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Lu L, Wu F, Peng J, Wu X, Hou X, Zheng Y, Yang H, Deng Z, Dai C, Zhao N, Zhou K, Wan Q, Tang G, Cui J, Yu S, Luo X, Yang C, Chen S, Ran P, Zhou Y. Clinical characterization and outcomes of impulse oscillometry-defined bronchodilator response: an ECOPD cohort-based study. Respir Res 2024; 25:149. [PMID: 38555433 PMCID: PMC10981824 DOI: 10.1186/s12931-024-02765-7] [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: 12/14/2023] [Accepted: 03/11/2024] [Indexed: 04/02/2024] Open
Abstract
BACKGROUND The clinical significance of the impulse oscillometry-defined small airway bronchodilator response (IOS-BDR) is not well-known. Accordingly, this study investigated the clinical characteristics of IOS-BDR and explored the association between lung function decline, acute respiratory exacerbations, and IOS-BDR. METHODS Participants were recruited from an Early Chronic Obstructive Pulmonary Disease (ECOPD) cohort subset and were followed up for two years with visits at baseline, 12 months, and 24 months. Chronic obstructive pulmonary disease (COPD) was defined as a post-bronchodilator forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) ratio < 0.70. IOS-BDR was defined as meeting any one of the following criteria: an absolute change in respiratory system resistance at 5 Hz ≤ - 0.137 kPa/L/s, an absolute change in respiratory system reactance at 5 Hz ≥ 0.055 kPa/L/s, or an absolute change in reactance area ≤ - 0.390 kPa/L. The association between IOS-BDR and a decline in lung function was explored with linear mixed-effects model. The association between IOS-BDR and the risk of acute respiratory exacerbations at the two-year follow-up was analyzed with the logistic regression model. RESULTS This study involved 466 participants (92 participants with IOS-BDR and 374 participants without IOS-BDR). Participants with IOS-BDR had higher COPD assessment test and modified Medical Research Council dyspnea scale scores, more severe emphysema, air trapping, and rapid decline in FVC than those without IOS-BDR over 2-year follow-up. IOS-BDR was not associated with the risk of acute respiratory exacerbations at the 2-year follow-up. CONCLUSIONS The participants with IOS-BDR had more respiratory symptoms, radiographic structural changes, and had an increase in decline in lung function than those without IOS-BDR. TRIAL REGISTRATION Chinese Clinical Trial Registry, ChiCTR1900024643. Registered on 19 July, 2019.
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Affiliation(s)
- Lifei Lu
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Fan Wu
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Guangzhou National Laboratory, Guangzhou, China
| | - Jieqi Peng
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Guangzhou National Laboratory, Guangzhou, China
| | - Xiaohui Wu
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | | | | | - Huajing Yang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Zhishan Deng
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Cuiqiong Dai
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Ningning Zhao
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Kunning Zhou
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Qi Wan
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Gaoying Tang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jiangyu Cui
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Shuqing Yu
- Lianping County People's Hospital, Heyuan, China
| | - Xiangwen Luo
- Lianping County People's Hospital, Heyuan, China
| | - Changli Yang
- Wengyuan County People's Hospital, Shaoguan, China
| | | | - Pixin Ran
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
- Guangzhou National Laboratory, Guangzhou, China.
| | - Yumin Zhou
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
- Guangzhou National Laboratory, Guangzhou, China.
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D’Ors-Vilardebó C, Cebrià i Iranzo MÀ, González-King-Garibotti C, Vázquez-Arce MI, Calvache-Mateo A, López-López L, Valenza MC. Association between Post-Hospitalization Psychological Distress, Exercise Capacity, Physical Function and Health Status in COVID-19 Survivors. Healthcare (Basel) 2024; 12:577. [PMID: 38470688 PMCID: PMC10930704 DOI: 10.3390/healthcare12050577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 02/26/2024] [Accepted: 02/29/2024] [Indexed: 03/14/2024] Open
Abstract
This study aims to determine whether post-hospitalization psychological distress is associated with exercise capacity, physical function and health status in COVID-19 survivors. In this observational study, hospitalized COVID patients were included and divided into two groups according to the mental component summary subscale of the 12-item Short-Form Health Survey. Patients with a score ≤ 45 were included in the psychological distress group, and patients with a score > 45 were included in the non-psychological distress group. The main variables were exercise capacity, physical function, and health status. Patients were evaluated at discharge, 3 months, and at 6 months follow-up. Finally, a total of 60 patients were included in the study. Significant differences were found in exercise capacity, physical function, and health status (p < 0.05), with worse results in the group with psychological distress at discharge and 3 months follow-up. At 6 months after discharge, COVID patients with psychological distress exhibited worse results in exercise capacity, physical function, and health status, being significant exercise capacity and physical function (p < 0.05). It can be concluded that COVID patients with psychological distress at hospital discharge reported worse exercise capacity, physical function and health status at hospital discharge, 3 months and 6 months follow-up.
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Affiliation(s)
- Clara D’Ors-Vilardebó
- Physical Medicine and Rehabilitation Service, La Fe Hospital in Valencia, La Fe Health Research Institute (IISLAFE), 46026 Valencia, Spain
| | - Maria Àngels Cebrià i Iranzo
- Physical Medicine and Rehabilitation Service, La Fe Hospital in Valencia, La Fe Health Research Institute (IISLAFE), 46026 Valencia, Spain
- Physiotherapy Department, University of Valencia, 46026 Valencia, Spain
| | - Carola González-King-Garibotti
- Physical Medicine and Rehabilitation Service, La Fe Hospital in Valencia, La Fe Health Research Institute (IISLAFE), 46026 Valencia, Spain
| | - María Isabel Vázquez-Arce
- Physical Medicine and Rehabilitation Service, La Fe Hospital in Valencia, La Fe Health Research Institute (IISLAFE), 46026 Valencia, Spain
| | - Andrés Calvache-Mateo
- Physiotherapy Department, Faculty of Health Sciences, University of Granada, Av. De la Ilustración, 60, 18016 Granada, Spain
| | - Laura López-López
- Physiotherapy Department, Faculty of Health Sciences, University of Granada, Av. De la Ilustración, 60, 18016 Granada, Spain
| | - Marie Carmen Valenza
- Physiotherapy Department, Faculty of Health Sciences, University of Granada, Av. De la Ilustración, 60, 18016 Granada, Spain
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3
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Shi H. The effect of social support on home isolation anxiety and depression among college students in the post-pandemic era: the mediating effect of perceived loss of control and the moderating role of family socioeconomic status. Front Public Health 2024; 12:1288848. [PMID: 38406501 PMCID: PMC10884108 DOI: 10.3389/fpubh.2024.1288848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 01/30/2024] [Indexed: 02/27/2024] Open
Abstract
Background There is an escalating concern about the rising levels of anxiety and depression among college students, especially during the post-pandemic era. A thorough examination of the various dimensions of social support and their impact on these negative emotions in college students is imperative. Aim This study aimed to determine if a perceived loss of control mediates the relationship between social support and levels of anxiety and depression among college students during the post-pandemic era. Additionally, it examined whether family socioeconomic status moderates this mediated relationship. Methods We administered an online cross-sectional survey in China, securing responses from 502 participants. The sample comprised home-isolated college students impacted by COVID-19. Established scales were employed to assess social support, anxiety, depression, perceived loss of control, and family socioeconomic status. Analytical techniques included descriptive statistics, correlation analysis, and a bootstrap method to investigate mediating and moderating effects. Results Social support was found to negatively affect anxiety and depression in college students, with perceived loss of control partially mediating this relationship. In addition, family socio-economic status was shown to moderate this moderating process. Furthermore, family socioeconomic status influenced this mediation, with higher socioeconomic families exhibiting a stronger moderating effect on perceived loss of control across different dimensions of social support. Conclusion This study may help to develop strategies to mitigate the impact of anxiety and depression in the lives and studies of university students during unexpected public health crises, and to promote better mental health among college students.
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Affiliation(s)
- Hui Shi
- School of Media and Communication, Shanghai Jiao Tong University, Shanghai, China
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4
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Janssen ML, Türk Y, Baart SJ, Hanselaar W, Aga Y, van der Steen-Dieperink M, van der Wal FJ, Versluijs VJ, Hoek RAS, Endeman H, Boer DP, Hoiting O, Hoelters J, Achterberg S, Stads S, Heller-Baan R, Dubois AVF, Elderman JH, Wils EJ. Safety and Outcome of High-Flow Nasal Oxygen Therapy Outside ICU Setting in Hypoxemic Patients With COVID-19. Crit Care Med 2024; 52:31-43. [PMID: 37855812 PMCID: PMC10715700 DOI: 10.1097/ccm.0000000000006068] [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] [Indexed: 10/20/2023]
Abstract
OBJECTIVE High-flow nasal oxygen (HFNO) therapy is frequently applied outside ICU setting in hypoxemic patients with COVID-19. However, safety concerns limit more widespread use. We aimed to assess the safety and clinical outcomes of initiation of HFNO therapy in COVID-19 on non-ICU wards. DESIGN Prospective observational multicenter pragmatic study. SETTING Respiratory wards and ICUs of 10 hospitals in The Netherlands. PATIENTS Adult patients treated with HFNO for COVID-19-associated hypoxemia between December 2020 and July 2021 were included. Patients with treatment limitations were excluded from this analysis. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS Outcomes included intubation and mortality rate, duration of hospital and ICU stay, severity of respiratory failure, and complications. Using propensity-matched analysis, we compared patients who initiated HFNO on the wards versus those in ICU. Six hundred eight patients were included, of whom 379 started HFNO on the ward and 229 in the ICU. The intubation rate in the matched cohort ( n = 214 patients) was 53% and 60% in ward and ICU starters, respectively ( p = 0.41). Mortality rates were comparable between groups (28-d [8% vs 13%], p = 0.28). ICU-free days were significantly higher in ward starters (21 vs 17 d, p < 0.001). No patient died before endotracheal intubation, and the severity of respiratory failure surrounding invasive ventilation and clinical outcomes did not differ between intubated ward and ICU starters (respiratory rate-oxygenation index 3.20 vs 3.38; Pa o2 :F io2 ratio 65 vs 64 mm Hg; prone positioning after intubation 81 vs 78%; mortality rate 17 vs 25% and ventilator-free days at 28 d 15 vs 13 d, all p values > 0.05). CONCLUSIONS In this large cohort of hypoxemic patients with COVID-19, initiation of HFNO outside the ICU was safe, and clinical outcomes were similar to initiation in the ICU. Furthermore, the initiation of HFNO on wards saved time in ICU without excess mortality or complicated course. Our results indicate that HFNO initiation outside ICU should be further explored in other hypoxemic diseases and clinical settings aiming to preserve ICU capacity and healthcare costs.
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Affiliation(s)
- Matthijs L Janssen
- Department of Intensive Care, Franciscus Gasthuis and Vlietland Ziekenhuis, Rotterdam, The Netherlands
- Department of Intensive Care, Erasmus MC, Rotterdam, The Netherlands
- Department of Respiratory Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Respiratory Medicine, Franciscus Gasthuis and Vlietland Ziekenhuis, Rotterdam, The Netherlands
- Department of Biostatistics, Erasmus MC, Rotterdam, The Netherlands
- Department of Intensive Care, Martini Ziekenhuis, Groningen, The Netherlands
- Department of Respiratory Medicine, Martini Ziekenhuis, Groningen, The Netherlands
- Department of Intensive Care, Maasstad Ziekenhuis, Rotterdam, The Netherlands
- Department of Intensive Care, Canisius-Wilhelmina Ziekenhuis, Nijmegen, The Netherlands
- Department of Respiratory Medicine, Canisius-Wilhelmina Ziekenhuis, Nijmegen, The Netherlands
- Department of Intensive Care, Haaglanden Medisch Centrum, Den Haag, The Netherlands
- Department of Intensive Care, Ikazia Ziekenhuis, Rotterdam, The Netherlands
- Department of Respiratory Medicine, Ikazia Ziekenhuis, Rotterdam, The Netherlands
- Department of Respiratory Medicine, Admiraal de Ruyter Ziekenhuis, Goes, The Netherlands
- Department of Intensive Care, IJsselland Ziekenhuis, Capelle aan den Ijssel, The Netherlands
| | - Yasemin Türk
- Department of Respiratory Medicine, Franciscus Gasthuis and Vlietland Ziekenhuis, Rotterdam, The Netherlands
| | - Sara J Baart
- Department of Biostatistics, Erasmus MC, Rotterdam, The Netherlands
| | - Wessel Hanselaar
- Department of Respiratory Medicine, Franciscus Gasthuis and Vlietland Ziekenhuis, Rotterdam, The Netherlands
| | - Yaar Aga
- Department of Intensive Care, Franciscus Gasthuis and Vlietland Ziekenhuis, Rotterdam, The Netherlands
| | | | | | - Vera J Versluijs
- Department of Respiratory Medicine, Martini Ziekenhuis, Groningen, The Netherlands
| | - Rogier A S Hoek
- Department of Respiratory Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Henrik Endeman
- Department of Intensive Care, Erasmus MC, Rotterdam, The Netherlands
| | - Dirk P Boer
- Department of Intensive Care, Maasstad Ziekenhuis, Rotterdam, The Netherlands
| | - Oscar Hoiting
- Department of Intensive Care, Canisius-Wilhelmina Ziekenhuis, Nijmegen, The Netherlands
| | - Jürgen Hoelters
- Department of Respiratory Medicine, Canisius-Wilhelmina Ziekenhuis, Nijmegen, The Netherlands
| | - Sefanja Achterberg
- Department of Intensive Care, Haaglanden Medisch Centrum, Den Haag, The Netherlands
| | - Susanne Stads
- Department of Intensive Care, Ikazia Ziekenhuis, Rotterdam, The Netherlands
| | - Roxane Heller-Baan
- Department of Respiratory Medicine, Ikazia Ziekenhuis, Rotterdam, The Netherlands
| | - Alain V F Dubois
- Department of Respiratory Medicine, Admiraal de Ruyter Ziekenhuis, Goes, The Netherlands
| | - Jan H Elderman
- Department of Intensive Care, Erasmus MC, Rotterdam, The Netherlands
- Department of Intensive Care, IJsselland Ziekenhuis, Capelle aan den Ijssel, The Netherlands
| | - Evert-Jan Wils
- Department of Intensive Care, Franciscus Gasthuis and Vlietland Ziekenhuis, Rotterdam, The Netherlands
- Department of Intensive Care, Erasmus MC, Rotterdam, The Netherlands
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5
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Duan Y, Jiang M, Suo L, Xu M, Li X, Wang Q, Bai C, Wu J, Xu Z, Yang W, Feng L, Li J. Evaluating the accessibility and capacity of SARS-CoV-2 vaccination and analyzing convenience-related factors during the Omicron variant epidemic in Beijing, China. Hum Vaccin Immunother 2023; 19:2289250. [PMID: 38111955 PMCID: PMC10760373 DOI: 10.1080/21645515.2023.2289250] [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: 10/18/2023] [Accepted: 11/27/2023] [Indexed: 12/20/2023] Open
Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination service system lacks standardized indicators to assess resource allocation. Moreover, data on specific vaccination-promoting measures is limited. This study aimed to evaluate vaccination accessibility and capacity and investigate convenience-related factors in China during the Omicron variant epidemic. We collected information on SARS-CoV-2 vaccination services among vaccination sites in Beijing. Analysis was performed using nearest neighbor, Ripley's K, hot spot analysis, and generalized estimating equations. Overall, 299 vaccination sites were included. The demand for the SARS-CoV-2 vaccine increased with the increase in daily new cases, and the number of staff administering vaccines should be increased in urban areas at the beginning of the epidemic. Providing vaccination for both children and adults, extending vaccination service hours, and offering a wider range of vaccine categories significantly increased the doses of vaccines administered (all P < .05). The provision of mobile vaccination vehicles effectively increased the doses of vaccines administered to individuals aged ≥ 60 years (P < .05). The allocation of SARS-CoV-2 vaccination services should be adjusted according to geographic location, population size, and vaccination demands. Simultaneous provision of vaccination services for children and their guardians, flexible service hours, prompt innovative vaccine production, and tailored vaccination strategies can foster vaccination uptake.
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Affiliation(s)
- Yuping Duan
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- State Key Laboratory of Respiratory Health and Multimorbidity, Beijing, China
- Key Laboratory of Pathogen Infection Prevention and Control, Ministry of Education, Peking Union Medical College, Beijing, China
| | - Mingyue Jiang
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- State Key Laboratory of Respiratory Health and Multimorbidity, Beijing, China
- Key Laboratory of Pathogen Infection Prevention and Control, Ministry of Education, Peking Union Medical College, Beijing, China
| | - Luodan Suo
- Beijing Centre for Disease Prevention and Control, Beijing Research Centre for Preventive Medicine, Beijing, China
| | - Mingyu Xu
- Beijing Centre for Disease Prevention and Control, Beijing Research Centre for Preventive Medicine, Beijing, China
| | - Xiaomei Li
- Beijing Centre for Disease Prevention and Control, Beijing Research Centre for Preventive Medicine, Beijing, China
| | - Qing Wang
- Xicheng District Centre for Diseases Control and Prevention, Beijing, China
| | - Chengxu Bai
- Beijing Centre for Disease Prevention and Control, Beijing Research Centre for Preventive Medicine, Beijing, China
| | - Jiang Wu
- Beijing Centre for Disease Prevention and Control, Beijing Research Centre for Preventive Medicine, Beijing, China
| | - Zheng Xu
- Beijing Municipal Health Commission, Beijing, China
| | - Weizhong Yang
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- State Key Laboratory of Respiratory Health and Multimorbidity, Beijing, China
- Key Laboratory of Pathogen Infection Prevention and Control, Ministry of Education, Peking Union Medical College, Beijing, China
| | - Luzhao Feng
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- State Key Laboratory of Respiratory Health and Multimorbidity, Beijing, China
- Key Laboratory of Pathogen Infection Prevention and Control, Ministry of Education, Peking Union Medical College, Beijing, China
| | - Juan Li
- Beijing Centre for Disease Prevention and Control, Beijing Research Centre for Preventive Medicine, Beijing, China
- Capital Medical University, Beijing, China
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6
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Tian S, Liu T, Zhao XJ, Liu XL, Li XL, Du KG, Fang LQ, Kou ZQ, Wei YH, Wang GL. Neutralization against emerging Omicron subvariants after SARS-CoV-2 reinfection. J Infect 2023; 87:598-601. [PMID: 37802470 DOI: 10.1016/j.jinf.2023.09.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 09/22/2023] [Accepted: 03/13/2023] [Indexed: 10/09/2023]
Affiliation(s)
- Shen Tian
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, PR China; Institute of Public Health, Guangzhou Medical University, Guangzhou, PR China; Guangzhou Center for Disease Control and Prevention, Guangzhou, PR China
| | - Ti Liu
- Shandong Center for Disease Control and Prevention, Jinan, PR China
| | - Xin-Jing Zhao
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, PR China; Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, PR China
| | - Xiao-Lin Liu
- Shandong Center for Disease Control and Prevention, Jinan, PR China
| | - Xin-Lou Li
- Department of Medical Research, Key Laboratory of Environmental Sense Organ Stress and Health of the Ministry of Ecology and Environment, PLA Strategic Support Force Medical Center, Beijing, PR China
| | - Kai-Ge Du
- Shandong Center for Disease Control and Prevention, Jinan, PR China
| | - Li-Qun Fang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, PR China; Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, PR China.
| | - Zeng-Qiang Kou
- Shandong Center for Disease Control and Prevention, Jinan, PR China.
| | - Yue-Hong Wei
- Institute of Public Health, Guangzhou Medical University, Guangzhou, PR China; Guangzhou Center for Disease Control and Prevention, Guangzhou, PR China.
| | - Guo-Lin Wang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, PR China.
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7
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Li J, Liu Y, Wei X, Liu Z, Yang Z, Liu L, Zhou M, Xu G, Chen L, Ding Y, Lei H, Yang Z, Chen S, Zhang X, Tang Y, Fu H, He S, Guo B, Liang X, Zhang L, Zhang W, Wu J, Wang C, Hu C, Hu R, Luo X, Quan X, Zeng C, Liang S, Liu T, Lv J, Luo Q, Qi Q, Xu L, Xiong Y, Liu J, Huang D, Xiao C, Liu J, Yang T, Xiang Y, Li Q, Nan Y, Li J, Zhang Y, Wu Y, Liu Y. Antibody responses to SARS-CoV-2 Omicron infection in patients with hematological malignancies: A multicenter, prospective cohort study. J Med Virol 2023; 95:e29300. [PMID: 38063070 DOI: 10.1002/jmv.29300] [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: 08/13/2023] [Revised: 10/15/2023] [Accepted: 11/24/2023] [Indexed: 12/18/2023]
Abstract
Little is known about antibody responses to natural Omicron infection and the risk factors for poor responders in patients with hematological malignancies (HM). We conducted a multicenter, prospective cohort study during the latest Omicron wave in Chongqing, China, aiming to compare the antibody responses, as assessed by IgG levels of anti-receptor binding domain of spike protein (anti-S-RBD), to Omicron infection in the HM cohort (HMC) with healthy control cohort (HCC), and solid cancer cohort (SCC). In addition, we intend to explore the risk factors for poor responders in the HMC. Among the 466 HM patients in this cohort, the seroconversion rate was 92.7%, no statistically difference compared with HCC (98.2%, p = 0.0513) or SCC (100%, p = 0.1363). The median anti-S-RBD IgG titer was 29.9 ng/mL, significantly lower than that of HCC (46.9 ng/mL, p < 0.0001) or SCC (46.2 ng/mL, p < 0.0001). Risk factors associated with nonseroconversion included no COVID-19 vaccination history (odds ratio [OR] = 4.58, 95% confidence interval [CI]: 1.75-12.00, p = 0.002), clinical course of COVID-19 ≤ 7 days (OR = 2.86, 95% CI: 1.31-6.25, p = 0.008) and severe B-cell reduction (0-10/μL) (OR = 3.22, 95% CI: 1.32-7.88, p = 0.010). Risk factors associated with low anti-S-RBD IgG titer were clinical course of COVID-19 ≤ 7 days (OR = 2.58, 95% CI: 1.59-4.18, p < 0.001) and severe B-cell reduction (0-10/μL) (OR = 2.87, 95% CI: 1.57-5.24, p < 0.001). This study reveals a poor antibody responses to Omicron (BA.5.2.48) infection in HM patients and identified risk factors for poor responders. Highlights that HM patients, especially those with these risk factors, may be susceptible to SARS-CoV-2 reinfection, and the postinfection vaccination strategies for these patients should be tailored. Clinical trial: ChiCTR2300071830.
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Affiliation(s)
- Jun Li
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Yi Liu
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Xia Wei
- Department of Hematology, the Third Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Zhanshu Liu
- Department of Hematology, Yongchuan Hospital of Chongqing Medical University, Chongqing, China
| | - Zailiang Yang
- Department of Hematology and Medical Oncology, Chongqing University Fuling Hospital, Chongqing, China
| | - Ling Liu
- Department of Medical Laboratory, People's Hospital of Chongqing Liang Jiang New Area, Chongqing, China
| | - Meiyu Zhou
- Department of Hematology and Medical Oncology, Chongqing University Fuling Hospital, Chongqing, China
| | - Guofa Xu
- Department of Hematology and Medical Oncology, Chongqing University Fuling Hospital, Chongqing, China
| | - Lanting Chen
- Department of Hematology, Yongchuan Hospital of Chongqing Medical University, Chongqing, China
| | - Yao Ding
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Haike Lei
- Department of Chongqing Cancer Multi-omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Zailin Yang
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Shuang Chen
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Xiaomei Zhang
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Yifeng Tang
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Huihui Fu
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Sanxiu He
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Bingling Guo
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Xiping Liang
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Lingqian Zhang
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Wenjun Zhang
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Jing Wu
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Chaoyu Wang
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Chongling Hu
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Renzhi Hu
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Xin Luo
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Xi Quan
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Chensi Zeng
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Shunsi Liang
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Tingting Liu
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Jing Lv
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Qin Luo
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Qin Qi
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Luxiang Xu
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Yan Xiong
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Jueyin Liu
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Dehong Huang
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Chunyan Xiao
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Jun Liu
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Tao Yang
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Ying Xiang
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Qiying Li
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Yingyu Nan
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Jieping Li
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Yong Zhang
- Department of Hematology, the Third Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yongzhong Wu
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Yao Liu
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
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8
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Li H, Jia X, Wang Y, Lv Y, Wang J, Zhai Y, Xue X. Differences in the severity and mortality risk factors for patients hospitalized for COVID-19 pneumonia between the early wave and the very late stage of the pandemic. Front Med (Lausanne) 2023; 10:1238713. [PMID: 37841011 PMCID: PMC10568453 DOI: 10.3389/fmed.2023.1238713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 09/13/2023] [Indexed: 10/17/2023] Open
Abstract
Background Since China's dynamic zero-COVID policy is cancelled on December 7, 2022, the rapidly growing number of patients has brought a major public health challenge. This study aimed to assess whether there were differences in the severity and mortality risk factors for patients hospitalized for COVID-19 pneumonia between the early wave and the very late stage of the pandemic. Methods A retrospective cross-sectional study was carried out using data from 223 hospitalized patients diagnosed with COVID-19 pneumonia during the Omicron surge in Xi'an People's Hospital (Xi'an Fourth Hospital) from December 8, 2022, to January 31, 2023. Univariable and multivariable logistic regression analyses were used to identify potential risk factors associated with the severity and mortality of COVID-19 pneumonia during the first wave of the pandemic after the dynamic zero-COVID policy was retracted. Differences in the severity and mortality risk factors were assessed at different stages of the pandemic, mainly from demographic, clinical manifestation, laboratory tests and radiological findings of patients on admission. Results The mean age of the 223 participants was 71.2 ± 17.4. Compared with the patients in the initial stage of the pandemic, the most common manifestation among patients in this study was cough (90.6%), rather than fever (79.4%). Different from the initial stage of the pandemic, older age, chest tightness, elevated neutrophil-to-lymphocyte ratio (NLR), decreased albumin (ALB) level and ground glass opacification (GGO) in radiological finding were identified as severity risk factors, instead of mortality risk factors for COVID-19 patients in the very late stage of the pandemic. Arterial partial pressure of oxygen/fraction of inspired oxygen (PaO2/FiO2) ≤300 mmHg, cardiovascular disease and laboratory findings including elevated levels of D-dimer, α-hydroxybutyrate dehydrogenase (α-HBDH), total bilirubin (TBIL), alanine aminotransferase (ALT), urea nitrogen (BUN), creatinine (CR), fasting blood glucose (FBG) and decreased platelet count (PLT) were still associated with mortality in the very late stage of the pandemic. Conclusion Monitoring continuously differences in the severity and mortality risk factors for COVID-19 patients between different stages of the pandemic could provide evidence for exploring uncharted territory in the coming post-pandemic era.
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Affiliation(s)
- Haiyan Li
- Department of Pharmacy, Xi’an People’s Hospital (Xi’an Fourth Hospital), Xi’an, China
| | - Xiaoni Jia
- Department of Science and Education, Xi’an Mental Health Center, Xi’an, China
- Department of Pharmacy, Xi’an Mental Health Center, Xi’an, China
| | - Yu Wang
- Department of Endocrinology, Xi’an People’s Hospital (Xi’an Fourth Hospital), Xi’an, China
| | - Yali Lv
- Department of Neurology, Xi’an People’s Hospital (Xi’an Fourth Hospital), Xi’an, China
| | - Jing Wang
- Department of Endocrinology, Xi’an People’s Hospital (Xi’an Fourth Hospital), Xi’an, China
| | - Yuyao Zhai
- Department of Pharmacy, Xi’an People’s Hospital (Xi’an Fourth Hospital), Xi’an, China
| | - Xiaorong Xue
- Department of Pharmacy, Xi’an People’s Hospital (Xi’an Fourth Hospital), Xi’an, China
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9
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Yin C, Hu B, Li K, Liu X, Wang S, He R, Ding H, Jin M, Chen C. Clinical characteristics and prognostic nomograms of 12555 non-severe COVID-19 cases with Omicron infection in Shanghai. BMC Infect Dis 2023; 23:606. [PMID: 37716953 PMCID: PMC10504722 DOI: 10.1186/s12879-023-08582-5] [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: 05/02/2023] [Accepted: 09/04/2023] [Indexed: 09/18/2023] Open
Abstract
BACKGROUND Omicron variant of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has rapidly become a global threat to public health. Numerous asymptomatic and mild cases had been admitted in shelter hospitals to quickly win the fight against Omicron pandemic in Shanghai. However, little is known about influencing factors for deterioration and length of stay (LOS) in hospitals among these non-severe cases. METHODS This study included 12,555 non-severe cases with COVID-19 in largest shelter hospital of Shanghai, aiming to explore prognostic factors and build effective models for prediction of LOS. RESULTS Data showed that 75.0% of participants were initially asymptomatic. In addition, 94.6% were discharged within 10 days, only 0.3% with deterioration in hospitals. The multivariate analysis indicated that less comorbidities (OR = 1.792, P = 0.012) and booster vaccination (OR = 0.255, P = 0.015) was associated with the decreased risk of deterioration. Moreover, age (HR = 0.991, P < 0.001), number of symptoms (HR = 0.969, P = 0.005), time from diagnosis to admission (HR = 1.013, P = 0.001) and Cycle threshold (CT) values of N gene (HR = 1.081, P < 0.001) were significant factors associated with LOS. Based on these factors, a concise nomogram model for predicting patients discharged within 3 days or more than 10 days was built in the development cohort. In validation cohort, 0.75 and 0.73 of Areas under the curve (AUC) in nomograms, similar with AUC in models of simple machine learning, showed good performance in estimating LOS. CONCLUSION Collectively, this study not only provides important evidence to deeply understand clinical characteristics and risk factors of short-term prognosis in Shanghai Omicron outbreaks, but also offers a concise and effective nomogram model to predict LOS. Our findings will play critical roles in screening high-risk groups, providing advice on duration of quarantine and helping decision-makers with better preparation in outbreak of COVID-19.
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Affiliation(s)
- Chun Yin
- Department of Cardiology, Xinqiao Hospital, Third Military Medical University (Army Medical University), Chongqing, China
- Department of Cardiology, the 902Nd Hospital of PLA Joint Service Support Force, Bengbu, China
| | - Bo Hu
- Department of Radiology, Air Force Hospital of Eastern Theater Command, Malujie Road, Nanjing, China
| | - Kunyan Li
- Department of Cardiology, Xinqiao Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Xian Liu
- Department of Pharmaceutical Sciences, Beijing Institute of Radiation Medicine, Beijing, China
| | - Shuili Wang
- Department of Cardiology, the 902Nd Hospital of PLA Joint Service Support Force, Bengbu, China
| | - Rulin He
- Department of Cardiology, the 902Nd Hospital of PLA Joint Service Support Force, Bengbu, China
| | - Haibing Ding
- Department of Cardiology, the 902Nd Hospital of PLA Joint Service Support Force, Bengbu, China
| | - Mingpeng Jin
- Key Laboratory of Arrhythmias of the Ministry of Education of China, Research Center for Translational Medicine, East Hospital, Tongji University School of Medicine, Shanghai, China.
| | - Cheng Chen
- The Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China.
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10
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Long J, Li J, Xie B, Jiao Z, Shen G, Liao W, Song X, Le H, Xia J, Wu S. Morphometric similarity network alterations in COVID-19 survivors correlate with behavioral features and transcriptional signatures. Neuroimage Clin 2023; 39:103498. [PMID: 37643521 PMCID: PMC10474075 DOI: 10.1016/j.nicl.2023.103498] [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: 04/17/2023] [Revised: 07/24/2023] [Accepted: 08/15/2023] [Indexed: 08/31/2023]
Abstract
OBJECTIVES To explore the differences in the cortical morphometric similarity network (MSN) between COVID-19 survivors and healthy controls, and the correlation between these differences and behavioralfeatures and transcriptional signatures. MATERIALS & METHODS 39 COVID-19 survivors and 39 age-, sex- and education years-matched healthy controls (HCs) were included. All participants underwent MRI and behavioral assessments (PCL-17, GAD-7, PHQ-9). MSN analysis was used to compute COVID-19 survivors vs. HCs differences across brain regions. Correlation analysis was used to determine the associations between regional MSN differences and behavioral assessments, and determine the spatial similarities between regional MSN differences and risk genes transcriptional activity. RESULTS COVID-19 survivors exhibited decreased regional MSN in insula, precuneus, transverse temporal, entorhinal, para-hippocampal, rostral middle frontal and supramarginal cortices, and increased regional MSN in pars triangularis, lateral orbitofrontal, superior frontal, superior parietal, postcentral, and inferior temporal cortices. Regional MSN value of lateral orbitofrontal cortex was positively associated with GAD-7 and PHQ-9 scores, and rostral middle frontal was negatively related to PHQ-9 scores. The analysis of spatial similarities showed that seven risk genes (MFGE8, MOB2, NUP62, PMPCA, SDSL, TMEM178B, and ZBTB11) were related to regional MSN values. CONCLUSION The MSN differences were associated with behavioral and transcriptional signatures, early psychological counseling or intervention may be required to COVID-19 survivors. Our study provided a new insight into understanding the altered coordination of structure in COVID-19 and may offer a new endophenotype to further investigate the brain substrate.
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Affiliation(s)
- Jia Long
- Department of Radiology, South China Hospital, Medical School, Shenzhen University, Shenzhen 518116, PR China
| | - Jiao Li
- School of Life Science and Technology, University of Electronic Science and Technology of China Chengdu, 610054, PR China
| | - Bing Xie
- Department of Radiology, South China Hospital, Medical School, Shenzhen University, Shenzhen 518116, PR China
| | - Zhuomin Jiao
- Department of Neurology, South China Hospital, Medical School, Shenzhen University, Shenzhen 518116, PR China
| | - Guoqiang Shen
- Department of Radiology, South China Hospital, Medical School, Shenzhen University, Shenzhen 518116, PR China
| | - Wei Liao
- School of Life Science and Technology, University of Electronic Science and Technology of China Chengdu, 610054, PR China
| | - Xiaomin Song
- Department of Radiology, South China Hospital, Medical School, Shenzhen University, Shenzhen 518116, PR China
| | - Hongbo Le
- Department of Radiology, South China Hospital, Medical School, Shenzhen University, Shenzhen 518116, PR China.
| | - Jun Xia
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen 518035, PR China.
| | - Song Wu
- South China Hospital, Medical School, Shenzhen University, Shenzhen 518116, PR China.
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11
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Shao J, Fan R, Guo C, Huang X, Guo R, Zhang F, Hu J, Huang G, Cao L. Composite Interventions on Outcomes of Severely and Critically Ill Patients with COVID-19 in Shanghai, China. Microorganisms 2023; 11:1859. [PMID: 37513031 PMCID: PMC10383482 DOI: 10.3390/microorganisms11071859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Revised: 07/17/2023] [Accepted: 07/19/2023] [Indexed: 07/30/2023] Open
Abstract
Background: The sixty-day effects of initial composite interventions for the treatment of severely and critically ill patients with COVID-19 are not fully assessed. Methods: Using a Bayesian piecewise exponential model, we analyzed the 60-day mortality, health-related quality of life (HRQoL), and disability in 1082 severely and critically ill patients with COVID-19 between 8 December 2022 and 9 February 2023 in Shanghai, China. The final 60-day follow-up was completed on 10 April 2023. Results: Among 1082 patients (mean age, 78.0 years, 421 [38.9%] women), 139 patients (12.9%) died within 60 days. Azvudine had a 99.8% probability of improving 2-month survival (adjusted HR, 0.44 [95% credible interval, 0.24-0.79]), and Paxlovid had a 91.9% probability of improving 2-month survival (adjusted HR, 0.71 [95% credible interval, 0.44-1.14]) compared with the control. IL-6 receptor antagonist, baricitinib and a-thymosin each had a high probability of benefit (99.5%, 99.4%, and 97.5%, respectively) compared to their controls, while the probability of trail-defined statistical futility (HR > 0.83) was high for therapeutic anticoagulation (99.8%; HR, 1.64 [95% CrI, 1.06-2.50]) and glucocorticoid (91.4%; HR, 1.20 [95% CrI, 0.71-2.16]). Paxlovid, Azvudine, and therapeutic anticoagulation showed a significant reduction in disability (p < 0.05) Conclusions: Among severely and critically ill patients with COVID-19 who received 1 or more therapeutic interventions, treatment with Azvudine had a high probability of improved 60-day mortality compared with the control, indicating its potential in a resource-limited scenario. Treatment with an IL-6 receptor antagonist, baricitinib, and a-thymosin also had high probabilities of benefit in improving 2-month survival, among which a-thymosin could improve HRQoL. Treatment with Paxlovid, Azvudine, and therapeutic anticoagulation could significantly reduce disability at day 60.
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Affiliation(s)
- Jiasheng Shao
- Department of Immunology and Rheumatology, Jiading District Central Hospital Affiliated Shanghai University of Medicine & Health Sciences, Shanghai 201899, China
- Tulane National Primate Research Center, Tulane University School of Medicine, 18703 Three Rivers Road, Covington, LA 70433, USA
| | - Rong Fan
- Tulane National Primate Research Center, Tulane University School of Medicine, 18703 Three Rivers Road, Covington, LA 70433, USA
- Genomics, Biotechnology Center, Center for Molecular and Cellular Bioengineering, Technische Universität, 01307 Dresden, Germany
| | - Chengnan Guo
- Shanghai Institute of Infectious Disease and Biosecurity, School of Public Health, Fudan University, Shanghai 200032, China
| | - Xuyuan Huang
- Department of Urology, Renji Hospital, Shanghai JiaoTong University, Shanghai 200127, China
| | - Runsheng Guo
- Department of General Surgery, Jiading District Central Hospital Affiliated Shanghai University of Medicine & Health Sciences, Shanghai 201899, China
| | - Fengdi Zhang
- Department of Infectious Disease, Shanghai East Hospital, Tongji University School of Medicine, Shanghai 200120, China
| | - Jianrong Hu
- Department of Respiratory Medicine, Jiading District Central Hospital Affiliated Shanghai University of Medicine & Health Sciences, Shanghai 201899, China
| | - Gang Huang
- Shanghai Key Laboratory of Molecular Imaging, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China
| | - Liou Cao
- Department of Nephrology, Molecular Cell Lab for Kidney Disease, Shanghai Peritoneal Dialysis Research Center, Ren Ji Hospital, Uremia Diagnosis and Treatment Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
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