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Lu H, Li Y, Lai M, Guan T, Yu Y, Zheng Z, Zhuang Y. Clinicopathologic features and long-term prognosis of hepatitis B virus-associated glomerulonephritis: a retrospective cohort study. J Nephrol 2023; 36:2335-2344. [PMID: 37523106 PMCID: PMC10638113 DOI: 10.1007/s40620-023-01685-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Accepted: 01/02/2023] [Indexed: 08/01/2023]
Abstract
BACKGROUND Hepatitis B virus-associated glomerulonephritis is a common form of secondary glomerulonephritis in China. However, the clinicopathological features and long-term prognosis of Hepatitis B virus-associated Glomerulonephritis remain only partially known. METHODS Biopsy-proven Hepatitis B virus-associated Glomerulonephritis patients were enrolled between November 1994 and December 2013 at our center. The composite endpoints were doubling serum creatinine, end-stage renal disease, or death from renal disease during follow-up. The clinicopathological features and predictors of the long-term prognosis of Hepatitis B virus-associated Glomerulonephritis patients were explored. RESULTS The median age of the 259 Hepatitis B virus-associated Glomerulonephritis patients was 31.0 years (IQR 24.0-40.0), and 71.0% were males. Among the patients, 45.2% presented with nephrotic syndrome, and 45.9% presented with proteinuria combined with hematuria. The two most prevalent pathological patterns were IgA nephropathy (27.0%) and membranous nephropathy (27.0%). The mean follow-up period was 68.8 ± 46.9 months. The 3-, 5-, and 10-year clinical event-free survival rates were 93.4%, 85.2%, and 70.3%, respectively. Multivariable Cox regression analysis showed that hypertension (HR 2.580, 95% CI 1.351-4.927, P = 0.004), hyperuricemia (HR 2.101, 95% CI 1.116-3.954, P = 0.021), glomerulosclerosis (P = 0.001), and intrarenal arterial lesions (P = 0.041) were independent predictors of composite clinical event endpoint. Patients in the antiviral therapy group exhibited a significantly better prognosis compared to those who received no antiviral therapy (log-rank χ2 = 5.772, P = 0.016). CONCLUSION Hepatitis B virus-associated Glomerulonephritis has specific clinicopathologic features and should not be considered a benign disease in adults. Hypertension, hyperuricemia, glomerulosclerosis, and intrarenal arterial lesions were independent predictors of the long-term prognosis in Hepatitis B virus-associated Glomerulonephritis patients. Antiviral therapy could be effective in improving the long-term prognosis of Hepatitis B virus-associated Glomerulonephritis patients.
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Affiliation(s)
- Hailing Lu
- Department of Nephrology, 900 Hospital of the Joint Logistics Team, PLA, Fuzhou General Clinical Medical College of Fujian Medical University, 156 Xierhuanbei Road, Fuzhou, 350025, Fujian, China
| | - Yu Li
- Department of Nephrology, Zhongshan Hospital Affiliated to Xiamen University, Xiamen, China
| | - Maxiu Lai
- Department of Nephrology, 900 Hospital of the Joint Logistics Team, PLA, Fuzhou General Clinical Medical College of Fujian Medical University, 156 Xierhuanbei Road, Fuzhou, 350025, Fujian, China
| | - Tianjun Guan
- Department of Nephrology, Zhongshan Hospital Affiliated to Xiamen University, Xiamen, China
| | - Yinghao Yu
- Department of Pathology, 900 Hospital of the Joint Logistics Team, PLA, Fuzhou General Clinical Medical College of Fujian Medical University, Fuzhou, China
| | - Zhiyong Zheng
- Department of Pathology, 900 Hospital of the Joint Logistics Team, PLA, Fuzhou General Clinical Medical College of Fujian Medical University, Fuzhou, China
| | - Yongze Zhuang
- Department of Nephrology, 900 Hospital of the Joint Logistics Team, PLA, Fuzhou General Clinical Medical College of Fujian Medical University, 156 Xierhuanbei Road, Fuzhou, 350025, Fujian, China.
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Wang H, Liu S, Xie L, Wang J. Gut microbiota signature in children with autism spectrum disorder who suffered from chronic gastrointestinal symptoms. BMC Pediatr 2023; 23:476. [PMID: 37730588 PMCID: PMC10510216 DOI: 10.1186/s12887-023-04292-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 09/06/2023] [Indexed: 09/22/2023] Open
Abstract
BACKGROUND Children diagnosed with autism spectrum disorder (ASD) frequently suffer from persistent gastrointestinal symptoms, such as constipation and diarrhea. Various studies have highlighted differences in gut microbiota composition between individuals with ASD and healthy controls of similar ages. However, it's essential to recognize that these disparities may be influenced by cultural practices, dietary habits, and environmental factors. METHODS In this study, we collected fecal samples from both children diagnosed with ASD (n = 42) and healthy individuals (n = 41) residing in the southeastern coastal region of China. Subsequently, 16 S rRNA gene sequencing and advanced bioinformatics analyses were conducted to investigate the distinctive features of gut microbial communities within each group. RESULTS The ASD group consisted of 28 males and 14 females, with a median age of 5.8 years, while the control group included 25 males and 16 females, with a median age of 6.8 years. Among the 83 sequenced fecal samples, a total of 1031 operational taxonomic units (OTUs) were identified. These included 122 unique OTUs specific to the control group and 285 unique OTUs specific to the ASD group. Analyses of α-diversity and β-diversity unveiled significant differences in the abundance and composition of gut microbiota between the two groups. It was found that the dominant bacterial taxa in healthy individuals were UBA1819, Flavonifractor, and Bradyrhizobium. In contrast, the ASD group exhibited a prevalence of Streptococcus, Ruminococcus, and Ruminiclostridium. Further analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Clusters of Orthologous Groups (COG) showed significant differences in the metabolic functionalities of the gut microbiota between the two groups. Notably, the metabolic pathway related to alpha-linolenic acid (ALA) in the gut microbiota of the ASD group was notably diminished compared to the control group. Conversely, the ASD group demonstrated significantly elevated levels of metabolic pathways involving uncharacterized conserved proteins, aminoglycoside phosphotransferase, and inorganic pyrophosphatase compared to the control group. CONCLUSIONS Overall, these results confirm that there are significant differences in the gut microbiota structure between children with ASD and healthy controls in the southeast coastal region of China. This underscores the critical significance of delving into clinical interventions capable of mitigating the gastrointestinal and psychological symptoms encountered by children with ASD. A particularly encouraging path for such interventions lies in the realm of fecal microbiota transplantation, a prospect that merits deeper inquiry.
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Affiliation(s)
- Hui Wang
- Child Healthcare Department, Xiamen Children's Hospital, Children's Hospital of Fudan University at Xiamen, Xiamen, 361006, China
| | - Shu Liu
- Child Healthcare Department, Xiamen Children's Hospital, Children's Hospital of Fudan University at Xiamen, Xiamen, 361006, China
| | - Liqing Xie
- Child Healthcare Department, Xiamen Children's Hospital, Children's Hospital of Fudan University at Xiamen, Xiamen, 361006, China
| | - Jinhui Wang
- Department of Clinical Laboratory, Xiamen Children's Hospital, Children's Hospital of Fudan University at Xiamen, No.92-98 Yibin Road, Huli District, Xiamen, 361006, China.
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Lin SN, Rui J, Chen QP, Zhao B, Yu SS, Li ZY, Zhao ZY, Wang Y, Zhu YZ, Xu JW, Yang M, Liu XC, Yang TL, Luo L, Deng B, Huang JF, Liu C, Li PH, Liu WK, Xie F, Chen Y, Su YH, Zhao BH, Chiang YC, Chen TM. Effectiveness of potential antiviral treatments in COVID-19 transmission control: a modelling study. Infect Dis Poverty 2021; 10:53. [PMID: 33874998 PMCID: PMC8054260 DOI: 10.1186/s40249-021-00835-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 04/03/2021] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Novel coronavirus disease 2019 (COVID-19) causes an immense disease burden. Although public health countermeasures effectively controlled the epidemic in China, non-pharmaceutical interventions can neither be maintained indefinitely nor conveniently implemented globally. Vaccination is mainly used to prevent COVID-19, and most current antiviral treatment evaluations focus on clinical efficacy. Therefore, we conducted population-based simulations to assess antiviral treatment effectiveness among different age groups based on its clinical efficacy. METHODS We collected COVID-19 data of Wuhan City from published literature and established a database (from 2 December 2019 to 16 March 2020). We developed an age-specific model to evaluate the effectiveness of antiviral treatment in patients with COVID-19. Efficacy was divided into three types: (1) viral activity reduction, reflected as transmission rate decrease [reduction was set as v (0-0.8) to simulate hypothetical antiviral treatments]; (2) reduction in the duration time from symptom onset to patient recovery/removal, reflected as a 1/γ decrease (reduction was set as 1-3 days to simulate hypothetical or real-life antiviral treatments, and the time of asymptomatic was reduced by the same proportion); (3) fatality rate reduction in severely ill patients (fc) [reduction (z) was set as 0.3 to simulate real-life antiviral treatments]. The population was divided into four age groups (groups 1, 2, 3 and 4), which included those aged ≤ 14; 15-44; 45-64; and ≥ 65 years, respectively. Evaluation indices were based on outbreak duration, cumulative number of cases, total attack rate (TAR), peak date, number of peak cases, and case fatality rate (f). RESULTS Comparing the simulation results of combination and single medication therapy s, all four age groups showed better results with combination medication. When 1/γ = 2 and v = 0.4, age group 2 had the highest TAR reduction rate (98.48%, 56.01-0.85%). When 1/γ = 2, z = 0.3, and v = 0.1, age group 1 had the highest reduction rate of f (83.08%, 0.71-0.12%). CONCLUSIONS Antiviral treatments are more effective in COVID-19 transmission control than in mortality reduction. Overall, antiviral treatments were more effective in younger age groups, while older age groups showed higher COVID-19 prevalence and mortality. Therefore, physicians should pay more attention to prevention of viral spread and patients deaths when providing antiviral treatments to patients of older age groups.
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Affiliation(s)
- Sheng-Nan Lin
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China
| | - Jia Rui
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China
| | - Qiu-Ping Chen
- Medical Insurance Office, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, People's Republic of China
| | - Bin Zhao
- Clinical Medical Laboratory, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, People's Republic of China
| | - Shan-Shan Yu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China
| | - Zhuo-Yang Li
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China
| | - Ze-Yu Zhao
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China
| | - Yao Wang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China
| | - Yuan-Zhao Zhu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China
| | - Jing-Wen Xu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China
| | - Meng Yang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China
| | - Xing-Chun Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China
| | - Tian-Long Yang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China
| | - Li Luo
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China
| | - Bin Deng
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China
| | - Jie-Feng Huang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China
| | - Chan Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China
| | - Pei-Hua Li
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China
| | - Wei-Kang Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China
| | - Fang Xie
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China
| | - Yong Chen
- Department of Stomatology, School of Medicine, Xiamen University, Xiamen, Fujian, People's Republic of China
| | - Yan-Hua Su
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China
| | - Ben-Hua Zhao
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China.
| | - Yi-Chen Chiang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China.
| | - Tian-Mu Chen
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an, Xiamen, Fujian, People's Republic of China.
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Liu X, Zhang M, Cheng Q, Zhang Y, Ye G, Huang X, Zhao Z, Rui J, Hu Q, Frutos R, Chen T, Song T, Kang M. Dengue fever transmission between a construction site and its surrounding communities in China. Parasit Vectors 2021; 14:22. [PMID: 33407778 PMCID: PMC7787407 DOI: 10.1186/s13071-020-04463-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2020] [Accepted: 11/05/2020] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Due to an increase in mosquito habitats and the lack facilities to carry out basic mosquito control, construction sites in China are more likely to experience secondary dengue fever infection after importation of an initial infection, which may then increase the number of infections in the neighboring communities and the chance of community transmission. The aim of this study was to investigate how to effectively reduce the transmission of dengue fever at construction sites and the neighboring communities. METHODS The Susceptible-Exposed-Infectious/Asymptomatic-Recovered (SEIAR) model of human and SEI model of mosquitoes were developed to estimate the transmission of dengue virus between humans and mosquitoes within the construction site and within a neighboring community, as well between each of these. With the calibrated model, we further estimated the effectiveness of different intervention scenarios targeting at reducing the transmissibility at different locations (i.e. construction sites and community) with the total attack rate (TAR) and the duration of the outbreak (DO). RESULTS A total of 102 construction site-related and 131 community-related cases of dengue fever were reported in our area of study. Without intervention, the number of cases related to the construction site and the community rose to 156 (TAR: 31.25%) and 10,796 (TAR: 21.59%), respectively. When the transmission route from mosquitoes to humans in the community was cut off, the number of community cases decreased to a minimum of 33 compared with other simulated scenarios (TAR: 0.068%, DO: 60 days). If the transmission route from infectious mosquitoes in the community and that from the construction site to susceptible people on the site were cut off at the same time, the number of cases on the construction site dropped to a minimum of 74 (TAR: 14.88%, DO: 66 days). CONCLUSIONS To control the outbreak of dengue fever effectively on both the construction site and in the community, interventions needed to be made both within the community and from the community to the construction site. If interventions only took place within the construction site, the number of cases on the construction site would not be reduced. Also, interventions implemented only within the construction site or between the construction site and the community would not lead to a reduction in the number of cases in the community.
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Affiliation(s)
- Xingchun Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian People’s Republic of China
| | - Meng Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong People’s Republic of China
| | - Qu Cheng
- Division of Environmental Health Sciences School of Public Health, University of California, Berkeley, CA 94720 USA
| | - Yingtao Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong People’s Republic of China
| | - Guoqiang Ye
- Zhanjiang Municipal Center for Disease Control and Prevention, Zhanjiang, Guangdong People’s Republic of China
| | - Xiqing Huang
- Zhanjiang Municipal Center for Disease Control and Prevention, Zhanjiang, Guangdong People’s Republic of China
| | - Zeyu Zhao
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian People’s Republic of China
| | - Jia Rui
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian People’s Republic of China
| | - Qingqing Hu
- Division of Public Health, School of Medicine, University of Utah, 201 Presidents Circle, Salt Lake City, UT 84112 USA
| | | | - Tianmu Chen
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian People’s Republic of China
| | - Tie Song
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong People’s Republic of China
| | - Min Kang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong People’s Republic of China
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