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An Y, He L, Xu X, Piao M, Wang B, Liu T, Cao H. Gut microbiota in post-acute COVID-19 syndrome: not the end of the story. Front Microbiol 2024; 15:1500890. [PMID: 39777148 PMCID: PMC11703812 DOI: 10.3389/fmicb.2024.1500890] [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: 09/24/2024] [Accepted: 12/09/2024] [Indexed: 01/11/2025] Open
Abstract
The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has led to major global health concern. However, the focus on immediate effects was assumed as the tip of iceberg due to the symptoms following acute infection, which was defined as post-acute COVID-19 syndrome (PACS). Gut microbiota alterations even after disease resolution and the gastrointestinal symptoms are the key features of PACS. Gut microbiota and derived metabolites disorders may play a crucial role in inflammatory and immune response after SARS-CoV-2 infection through the gut-lung axis. Diet is one of the modifiable factors closely related to gut microbiota and COVID-19. In this review, we described the reciprocal crosstalk between gut and lung, highlighting the participation of diet and gut microbiota in and after COVID-19 by destroying the gut barrier, perturbing the metabolism and regulating the immune system. Therefore, bolstering beneficial species by dietary supplements, probiotics or prebiotics and fecal microbiota transplantation (FMT) may be a novel avenue for COVID-19 and PACS prevention. This review provides a better understanding of the association between gut microbiota and the long-term consequences of COVID-19, which indicates modulating gut dysbiosis may be a potentiality for addressing this multifaceted condition.
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Affiliation(s)
| | | | | | | | | | - Tianyu Liu
- Tianjin Key Laboratory of Digestive Diseases, Department of Gastroenterology and Hepatology, Tianjin Institute of Digestive Diseases, National Key Clinical Specialty, General Hospital, Tianjin Medical University, Tianjin, China
| | - Hailong Cao
- Tianjin Key Laboratory of Digestive Diseases, Department of Gastroenterology and Hepatology, Tianjin Institute of Digestive Diseases, National Key Clinical Specialty, General Hospital, Tianjin Medical University, Tianjin, China
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Wang X, Ke J, Cheng R, Xian H, Li J, Chen Y, Wu B, Han M, Wu Y, Jia W, Yu P, Liu J, Luo H, Yi Y. Malnutrition is associated with severe outcome in elderly patients hospitalised with COVID-19. Sci Rep 2024; 14:24367. [PMID: 39420101 PMCID: PMC11486994 DOI: 10.1038/s41598-024-76363-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Accepted: 10/14/2024] [Indexed: 10/19/2024] Open
Abstract
Some studies have identified influencing factors of COVID-19 illness in elderly, such as underlying diseases, but research on the effect of nutritional status is still lacking. This study retrospectively examined the influence of nutritional status on the outcome of elderly COVID-19 inpatients. A retrospective analysis of the clinical data of 4241 COVID-19 patients who were admitted to a third-class hospital of Nanchang between November 1, 2022 and January 31, 2023 was conducted. Nutritional status was assessed using the prognostic nutritional index (PNI) and controlling nutritional status score (CONUT). The influence of nutritional status on the outcome of COVID-19 patients was determined through multivariate adjustment analysis, restrictive cubic spline, and receiver operating characteristic curve (ROC). Compared with mild/no malnutrition, severe malnutrition substantially increased the critical outcome of COVID-19. A linear relationship was observed between the odds ratio (OR) and PNI and CONUT (P > 0.05). The area under the ROC curve indicated that PNI was the better predictor. The optimal cutoff value of PNI was 38.04 (95%CI: 0.797 ~ 0.836, AUC = 0.817), with a sensitivity of 70.7% and a specificity of 79.6%. The critical illness of elderly COVID-19 patients shows a linear relationship with malnutrition at admission. The use of PNI to assess the prognosis of COVID-19 eldeely patients is reliable, highlighting the importance for doctors to closely pay attention to the nutritional status of COVID-19 patients. Focusing on nutritional status in clinical practice can effectively reduce the critical illness of elderly COVID-19 patients.
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Affiliation(s)
- Xiaoman Wang
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China, 66 Xuefu Avenue, 330006
- School of Public Health, Jiangxi Medical College, Jiangxi Provincial Key Laboratory of Preventive Medicine, Jiangxi Medical College, Nanchang University, Nanchang University, Nanchang, 330006, P.R. China
| | - Jingyao Ke
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China, 66 Xuefu Avenue, 330006
- School of Public Health, Jiangxi Medical College, Jiangxi Provincial Key Laboratory of Preventive Medicine, Jiangxi Medical College, Nanchang University, Nanchang University, Nanchang, 330006, P.R. China
| | - Rui Cheng
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China, 66 Xuefu Avenue, 330006
- School of Public Health, Jiangxi Medical College, Jiangxi Provincial Key Laboratory of Preventive Medicine, Jiangxi Medical College, Nanchang University, Nanchang University, Nanchang, 330006, P.R. China
| | - Hongfei Xian
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China, 66 Xuefu Avenue, 330006
- School of Public Health, Jiangxi Medical College, Jiangxi Provincial Key Laboratory of Preventive Medicine, Jiangxi Medical College, Nanchang University, Nanchang University, Nanchang, 330006, P.R. China
| | - Jingyi Li
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China, 66 Xuefu Avenue, 330006
- School of Public Health, Jiangxi Medical College, Jiangxi Provincial Key Laboratory of Preventive Medicine, Jiangxi Medical College, Nanchang University, Nanchang University, Nanchang, 330006, P.R. China
| | - Yongsen Chen
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China, 66 Xuefu Avenue, 330006
- School of Public Health, Jiangxi Medical College, Jiangxi Provincial Key Laboratory of Preventive Medicine, Jiangxi Medical College, Nanchang University, Nanchang University, Nanchang, 330006, P.R. China
| | - Bin Wu
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China, 66 Xuefu Avenue, 330006
- School of Public Health, Jiangxi Medical College, Jiangxi Provincial Key Laboratory of Preventive Medicine, Jiangxi Medical College, Nanchang University, Nanchang University, Nanchang, 330006, P.R. China
| | - Mengqi Han
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China, 66 Xuefu Avenue, 330006
- School of Public Health, Jiangxi Medical College, Jiangxi Provincial Key Laboratory of Preventive Medicine, Jiangxi Medical College, Nanchang University, Nanchang University, Nanchang, 330006, P.R. China
| | - Yifan Wu
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China, 66 Xuefu Avenue, 330006
- School of Public Health, Jiangxi Medical College, Jiangxi Provincial Key Laboratory of Preventive Medicine, Jiangxi Medical College, Nanchang University, Nanchang University, Nanchang, 330006, P.R. China
| | - Weijie Jia
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China, 66 Xuefu Avenue, 330006
- School of Public Health, Jiangxi Medical College, Jiangxi Provincial Key Laboratory of Preventive Medicine, Jiangxi Medical College, Nanchang University, Nanchang University, Nanchang, 330006, P.R. China
| | - Pengfei Yu
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China, 66 Xuefu Avenue, 330006
| | - Jianmo Liu
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China, 66 Xuefu Avenue, 330006
| | - Haowen Luo
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China, 66 Xuefu Avenue, 330006
| | - Yingping Yi
- Department of Medical Big Data Research Centre, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China, 66 Xuefu Avenue, 330006.
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Aleebrahim-Dehkordi E, Soveyzi F, Deravi N, Saghazadeh A, Rezaei N. Mental Healthcare in Pediatrics During the COVID-19 Pandemic: A Call for International Public Health Action. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1458:19-34. [PMID: 39102187 DOI: 10.1007/978-3-031-61943-4_2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/06/2024]
Abstract
Public health measures associated with coronavirus disease 2019 (COVID-19), such as lockdowns and quarantine of suspected cases, can negatively affect children's mental health status. Although the current crisis provides personal growth and family cohesion opportunities, pitfalls appear to outweigh the benefits. The magnitude and quality of its impact on children depend on several factors, including anxiety, lack of social contact, and a reduced opportunity for stress regulation, along with an increased risk for parental mental health issues, child maltreatment, and domestic violence. Children with special needs and social disadvantages like trauma experiences, disabilities, pre-existing mental illness, e.g., autism spectrum disorders and hyperactivity, and low socioeconomic status, may be at higher risk in this context. Here, the potentials social support can provide for pediatrics, both healthy children and children with special needs, are reviewed after an overview of quarantine's adverse effects on this special population during a pandemic. The most common psychological issues associated with the COVID-19 pandemic are sleep disorders, mood swings, depression, anxiety, decreased attention, stress, irritability, anger, and fear. Moreover, the impact of COVID-19 on children's physical health includes weight gain, reduced physical activity, immune dysregulation, and cardiometabolic disorders. All support systems, involving parents, teachers/school counselors, pediatricians, mental healthcare workers, and Health and Art (HEART) groups, need to enter the scene and make their share of children's mental health care.
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Affiliation(s)
- Elahe Aleebrahim-Dehkordi
- Systematic Review and Meta-Analysis Expert Group (SRMEG), Universal Scientific Education and Research Network (USERN), Tehran, Iran
| | - Faezeh Soveyzi
- Systematic Review and Meta-Analysis Expert Group (SRMEG), Universal Scientific Education and Research Network (USERN), Tehran, Iran
- Radiology Resident at MUMS, Radiology Department Mashhad University of Medical Sciences, Mashhad, Iran
| | - Niloofar Deravi
- Systematic Review and Meta-Analysis Expert Group (SRMEG), Universal Scientific Education and Research Network (USERN), Tehran, Iran
- Student's Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Amene Saghazadeh
- Research Center for Immunodeficiencies, Children's Medical Center, Tehran University of Medical Sciences, Dr. Qarib St, Keshavarz Blvd, 14194, Tehran, Iran
- MetaCognition Interest Group (MCIG), Universal Scientific Education and Research Network (USERN), Tehran, Iran
| | - Nima Rezaei
- Research Center for Immunodeficiencies, Children's Medical Center, Tehran University of Medical Sciences, Dr. Qarib St, Keshavarz Blvd, 14194, Tehran, Iran.
- Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
- Network of Immunity in Infection, Malignancy and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Tehran, Iran.
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Zhou L, Li H, Zhang S, Yang H, Ma Y, Wang Y. Impact of ultra-processed food intake on the risk of COVID-19: a prospective cohort study. Eur J Nutr 2023; 62:275-287. [PMID: 35972529 PMCID: PMC9379888 DOI: 10.1007/s00394-022-02982-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 07/29/2022] [Indexed: 02/07/2023]
Abstract
PURPOSE Nutrition plays a key role in supporting the human immune system and reducing the risk of infections. However, there is limited evidence exploring the relationship between diet and the risk of COVID-19. This study aimed to assess the associations between consumption of ultra-processed foods (UPF) and COVID-19 risk. METHODS In total, 41,012 participants from the UK Biobank study with at least 2 of up to 5 times 24-h dietary assessments were included in this study. Dietary intakes were collected using an online 24-h dietary recall questionnaire and food items were categorized according to their degree of processing by the NOVA classification. COVID-19 infection was defined as individuals tested COVID-19 positive or dead of COVID-19. Association between average UPF consumption (% daily gram intake) and COVID-19 infection was assessed by multivariable logistic regression adjusted for potential confounders. RESULTS Compared to participants in the lowest quartile of UPF proportion (% daily gram intake) in the diet, participants in the 2nd, 3rd, and highest quartiles were associated with a higher risk of COVID-19 with the odds ratio (OR) value of 1.03 (95% CI: 0.94-1.13), 1.24 (95% CI: 1.13-1.36), and 1.22 (95% CI: 1.12-1.34), respectively (P for trend < 0.001), after adjusting for potential confounders. The results were robust in a series of sensitivity analyses. No interaction effect was identified between the UPF proportions and age groups, education level, body mass index, and comorbidity status. BMI mediated 13.2% of this association. CONCLUSION Higher consumption of UPF was associated with an increased risk of COVID-19 infection. Further studies are needed to better understand the underlying mechanisms in such association.
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Affiliation(s)
- Lihui Zhou
- School of Public Health, Tianjin Medical University, No. 22, Qixiangtai Road, Heping District, Tianjin, 300070, China
| | - Huiping Li
- School of Public Health, Tianjin Medical University, No. 22, Qixiangtai Road, Heping District, Tianjin, 300070, China.,Department of Clinical Sciences in Malmö, Lund University, Malmö, Sweden
| | - Shunming Zhang
- School of Public Health, Tianjin Medical University, No. 22, Qixiangtai Road, Heping District, Tianjin, 300070, China.,Department of Clinical Sciences in Malmö, Lund University, Malmö, Sweden
| | - Hongxi Yang
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Yue Ma
- School of Public Health, Tianjin Medical University, No. 22, Qixiangtai Road, Heping District, Tianjin, 300070, China
| | - Yaogang Wang
- School of Public Health, Tianjin Medical University, No. 22, Qixiangtai Road, Heping District, Tianjin, 300070, China.
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