Factors associated with negative T-SPOT.TB results among smear-negative tuberculosis patients in China

Kang, Wanli; Wu, Meiying; Yang, Kunyun; Ertai, A; Wu, Shucai; Geng, Shujun; Li, Zhihui; Li, Mingwu; Tang, Shenjie

doi:10.1038/s41598-018-22495-3

Cited by 5 publications

(3 citation statements)

References 16 publications

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“…Clinical characteristic analysis showed significantly decreased albumin and serum creatinine, and increased erythrocyte sedimentation rate (ESR) for the TB patients (Table 2 ). Here, the albumin of SPPT patients was significantly lower than that of SNPT patients (SPPT: 35.30 g/L; SNPT: 39.20 g/L; adjusted p = 0.002), indicating more serious chronic inflammation/malnutrition for the SPPT patients [ 28 , 29 ]; the serum creatinine was significantly lower in TB patients compared with controls, but showed no difference between SPPT and SNPT patients, suggesting renal injury induced by tuberculous drugs; the ESR of SPPT patients (67.50 mm/h) was significantly higher than that of SNPT patients (43.00 mm/h), and ESR had been reported to identify active tuberculosis and differentiate pulmonary tuberculosis from bacterial community-acquired pneumonia [ 30 ].…”

Section: Resultsmentioning

confidence: 99%

Combining metabolome and clinical indicators with machine learning provides some promising diagnostic markers to precisely detect smear-positive/negative pulmonary tuberculosis

Wang

et al. 2022

BMC Infect Dis

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Background Tuberculosis (TB) had been the leading lethal infectious disease worldwide for a long time (2014–2019) until the COVID-19 global pandemic, and it is still one of the top 10 death causes worldwide. One important reason why there are so many TB patients and death cases in the world is because of the difficulties in precise diagnosis of TB using common detection methods, especially for some smear-negative pulmonary tuberculosis (SNPT) cases. The rapid development of metabolome and machine learning offers a great opportunity for precision diagnosis of TB. However, the metabolite biomarkers for the precision diagnosis of smear-positive and smear-negative pulmonary tuberculosis (SPPT/SNPT) remain to be uncovered. In this study, we combined metabolomics and clinical indicators with machine learning to screen out newly diagnostic biomarkers for the precise identification of SPPT and SNPT patients. Methods Untargeted plasma metabolomic profiling was performed for 27 SPPT patients, 37 SNPT patients and controls. The orthogonal partial least squares-discriminant analysis (OPLS-DA) was then conducted to screen differential metabolites among the three groups. Metabolite enriched pathways, random forest (RF), support vector machines (SVM) and multilayer perceptron neural network (MLP) were performed using Metaboanalyst 5.0, “caret” R package, “e1071” R package and “Tensorflow” Python package, respectively. Results Metabolomic analysis revealed significant enrichment of fatty acid and amino acid metabolites in the plasma of SPPT and SNPT patients, where SPPT samples showed a more serious dysfunction in fatty acid and amino acid metabolisms. Further RF analysis revealed four optimized diagnostic biomarker combinations including ten features (two lipid/lipid-like molecules and seven organic acids/derivatives, and one clinical indicator) for the identification of SPPT, SNPT patients and controls with high accuracy (83–93%), which were further verified by SVM and MLP. Among them, MLP displayed the best classification performance on simultaneously precise identification of the three groups (94.74%), suggesting the advantage of MLP over RF/SVM to some extent. Conclusions Our findings reveal plasma metabolomic characteristics of SPPT and SNPT patients, provide some novel promising diagnostic markers for precision diagnosis of various types of TB, and show the potential of machine learning in screening out biomarkers from big data.

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Section: Resultsmentioning

confidence: 99%

Combining metabolome and clinical indicators with machine learning provides some promising diagnostic markers to precisely detect smear-positive/negative pulmonary tuberculosis

Wang

et al. 2022

BMC Infect Dis

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“…The T-SPOT.TB assay has been widely used in China in recent years as a diagnostic tool for TB infection. The T-SPOT.TB assay shows high sensitivity and scores over bacterial cultures to diagnose smear-negative TB [12]. Prompt and definitive diagnosis of abdominal TB requires a coordinated approach involving laboratory tests (notably the T-SPOT.TB assay), radiological examination, and invasive procedures for optimal decision making and management.…”

Section: Discussionmentioning

confidence: 99%

Isolated gastric varices secondary to abdominal tuberculosis mimicking lymphoma: a case report

Gong

Rong

et al. 2019

BMC Gastroenterol

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Background Abdominal tuberculosis (TB) rarely presents with abdominal masses and rarely causes isolated gastric varices. Case presentation We report a case of isolated gastric varices secondary to abdominal TB mimicking lymphoma. A 42-year-old woman without any history of liver disease presented with melena and mild abdominal pain. Upon admission to the hospital, laboratory investigations revealed a hemoglobin level of 76 g/L. Gastroduodenoscopic examination showed isolated gastric fundal varices with red color signs. Abdominal contrast-enhanced computed tomography (CECT) revealed non-enhanced masses of soft-tissue density in the lesser omental and the retropancreatic areas, multiple para-aortic lymph nodes, and multiple small hypodense splenic lesions. Positron emission tomography-CT showed hypermetabolic [F-18]2-fluoro-2-deoxyglucose activity involving multiple regional lymph nodes and the bone marrow, suggestive of lymphoma. Bone marrow biopsy revealed no abnormality. Histopathological examination of a CT-guided biopsy specimen showed granulomatous inflammation with necrosis and microorganisms that stained positive with acid-fast stains. Abdominal CECT showed a decrease in the size of the lesser omental and peripancreatic masses, as well as the para-aortic lymph nodes after 4-month anti-TB therapy. Conclusions TB should be considered among the differential diagnoses in patients with abdominal masses, isolated gastric varices, and regional lymphadenopathy. Prompt and definitive diagnosis of abdominal TB requires a coordinated approach involving laboratory tests, radiological examination, and invasive procedures for optimal decision making and management.

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“…As the serum albumin levels decreased the chance of death increased especially in HIV patients with tuberculosis [15] . A study done by Svenson et al in the year 2016 at Sweden stated that in multi drugresistant tuberculosis (MDR-TB) the albumin concentration and body weight are altered; this potential change will affect the drug disposition in long treatment period [16] . A study done by Matos et al suggest that malnutrition is frequently seen in patients with tuberculosis.…”

Section: Serum Albumin Levels In Tuberculosismentioning

confidence: 99%

Prevalence of hypoalbuminemia among tuberculosis patients receiving anti tuberculosis therapy: A cross sectional study

Ganesan¹,

Gopinath²

2019

Int. J. Adv. Biochem. Res.

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Background: Tuberculosis (TB) is one of the most common disease seen in overcrowding population. The high prevalence of tuberculosis in developing countries is due to various factors like poverty, malnutrition, overcrowding and poor socioeconomic status. It is having also been recorded that malnutrition is one of the major causes for the incidence of this disease in healthy individuals. Malnutrition can lead to poor prognosis of the Anti-tuberculosis therapy (ATT). Hence, Prevalence of hypoalbuminemia is of major concern in determining the prognosis of the disease. Objective: To estimate the serum total protein, albumin and globulin of patients with TB and compare albumin levels with Pulmonary Tuberculosis (PTB) patients and Extra Pulmonary Tuberculosis (EPTB) patients. Also, to correlate albumin levels with Body Mass Index (BMI) and Waist Hip Ratio (WHR) of the patients. Method: This cross-sectional study was conducted in 100 patients in two groups namely PTB and EPTB. The albumin levels were noted along with the BMI and WHR of the patients in both groups of TB. Results: The average age of the patients was 38.9 years. There was 65% of patients with PTB and 35% of patients with EPTB. The mean albumin, BMI and WHR of the patients were 3.2 ± 0.6, 19.7 ± 3.7 and 0.96 ± 0.01 respectively. The albumin levels of PTB group was 3.1 ± 0.6 and EPTB was 3.4 ± 0.6. the WHR of PTB patients was 0.99 ± 0.12 and EPTB was 0.90 ± 0.15. Albumin and WHR showed statistical significance with p value 0.007 and 0.003 respectively. Conclusion:Hypoalbuminemia in TB patients correlated with the BMI and with WHR. Sputum positivity was independent of the albumin levels. The results highlighted the prevalence of low albumin levels and malnutrition in patients with TB, especially PTB.

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Factors associated with negative T-SPOT.TB results among smear-negative tuberculosis patients in China

Cited by 5 publications

References 16 publications

Combining metabolome and clinical indicators with machine learning provides some promising diagnostic markers to precisely detect smear-positive/negative pulmonary tuberculosis

Combining metabolome and clinical indicators with machine learning provides some promising diagnostic markers to precisely detect smear-positive/negative pulmonary tuberculosis

Isolated gastric varices secondary to abdominal tuberculosis mimicking lymphoma: a case report

Prevalence of hypoalbuminemia among tuberculosis patients receiving anti tuberculosis therapy: A cross sectional study

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