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Yu Z, Shang Z, Huang Q, Wen F, Patil S. Integrating systemic immune-inflammation index, fibrinogen, and T-SPOT.TB for precision distinction of active pulmonary tuberculosis in the era of mycobacterial disease research. Front Microbiol 2024; 15:1382665. [PMID: 38725688 PMCID: PMC11079184 DOI: 10.3389/fmicb.2024.1382665] [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: 02/06/2024] [Accepted: 04/15/2024] [Indexed: 05/12/2024] Open
Abstract
Background The clinical challenge of differentiating suspected tuberculosis with positive T-SPOT.TB results persist. This study aims to investigate the utility of the Systemic Immune-Inflammation Index (SII), Fibrinogen, and T-SPOT.TB in distinguishing between active pulmonary tuberculosis (PTB) and non-tuberculous lung diseases. Methods A retrospective analysis included 1,327 cases of active PTB with positive T-SPOT.TB results and 703 cases of non-tuberculous lung diseases from May 2016 to December 2020 at Meizhou People's Hospital. These were designated as the case group and the control group, respectively. The detection indicators of T-SPOT.TB: Early Secreted Antigenic Target 6 (ESAT-6), Culture Filtrate Protein 10 (CFP-10), as well as SII and Fibrinogen levels-were compared and analyzed for association and joint diagnostic value between the two groups. Results The case group showed higher values of ESAT-6, CFP-10, SII, and Fibrinogen compared to the control group (all p < 0.001). In the case group, SII and Fibrinogen did not correlate with ESAT-6 and CFP-10 (∣rs∣ all < 0.3) but were positively correlated with C-reactive protein (CRP; rs all > 0.3). SII and Fibrinogen values in smear-positive pulmonary tuberculosis were higher than in smear-negative cases (all p < 0.05). The optimal diagnostic thresholds for ESAT-6, CFP-10, SII, and Fibrinogen in differentiating between active PTB and non-tuberculous lung diseases were 21.50 SFCs/106 PBMC, 22.50 SFCs/106 PBMC, 2128.32, and 5.02 g/L, respectively. Regression logistic analysis showed that ESAT-6 < 21.5 (OR: 1.637, 95% CI: 1.311-2.043, p < 0.001), CFP-10 < 22.5 (OR: 3.918, 95% CI: 3.138-4.892, p = 0.025), SII < 2128.32 (OR: 0.763, 95% CI: 0.603-0.967, p < 0.001), and FIB < 5.02 (OR: 2.287, 95% CI: 1.865-2.806, p < 0.001) were independent risk factors for active PTB. The specificity for ESAT-6 + CFP-10, ESAT-6 + CFP-10 + SII, ESAT-6 + CFP-10 + FIB, and ESAT-6 + CFP-10 + SII + FIB was 82.5%, 83.2%, 95.8%, and 80.1%, respectively, while sensitivity was 52.6%, 53.0%, 55.8%, and 44.7%, and positive predictive values were 85.0%, 85.6%, 84.1%, and 89.6%, respectively. Conclusion SII and Fibrinogen are positively correlated with the degree of tuberculosis inflammation and the bacterial load of Mycobacterium tuberculosis. The combined detection of SII, Fibrinogen, and T-SPOT.TB is significant in distinguishing between active PTB with positive T-SPOT.TB results and non-tuberculous lung diseases.
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Affiliation(s)
- Zhikang Yu
- Research Experiment Center, Meizhou People's Hospital, Meizhou Academy of Medical Sciences, Meizhou, China
- Guangdong Engineering Technological Research Center of Clinical Molecular Diagnosis and Antibody Drugs, Meizhou, China
| | - Zifang Shang
- Research Experiment Center, Meizhou People's Hospital, Meizhou Academy of Medical Sciences, Meizhou, China
- Guangdong Engineering Technological Research Center of Clinical Molecular Diagnosis and Antibody Drugs, Meizhou, China
| | - Qingyan Huang
- Research Experiment Center, Meizhou People's Hospital, Meizhou Academy of Medical Sciences, Meizhou, China
- Guangdong Engineering Technological Research Center of Clinical Molecular Diagnosis and Antibody Drugs, Meizhou, China
| | - Feiqiu Wen
- Department of Haematology and Oncology, Shenzhen Children’s Hospital, Shenzhen, China
| | - Sandip Patil
- Department of Haematology and Oncology, Shenzhen Children’s Hospital, Shenzhen, China
- Paediatric Research Institute, Shenzhen Children’s Hospital, Shenzhen, China
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Feng S, Wang S, Liu C, Wu S, Zhang B, Lu C, Huang C, Chen T, Zhou C, Zhu J, Chen J, Xue J, Wei W, Zhan X. Prediction model for spinal cord injury in spinal tuberculosis patients using multiple machine learning algorithms: a multicentric study. Sci Rep 2024; 14:7691. [PMID: 38565845 PMCID: PMC10987632 DOI: 10.1038/s41598-024-56711-0] [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: 11/29/2023] [Accepted: 03/09/2024] [Indexed: 04/04/2024] Open
Abstract
Spinal cord injury (SCI) is a prevalent and serious complication among patients with spinal tuberculosis (STB) that can lead to motor and sensory impairment and potentially paraplegia. This research aims to identify factors associated with SCI in STB patients and to develop a clinically significant predictive model. Clinical data from STB patients at a single hospital were collected and divided into training and validation sets. Univariate analysis was employed to screen clinical indicators in the training set. Multiple machine learning (ML) algorithms were utilized to establish predictive models. Model performance was evaluated and compared using receiver operating characteristic (ROC) curves, area under the curve (AUC), calibration curve analysis, decision curve analysis (DCA), and precision-recall (PR) curves. The optimal model was determined, and a prospective cohort from two other hospitals served as a testing set to assess its accuracy. Model interpretation and variable importance ranking were conducted using the DALEX R package. The model was deployed on the web by using the Shiny app. Ten clinical characteristics were utilized for the model. The random forest (RF) model emerged as the optimal choice based on the AUC, PRs, calibration curve analysis, and DCA, achieving a test set AUC of 0.816. Additionally, MONO was identified as the primary predictor of SCI in STB patients through variable importance ranking. The RF predictive model provides an efficient and swift approach for predicting SCI in STB patients.
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Affiliation(s)
- Sitan Feng
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Shujiang Wang
- Department of Outpatient, General Hospital of Eastern Theater Command, Nanjing, Jiangsu, People's Republic of China
| | - Chong Liu
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Shaofeng Wu
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Bin Zhang
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China
- Department of Spine Ward, Bei Jing Ji Shui Tan Hospital Gui Zhou Hospital, Guiyang, Guizhou, People's Republic of China
| | - Chunxian Lu
- Department of Spine and Osteopathy Ward, Bai Se People's Hospital, Baise, Guangxi, People's Republic of China
| | - Chengqian Huang
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Tianyou Chen
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Chenxing Zhou
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Jichong Zhu
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Jiarui Chen
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Jiang Xue
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Wendi Wei
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Xinli Zhan
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China.
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Huang C, Zhuo J, Liu C, Wu S, Zhu J, Chen T, Zhang B, Feng S, Zhou C, Wang Z, Huang S, Chen L, Xinli Zhan. Development and validation of a diagnostic model to differentiate spinal tuberculosis from pyogenic spondylitis by combining multiple machine learning algorithms. BIOMOLECULES & BIOMEDICINE 2024; 24:401-410. [PMID: 37897663 PMCID: PMC10950342 DOI: 10.17305/bb.2023.9663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 10/19/2023] [Accepted: 10/27/2023] [Indexed: 10/30/2023]
Abstract
This study focused on the development and validation of a diagnostic model to differentiate between spinal tuberculosis (STB) and pyogenic spondylitis (PS). We analyzed a total of 387 confirmed cases, out of which 241 were diagnosed with STB and 146 were diagnosed with PS. These cases were randomly divided into a training group (n = 271) and a validation group (n = 116). Within the training group, four machine learning (ML) algorithms (least absolute shrinkage and selection operator [LASSO], logistic regression analysis, random forest, and support vector machine recursive feature elimination [SVM-RFE]) were employed to identify distinctive variables. These specific variables were then utilized to construct a diagnostic model. The model's performance was subsequently assessed using the receiver operating characteristic (ROC) curves and the calibration curves. Finally, internal validation of the model was undertaken in the validation group. Our findings indicate that PS patients had an average platelet-to-neutrophil ratio (PNR) of 277.86, which was significantly higher than the STB patients' average of 69.88. The average age of PS patients was 54.71 years, older than the 48 years recorded for STB patients. Notably, the neutrophil-to-lymphocyte ratio (NLR) was higher in PS patients at 6.15, compared to the 3.46 NLR in STB patients. Additionally, the platelet volume distribution width (PDW) in PS patients was 0.2, compared to 0.15 in STB patients. Conversely, the mean platelet volume (MPV) was lower in PS patients at an average of 4.41, whereas STB patients averaged 8.31. Hemoglobin (HGB) levels were lower in PS patients at an average of 113.31 compared to STB patients' average of 121.64. Furthermore, the average red blood cell (RBC) count was 4.26 in PS patients, which was less than the 4.58 average observed in STB patients. After evaluation, seven key factors were identified using the four ML algorithms, forming the basis of our diagnostic model. The training and validation groups yielded area under the curve (AUC) values of 0.841 and 0.83, respectively. The calibration curves demonstrated a high alignment between the nomogram-predicted values and the actual measurements. The decision curve indicated optimal model performance with a threshold set between 2% and 88%. In conclusion, our model offers healthcare practitioners a reliable tool to efficiently and precisely differentiate between STB and PS, thereby facilitating swift and accurate diagnoses.
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Affiliation(s)
- Chengqian Huang
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Jing Zhuo
- Surgical Operation Department, Baise People’s Hospital, Affiliated Southwest Hospital of Youjiang Medical University for Nationalities, Baise, China
| | - Chong Liu
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Shaofeng Wu
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Jichong Zhu
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Tianyou Chen
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Bin Zhang
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Sitan Feng
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Chenxing Zhou
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Zequn Wang
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Shengsheng Huang
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Liyi Chen
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Xinli Zhan
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
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Shojaan H, Kalami N, Ghasempour Alamdari M, Emami Alorizy SM, Ghaedi A, Bazrgar A, Khanzadeh M, Lucke-Wold B, Khanzadeh S. Diagnostic value of the neutrophil lymphocyte ratio in discrimination between tuberculosis and bacterial community acquired pneumonia: A meta-analysis. J Clin Tuberc Other Mycobact Dis 2023; 33:100395. [PMID: 37692090 PMCID: PMC10485633 DOI: 10.1016/j.jctube.2023.100395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/12/2023] Open
Abstract
Background We conducted a systematic review and meta-analysis, based on Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines, to evaluate current literature on diagnostic value of neutrophil to lymphocyte ratio (NLR) in discrimination between tuberculosis (TB) and bacterial community acquired pneumonia (B-CAP). Methods Literature search was conducted from July 20, 2023 using Scopus, PubMed, and Web of Science databases. STATA software (version 12.0; Stata Corporation) was used for all analyses. Results We found that patients with TB had significantly lower levels of NLR compared to those with B-CAP (SMD = -1.09, 95 %CI = -1.78- -0.40, P = 0.002). In the quality subgroup analysis, we found that patients with TB had significantly lower level of NLR compared to those with B-CAP consistent in moderate (SMD = -0.86, 95 %CI = -2.30, 0.57, P = 0.23) and high-quality studies (SMD = -1.25, 95 %CI = -2.07, -0.42). In the subgroup analysis based on continent, we found that patients with TB had significantly lower level of NLR compared to those with B-CAP in studies performed in Asian populations (SMD = -1.37, 95 %CI = -2.13, -0.61, P < 0.001), but not on African population (SMD = -0.02, 95 %CI = -1.06, 1.02, P = 0.97). The result of this study did not change after execution of sensitivity analysis. The pooled sensitivity of NLR was 0.86 (95% CI = 0.80, 0.91), and the pooled specificity was0.88 (95% CI = 0.69, 0.95). Conclusion Patients with TB had a significantly lower NLR levels compared to those with B-CAP, so we utilized this biomarker for distinguishing between the disorders.
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Affiliation(s)
- Horieh Shojaan
- Tuberculosis and Lung Disease Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Niusha Kalami
- Tuberculosis and Lung Disease Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | | | | | - Arshin Ghaedi
- Student Research Committee, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
- Trauma Research Center, Shahid Rajaee (Emtiaz) Trauma Hospital, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Aida Bazrgar
- Student Research Committee, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Monireh Khanzadeh
- Geriatric & Gerontology Department, Medical School, Tehran University of Medical and Health Sciences, Tehran, Iran
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Wang J, Deng L, Ding Z, Zhang Y, Zhang Y, Li K, Zhao C, Zhang Q. Comparative Study on the Efficacy of Two Perioperative Chemotherapy Regimens for Lumbar Brucellosis. Drug Des Devel Ther 2023; 17:3523-3536. [PMID: 38046280 PMCID: PMC10691375 DOI: 10.2147/dddt.s427477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Accepted: 11/15/2023] [Indexed: 12/05/2023] Open
Abstract
Objective The clinical efficacy of perioperative chemotherapy regimen (rifampicin, doxycycline, levofloxacin, ceftriaxone) was evaluated for lumbar brucellosis spondylitis patients with neurological injury. Methods In Beijing Ditan Hospital affiliated with Capital Medical University, 32 patients with lumbar brucellosis spondylitis underwent surgery and triple perioperative chemotherapy (rifampicin, doxycycline, levofloxacin) between 2011 and 2021 due to neurological injury, and 34 patients matched up with the triple group underwent rifampicin, doxycycline, levofloxacin, and ceftriaxone. Both groups were compared in terms of changes in inflammation index, low back/leg pain, lumbar function, neurological function, and adverse drug reactions. Results There was no significant difference in erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), low back pain visual analogue scale (VAS), leg pain VAS, lumbar Oswestry disability index (ODI) and nerve function injury rate between the two groups before chemotherapy (P>0.05). The ESR, CRP at 1 week and 2 weeks after chemotherapy and 1 week, 2 weeks, 1 month postoperatively in the quadruple group were significantly lower than those in the triple group, which is the same to ESR 3 months postoperatively (P<0.05). The low back pain VAS, leg pain VAS and lumbar ODI in the quadruple group were significantly lower than those in the triple group at 1 month and 3 months postoperatively (P<0.05). The recovery rate of neurological function in the quadruple group was significantly higher than that in the triple group at 3 and 6 months postoperatively (P<0.05). Both groups did not experience significantly different perioperative and postoperative adverse reactions (P>0.05). Conclusion For lumbar brucellosis spondylitis with neurological injury, quadruple perioperative chemotherapy of rifampicin, doxycycline, levofloxacin and ceftriaxone can significantly reduce perioperative inflammation, and improve low back/leg pain, as well as promoting neurological function recovery in the short term.
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Affiliation(s)
- Jie Wang
- Department of Orthopedics, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, People’s Republic of China
| | - Lei Deng
- Department of First School of Clinical Medicine, Henan University of Chinese Medicine, Henan, 450003, People’s Republic of China
| | - Zihao Ding
- Department of Orthopedics, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100020, People’s Republic of China
| | - Yaosheng Zhang
- Department of Orthopedics, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100020, People’s Republic of China
| | - Yao Zhang
- Department of Orthopedics, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, People’s Republic of China
| | - Kangpeng Li
- Department of Orthopedics, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, People’s Republic of China
| | - Changsong Zhao
- Department of Orthopedics, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, People’s Republic of China
| | - Qiang Zhang
- Department of Orthopedics, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, People’s Republic of China
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Li M, Li X, Gao H, Li P, Zhang L, Zhang X, Liu P, Yang X, Wu L, Zeng J, Wu S, Sun L. U-Shaped Association Between Monocyte-Lymphocyte Ratio and Risk of Cardiac Conduction Block. J Inflamm Res 2023; 16:5393-5402. [PMID: 38026237 PMCID: PMC10664808 DOI: 10.2147/jir.s438722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 11/14/2023] [Indexed: 12/01/2023] Open
Abstract
Purpose Inflammation plays a critical role in the development of cardiac conduction block (CCB), which is associated with an increased risk of morbidity and mortality. The monocyte-lymphocyte ratio (MLR) acts as a novel inflammatory marker; however, its association with CCB has not yet been studied. This study aimed to investigate the association between MLR and CCB risk. Patients and Methods In total, 82,472 CCB-free participants were identified from the Kailuan study. MLR was calculated using the monocyte count/lymphocyte count. The participants were stratified based on quartiles of MLR levels. Incident CCB and its subtypes were ascertained from electrocardiograms at biennial follow-up visits. The Cox proportional hazards model and restricted cubic spline analysis were used to investigate the association between MLR with CCB and its subtypes. Results During a median follow-up of 10.4 years, 3222 incident CCB cases were observed. A U-shaped association was observed between MLR and CCB risk (Pnonlinearity <0.05). After multivariate adjustment, individuals in the highest MLR quartile had a hazard ratio (HR) of 1.212 (95% CI: 1.097-1.340; Q4 vs Q2), while those in the lowest MLR quartile had an HR of 1.106 (95% CI: 1.000-1.224; Q1 vs Q2). Sensitivity and subgroup analyses yielded consistent results. The U-shaped association persisted for atrioventricular block (AVB) in subtype analyses. Conclusion MLR was significantly associated with an increased risk of new-onset CCB. Assessing MLR may have clinical relevance for predicting CCB risk, providing valuable insights for preventive strategies and patient management. Pre-Registered Clinical Trial Number The pre-registered clinical trial number is ChiCTR-TNC-11001489.
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Affiliation(s)
- Man Li
- Department of Emergency, The Affiliated Hospital of North China University of Science and Technology, Tangshan, People’s Republic of China
- Graduate School, North China University of Science and Technology, Tangshan, People’s Republic of China
| | - Xintao Li
- Department of Cardiology, The First Hospital of Soochow University, Jiangsu, People’s Republic of China
| | - Hongwei Gao
- Department of Emergency, Caofeidian District hospital of Tangshan City, Tangshan, People’s Republic of China
| | - Peng Li
- Department of Emergency, The Affiliated Hospital of North China University of Science and Technology, Tangshan, People’s Republic of China
| | - Li Zhang
- Department of Emergency, The Affiliated Hospital of North China University of Science and Technology, Tangshan, People’s Republic of China
| | - Xiaoling Zhang
- Department of Emergency, The Affiliated Hospital of North China University of Science and Technology, Tangshan, People’s Republic of China
| | - Peipei Liu
- School of Public Health, North China University of Science and Technology, Tangshan, People’s Republic of China
| | - Xuemei Yang
- Graduate School, North China University of Science and Technology, Tangshan, People’s Republic of China
| | - Lili Wu
- Department of Cardiology, Shanghai Songjiang District Central Hospital, Shanghai, People’s Republic of China
| | - Jiangwei Zeng
- Graduate School, North China University of Science and Technology, Tangshan, People’s Republic of China
| | - Shouling Wu
- Department of Cardiology, Kailuan Hospital, Tangshan, People’s Republic of China
| | - Lixia Sun
- Department of Emergency, The Affiliated Hospital of North China University of Science and Technology, Tangshan, People’s Republic of China
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Yu Q, Luo H, Hu S, Sun D, Nie Q, Yan J. The survival analysis of rifampicin/multidrug-resistant tuberculosis patients based on the levels of inflammatory biomarkers: a retrospective cohort study. Front Cell Infect Microbiol 2023; 13:1118424. [PMID: 37197206 PMCID: PMC10183571 DOI: 10.3389/fcimb.2023.1118424] [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: 12/07/2022] [Accepted: 04/07/2023] [Indexed: 05/19/2023] Open
Abstract
Purpose The development of tuberculosis and inflammatory status are closely related. The aim of this study was to investigate the prognostic value of inflammatory biomarkers in patients with rifampicin/multidrug-resistant tuberculosis (RR/MDR-TB). Patients and methods This study recruited 504 patients with RR/MDR-TB from Wuhan Jinyintan Hospital. A total of 348 RR/MDR patients from January 2017 to December 2019 were defined as training set, the rest of patients as validation set. The patients were divided into three-risk degrees according to the levels of inflammatory biomarkers (median, 85th percentile). Kaplan-Meier curve and log-rank test were used to assess survival differences among the groups. Cox proportion risk regression was used to identify risk factors for RR/MDR-TB mortality. Results In training set, cox proportion risk regression analysis showed that high age (≥60 years) [OR (95%CI):1.053(1.03188-1.077)], smoking [OR (95%CI):2.206(1.191-4.085)], and bronchiectasia [OR (95%CI):2.867(1.548-5.311)] were prognostic factors for RR/MDR-TB patients. In addition, lower survival rates were observed in high CAR group [OR (95%CI):1.464(1.275-1.681)], high CPR group[OR (95%CI):1.268(1.101-1.459)], high CLR group[OR (95%CI):1.004(1.002-1.005)], high NLR group[OR (95%CI):1.103(1.069-1.139)], high PLR group[OR (95%CI):1.003(1.002-1.004)], and high MLR group[OR (95%CI):3.471(2.188-5.508)].Furthermore, AUCs of age, smoking, bronchiectasia, CAR, CPR, CLR, NLR, PLR, and MLR for predicting mortality in RR/MDR-TB patients were 0.697(95%CI:0.618-0.775), 0.603(95%CI:0.512-0.695), 0.629(95%CI:0.538-0.721), 0.748(95%CI:0.675-0.821, P<0.05), 0.754(95%CI:0.683-0.824, P<0.05), 0.759(95%CI:0.689-0.828, P<0.05), 0.789(95%CI:0.731-0.846, P<0.05), 0.740(95%CI:0.669-0.812, P<0.05), and 0.752(95%CI:0.685-0.819, P<0.05), respectively. Importantly, the AUC of predicting mortality of combination of six inflammatory biomarkers [0.823 (95%CI:0.769-0.876)] is higher than any single inflammatory biomarkers. Additionally, the similar results are also obtained in the validation set. Conclusion Inflammatory biomarkers could predict the survival status of RR/MDR-TB patients. Therefore, more attention should be paid to the level of inflammatory biomarkers in clinical practice.
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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, Wuhan, Hubei, China
| | - Hong Luo
- Department of Respiratory and Critical Care Medicine, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Shengling Hu
- Department of Infectious Diseases, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Dan Sun
- Department of Interventional Therapy, Wuhan Pulmonary Hospital, Wuhan, Hubei, China
| | - Qi Nie
- Department of MDR/RR-TB, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China
- *Correspondence: Qi Nie, ; Jisong Yan,
| | - Jisong Yan
- Department of Respiratory and Critical Care Medicine, Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China
- *Correspondence: Qi Nie, ; Jisong Yan,
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Wu S, Wei Y, Li H, Zhou C, Chen T, Zhu J, Liu L, Wu S, Ma F, Ye Z, Deng G, Yao Y, Fan B, Liao S, Huang S, Sun X, Chen L, Guo H, Chen W, Zhan X, Liu C. A Predictive Clinical-Radiomics Nomogram for Differentiating Tuberculous Spondylitis from Pyogenic Spondylitis Using CT and Clinical Risk Factors. Infect Drug Resist 2022; 15:7327-7338. [PMID: 36536861 PMCID: PMC9758984 DOI: 10.2147/idr.s388868] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 12/02/2022] [Indexed: 10/30/2023] Open
Abstract
OBJECTIVE The study aimed to develop and validate a nomogram model with clinical risk factors and radiomic features for differentiating tuberculous spondylitis (TS) from pyogenic spondylitis (PS). METHODS A total of 254 patients with TS (n = 141) or PS (n = 113) were randomly divided into training (n = 180) and validation (n = 74) groups. In addition, 43 patients (TS = 22 and PS = 21) were collected to construct a test cohort. t-test analysis, de-redundancy analysis, and minimum absolute shrinkage and selection operator (lasso) algorithm were utilized on the training set to obtain the optimal radiomics features from computed tomography (CT) for constructing the radiomics model and determine the radiomics score (Rad-score). Eight clinical risk predictors were identified to develop the clinical model. Combined with clinical risk predictors and Rad-scores, a nomogram model was constructed using multivariate logistic regression analysis. RESULTS A total of 1781 features were extracted, and 12 optimal radiomic features were utilized to construct the radiomic model and determine the Rad-score. The combined clinical radiomics model revealed good discrimination performance in both the training cohort and the validation cohort (AUC = 0.891 and 0.830) and was superior to the clinical (AUC = 0.807 and 0.785) and radiomics (AUC = 0.796 and 0.811) models. The calibration curve and DCA also depicted that the nomogram had better clinical efficacy. The discriminative performance of the model is well validated in the test cohort (AUC=0.877). CONCLUSION The clinical radiomic nomogram could serve as a promising predictive tool for differentiating TS from PS, which could be helpful for clinical decision-making.
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Affiliation(s)
- Shaofeng Wu
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Yating Wei
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Hao Li
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Chenxing Zhou
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Tianyou Chen
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Jichong Zhu
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Lu Liu
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Siling Wu
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Fengzhi Ma
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Zhen Ye
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Guobing Deng
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Yuanlin Yao
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Binguang Fan
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Shian Liao
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Shengsheng Huang
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Xuhua Sun
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Liyi Chen
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Hao Guo
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Wuhua Chen
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Xinli Zhan
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
| | - Chong Liu
- Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
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Monocyte-to-lymphocyte ratio is significantly associated with positive QuantiFERON-TB Gold-In-Tube and adult survival: an observational study. Sci Rep 2022; 12:20406. [PMID: 36437261 PMCID: PMC9701699 DOI: 10.1038/s41598-022-24376-2] [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: 09/13/2022] [Accepted: 11/14/2022] [Indexed: 11/28/2022] Open
Abstract
This study aimed to find significant factors associated with tuberculosis (TB) infection and disease development. The participants were from National Health and Nutrition Examination Survey (NHANES) and National Death Index (NDI). The tuberculosis infection was defined as a positive QuantiFERON-TB Gold-In-Tube (QFT-GIT). The Least Absolute Shrinkage and Selection Operator (LASSO) model was used to screen variables associated with QFT-GIT among 23 laboratory measures. Then the logistic regression analyses were performed to assess the independent factors, followed by a comprehensive nomogram model construction. Receiver operating characteristic (ROC) and Decision Curve (DCA) analyses were used to assess the performance of comprehensive model on QFT-GIT result and death risk. Of 5256 individuals included, 521 individuals had positive QFT-GIT. LASSO analysis indicated that 11 variables were associated with QFT-GIT result, and logistic regression analyses further found sodium and monocyte-to-lymphocyte ratio (MLR) were independent factors. After adjusting for potential confounders, the correlation of sodium and MLR with QFT-GIT result was still observed. The comprehensive model based on sodium, MLR, and important clinical characteristics can predict 0.8 probability of positive QFT-GIT and achieve more clinical net benefit. ROC analysis by training and validation sets showed the favorable prediction performance. Comprehensive model also presented favorable performance in evaluating the death risk of individuals with positive QFT-GIT. We also found MLR rather than sodium was independently related to the death risk. Both MLR itself and comprehensive model were all significantly related to the positive QFT-GIT and death risk, which might participate in the initiation and progression of tuberculosis infection.
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Liu QX, Tang DY, Xiang X, He JQ. Associations between nutritional and immune status and clinicopathologic factors in patients with tuberculosis: A comprehensive analysis. Front Cell Infect Microbiol 2022; 12:1013751. [PMID: 36506012 PMCID: PMC9731357 DOI: 10.3389/fcimb.2022.1013751] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Accepted: 10/31/2022] [Indexed: 11/25/2022] Open
Abstract
Objective This study was designed to assess and analyze nutritional status (NS) and immune status in patients with tuberculosis. Methods A retrospective analysis was conducted on 93 TB patients hospitalized in the tuberculosis ward of the West China Hospital of Sichuan University. Subgroup comparisons were made according to age (<65 years and ≥65 years), nutritional risk score 2002 (NRS 2002 <3 and ≥3), tuberculosis location [pulmonary tuberculosis and extrapulmonary tuberculosis (including pulmonary tuberculosis complicated with extrapulmonary tuberculosis)], and prognostic nutrition index (PNI) (<45 vs ≥45). Results Significantly increased weight loss was associated with extrapulmonary tuberculosis (P =0.0010). Serum albumin (P =0.0214), total lymphocyte count (P = 0.0009) and PNI (P = 0.0033) were significantly decreased in older patients. Neutrophils/lymphocytes (NLR) (P =0.0002), monocytes/lymphocytes (MLR) (P < 0.0001), and platelets/lymphocytes (PLR) (P =0.0107) were higher. According to NRS 2002, higher nutritional risk was associated with lower body weight and body mass index (BMI) (P < 0.0001), higher weight loss (P = 0.0012), longer duration of hospitalization (P =0.0100), lower serum albumin level and hemoglobin concentration (P <0.01), lower creatinine level, and lower PNI (P < 0.01). 0.0001), lower total lymphocyte count (P = 0.0004), higher neutrophil and monocyte counts (P <0.05), and higher NLR (P = 0.0002), MLR (P = 0.0006), and PLR (P = 0.0156). Lower PNI was associated with lower body weight (P = 0.0001) and BMI (P =0.0074), lower total protein, albumin, and hemoglobin concentrations (P < 0.0001), and lower total lymphocyte count (P < 0.0001) and creatinine levels (P = 0.0336), higher age (P =0.0002) and NRS 2002 score, P < 0.0001), longer hos-pital stay (P = 0.0003), higher neutrophil count (P = 0.0042), and NLR, MLR, and PLR (P <0.0001) were significantly correlated. In multivariate logistic regression analysis, weight loss (OR: 0.209, 95% CI: 0.060-0.722; p =0.013) was significantly associated with higher nutritional risk (NRS 2002≥3). In multiple linear regression analysis, the NRS 2002 score was higher (B=2.018; p =0.023), and extrapulmonary tuberculosis (B=-6.205; p =0.007) was linked with a longer duration of hos-pitalization. Conclusions Older tuberculosis patients are at nutritional risk, and older patients (≥65 years old) need to pay attention to nutritional monitoring and intervention. Older TB patients and those at risk of malnutrition have increased immune ratio and impaired immune function. Management of TB patients using basic diagnostic tools to assess nutritional and immune status and calculate PNI and immunological indexes (NLR, MLR, PLR) to improve treatment outcomes.
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Affiliation(s)
- Quan-Xian Liu
- Department of Respiratory and Critical Care Medicine, West China Hospital of Sichuan University, Chengdu, China
- Department of Tuberculosis, Affiliated Hospital of Zunyi Medical University, Zunyi, China
| | - Dao-Yan Tang
- Department of Respiratory and Critical Care Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Xi Xiang
- Department of Respiratory and Critical Care Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Jian-Qing He
- Department of Respiratory and Critical Care Medicine, West China Hospital of Sichuan University, Chengdu, China
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Zeng J, Chen M, Feng Q, Wan H, Wang J, Yang F, Cao H. The Platelet-to-Lymphocyte Ratio Predicts Diabetic Retinopathy in Type 2 Diabetes Mellitus. Diabetes Metab Syndr Obes 2022; 15:3617-3626. [PMID: 36444389 PMCID: PMC9700435 DOI: 10.2147/dmso.s378284] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 11/15/2022] [Indexed: 11/22/2022] Open
Abstract
INTRODUCTION As a severe and specific neurovascular complication of type 2 diabetes mellitus (T2DM), diabetic retinopathy (DR) remains the leading cause of vision loss and preventable blindness in adults aged 20 to 74. The pathogenesis of DR is not completely understood, however, studies indicate that chronic inflammation plays a significant role. Emerging evidence suggests that the neutrophil-to-lymphocyte ratio (NLR), the platelet-to-lymphocyte ratio (PLR), and the monocyte-to-lymphocyte ratio (MLR) are novel potential inflammatory response markers. The purpose of this study was to investigate the relationships between the NLR, PLR, MLR, and DR. PATIENTS AND METHODS 290 patients who had been diagnosed with T2DM participated in the study. Patients were categorized into three groups: 142 control subjects with T2DM, 124 subjects with nonproliferative diabetic retinopathy (NPDR), and 24 patients with proliferative diabetic retinopathy (PDR). Characteristics, laboratory data, as well as NLR, PLR and MLR levels of the study groups were compared. RESULTS In patients with DR, the median NLR, PLR, and MLR were significantly higher than in patients without DR (p = 0.012, p < 0.001, and p = 0.043, respectively). In the post hoc analysis, there was no correlation between the severity of retinopathy and the increase in NLR or PLR. Multiple logistic regression revealed that the PLR was an independent risk factor for DR (odds ratio [OR]: 1.020, 95% confidence interval [CI]: 1.010-1.029 p = 0.026). Based on the receiver operating characteristic (ROC) curve, the cutoff value of PLR as an indicator for diagnosing DR was estimated to be 129.65, with a sensitivity and specificity of 53.4% and 76.1%, respectively, and an area under the curve of 0.668 (95% CI: 0.605-0.730, p < 0.001). CONCLUSION Our findings suggest that PLR may be an independent risk factor for evaluating DR in type 2 diabetes patients.
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Affiliation(s)
- Jing Zeng
- Geriatric Diseases Institute of Chengdu/Cancer Prevention and Treatment Institute of Chengdu, Department of Endocrinology and Metabolism, Chengdu Fifth People’s Hospital (The Second Clinical Medical College, Affiliated Fifth People’s Hospital of Chengdu University of Traditional Chinese Medicine), Chengdu, People’s Republic of China
| | - Min Chen
- Geriatric Diseases Institute of Chengdu/Cancer Prevention and Treatment Institute of Chengdu, Department of Endocrinology and Metabolism, Chengdu Fifth People’s Hospital (The Second Clinical Medical College, Affiliated Fifth People’s Hospital of Chengdu University of Traditional Chinese Medicine), Chengdu, People’s Republic of China
| | - Qiu Feng
- Geriatric Diseases Institute of Chengdu/Cancer Prevention and Treatment Institute of Chengdu, Department of Endocrinology and Metabolism, Chengdu Fifth People’s Hospital (The Second Clinical Medical College, Affiliated Fifth People’s Hospital of Chengdu University of Traditional Chinese Medicine), Chengdu, People’s Republic of China
| | - Haiyan Wan
- Geriatric Diseases Institute of Chengdu/Cancer Prevention and Treatment Institute of Chengdu, Department of Endocrinology and Metabolism, Chengdu Fifth People’s Hospital (The Second Clinical Medical College, Affiliated Fifth People’s Hospital of Chengdu University of Traditional Chinese Medicine), Chengdu, People’s Republic of China
| | - Jianbo Wang
- Geriatric Diseases Institute of Chengdu/Cancer Prevention and Treatment Institute of Chengdu, Department of Medical Record, Chengdu Fifth People’s Hospital (The Second Clinical Medical College, Affiliated Fifth People’s Hospital of Chengdu University of Traditional Chinese Medicine), Chengdu, People’s Republic of China
| | - Fan Yang
- Geriatric Diseases Institute of Chengdu/Cancer Prevention and Treatment Institute of Chengdu, Department of Endocrinology and Metabolism, Chengdu Fifth People’s Hospital (The Second Clinical Medical College, Affiliated Fifth People’s Hospital of Chengdu University of Traditional Chinese Medicine), Chengdu, People’s Republic of China
| | - Hongyi Cao
- Geriatric Diseases Institute of Chengdu/Cancer Prevention and Treatment Institute of Chengdu, Department of Endocrinology and Metabolism, Chengdu Fifth People’s Hospital (The Second Clinical Medical College, Affiliated Fifth People’s Hospital of Chengdu University of Traditional Chinese Medicine), Chengdu, People’s Republic of China
- Correspondence: Hongyi Cao; Fan Yang, Geriatric Diseases Institute of Chengdu/Cancer Prevention and Treatment Institute of Chengdu, Department of Endocrinology and Metabolism, Chengdu Fifth People’s Hospital (The Second Clinical Medical College, Affiliated Fifth People’s Hospital of Chengdu University of Traditional Chinese Medicine), No. 33, Mashi Street, Wenjiang District, Chengdu, Sichuan, 611130, People’s Republic of China, Tel +86 13730683979, Fax +86 028-82713097, Email ;
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