A routine blood test-associated predictive model and application for tuberculosis diagnosis: a retrospective cohort study from northwest China

Expression profiling of TRIM gene family reveals potential diagnostic biomarkers for rifampicin-resistant tuberculosis

The epidemic of pulmonary tuberculosis (TB), especially rifampin-resistant tuberculosis (RR-TB) presents a major challenge for TB control today. However, there is a lack of reliable and specific biomarkers for the early diagnosis of RR-TB. We utilized reverse transcription-quantitative polymerase chain reaction (RT-qPCR) to profile the transcript levels of 72 tripartite motif (TRIM) genes from a discovery cohort of 10 drug-sensitive tuberculosis (DS-TB) patients, 10 RR-TB patients, and 10 healthy controls (HCs). A total of 35 differentially expressed genes (DEGs) were screened out, all of which were down-regulated. The bio functions and pathways of these DEGs were enriched in protein ubiquitination, regulation of the viral process, Interferon signaling, and innate immune response, etc. A protein-protein interaction network (PPI) was constructed and analyzed using STRING and Cytoscape. Twelve TRIM genes were identified as hub genes, and seven (TRIM1, 9, 21, 32, 33, 56, 66) of them were verified by RT-qPCR in a validation cohort of 95 subjects. Moreover, we established the RR-TB decision tree models based on the 7 biomarkers. The receiver operating characteristic (ROC) analyses showed that the models exhibited the areas under the curve (AUC) values of 0.878 and 0.868 in discriminating RR-TB from HCs and DS-TB, respectively. Our study proposes potential biomarkers for RR-TB diagnosis, and also provides a new experimental basis to understand the pathogenesis of RR-TB.

Evaluation of prognostic significance of hematological profiles after the intensive phase treatment in pulmonary tuberculosis patients from Romania

We evaluated in this cohort study the predictive ability of 23 peripheral blood parameters and ratios for treatment outcomes after the 2-month intensive phase in patients with PTB. In 63 patients out of 90 that turned culture negative, a significant decrease in white blood cell count, neutrophils, monocyte, hemoglobin, platelet, plateletcrit, erythrocyte sedimentation rate, MLR, NLR, PLR and SII values after anti-TB therapy compared to pretreatment was observed (p <0.001). Logistic regression analysis generated a model of predictors consisting of nine covariates. Spearman’s correlation analysis revealed significant positive correlations between NLR with NEU (r = 0.79, p<0.01), SII with NEU (r = 0.846, p<0.01), PLT with SII (r = 0.831, p<0.01), PLT with PCT (r = 0.71, p<0.01) and MPV with P-LCR (r = 0,897, p<0.01) in 63 patients out of 90 that turned culture negative after 2 months of treatment. ROC curve analysis indicated that all areas under the curve (AUC) revealed no statistically significant results, except lymphocyte for culture conversion. In summary, here we observed a set of hematological parameters that declined significantly as the disease was treated in patients that turned culture negative. Despite some limitations, our findings are useful for further studies aiming to identify hematological profiles that could predict the treatment outcome.

A valuable computed tomography-based new diagnostic tool for severe chest lesions in active pulmonary tuberculosis: combined application of influencing factors

The objective of the present investigation was to explore the influencing factors and value of computed tomography (CT) for diagnosing severe chest lesions in active pulmonary tuberculosis (APTB). This retrospective investigation included 463 patients diagnosed with APTB. Relevant clinical features were collected. Patients were assigned to mild/moderate group or advanced group depending on the lesion severity on chest CT, severe chest CT lesion refers to the moderately dense or less diffuse lesion that exceeds the total volume of one lung, or the dense fusion lesion greater than one third of the volume of one lung, or the lesion with cavity diameter ≥4 cm. Independent risk factors for severe lesions were determined by univariate and multivariate logistic regression analyses, and the diagnostic efficiency of the risk factors was assessed by receiver operating characteristic curve (ROC). Chest CT demonstrated that there were 285 (61.56%) cases with severe lesions; multivariate Logistic regression analysis showed dust exposure [odds ratio (OR) = 4.108, 95% confidence interval (CI) 2.416–6.986], patient classification (OR = 1.792, 95% CI 1.067–3.012), age (OR = 1.018, 95% CI 1.005–1.030), and albumin-globulin ratio (OR = 0.179, 95% CI 0.084–0.383) to be independently correlated with severe lesions on chest CT. ROC curve analysis showed the cutoff values of age, albumin-globulin ratio and combined score to be 39 years, 0.918 and −0.085, respectively. The predictive value of combined score area under the curve 0.753 (95% CI 0.708–0.798) was higher than that of any single factor. The combined score of these four factors further improved the predictive efficacy.