Clinical characteristics and chest computed tomography findings of smear-positive and smear-negative pulmonary tuberculosis in hospitalized adult patients

Construction and Validation of a Nomogram to Identify the Risk of Cavitation in Pulmonary Tuberculosis

Background

The present study aimed to construct and validate a nomogram based on clinical metrics to identify CPTB.

Patients and Methods

The present study retrospectively recruited pulmonary tuberculosis (PTB) patients admitted to Jiashan County First People's Hospital in China from November 2018 to September 2023. PTB patients were classified into the CPTB group and the non-CPTB group based on chest computed tomography findings, and were randomly allocated to the training set (70%) and the validation cohort (30%). The training set and validation set were used to establish and validate nomogram, respectively. Multivariate logistic regression analysis (MLSA) was used to identify the independent risk factors for CPTB in patients with PTB. Statistically significant variables in the MLSA were then used to construct a nomogram predicting CPTB in patients with PTB. The receiver operating characteristic (ROC) curve, calibration curve analysis (CCA), and decision curve analysis (DCA) were used for the evaluation of the nomogram.

Results

A total of 293 PTB patients, including 208 in the training set (85 CPTB) and 85 in the validation set (33 CPTB\), were included in this study. Stepwise MLSA showed that sputum smear (≥2+), smoking(yes), glycosylated hemoglobin A1c(HbA1c), hemoglobin (HB), and systemic inflammatory response index (SIRI) were independent risk factors for the development of cavitation in patients with PTB. The nomogram identifying the high-risk CPTB patients was successfully established and showed a strong predictive capacity, with area under the curves (AUCs) of 0.875 (95% CI:0.806-0.909) and 0.848 (95% CI:0.751-0.946) in the training set and validation set respectively. In addition, the CCA and DCA corroborated the nomogram's high level of accuracy and clinical applicability within both the training and validation sets.

Conclusion

The constructed nomogram, consisting of sputum smear positivity, smoking, HbA1C, HB, and SIRI, serves as a practical and effective tool for early identification and personalized management of CPTB.

Clinical and Imaging Characteristics of Smear Negative Pulmonary Tuberculosis Patients: A Comparative Study

Background

Prevalence surveys in Ethiopia indicate smear negative pulmonary tuberculosis (SNPTB) taking the major share of the overall TB burden. It has also been a diagnostic dilemma worldwide leading to diagnostic delays and difficulty in monitoring treatment outcomes. This study determines and compares the clinical and imaging findings in SNPTB and smear positive PTB (SPPTB). Methodology. A case-control study was conducted on 313 PTB (173 SNPTB) patients. Data and sputum samples were collected from consented patients. Smear microscopy, GeneXpert, and culture analyses were performed on sputum samples. Data were analyzed using Stata version 17; a P value < 0.05 was considered statistically significant.

Results

Of the 173 SNPTB patients, 42% were culture positive with discordances between test results reported by health facilities and Armauer Hansen Research Institute laboratory using concentrated smear microscopy. A previous history of TB and fewer cavitary lesions were significantly associated with SNPTB.

Conclusions

Though overall clinical presentations of SNPTB patients resemble those seen in SPPTB patients, a prior history of TB was strongly associated with SNPTB. Subject to further investigations, the relatively higher discrepancies seen in TB diagnoses reflect the posed diagnostic challenges in SNPTB patients, as a higher proportion of these patients are also seen in Ethiopia.

Imaging of thoracic tuberculosis: pulmonary and extrapulmonary

Tuberculosis (TB) remains the leading cause of death from a single infectious agent globally, despite being a potentially curable disease. This disease typically affects the lungs but may involve many extrapulmonary sites, especially in patients with risk factors such as HIV infection. The clinical features of extrapulmonary TB may mimic many different disease entities, particularly at less common thoracic sites such as the heart, chest wall, and breast. Imaging has an important role in the early diagnosis of TB, helping to detect disease, guide appropriate laboratory investigation, demonstrate complications, and monitor disease progress and response to treatment. Imaging supports the clinical objective of achieving effective treatment outcome and complication prevention. This review aims to highlight the imaging spectrum of TB affecting both pulmonary and extrapulmonary sites in the thorax. We also briefly provide key background information about TB, such as epidemiology, pathogenesis, and diagnosis.

Active pulmonary tuberculosis: something old, something new, something borrowed, something blue

Tuberculosis remains a major global health issue affecting all countries and age groups. Radiology plays a crucial role in the diagnosis and management of pulmonary tuberculosis (PTB). This review aims to improve understanding and diagnostic value of imaging in PTB. We present the old, well-established findings ranging from primary TB to the common appearances of post-primary TB, including dissemination with tree-in-bud nodularity, haematogenous dissemination with miliary nodules and lymphatic dissemination. We discuss new concepts in active PTB with special focus on imaging findings in immunocompromised individuals. We illustrate PTB appearances borrowed from other diseases in which the signs were initially described: the reversed halo sign, the galaxy sign and the cluster sign. There are several radiological signs that have been shown to correlate with positive or negative sputum smears, and radiologists should be aware of these signs as they play an important role in guiding the need for isolation and empirical anti-tuberculous therapy.

Microarray-based selection of a serum biomarker panel that can discriminate between latent and active pulmonary TB

Bacterial culture of M. tuberculosis (MTB), the causative agent of tuberculosis (TB), from clinical specimens is the gold standard for laboratory diagnosis of TB, but is slow and culture-negative TB cases are common. Alternative immune-based and molecular approaches have been developed, but cannot discriminate between active TB (ATB) and latent TB (LTBI). Here, to identify biomarkers that can discriminate between ATB and LTBI/healthy individuals (HC), we profiled 116 serum samples (HC, LTBI and ATB) using a protein microarray containing 257 MTB secreted proteins, identifying 23 antibodies against MTB antigens that were present at significantly higher levels in patients with ATB than in those with LTBI and HC (Fold change > 1.2; p < 0.05). A 4-protein biomarker panel (Rv0934, Rv3881c, Rv1860 and Rv1827), optimized using SAM and ROC analysis, had a sensitivity of 67.3% and specificity of 91.2% for distinguishing ATB from LTBI, and 71.2% sensitivity and 96.3% specificity for distinguishing ATB from HC. Validation of the four candidate biomarkers in ELISA assays using 440 serum samples gave consistent results. The promising sensitivity and specificity of this biomarker panel suggest it merits further investigation for its potential as a diagnostic for discriminating between latent and active TB.

Clinical and CT characteristics of Xpert MTB/RIF-negative pulmonary tuberculosis

Purpose

To determine the diagnostic accuracy of the Xpert MTB/RIF assay in patients with smear-negative pulmonary tuberculosis (TB) and to assess clinical and CT characteristics of Xpert-negative pulmonary TB.

Material and methods

We retrospectively reviewed the records of 1,400 patients with suspected pulmonary TB for whom the sputum Xpert MTB/RIF assay was performed between September 1, 2014 and February 28, 2020. Clinical and CT characteristics of smear-negative pulmonary TB patients with negative Xpert MTB/RIF results were compared with positive results.

Results

Of 1,400 patients, 365 (26.1%) were diagnosed with pulmonary TB and 190 of 365 patients (52.1%) were negative for sputum acid-fast bacilli. The diagnosis of pulmonary TB was based on a positive culture, positive Xpert MTB/RIF or the clinical diagnoses of patients treated with an anti-TB medication. The sensitivity, specificity, positive predictive and negative predictive values of sputum Xpert MTB/RIF for smear-negative pulmonary TB were 41.1%, 100%, 100%, and 90.1%, respectively. Finally, 172 patients with smear-negative pulmonary TB who underwent chest CT within 2 weeks of diagnosis were included to compare Xpert-positive (n = 66) and Xpert- negative (n = 106) groups. Patients with sputum Xpert-negative TB showed lower positive rates for sputum culture (33.0% vs. 81.8%, p<0.001) and bronchoalveolar lavage culture (53.3% vs. 84.6%, p = 0.042) than in Xpert-positive TB. Time to start TB medication was longer in patients with Xpert-negative TB than in Xpert-positive TB (11.3±16.4 days vs. 5.0±8.7 days, p = 0.001). On chest CT, sputum Xpert-negative TB showed significantly lower frequency of consolidation (21.7% vs. 39.4%, p = 0.012), cavitation (23.6% vs. 37.9%, p = 0.045), more frequent peripheral location (50.9% vs. 21.2 p = 0.001) with lower area of involvement (4.3±4.3 vs. 7.6±6.4, p<0.001). Multivariate analysis revealed peripheral location (odds ratios, 2.565; 95% confidence interval: 1.157–5.687; p = 0.020) and higher total extent of the involved lobe (odds ratios, 0.928; 95% confidence interval: 0.865–0.995; p = 0.037) were significant factors associated with Xpert MTB/RIF-negative TB. Regardless of Xpert positivity, more than 80% of all cases were diagnosed of TB on chest CT by radiologists.

Conclusion

The detection rate of sputum Xpert MTB/RIF assay was relatively low for smear negative pulmonary TB. Chest CT image interpretation may play an important role in early diagnosis and treatment of Xpert MTB/RIF-negative pulmonary TB.

Radiologist observations of computed tomography (CT) images predict treatment outcome in TB Portals, a real-world database of tuberculosis (TB) cases

The TB Portals program provides a publicly accessible repository of TB case data containing multi-modal information such as case clinical characteristics, pathogen genomics, and radiomics. The real-world resource contains over 3400 TB cases, primarily drug resistant cases, and CT images with radiologist annotations are available for many of these cases. The breadth of data collected offers a patient-centric view into the etiology of the disease including the temporal context of the available imaging information. Here, we analyze a cohort of new TB cases with available radiologist observations of CTs taken around the time of initial registration of the case into the database and with available follow up to treatment outcome of cured or died. Follow up ranged from 5 weeks to a little over 2 years consistent with the longest treatment regimens for drug resistant TB and cases were registered within the years 2008 to 2019. The radiologist observations were incorporated into machine learning pipelines to test various class balancing strategies on the performance of predictive models. The modeling results support that the radiologist observations are predictive of treatment outcome. Moreover, inferential statistical analysis identifies markers of TB disease spread as having an association with poor treatment outcome including presence of radiologist observations in both lungs, swollen lymph nodes, multiple cavities, and large cavities. While the initial results are promising, further data collection is needed to incorporate methods to mitigate potential confounding such as including additional model covariates or matching cohorts on covariates of interest (e.g. demographics, BMI, comorbidity, TB subtype, etc.). Nonetheless, the preliminary results highlight the utility of the resource for hypothesis generation and exploration of potential biomarkers of TB disease severity and support these additional data collection efforts.

Comparison of the diagnostic efficacy of the CapitalBio Mycobacterium real-time polymerase chain reaction detection test and Xpert MTB/RIF in smear-negative pulmonary tuberculosis

To compare the diagnostic efficacy of CapitalBio Mycobacterium real-time polymerase chain reaction (RT-PCR) detection test and the first-generation Xpert MTB/RIF in smear-negative pulmonary tuberculosis (PTB). In this retrospective study of smear-negative PTB, we reviewed patient medical records to determine the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) of Xpert MTB/RIF, CapitalBio Mycobacterium detection test, and the parallel test (positive result for either of the Xpert MTB/RIF and CapitalBio Mycobacterium detection tests) to evaluate their diagnostic accuracy against a composite reference standard. In total, 1553 patients were evaluated. The sensitivity, specificity, PPV, NPV, and AUC of Xpert MTB/RIF, CapitalBio Mycobacterium detection test, and the parallel test were 57.1%, 92.9%, 81.1%, 95.9%, and 0.75; 53.4%, 97.7%, 98.6%, 41.5%, and 0.76; and 66.2%, 90.8%, 95.5%, 47.7%, and 0.79, respectively. For the bronchoalveolar lavage fluid (BALF) specimens, these values for Xpert MTB/RIF, CapitalBio Mycobacterium detection test, and the parallel test were 68.8%, 97.7%, 99.2%, 43.9%, and 0.83; 61.7%, 97.7%, 99.1%, 38.9%, and 0.80; and 77.0%, 95.5%, 98.6%, 50.9%, and 0.86, respectively. CapitalBio Mycobacterium detection test had moderate accuracy for smear-negative PTB, similar to Xpert MTB/RIF. The parallel test improved the sensitivity. BALF significantly improved the sensitivity and diagnostic accuracy of the test. The maximum diagnostic accuracy for smear-negative PTB was obtained with the parallel test and BALF specimens. BALF was the most effective specimen for diagnosing smear-negative PTB.

Pulmonary Cryptococcosis in a Nurse Initially Suspected of Having Pulmonary Tuberculosis

Patient: Female, 34-year-old

Final Diagnosis: Pulmonary cryptococcosis

Symptoms: None

Medication: —

Clinical Procedure: Bronchoscopy

Specialty: Infectious Diseases