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Fang T, Xiang Y, Li W, Liu B, Liu H, Wu Y, Xu D, Li M, Yang S, Li J, Yu Y, Zhao X, Zhao LL, Wan K, Yuan X, Tan Y, Li G. Analysis on epidemiological and drug resistance characteristics of lymph node tuberculosis from Hunan province, China. Front Public Health 2024; 12:1432065. [PMID: 39035178 PMCID: PMC11257862 DOI: 10.3389/fpubh.2024.1432065] [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: 05/13/2024] [Accepted: 06/24/2024] [Indexed: 07/23/2024] Open
Abstract
Objectives To investigate the clinical epidemiological and drug resistance (DR) characteristics of lymph node tuberculosis (LNTB) in Hunan Province which locates in South-central China, and to provide scientific clues for effective prevention and treatment of LNTB. Methods We retrospectively collected LNTB patients with Mycobacterium tuberculosis culture positive at Hunan Chest Hospital, the biggest TB reference hospital in South-central China, from January 2013 to December 2021. The multiple demographic, clinical and drug susceptibility data of patients were collected from the hospital's electronic patient records. Descriptive statistical methods, Chi-square test and logistic regression analysis were employed as statistical methods. Results Of the 577 LNTB cases, 373 (64.64%) were males, 352 (61.01%) were farmers; majority (161, 33.10%) aged at 20-29 years old; 147 (25.48%) had simple LNTB, 350 (60.66%) had LNTB combined with pulmonary TB (PTB) (defined as LNTB-PTB), and 80 (13.86%) had LNTB combined with other extrapulmonary TB (EPTB) (defined as LNTB-EPTB). A total of 345 (59.79%, 345/577) LNTB patients had cervical node infection, and the simple LNTB patients (81.63%, 120/147) had higher proportion of this infection than LNTB-PTB (51.71%, 181/350) and LNTB-EPTB (55.00%, 44/80) (both p values <0.017), respectively. LNTB-EPTB was more inclined to have abdominal tuberculous LNs (20%, 16/80) and at least four tuberculous lesions (22.50%, 18/80) than simple LNTB and LNTB-PTB. Seventy-seven (13.34%) and 119 (20.62%) were resistant to rifampicin (RIF) and isoniazid (INH), respectively; 72 (12.48%) were multi-drug resistant (MDR), and a total of 150 (26.00%) were DR (resistant to at least one of RIF, INH, ethambutol and streptomycin). LNTB patients aged 30-34 and 50-54 years old (compared to those aged <30 years) were independent predictors of RIF resistance (RR) (ORs were 3.47 and 2.83, respectively; 95% CIs were 1.64-7.35 and 1.08-7.46, respectively). Conclusion Our study disclosed the epidemiological and DR characteristics of LNTB in Hunan Province, China. High LNTB prevalence was found in younger people while high RR LNTB prevalence was found in older ones, suggesting that we should conduct further studies to clarify the occurrence of RR in LNTB, meanwhile, strengthen the diagnoses and treatments of LNTB to prevent the emergence of RR.
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Affiliation(s)
- Tanwei Fang
- Hunan Institute for Tuberculosis Control & Hunan Chest Hospital, Changsha, China
| | - Yu Xiang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Public Health, University of South China, Hengyang, China
| | - Wenbin Li
- Hunan Institute for Tuberculosis Control & Hunan Chest Hospital, Changsha, China
| | - Binbin Liu
- Hunan Institute for Tuberculosis Control & Hunan Chest Hospital, Changsha, China
| | - Haican Liu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yaning Wu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Da Xu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Machao Li
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shuliu Yang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Public Health, University of South China, Hengyang, China
| | - Jixiang Li
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Public Health, University of South China, Hengyang, China
| | - Yanyan Yu
- Hunan Institute for Tuberculosis Control & Hunan Chest Hospital, Changsha, China
- School of Basic Medical Sciences, Central South University, Changsha, China
| | - Xiuqin Zhao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Li-li Zhao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Kanglin Wan
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiuqin Yuan
- School of Public Health, University of South China, Hengyang, China
| | - Yunhong Tan
- Hunan Institute for Tuberculosis Control & Hunan Chest Hospital, Changsha, China
| | - Guilian Li
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
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Kurosaki F, Kuroki T, Nomura Y, Numao T, Bando M, Maemondo M. Prolonged paradoxical reaction requiring over 5 years of corticosteroid administration in a patient with severe tuberculous meningitis. J Infect Chemother 2024; 30:357-361. [PMID: 37922986 DOI: 10.1016/j.jiac.2023.10.027] [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: 08/17/2023] [Revised: 10/21/2023] [Accepted: 10/31/2023] [Indexed: 11/07/2023]
Abstract
Tuberculous meningitis (TBM) is a rare disease in low-incidence countries like Japan, where general physicians have fewer experience with TBM. Despite its proper treatment and early improvement of the condition, TBM often causes paradoxical reactions (PRs), which can lead to severe complications such as stroke. As PRs in the brain are difficult to detect without regular neuroimaging surveillance and have a later onset than in other organs, delayed treatment can be fatal. We report a case of a 54-year-old, human immunodeficiency virus (HIV)-negative man who presented with TBM and miliary tuberculosis (TB) in an unconscious state. Standard anti-tuberculous therapy with adjunctive systemic high-dose dexamethasone brought rapid clinical and microbiological improvement, which allowed the dexamethasone to be tapered. However, he developed cerebral infarction with left hemiplegia due to a TBM-related PR five months after admission. Therefore, the initial high-dose dexamethasone was again added to the anti-tuberculous drugs, achieving the significant effects on the PR-related lesions. Anti-tuberculous drugs had been administered for 3 years and the dexamethasone was carefully tapered. Nevertheless, enlargement of PR-related lesions in the brain recurred 5 years later. Accordingly, the dose of corticosteroid was again increased, resulting in resolving the lesions. It is important to note that severe TBM may cause prolonged PRs, which require a long-term neuroimaging follow-up and anti-inflammatory drugs for the successful management of the TBM-related PR.
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Affiliation(s)
- Fumio Kurosaki
- Division of Pulmonary Medicine, Department of Medicine, Jichi Medical University, Shimotsuke, Tochigi, Japan; Department of Pulmonary Medicine, National Hospital Organization Utsunomiya National Hospital, Utsunomiya, Tochigi, Japan.
| | - Tomonori Kuroki
- Division of Pulmonary Medicine, Department of Medicine, Jichi Medical University, Shimotsuke, Tochigi, Japan; Department of Pulmonary Medicine, National Hospital Organization Utsunomiya National Hospital, Utsunomiya, Tochigi, Japan
| | - Yushi Nomura
- Department of Pulmonary Medicine, National Hospital Organization Utsunomiya National Hospital, Utsunomiya, Tochigi, Japan
| | - Toshio Numao
- Department of Pulmonary Medicine, National Hospital Organization Utsunomiya National Hospital, Utsunomiya, Tochigi, Japan
| | - Masashi Bando
- Division of Pulmonary Medicine, Department of Medicine, Jichi Medical University, Shimotsuke, Tochigi, Japan
| | - Makoto Maemondo
- Division of Pulmonary Medicine, Department of Medicine, Jichi Medical University, Shimotsuke, Tochigi, Japan
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Chen X, Chen F, Liang C, He G, Chen H, Wu Y, Chen Y, Shuai J, Yang Y, Dai C, Cao L, Wang X, Cai E, Wang J, Wu M, Zeng L, Zhu J, Hai D, Pan W, Pan S, Zhang C, Quan S, Su F. MRI advances in the imaging diagnosis of tuberculous meningitis: opportunities and innovations. Front Microbiol 2023; 14:1308149. [PMID: 38149270 PMCID: PMC10750405 DOI: 10.3389/fmicb.2023.1308149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 11/14/2023] [Indexed: 12/28/2023] Open
Abstract
Tuberculous meningitis (TBM) is not only one of the most fatal forms of tuberculosis, but also a major public health concern worldwide, presenting grave clinical challenges due to its nonspecific symptoms and the urgent need for timely intervention. The severity and the rapid progression of TBM underscore the necessity of early and accurate diagnosis to prevent irreversible neurological deficits and reduce mortality rates. Traditional diagnostic methods, reliant primarily on clinical findings and cerebrospinal fluid analysis, often falter in delivering timely and conclusive results. Moreover, such methods struggle to distinguish TBM from other forms of neuroinfections, making it critical to seek advanced diagnostic solutions. Against this backdrop, magnetic resonance imaging (MRI) has emerged as an indispensable modality in diagnostics, owing to its unique advantages. This review provides an overview of the advancements in MRI technology, specifically emphasizing its crucial applications in the early detection and identification of complex pathological changes in TBM. The integration of artificial intelligence (AI) has further enhanced the transformative impact of MRI on TBM diagnostic imaging. When these cutting-edge technologies synergize with deep learning algorithms, they substantially improve diagnostic precision and efficiency. Currently, the field of TBM imaging diagnosis is undergoing a phase of technological amalgamation. The melding of MRI and AI technologies unquestionably signals new opportunities in this specialized area.
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Affiliation(s)
- Xingyu Chen
- Department of Infectious Diseases, Wenzhou Central Hospital, Wenzhou, China
- The First School of Medicine, Wenzhou Medical University, Wenzhou, China
| | - Fanxuan Chen
- School of Biomedical Engineering, School of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, China
| | - Chenglong Liang
- The First School of Medicine, Wenzhou Medical University, Wenzhou, China
| | - Guoqiang He
- Postgraduate Training Base Alliance of Wenzhou Medical University, Wenzhou, China
- Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, China
| | - Hao Chen
- The First School of Medicine, Wenzhou Medical University, Wenzhou, China
| | - Yanchan Wu
- School of Electrical and Information Engineering, Quzhou University, Quzhou, China
| | - Yinda Chen
- School of Electrical and Information Engineering, Quzhou University, Quzhou, China
| | - Jincen Shuai
- Baskin Engineering, University of California, Santa Cruz, CA, United States
| | - Yilei Yang
- The First School of Medicine, Wenzhou Medical University, Wenzhou, China
| | | | - Luhuan Cao
- Wenzhou Medical University, Wenzhou, China
| | - Xian Wang
- Wenzhou Medical University, Wenzhou, China
| | - Enna Cai
- Wenzhou Medical University, Wenzhou, China
| | | | | | - Li Zeng
- Wenzhou Medical University, Wenzhou, China
| | | | - Darong Hai
- Wenzhou Medical University, Wenzhou, China
| | - Wangzheng Pan
- Renji College of Wenzhou Medical University, Wenzhou, China
| | - Shuo Pan
- The First School of Medicine, Wenzhou Medical University, Wenzhou, China
| | - Chengxi Zhang
- School of Materials Science and Engineering, Shandong Jianzhu University, Jinan, China
| | - Shichao Quan
- Department of Big Data in Health Science, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
- Key Laboratory of Intelligent Treatment and Life Support for Critical Diseases of Zhejiang Province, Wenzhou, China
- Zhejiang Engineering Research Center for Hospital Emergency and Process Digitization, Wenzhou, China
| | - Feifei Su
- Department of Infectious Diseases, Wenzhou Central Hospital, Wenzhou, China
- Wenzhou Key Laboratory of Diagnosis and Treatment of Emerging and Recurrent Infectious Diseases, Wenzhou, China
- Department of Infectious Diseases, Wenzhou Sixth People’s Hospital, Wenzhou, China
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Asare-Baah M, Johnston L, Ramirez-Hiller T, Séraphin MN, Lauzardo M. Central Nervous System Tuberculosis: Risk Factors for Mortality in a Propensity Score-Matched Case-Control Study. Open Forum Infect Dis 2023; 10:ofad559. [PMID: 38088977 PMCID: PMC10715679 DOI: 10.1093/ofid/ofad559] [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: 10/11/2023] [Indexed: 12/30/2023] Open
Abstract
Background Despite advancements in tuberculosis (TB) control and treatment in the United States (US), patients with central nervous system TB (CNS-TB) continue to experience significantly higher mortality rates than those without CNS-TB. This raises concerns regarding clinical management and the need for a deeper understanding of the risk factors contributing to these deaths. This study aimed to determine the predictors of mortality in patients with CNS-TB. Methods We conducted a retrospective 1:2 propensity score-matched case-control study. Cases were TB patients diagnosed with TB of the meninges, brain, spinal cord, or peripheral nerves, as documented in the Florida Department of Health (FDOH) TB registry, between 2009 and 2021. Controls were TB patients without CNS-TB, also reported in the FDOH TB registry during the same timeframe. We employed conditional logistic regression models to investigate the factors contributing to mortality in cases compared with controls. Results We analyzed data from 116 cases and 232 matched controls. Patients with CNS-TB had a 5.69-fold higher risk of death than those without CNS-TB (adjusted odds ratio [aOR], 5.69 [95% confidence interval {CI}, 2.91-11.6]). Increased risk of death was associated with human immunodeficiency virus (HIV) coinfection (aOR, 1.93 [95% CI, .82-4.37]) and diabetes (aOR, 3.13 [95% CI, 1.28-7.47]). Miliary TB and non-HIV immunosuppression were significantly associated with being a case, while cavitary TB was less likely to be associated with being a case. Conclusions Clinical management should prioritize screening and close monitoring of patients with HIV coinfection and diabetes to improve patient outcomes.
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Affiliation(s)
- Michael Asare-Baah
- Department of Epidemiology, College of Public Health and Health Professions, College of Medicine, University of Florida,Gainesville, Florida, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
| | - Lori Johnston
- Bureau of Tuberculosis Control, Florida Department of Health, Tallahassee, Florida, USA
| | - Tatiana Ramirez-Hiller
- Pediatric Research Hub, Department of Pediatrics, College of Medicine, University of Florida,Gainesville, Florida, USA
| | - Marie Nancy Séraphin
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
- Division of Infectious Diseases and Global Medicine, College of Medicine, University of Florida,Gainesville, Florida, USA
| | - Michael Lauzardo
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
- Division of Infectious Diseases and Global Medicine, College of Medicine, University of Florida,Gainesville, Florida, USA
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Zhu X, He N, Tong L, Gu ZH, Li H. Clinical characteristics of tuberculous meningitis in older patients compared with younger and middle-aged patients: a retrospective analysis. BMC Infect Dis 2023; 23:699. [PMID: 37853321 PMCID: PMC10585848 DOI: 10.1186/s12879-023-08700-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Accepted: 10/12/2023] [Indexed: 10/20/2023] Open
Abstract
BACKGROUND Few studies have analyzed the clinical characteristics and adverse factors affecting prognosis in older patients with tuberculous meningitis (TBM). This study aimed to compare the clinical characteristics of TBM in older patients with those in younger and middle-aged patients. METHODS This single-center retrospective study extracted data on the clinical features, cerebrospinal fluid changes, laboratory results, imaging features, and outcomes of patients with TBM from patient medical records and compared the findings in older patients (aged 60 years and older) with those of younger and middle-aged patients (aged 18-59 years). RESULTS The study included 197 patients with TBM, comprising 21 older patients aged 60-76 years at onset, and 176 younger and middle-aged patients aged 18-59 years at onset. Fever was common in both older (81%) and younger and middle-aged patients (79%). Compared with younger and middle-aged patients, older patients were more likely to have changes in awareness levels (67% vs. 40%), peripheral nerve dysfunction (57% vs. 29%), changes in cognitive function (48% vs. 20%), and focal seizures (33% vs. 6%), and less likely to have headache (71% vs. 93%), neck stiffness on meningeal stimulation (38% vs. 62%), and vomiting (47% vs. 68%). The Medical Research Council staging on admission of older patients was stage II (52%) and stage III (38%), whereas most younger and middle-aged patients had stage I (33%) and stage II (55%) disease. Neurological function evaluated on the 28th day of hospitalization was more likely to show poor prognosis in older patients than in younger and middle-aged patients (76% vs. 25%). Older patients had significantly higher red blood cell counts and blood glucose levels, and significantly lower serum albumin and sodium levels than those in younger and middle-aged patients. The cerebrospinal fluid protein levels, nucleated cell counts, glucose levels, and chloride levels did not differ significantly by age. CONCLUSION In patients with TBM, older patients have more severe clinical manifestations, a higher incidence of hydrocephalus and cerebral infarction, and longer hospital stays than younger and middle-aged patients. Older patients thus require special clinical attention.
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Affiliation(s)
- Xiaolin Zhu
- Department of Emergency Medicine, West China Hospital, Sichuan University/West China School of Nursing, Sichuan University, Chengdu, 610041, Sichuan, P. R. China
- Institute of Disaster Medicine, Sichuan University, Chengdu, 610041, Sichuan, P. R. China
- Nursing Key Laboratory of Sichuan Province, Chengdu, 610041, Sichuan, P. R. China
| | - Na He
- Department of Emergency Medicine, West China Hospital, Sichuan University/West China School of Nursing, Sichuan University, Chengdu, 610041, Sichuan, P. R. China
- Institute of Disaster Medicine, Sichuan University, Chengdu, 610041, Sichuan, P. R. China
- Nursing Key Laboratory of Sichuan Province, Chengdu, 610041, Sichuan, P. R. China
| | - Le Tong
- Department of Emergency Medicine, West China Hospital, Sichuan University/West China School of Nursing, Sichuan University, Chengdu, 610041, Sichuan, P. R. China
- Institute of Disaster Medicine, Sichuan University, Chengdu, 610041, Sichuan, P. R. China
- Nursing Key Laboratory of Sichuan Province, Chengdu, 610041, Sichuan, P. R. China
| | - Zhi Han Gu
- Emergency Department of West China Hospital of Sichuan University/Emergency Teaching and Research Department of West China Hospital of Sichuan University, Chengdu, 610041, P. R. China
| | - Hong Li
- Department of Emergency Medicine, West China Hospital, Sichuan University/West China School of Nursing, Sichuan University, Chengdu, 610041, Sichuan, P. R. China.
- Institute of Disaster Medicine, Sichuan University, Chengdu, 610041, Sichuan, P. R. China.
- Nursing Key Laboratory of Sichuan Province, Chengdu, 610041, Sichuan, P. R. China.
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Saifon W, Karaketklang K, Jitmuang A. Distinguishing clinical characteristics of central nervous system tuberculosis in immunodeficient and non-immunodeficient individuals: a 12-year retrospective study. Ann Clin Microbiol Antimicrob 2023; 22:69. [PMID: 37550721 PMCID: PMC10408106 DOI: 10.1186/s12941-023-00615-w] [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] [Accepted: 07/23/2023] [Indexed: 08/09/2023] Open
Abstract
BACKGROUND Central nervous system tuberculosis (CNS TB) is a severe Mycobacterium tuberculosis (MTB) infection. It is unclear whether a patient's immune status alters the clinical manifestations and treatment outcomes of CNS TB. METHODS Between January 2007-December 2018, chart reviews of CNS TB, including tuberculous meningitis (TBM), tuberculoma/abscess, and TB myelitis, were made. Subjects were categorized as immunodeficient (ID) and non-immunodeficient (NID). RESULTS Of 310 subjects, 160 (51.6%) were in the ID group-132 (42.6%) had HIV and 28 (9.0%) had another ID, and 150 (48.4%) were in the NID group. The mean age was 43.64 ± 16.76 years, and 188 (60.6%) were male. There were 285 (91.9%) TBM, 16 (5.2%) tuberculoma/abscess, and 9 (2.9%) myelitis cases. The TBM characteristics in the ID group were younger age (p = 0.003), deep subcortical location of tuberculoma (p = 0.030), lower hemoglobin level (p < 0.001), and lower peripheral white blood cell count (p < 0.001). Only HIV individuals with TBM had an infection by multidrug-resistant MTB (p = 0.013). TBM mortality was varied by immune status -HIV 22.8%, other ID 29.6%, and NID 14.8% (p < 0.001). Factors significantly associated with unfavorable outcomes in TBM also differed between the HIV and NID groups. CONCLUSIONS TBM is the most significant proportion of CNS TB. Some of the clinical characteristics of TBM, such as age, radiographic findings, hematological derangement, and mortality, including factors associated with unfavorable outcomes, differed between ID and non-ID patients.
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Affiliation(s)
- Woraseth Saifon
- Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Khemajira Karaketklang
- Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Anupop Jitmuang
- Division of Infectious Diseases and Tropical Medicine, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Wanglang Road, Bangkok Noi, Bangkok, 10700, Thailand.
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