugi Hospital
| | - Masahiro Seike
- Department of Pulmonary Medicine and Oncology, Nippon Medical School
| | - Hayato Ohwada
- Department of Industrial Administration, Tokyo University of Science
| | - Shoji Yokobori
- Department of Emergency and Critical Care Medicine, Nippon Medical School
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McManus NM, Offman R, Oetman JD. Emergency Department Management of COVID-19: An Evidence-Based Approach. West J Emerg Med 2020; 21:32-44. [PMID: 33052814 PMCID: PMC7673887 DOI: 10.5811/westjem.2020.8.48288] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 07/14/2020] [Accepted: 08/21/2020] [Indexed: 01/08/2023] Open
Abstract
The novel coronavirus, SARs-CoV-2, causes a clinical disease known as COVID-19. Since being declared a global pandemic, a significant amount of literature has been produced and guidelines are rapidly changing as more light is shed on this subject. Decisions regarding disposition must be made with attention to comorbidities. Multiple comorbidities portend a worse prognosis. Many clinical decision tools have been postulated; however, as of now, none have been validated. Laboratory testing available to the emergency physician is nonspecific but does show promise in helping prognosticate and risk stratify. Radiographic testing can also aid in the process. Escalating oxygen therapy seems to be a safe and effective therapy; delaying intubation for only the most severe cases in which respiratory muscle fatigue or mental status demands this. Despite thrombotic concerns in COVID-19, the benefit of anticoagulation in the emergency department (ED) seems to be minimal. Data regarding adjunctive therapies such as steroids and nonsteroidal anti-inflammatories are variable with no concrete recommendations, although steroids may decrease mortality in those patients developing acute respiratory distress syndrome. With current guidelines in mind, we propose a succinct flow sheet for both the escalation of oxygen therapy as well as ED management and disposition of these patients.
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Affiliation(s)
- Nicholas M McManus
- Mercy Health - Muskegon, Department of Emergency Medicine. Muskegon, Michigan; Michigan State University College of Osteopathic Medicine, Department of Osteopathic Medical Specialties, East Lansing, Michigan
| | - Ryan Offman
- Mercy Health - Muskegon, Department of Emergency Medicine. Muskegon, Michigan; Michigan State University College of Osteopathic Medicine, Department of Osteopathic Medical Specialties, East Lansing, Michigan
| | - Jason D Oetman
- Mercy Health - Muskegon, Department of Emergency Medicine. Muskegon, Michigan; Michigan State University College of Osteopathic Medicine, Department of Osteopathic Medical Specialties, East Lansing, Michigan
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