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Rajakumar HK, Coimbatore Sathyabal V, Palaniyandi A, Balakrishnan D. Exploring mean platelet volume and neutrophil-to-albumin ratio as surrogate markers for monitoring tuberculosis treatment: a prospective longitudinal study. BMC Pulm Med 2024; 24:406. [DOI: https:/doi.org/10.1186/s12890-024-03236-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Accepted: 08/19/2024] [Indexed: 10/02/2024] Open
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Rajakumar HK, Coimbatore Sathyabal V, Palaniyandi A, Balakrishnan D. Exploring mean platelet volume and neutrophil-to-albumin ratio as surrogate markers for monitoring tuberculosis treatment: a prospective longitudinal study. BMC Pulm Med 2024; 24:406. [PMID: 39180021 PMCID: PMC11344401 DOI: 10.1186/s12890-024-03236-x] [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: 04/24/2024] [Accepted: 08/19/2024] [Indexed: 08/26/2024] Open
Abstract
BACKGROUND Tuberculosis (TB) remains a global health challenge, with India bearing a significant burden. Despite advancements in TB diagnosis and treatment, monitoring TB treatment is challenging, particularly in resource-limited settings. This study aimed to explore the mean platelet volume (MPV) as a potential surrogate marker for monitoring TB treatment and assessing if the neutrophil-to-albumin ratio (NAR) enhances treatment monitoring. METHODS Patients diagnosed with TB following NTEP guidelines were recruited. Participants underwent routine blood tests during the six-month Anti-Tubercular therapy course at the start, end of the intensive phase, and end of the continuous phase. Statistical analyses included Spearman correlation, Friedman test, linear mixed effects (LME) models, and multiple linear regression. RESULTS 150 individuals were included for analysis. Deviations from normality were noted. Significant associations were found between CRP and sputum grade. MPV mediated between CRP and sputum grade. Significant differences were observed across the three-time points. LME models showed changes in MPV and CRP levels over time. Including NAR enhanced predictive capability. CONCLUSIONS MPV may serve as a promising surrogate marker for monitoring ATT. Personalized approaches are crucial in TB treatment monitoring. LME models revealed MPV and CRP level trends. Future research should explore MPV's treatment response mechanisms and cost-effectiveness.
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Affiliation(s)
| | | | - Arulkumaran Palaniyandi
- Department of Respiratory Medicine, Government Medical College, Omandurar Government Estate, Chennai, India
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Alcantara CA, Glassman I, Nguyen KH, Parthasarathy A, Venketaraman V. Neutrophils in Mycobacterium tuberculosis. Vaccines (Basel) 2023; 11:vaccines11030631. [PMID: 36992214 DOI: 10.3390/vaccines11030631] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 03/07/2023] [Accepted: 03/09/2023] [Indexed: 03/16/2023] Open
Abstract
Mycobacterium tuberculosis (M. tb) continues to be a leading cause of mortality within developing countries. The BCG vaccine to promote immunity against M. tb is widely used in developing countries and only in specific circumstances within the United States. However, current the literature reports equivocal data on the efficacy of the BCG vaccine. Critical within their role in the innate immune response, neutrophils serve as one of the first responders to infectious pathogens such as M. tb. Neutrophils promote effective clearance of M. tb through processes such as phagocytosis and the secretion of destructive granules. During the adaptative immune response, neutrophils modulate communication with lymphocytes to promote a strong pro-inflammatory response and to mediate the containment M. tb through the production of granulomas. In this review, we aim to highlight and summarize the role of neutrophils during an M. tb infection. Furthermore, the authors emphasize the need for more studies to be conducted on effective vaccination against M. tb.
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Affiliation(s)
- Cheldon Ann Alcantara
- Department of Basic Sciences, College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA
| | - Ira Glassman
- Department of Basic Sciences, College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA
| | - Kevin H Nguyen
- Department of Basic Sciences, College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA
| | | | - Vishwanath Venketaraman
- Department of Basic Sciences, College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA
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Yu Q, Yan J, Tian S, Weng W, Luo H, Wei G, Long G, Ma J, Gong F, Wang X. A scoring system developed from a nomogram to differentiate active pulmonary tuberculosis from inactive pulmonary tuberculosis. Front Cell Infect Microbiol 2022; 12:947954. [PMID: 36118035 PMCID: PMC9478038 DOI: 10.3389/fcimb.2022.947954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 08/15/2022] [Indexed: 11/29/2022] Open
Abstract
Purpose This study aimed to develop and validate a scoring system based on a nomogram of common clinical metrics to discriminate between active pulmonary tuberculosis (APTB) and inactive pulmonary tuberculosis (IPTB). Patients and methods A total of 1096 patients with pulmonary tuberculosis (PTB) admitted to Wuhan Jinyintan Hospital between January 2017 and December 2019 were included in this study. Of these patients with PTB, 744 were included in the training cohort (70%; 458 patients with APTB, and 286 patients with IPTB), and 352 were included in the validation cohort (30%; 220 patients with APTB, and 132 patients with IPTB). Data from 744 patients from the training cohort were used to establish the diagnostic model. Routine blood examination indices and biochemical indicators were collected to construct a diagnostic model using the nomogram, which was then transformed into a scoring system. Furthermore, data from 352 patients from the validation cohort were used to validate the scoring system. Results Six variables were selected to construct the prediction model. In the scoring system, the mean corpuscular volume, erythrocyte sedimentation rate, albumin level, adenosine deaminase level, monocyte-to-high-density lipoprotein ratio, and high-sensitivity C-reactive protein-to-lymphocyte ratio were 6, 4, 7, 5, 5, and 10, respectively. When the cut-off value was 15.5, the scoring system for recognizing APTB and IPTB exhibited excellent diagnostic performance. The area under the curve, specificity, and sensitivity of the training cohort were 0.919, 84.06%, and 86.36%, respectively, whereas those of the validation cohort were 0.900, 82.73, and 86.36%, respectively. Conclusion This study successfully constructed a scoring system for distinguishing APTB from IPTB that performed well.
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Affiliation(s)
- Qi Yu
- Department of Infectious Diseases, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Hubei Clinical Research Center for Infectious Diseases, Wuhan Research Center for Communicable Disease Diagnosis and Treatment, Chinese Academy of Medical Sciences, Joint Laboratory of Infectious Diseases and Health, Wuhan Institute of Virology and Wuhan Jinyintan Hospital, Chinese Academy of Sciences, Wuhan, China
| | - Jisong Yan
- Department of Respiratory and Critical Care Medicine, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Hubei Clinical Research Center for Infectious Diseases, Wuhan Research Center for Communicable Disease Diagnosis and Treatment, Chinese Academy of Medical Sciences, Joint Laboratory of Infectious Diseases and Health, Wuhan Institute of Virology and Wuhan Jinyintan Hospital, Chinese Academy of Sciences, Wuhan, China
| | - Shan Tian
- Department of Infectious Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wujin Weng
- Department of Oncology, Quzhou Hospital of traditional Chinese Medicine, Zhejiang University of Chinese Medicine, Quzhou, China
| | - Hong Luo
- Department of Respiratory and Critical Care Medicine, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Hubei Clinical Research Center for Infectious Diseases, Wuhan Research Center for Communicable Disease Diagnosis and Treatment, Chinese Academy of Medical Sciences, Joint Laboratory of Infectious Diseases and Health, Wuhan Institute of Virology and Wuhan Jinyintan Hospital, Chinese Academy of Sciences, Wuhan, China
| | - Gang Wei
- Department of Science and Education, Wuhan Jinyintan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Gangyu Long
- Department of Respiratory and Critical Care Medicine, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Hubei Clinical Research Center for Infectious Diseases, Wuhan Research Center for Communicable Disease Diagnosis and Treatment, Chinese Academy of Medical Sciences, Joint Laboratory of Infectious Diseases and Health, Wuhan Institute of Virology and Wuhan Jinyintan Hospital, Chinese Academy of Sciences, Wuhan, China
| | - Jun Ma
- Department of Laboratory Medicine, Wuhan Jinyintan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Fengyun Gong
- Department of Infectious Diseases, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Hubei Clinical Research Center for Infectious Diseases, Wuhan Research Center for Communicable Disease Diagnosis and Treatment, Chinese Academy of Medical Sciences, Joint Laboratory of Infectious Diseases and Health, Wuhan Institute of Virology and Wuhan Jinyintan Hospital, Chinese Academy of Sciences, Wuhan, China
- *Correspondence: Fengyun Gong, ; Xiaorong Wang,
| | - Xiaorong Wang
- Department of Respiratory and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- *Correspondence: Fengyun Gong, ; Xiaorong Wang,
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Yu Q, Weng W, Luo H, Yan J, Zhao X. The Novel Predictive Biomarkers for Type 2 Diabetes Mellitus in Active Pulmonary Tuberculosis Patients. Infect Drug Resist 2022; 15:4529-4539. [PMID: 35992755 PMCID: PMC9384973 DOI: 10.2147/idr.s377465] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 08/04/2022] [Indexed: 11/30/2022] Open
Abstract
Purpose This study was to explore the predictive value of monocyte to high-density lipoprotein cholesterol ratio (MHR), neutrophils to high-density lipoprotein cholesterol ratio (NHR), C-reactive protein-to-lymphocyte ratio (CLR), and C-reactive protein-to-albumin ratio (CAR) for type 2 diabetes mellitus (T2DM) in patients with active pulmonary tuberculosis (APTB). Patients and Methods A total of 991 active pulmonary tuberculosis (APTB) patients (201 with T2DM) were hospitalized in the Department of Tuberculosis, Wuhan Jinyintan Hospital, Tongji Medical College, Huazhong University of Science and Technology were included. The routine blood examination indicators and biochemical parameters were collected to calculate MHR, NHR, CLR, and CAR. The Pearson correlation analysis, Univariate Logistic regression analysis, and receiver operating characteristic (ROC) curve analysis were performed to assess the predictive value of MHR, NHR, CLR, and CAR for APTB-T2DM patients. Results The levels of MHR, NHR, CLR, and CAR in the APTB-T2DM patients were significantly higher than in the APTB-no T2DM patients (P < 0.05). Additionally, the MHR, NHR, CLR, and CAR have a positive correlation with fasting blood glucose in the whole study population. However, in the APTB-T2DM patients, MHR, NHR, and CAR were not correlated with fasting blood glucose, and only CLR was positively correlated with fasting blood glucose. The area under curve (AUC) predicting APTB-T2DM patients of the MHR, NHR, CLR, and CAR was 0.632, 0.72, 0.715, and 0.713, respectively. Further, univariate logistic regression analyses showed that the higher MHR, NHR, CLR, and CAR were independent risk factors for APTB-T2DM (P < 0.01). The MHR, NHR, CLR, and CAR quartiles were used to divide the APTB patients into four groups for further analysis. The prevalence of T2DM was significantly higher in APTB individuals as MHR, NHR, CLR, and CAR values increased (P < 0.05). Conclusion MHR, NHR, CLR, and CAR are simple and practicable inflammatory parameters that could be used for assessing T2DM in APTB. APTB patients have a greater possibility to be diagnosed with T2DM with the higher MHR, NHR CLR, and CAR values. Therefore, more attention should be given to the indicator in the examination of APTB.
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Affiliation(s)
- Qi Yu
- Department of Infectious Diseases, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology; Hubei Clinical Research Center for Infectious Diseases; Wuhan Research Center for Communicable Disease Diagnosis and Treatment, Chinese Academy of Medical Sciences; Joint Laboratory of Infectious Diseases and Health, Wuhan Institute of Virology and Wuhan Jinyintan Hospital, Chinese Academy of Sciences, Wuhan, 430023, People's Republic of China
| | - Wujin Weng
- Department of Oncology, Quzhou Hospital of Traditional Chinese Medicine, Zhejiang University of Chinese Medicine, Quzhou, 310053, People's Republic of China
| | - Hong Luo
- Department of Respiratory and Critical Care Medicine, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology; Hubei Clinical Research Center for Infectious Diseases; Wuhan Research Center for Communicable Disease Diagnosis and Treatment, Chinese Academy of Medical Sciences; Joint Laboratory of Infectious Diseases and Health, Wuhan Institute of Virology and Wuhan Jinyintan Hospital, Chinese Academy of Sciences, Wuhan, 430023, People's Republic of China
| | - Jisong Yan
- Department of Respiratory and Critical Care Medicine, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology; Hubei Clinical Research Center for Infectious Diseases; Wuhan Research Center for Communicable Disease Diagnosis and Treatment, Chinese Academy of Medical Sciences; Joint Laboratory of Infectious Diseases and Health, Wuhan Institute of Virology and Wuhan Jinyintan Hospital, Chinese Academy of Sciences, Wuhan, 430023, People's Republic of China
| | - Xin Zhao
- Department of Pediatrics, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510799, People's Republic of China
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Rankin AN, Hendrix SV, Naik SK, Stallings CL. Exploring the Role of Low-Density Neutrophils During Mycobacterium tuberculosis Infection. Front Cell Infect Microbiol 2022; 12:901590. [PMID: 35800386 PMCID: PMC9253571 DOI: 10.3389/fcimb.2022.901590] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 05/23/2022] [Indexed: 12/14/2022] Open
Abstract
Tuberculosis (TB) is caused by infection with the bacterium Mycobacterium tuberculosis (Mtb), which primarily infects the lungs but can also cause extrapulmonary disease. Both the disease outcome and the pathology of TB are driven by the immune response mounted by the host. Infection with Mtb elicits inflammatory host responses that are necessary to control infection, but can also cause extensive tissue damage when in excess, and thus must be precisely balanced. In particular, excessive recruitment of neutrophils to the site of infection has been associated with poor control of Mtb infection, prompting investigations into the roles of neutrophils in TB disease outcomes. Recent studies have revealed that neutrophils can be divided into subpopulations that are differentially abundant in TB disease states, highlighting the potential complexities in determining the roles of neutrophils in Mtb infection. Specifically, neutrophils can be separated into normal (NDN) and low-density neutrophils (LDNs) based on their separation during density gradient centrifugation and surface marker expression. LDNs are present in higher numbers during active TB disease and increase in frequency with disease progression, although their direct contribution to TB is still unknown. In addition, the abundance of LDNs has also been associated with the severity of other lung infections, including COVID-19. In this review, we discuss recent findings regarding the roles of LDNs during lung inflammation, emphasizing their association with TB disease outcomes. This review highlights the importance of future investigations into the relationship between neutrophil diversity and TB disease severity.
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Parker HA, Forrester L, Kaldor CD, Dickerhof N, Hampton MB. Antimicrobial Activity of Neutrophils Against Mycobacteria. Front Immunol 2021; 12:782495. [PMID: 35003097 PMCID: PMC8732375 DOI: 10.3389/fimmu.2021.782495] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 12/06/2021] [Indexed: 12/21/2022] Open
Abstract
The mycobacterium genus contains a broad range of species, including the human pathogens M. tuberculosis and M. leprae. These bacteria are best known for their residence inside host cells. Neutrophils are frequently observed at sites of mycobacterial infection, but their role in clearance is not well understood. In this review, we discuss how neutrophils attempt to control mycobacterial infections, either through the ingestion of bacteria into intracellular phagosomes, or the release of neutrophil extracellular traps (NETs). Despite their powerful antimicrobial activity, including the production of reactive oxidants such as hypochlorous acid, neutrophils appear ineffective in killing pathogenic mycobacteria. We explore mycobacterial resistance mechanisms, and how thwarting neutrophil action exacerbates disease pathology. A better understanding of how mycobacteria protect themselves from neutrophils will aid the development of novel strategies that facilitate bacterial clearance and limit host tissue damage.
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Affiliation(s)
| | | | | | | | - Mark B. Hampton
- Centre for Free Radical Research, Department of Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand
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