Screening performance of C-reactive protein for active pulmonary tuberculosis in HIV-positive patients: A systematic review with a meta-analysis

Evaluation of Systemic Inflammation Before and After Standard Anti-tuberculosis Treatment in Patients With Active Pulmonary Tuberculosis and Diabetes Mellitus

Background Diabetes mellitus (DM) is a common comorbidity of active pulmonary tuberculosis (APTB) that increases the risk of treatment failure during anti-tuberculosis chemotherapy. Evaluating systemic inflammatory response could help determine differences in response to treatment between APTB patients and those with APTB and DM. Methodology To explore changes in systemic inflammation, measured by a set of inflammatory mediators in subjects with APTB and TBDM before and after six months of anti-tuberculosis chemotherapy, 30 APTB and nine TBDM subjects underwent cytokine testing, including interleukin (IL)-6, IL-8, IL-10, interferon-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-α), and transforming growth factor-beta 1 (TGF-β1) by enzyme-linked immunosorbent assay, C-reactive protein by nephelometry, and sialic acid by colorimetric assay at baseline and following six months of standard anti-tuberculosis treatment. Sputum smear microscopy or molecular biology (Xpert MTB/RIF) was used for diagnosis, and sputum smear microscopy was performed monthly during the treatment of the patient with pulmonary tuberculosis to evaluate his evolution. Principal component analysis examined changes in the inflammatory status. Results Both groups showed negative sputum smear microscopy in the sixth month after starting anti-tuberculosis chemotherapy. TGF-β1 was found to be significantly higher in subjects with TBDM before treatment compared to APTB patients (p<0.001), and systemic inflammation continued only in TBDM subjects after treatment (accumulation and persistence of inflammatory mediators like IL-6, IL-8, IL-10, IFN-γ, TNF-α, TGF-β1, C-reactive protein, and sialic acid in blood). On the other hand, the mediators IFN-γ, C-reactive protein, and total sialic acid were found to be most influential in distinguishing pre- and post-treatment inflammatory response in subjects with APTB without DM. Conclusions Inflammatory mediators analyzed in combination, including IFN-γ, CRP, and total sialic acid, may be useful in evaluating the systemic inflammatory response in subjects with APTB and TBDM before and after anti-tuberculosis treatment. Determining these mediators revealed persistent systemic inflammation in TBDM subjects after six months of standard tuberculosis treatment, despite negative sputum smear microscopy results and good glycemic control. This suggests a need for inflammation-modulating therapies during tuberculosis control. Finally, monitoring sputum smear microscopy results alongside the determination of proposed inflammatory mediators (IFN-γ, CRP, and total sialic acid) are effective in evaluating the response to anti-tuberculosis treatment in APTB subjects without DM, warranting further investigation.

Convolutional Neural Network Model for Segmentation and Classification of Clear Cell Renal Cell Carcinoma Based on Multiphase CT Images

(1) Background: Computed tomography (CT) imaging challenges in diagnosing renal cell carcinoma (RCC) include distinguishing malignant from benign tissues and determining the likely subtype. The goal is to show the algorithm's ability to improve renal cell carcinoma identification and treatment, improving patient outcomes. (2) Methods: This study uses the European Deep-Health toolkit's Convolutional Neural Network with ECVL, (European Computer Vision Library), and EDDL, (European Distributed Deep Learning Library). Image segmentation utilized U-net architecture and classification with resnet101. The model's clinical efficiency was assessed utilizing kidney, tumor, Dice score, and renal cell carcinoma categorization quality. (3) Results: The raw dataset contains 457 healthy right kidneys, 456 healthy left kidneys, 76 pathological right kidneys, and 84 pathological left kidneys. Preparing raw data for analysis was crucial to algorithm implementation. Kidney segmentation performance was 0.84, and tumor segmentation mean Dice score was 0.675 for the suggested model. Renal cell carcinoma classification was 0.885 accurate. (4) Conclusion and key findings: The present study focused on analyzing data from both healthy patients and diseased renal patients, with a particular emphasis on data processing. The method achieved a kidney segmentation accuracy of 0.84 and mean Dice scores of 0.675 for tumor segmentation. The system performed well in classifying renal cell carcinoma, achieving an accuracy of 0.885, results which indicates that the technique has the potential to improve the diagnosis of kidney pathology.

From simple to complex: Protein-based biomarker discovery in tuberculosis

Tuberculosis (TB) is a deadly infectious disease that affects millions of people globally. TB proteomics signature discovery has been a rapidly growing area of research that aims to identify protein biomarkers for the early detection, diagnosis, and treatment monitoring of TB. In this review, we have highlighted recent advances in this field and how it is moving from the study of single proteins to high-throughput profiling and from only using proteomics to include additional types of data in multi-omics studies. We have further covered the different sample types and experimental technologies used in TB proteomics signature discovery, focusing on studies of HIV-negative adults. The published signatures were defined as either coming from hypothesis-based protein targeting or from unbiased discovery approaches. The methodological approaches influenced the type of proteins identified and were associated with the circulating protein abundance. However, both approaches largely identified proteins involved in similar biological pathways, including acute-phase responses and T-helper type 1 and type 17 responses. By analysing the frequency of proteins in the different signatures, we could also highlight potential robust biomarker candidates. Finally, we discuss the potential value of integration of multi-omics data and the importance of control cohorts and signature validation.

Construction and Validation of a Diagnostic Scoring System for Predicting Active Pulmonary Tuberculosis in Patients with Positive T-SPOT Based on Indicators Associated with Coagulation and Inflammation: A Retrospective Cross-Sectional Study

Introduction

Tuberculosis (TB) is a life-threatening single infectious disease, which remains a major global public health concern. This study was to establish and validate a clinically practical diagnostic scoring system for predicting active pulmonary tuberculosis (APTB) in patients with positive tuberculosis T cell spot test [T-SPOT] using indicators associated with coagulation and inflammation.

Methods

A single-center retrospective cross-sectional study was performed to include patients with positive T-SOPT registered and hospitalized at Wuhan Jinyintan Hospital between January 2017 and December 2019. All patients were separated into the active pulmonary tuberculosis (APTB) group and the inactive pulmonary tuberculosis (IPTB) group, according to the diagnostic criteria from China's Expert Consensus for APTB and IPTB. Subsequently, the patients were randomized into a training set and a validation set at a ratio of 2:1. Indicators associated with coagulation and inflammation, including prothrombin time activity (PTA), activated partial thromboplastin time (APTT), thrombin time (TT), fibrinogen concentration (Fbg-C), C-reactive protein/albumin ratio (CAR), C-reactive protein/prealbumin ratio (CPR), neutrophils count/lymphocyte count ratio (NLR), platelet count/lymphocyte count ratio (PLR), monocyte count/lymphocyte count ratio (MLR), and erythrocyte sedimentation rate (ESR) were obtained from electronic medical record system (EMRS). Stepwise logistic regression was performed in the training set to build a diagnostic model for predicting APTB, which was transformed into an easily applicable scoring system via nomogram. Receiver operating characteristic (ROC) analysis, calibration curve (CC), and decision curve analysis (DCA) were conducted to evaluate the predictive performance of the established diagnostic scoring system.

Results

A total of 508 patients [training set (211 cases of APTB and 116 cases of IPTB) and validation set (103 cases of APTB and 78 cases of IPTB)] with positive T-SPOT were recruited in the study. Stepwise logistic regression showed that CPR, MLR, ESR, APTT and Fbg-C were independent predictors for APTB. The scoring system was subsequently formulated based on the abovementioned predictors, which correspond to scores of 10, 6, 7, 5, and 5, respectively. In addition, patients are more likely to be diagnosed as APTB when the cut-off score was ≥16 scores, while patients with <16 scores are more likely to be diagnosed as IPTB. The scoring system showed good predictive efficacy in both the training set [area under the curve (AUC): 0.887] and the validation set (AUC: 0.898). Furthermore, both CC and DCA confirmed the clinical utility of the scoring system.

Conclusion

The data suggest that the combination of indicators associated with coagulation and inflammation could serve as biomarkers to identify APTB in patients with positive T-SPOT. In addition, patients with positive T-SPOT were more prone to be diagnosed with APTB when having a combined total of scores ≥16 in the scoring system.

Use of point-of-care C-reactive protein testing for screening of tuberculosis in the community in high-burden settings: a prospective, cross-sectional study in Zambia and South Africa

BACKGROUND

WHO recommends community-wide, systematic tuberculosis screening in high-prevalence settings. C-reactive protein has been proposed as a tuberculosis screening tool for people living with HIV. We aimed to assess the performance of a point-of-care C-reactive protein test for tuberculosis screening in the community in two countries with a high tuberculosis burden.

METHODS

We conducted a prospective, cross-sectional study in four communities in Zambia and South Africa, nested in a tuberculosis prevalence survey. We included adults (aged ≥15 years) who were sputum-eligible (tuberculosis-suggestive symptoms or computer-aided-detection score ≥40 on chest x-ray) and whose sputum was tested with Xpert Ultra and liquid culture. A 5% random sample of individuals who were non-sputum-eligible was also included. We calculated sensitivity and specificity of point-of-care C-reactive protein testing, alone and combined with symptom screening, to detect tuberculosis in participants who were sputum-eligible, compared with a microbiological reference standard (positive result in Xpert Ultra, culture, or both).

FINDINGS

Between Feb 19 and Aug 11, 2019, 9588 participants were enrolled in the tuberculosis prevalence study, 1588 of whom had C-reactive protein testing and received results (875 [55·1%] were women and girls, 713 [44·9%] were men and boys, 1317 [82·9%] were sputum-eligible, and 271 [17·1%] were non-sputum-eligible). Among participants who were sputum-eligible, we identified 76 individuals with tuberculosis, of whom 25 were living with HIV. Sensitivity of point-of-care C-reactive protein testing with a cutoff point of 5 mg/L or more was 50·0% (38/76, 95% CI 38·3-61·7) and specificity was 72·3% (890/1231, 69·7-74·8). Point-of-care C-reactive protein combined in parallel with symptom screening had higher sensitivity than symptom screening alone (60·5% [46/76, 95% CI 48·6-71·6] vs 34·2% [26/76, 23·7-46·0]). Specificity of point-of-care C-reactive protein combined in parallel with symptom screening was 51·7% (636/1231, 95% CI 48·8-54·5) versus 70·5% (868/1231, 67·9-73·0) with symptom screening alone. Similarly, in people living with HIV, sensitivity of point-of-care C-reactive protein combined with symptom screening was 72·0% (18/25, 95% CI 50·6-87·9) and that of symptom screening alone was 36·0% (9/25, 18·0-57·5). Specificity of point-of-care C-reactive protein testing combined in parallel with symptom screening in people living with HIV was 47·0% (118/251, 95% CI 40·7-53·4) versus 72·1% (181/251, 66·1-77·6) with symptom screening alone.

INTERPRETATION

Point-of-care C-reactive protein testing alone does not meet the 90% sensitivity stipulated by WHO's target product profile for desirable characteristics for screening tests for detecting tuberculosis. However, combined with symptom screening, it might improve identification of individuals with tuberculosis in communities with high prevalence, and might be particularly useful where other recommended tools, such as chest x-ray, might not be readily available.

FUNDING

European and Developing Countries Clinical Trials Partnership.

Changes of C-reactive protein and Procalcitonin after four weeks of treatment in patients with pulmonary TB

Objective

Tuberculosis (TB) remains a public health concern worldwide, affecting millions of people every year. Detailed characterization of disease pathophysiology is key to proper diagnosis, disease progression, or treatment follow-up and evaluation. The present study investigated C-reactive protein and Procalcitonin (PCT) as candidate markers of early treatment response and disease activity.

Methods

From September to December 2019, 21 HIV-negative consecutive TB patients were recruited, within the setting of the Gabonese TB specialized hospital and the National Laboratory of Public Health, in a prospective study. CRP and PCT levels were measured by chemiluminescence at diagnosis and 4 weeks following the initiation of anti-TB treatment.

Results

The mean concentration of CRP in TB patients was 114.7 mg/L (95 % CI: [83.8-145.6]) at diagnosis and 20.2 mg/L (95 % CI: [14.1-26.4]) 4 weeks following anti-TB treatment. The drop in CRP concentrations between diagnosis, and week 4 following anti-TB treatment showed was significant (p < 0.0001). The average concentration of PCT at the time of diagnosis was 0.3 ng/mL (95 % CI: [0.19-0.41]). PCT Concentration dropped below 0.05 ng/mL 4 weeks following the start of anti-TB treatment (p < 0.01).

Conclusion

CRP and PCT are potential TB biomarkers, each, carrying important keys. If the drop in both proteins may indicate a significant reduction of the Mtb burden, the maintenance of CRP above the inflammation threshold could indicate the presence of residual bacilli. However, the clinical translation of the present finding will require more investigation.