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Lan QW, Chen HK, Huang ZM, Bao TY, Liang CJ, Yi RT, Huang YY, He YX, Huang XQ, Gu B, Guo XG, Zhang QW. Global, regional, and national time trends in incidence for tuberculosis, 1990-2019: An age-period-cohort analysis for the Global Burden of Disease 2019 study. Heart Lung 2024; 65:19-30. [PMID: 38377628 DOI: 10.1016/j.hrtlng.2024.01.009] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 01/08/2024] [Accepted: 01/25/2024] [Indexed: 02/22/2024]
Abstract
BACKGROUND Tuberculosis (TB) represents a significant global health concern, being the leading cause of mortality from a single infectious agent worldwide. The investigation of TB incidence and epidemiological trends is critical for evaluating the effectiveness of control strategies and identifying ongoing challenges. OBJECTIVES This study presents the trend in TB incidence across 204 countries and regions over a 30-year period. METHODS The study utilises data sourced from the Global Burden of Disease (GBD) database. The age cohort model and gender subgroup analysis were employed to estimate the net drift (overall annual percentage change), local drift (age annual percentage change), longitudinal age curve (expected age ratio), and cycle and cohort effect (relative risk of cycle and birth cohort) of TB incidence from 1990 to 2019. This approach facilitates the examination and differentiation of age, period, and cohort effects in TB incidence trends, potentially identifying disparities in TB prevention across different countries. RESULTS Over the past three decades, a general downward trend in TB incidence has been observed in most countries. However, in 15 of the 204 countries, the overall incidence rate is still on the rise (net drift ≥0.0 %) or stagnant decline (≥-0.5 %). From 1990 to 2019, the net drift of tuberculosis mortality ranged from -2.2 % [95 % confidence interval (CI): -2.33, -2.05] in high Socio-demographic Index (SDI) countries to -1.7 % [95 % CI: -1.81, -1.62] in low SDI countries. In some below-average SDI countries,men in the birth cohort are at a disadvantage and at risk of deterioration, necessitating comprehensive TB prevention and treatment. CONCLUSIONS While the global incidence of TB has declined, adverse period and cohort effects have been identified in numerous countries, raising questions about the adequacy of TB healthcare provision across all age groups. Furthermore, this study reveals gender disparities in TB incidence.
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Affiliation(s)
- Qi-Wen Lan
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, PR China; Department of Medical Imageology, The Second Clinical School of Guangzhou Medical University, Guangzhou, PR China
| | - Hao-Kai Chen
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, PR China; Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, PR China
| | - Ze-Min Huang
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, PR China; Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, PR China
| | - Ting-Yu Bao
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, PR China; Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, PR China
| | - Chuang-Jia Liang
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, PR China; Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, PR China
| | - Rui-Ting Yi
- Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, PR China
| | - Yuan-Yi Huang
- Department of Clinical Medicine, The First Clinical School of Guangzhou Medical University, Guangzhou, PR China
| | - Ying-Xin He
- Department of Clinical Laboratory Medicine, Guangzhou Medical University, KingMed School of Laboratory Medicine, Guangzhou Medical University,Guangzhou, PR China
| | - Xu-Qi Huang
- Department of Clinical Medicine, The Sixth Clinical School of Guangzhou Medical University, Guangzhou, PR China
| | - Bing Gu
- Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, PR China.
| | - Xu-Guang Guo
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, PR China; Department of Clinical Laboratory Medicine Guangdong Provincial Key Laboratory of Major Obstetric Diseases; Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology; The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China; Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Dis-eases, King Med School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, 510000, China.
| | - Qing-Wei Zhang
- Division of Gastroenterology and Hepatology, NHC Key Laboratory of Digestive Diseases (Renji Hospital, Shanghai Jiaotong University School of Medicine), Shanghai Institute of Digestive Disease, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, PR China.
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Liu XH, Chen HK, Luo J, He XP, Zhang WL, Chen Y, Li XJ, Lan QW, Ma XM, Guo XG. Potassium affects the association between dietary intake of vitamin C and NAFLD among adults in the United States. PLoS One 2024; 19:e0295986. [PMID: 38635545 PMCID: PMC11025862 DOI: 10.1371/journal.pone.0295986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Accepted: 12/01/2023] [Indexed: 04/20/2024] Open
Abstract
INTRODUCTION Although the association between nonalcoholic fatty liver disease (NAFLD) and vitamin C has been well studied, the effects of dietary potassium intake on this relationship are still unclear. Thus, this study aimed to determine the effects of dietary potassium intake on the association between vitamin C and NAFLD. METHODS We performed a cross-sectional learn about with 9443 contributors the usage of 2007-2018 NHANES data. Multiple logistic regression evaluation has been utilized to check out the affiliation of dietary vitamin C intake with NAFLD and advanced hepatic fibrosis (AHF). Subsequently, we plotted a smoothed match curve to visualize the association. Especially, the analysis of AHF was conducted among the NAFLD population. In addition, stratified evaluation used to be developed primarily based on demographic variables to verify the steadiness of the results. Effect amendment by way of dietary potassium intake used to be assessed via interplay checks between vitamin C and NAFLD in the multivariable linear regression. RESULTS In this cross-sectional study, we found that vitamin C was negatively related to NAFLD and AHF. The relationship between vitamin C and NAFLD was different in the low, middle and high potassium intake groups. Furthermore, potassium intake significantly modified the negative relationship between vitamin C and NAFLD in most of the models. CONCLUSION Our research showed that potassium and vitamin C have an interactive effect in reducing NAFLD, which may have great importance for clinical medication.
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Affiliation(s)
- Xu-Hua Liu
- Department of Clinical Laboratory Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, China
| | - Hao-Kai Chen
- Department of Clinical Laboratory Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, China
| | - Jing Luo
- Department of Clinical Laboratory Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, China
| | - Xiang-Ping He
- Department of Clinical Laboratory Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Chinese and Western Clinical Medicine, The Chinese and Western Clinical School of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Wan-Lin Zhang
- Department of Clinical Laboratory Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Clinical Medicine, The First Clinical School of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Yue Chen
- Department of Clinical Laboratory Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Anesthesia, The Second Clinical School of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Xiu-Juan Li
- Department of Clinical Laboratory Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, China
| | - Qi-Wen Lan
- Department of Clinical Laboratory Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Medical Imageology, The Second Clinical School of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Xiao-Man Ma
- Department of Clinical Laboratory Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, China
| | - Xu-Guang Guo
- Department of Clinical Laboratory Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, China
- Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, King Med School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, Guangdong, China
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Huang ZM, Kang JQ, Chen PZ, Deng LF, Li JX, He YX, Liang J, Huang N, Luo TY, Lan QW, Chen HK, Guo XG. Identifying the Interaction Between Tuberculosis and SARS-CoV-2 Infections via Bioinformatics Analysis and Machine Learning. Biochem Genet 2023:10.1007/s10528-023-10563-x. [PMID: 37991568 DOI: 10.1007/s10528-023-10563-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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 10/25/2023] [Indexed: 11/23/2023]
Abstract
The number of patients with COVID-19 caused by severe acute respiratory syndrome coronavirus 2 is still increasing. In the case of COVID-19 and tuberculosis (TB), the presence of one disease affects the infectious status of the other. Meanwhile, coinfection may result in complications that make treatment more difficult. However, the molecular mechanisms underpinning the interaction between TB and COVID-19 are unclear. Accordingly, transcriptome analysis was used to detect the shared pathways and molecular biomarkers in TB and COVID-19, allowing us to determine the complex relationship between COVID-19 and TB. Two RNA-seq datasets (GSE114192 and GSE163151) from the Gene Expression Omnibus were used to find concerted differentially expressed genes (DEGs) between TB and COVID-19 to identify the common pathogenic mechanisms. A total of 124 common DEGs were detected and used to find shared pathways and drug targets. Several enterprising bioinformatics tools were applied to perform pathway analysis, enrichment analysis and networks analysis. Protein-protein interaction analysis and machine learning was used to identify hub genes (GAS6, OAS3 and PDCD1LG2) and datasets GSE171110, GSE54992 and GSE79362 were used for verification. The mechanism of protein-drug interactions may have reference value in the treatment of coinfection of COVID-19 and TB.
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Affiliation(s)
- Ze-Min Huang
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China
- Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, 511436, China
| | - Jia-Qi Kang
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China
- Department of Clinical Medicine, The First Clinical School of Guangzhou Medical University, Guangzhou, 511436, China
| | - Pei-Zhen Chen
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China
- Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, 511436, China
| | - Lin-Fen Deng
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China
- Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, 511436, China
| | - Jia-Xin Li
- Department of Clinical Medicine, The First Clinical School of Guangzhou Medical University, Guangzhou, 511436, China
| | - Ying-Xin He
- Clinical Laboratory Medicine, Guangzhou Medical University, Guangzhou, 510006, China
| | - Jie Liang
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China
- Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, 511436, China
| | - Nan Huang
- Clinical Laboratory Medicine, Guangzhou Medical University, Guangzhou, 510006, China
| | - Tian-Ye Luo
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China
- Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, 511436, China
| | - Qi-Wen Lan
- Department of Clinical Medicine, The Second Clinical School of Guangzhou Medical University, Guangzhou, 511436, China
| | - Hao-Kai Chen
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China
- Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, 511436, China
| | - Xu-Guang Guo
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China.
- Department of Clinical Laboratory Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China.
- Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, King Med School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, 510000, China.
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Xie SM, Lai JX, Liu CQ, Zhang XX, Lin YM, Lan QW, Hong DY, Chen XC, Qiao JD, Mao YL. UBR4 deficiency causes male sterility and testis abnormal in Drosophila. Front Endocrinol (Lausanne) 2023; 14:1165825. [PMID: 37529615 PMCID: PMC10390308 DOI: 10.3389/fendo.2023.1165825] [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] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 06/05/2023] [Indexed: 08/03/2023] Open
Abstract
Introduction It has been established that UBR4 encodes E3 ubiquitin ligase, which determines the specificity of substrate binding during protein ubiquitination and has been associated with various functions of the nervous system but not the reproductive system. Herein, we explored the role of UBR4 on fertility with a Drosophila model. Methods Different Ubr4 knockdown flies were established using the UAS/GAL4 activating sequence system. Fertility, hatchability, and testis morphology were studied, and bioinformatics analyses were conducted. Our results indicated that UBR4 deficiency could induce male sterility and influent egg hatchability in Drosophila. Results We found that Ubr4 deficiency affected the testis during morphological analysis. Proteomics analysis indicated 188 upregulated proteins and 175 downregulated proteins in the testis of Ubr4 knockdown flies. Gene Ontology analysis revealed significant upregulation of CG11598 and Sfp65A, and downregulation of Pelota in Ubr4 knockdown flies. These proteins were involved in the biometabolic or reproductive process in Drosophila. These regulated proteins are important in testis generation and sperm storage promotion. Bioinformatics analysis verified that UBR4 was low expressed in cryptorchidism patients, which further supported the important role of UBR4 in male fertility. Discussion Overall, our findings suggest that UBR4 deficiency could promote male infertility and may be involved in the protein modification of UBR4 by upregulating Sfp65A and CG11598, whereas downregulating Pelota protein expression.
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Affiliation(s)
- Shi-Ming Xie
- Department of Neurology, Institute of Neuroscience, Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, China
- The First Clinical Medicine School of Guangzhou Medical University, Guangzhou, China
| | - Jia-Xuan Lai
- Department of Neurology, Institute of Neuroscience, Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, China
- The First Clinical Medicine School of Guangzhou Medical University, Guangzhou, China
| | - Chu-Qiao Liu
- The Second Clinical Medicine School of Guangzhou Medical University, Guangzhou, China
| | - Xi-Xing Zhang
- The Second Clinical Medicine School of Guangzhou Medical University, Guangzhou, China
| | - Yong-Miao Lin
- The Second Clinical Medicine School of Guangzhou Medical University, Guangzhou, China
| | - Qi-Wen Lan
- The Second Clinical Medicine School of Guangzhou Medical University, Guangzhou, China
| | - De-Yao Hong
- The First Clinical Medicine School of Guangzhou Medical University, Guangzhou, China
| | - Xiao-Chuan Chen
- Department of Obstetrics and Gynecology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jing-Da Qiao
- Department of Neurology, Institute of Neuroscience, Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, China
| | - Yu-Ling Mao
- Department of Obstetrics and Gynecology, Center for Reproductive Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Key Laboratory for Reproductive Medicine of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
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Huang YY, Bao TY, Huang XQ, Lan QW, Huang ZM, Chen YH, Hu ZD, Guo XG. Machine learning algorithm to construct cuproptosis- and immune-related prognosis prediction model for colon cancer. World J Gastrointest Oncol 2023; 15:372-388. [PMID: 37009317 PMCID: PMC10052662 DOI: 10.4251/wjgo.v15.i3.372] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 12/22/2022] [Accepted: 02/15/2023] [Indexed: 03/14/2023] Open
Abstract
BACKGROUND Over the past few years, research into the pathogenesis of colon cancer has progressed rapidly, and cuproptosis is an emerging mode of cellular apoptosis. Exploring the relationship between colon cancer and cuproptosis benefits in identifying novel biomarkers and even improving the outcome of the disease.
AIM To look at the prognostic relationship between colon cancer and the genes associated with cuproptosis and the immune system in patients. The main purpose was to assess whether reasonable induction of these biomarkers reduces mortality among patients with colon cancers.
METHOD Data obtained from The Cancer Genome Atlas and Gene Expression Omnibus and the Genotype-Tissue Expression were used in differential analysis to explore differential expression genes associated with cuproptosis and immune activation. The least absolute shrinkage and selection operator and Cox regression algorithm was applied to build a cuproptosis- and immune-related combination model, and the model was utilized for principal component analysis and survival analysis to observe the survival and prognosis of the patients. A series of statistically meaningful transcriptional analysis results demonstrated an intrinsic relationship between cuproptosis and the micro-environment of colon cancer.
RESULTS Once prognostic characteristics were obtained, the CDKN2A and DLAT genes related to cuproptosis were strongly linked to colon cancer: The first was a risk factor, whereas the second was a protective factor. The finding of the validation analysis showed that the comprehensive model associated with cuproptosis and immunity was statistically significant. Within the component expressions, the expressions of HSPA1A, CDKN2A, and UCN3 differed markedly. Transcription analysis primarily reflects the differential activation of related immune cells and pathways. Furthermore, genes linked to immune checkpoint inhibitors were expressed differently between the subgroups, which may reveal the mechanism of worse prognosis and the different sensitivities of chemotherapy.
CONCLUSION The prognosis of the high-risk group evaluated in the combined model was poorer, and cuproptosis was highly correlated with the prognosis of colon cancer. It is possible that we may be able to improve patients’ prognosis by regulating the gene expression to intervene the risk score.
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Affiliation(s)
- Yuan-Yi Huang
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China
- Department of Clinical Medicine, The First Clinical School of Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China
| | - Ting-Yu Bao
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China
- Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China
| | - Xu-Qi Huang
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China
- Department of Clinical Medicine, The Sixth Clinical School of Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China
| | - Qi-Wen Lan
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China
- Department of Medical Imageology, The Second Clinical School of Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China
| | - Ze-Min Huang
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China
- Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China
| | - Yu-Han Chen
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China
- Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China
| | - Zhi-De Hu
- Department of Laboratory Medicine, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot 010010, Inner Mongolia Autonomous Region, China
| | - Xu-Guang Guo
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China
- Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China
- Guangdong Provincial Key Laboratory of Major Obstetric Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China
- Key Laboratory of Reproduction and Genetics of Guangdong Higher Education Institutes, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China
- Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, King Med School of Laboratory Medicine, Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China
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Lin M, Li YR, Lan QW, Long LJ, Liu JQ, Chen YW, Cao XJ, Wu GY, Li YP, Guo XG. Evaluation of GeneXpert EV assay for the rapid diagnosis of enteroviral meningitis: a systematic review and meta-analysis. Ann Clin Microbiol Antimicrob 2022; 21:25. [PMID: 35681153 PMCID: PMC9185958 DOI: 10.1186/s12941-022-00517-3] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 05/26/2022] [Indexed: 11/25/2022] Open
Abstract
Background GeneXpert enterovirus Assay is a PCR-based assay for Enterovirus meningitis diagnosis. However, there is currently no research about the performance of GeneXpert enterovirus assay in the diagnosis of enterovirus meningitis. Thus, a systematic review and meta-analysis is significant on the topic. Methods Embase, Cochrane Library, Web of Science, and PubMed were systematically reviewed with retrieval types. Some criteria were used to filter the studies. Only studies published in English, that made a comparison between GeneXpert enterovirus assay and RT-PCR, and could be formulated in a 2*2 table, were included. The quality of the included studies was evaluated by QUADAS-2. The effect of the GeneXpert enterovirus assay was assessed by the Sensitivity, Specificity, Positive Likelihood Ratio, Negative Likelihood Ratio, Diagnosis Odds Ratio, and summary receiver operating characteristic (SROC) curve. Publication bias and heterogeneity were evaluated by the Deeks' funnel test and Bivariate Box plot respectively. Results 7 studies were recruited in the analysis. The Pooled Sensitivity was 0.96 [95% CI (0.94–0.97)], Pooled Specificity was 0.99 [95% CI (0.98–0.99)], Positive Likelihood Ratio was 130.46 [95% CI (35.79–475.58)], Negative Likelihood Ratio was 0.04 [95% CI (0.02–0.10)], and Diagnostic Odds Ratio was 3648.23 (95% CI [963.99–13,806.72)]. In SROC Curve, Area Under Curve (AUC) was 0.9980, and Q*= 0.9849. In Deeks' funnel test, the P-value was 0.807 (P > 0.05), indicating no publication bias. The Bivariate Box plot indicated no evident heterogeneity. Conclusions The GeneXpert enterovirus assay demonstrated high diagnostic accuracy in diagnosing enterovirus meningitis. Supplementary Information The online version contains supplementary material available at 10.1186/s12941-022-00517-3.
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Affiliation(s)
- Min Lin
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China.,Department of Chinese and Western Medicine in Clinical Medicine, The Clinical School of Chinese and Western Medicine, Guangzhou Medical University, Guangzhou, 511436, China
| | - Yun-Ran Li
- Department of Chinese and Western Medicine in Clinical Medicine, The Clinical School of Chinese and Western Medicine, Guangzhou Medical University, Guangzhou, 511436, China
| | - Qi-Wen Lan
- Department of Medical Imageology, The Second Clinical School of Guangzhou Medical University, Guangzhou, 511436, China
| | - Li-Jun Long
- Department of Medical Laboratory Technology, The KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, 511436, China
| | - Jia-Qi Liu
- Department of Chinese and Western Medicine in Clinical Medicine, The Clinical School of Chinese and Western Medicine, Guangzhou Medical University, Guangzhou, 511436, China
| | - Ying-Wen Chen
- Department of Chinese and Western Medicine in Clinical Medicine, The Clinical School of Chinese and Western Medicine, Guangzhou Medical University, Guangzhou, 511436, China
| | - Xun-Jie Cao
- Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, 511436, China
| | - Ge-Yuan Wu
- Department of Chinese and Western Medicine in Clinical Medicine, The Clinical School of Chinese and Western Medicine, Guangzhou Medical University, Guangzhou, 511436, China
| | - Ya-Ping Li
- Department of Clinical Medicine, The Second Clinical School of Guangzhou Medical University, Guangzhou, 511436, China
| | - Xu-Guang Guo
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China. .,Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, 511436, China. .,Key Laboratory for Major Obstetric Diseases of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China. .,Department of Laboratory Medicine, Key Laboratory of Reproduction and Genetics of Guangdong Higher Education Institutes, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China.
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