Diagnosis Of Drug-resistant Tuberculosis Research Articles

Molecular Indicator for Distinguishing Multi-drug-Resistant Tuberculosis from Drug Sensitivity Tuberculosis and Potential Medications for Treatment.

The issue of multi-drug-resistant tuberculosis (MDR-TB) presents a substantial challenge to global public health. Regrettably, the diagnosis of drug-resistant tuberculosis (DR-TB) frequently necessitates an extended period or more extensive laboratory resources. The swift identification of MDR-TB poses a particularly challenging endeavor. To identify the biomarkers indicative of multi-drug resistance, we conducted a screening of the GSE147689 dataset for differentially expressed genes (DEGs) and subsequently conducted a gene enrichment analysis. Our analysis identified a total of 117 DEGs, concentrated in pathways related to the immune response. Three machine learning methods, namely random forest, decision tree, and support vector machine recursive feature elimination (SVM-RFE), were implemented to identify the top 10 genes according to their feature importance scores. A4GALT and S1PR1, which were identified as common genes among the three methods, were selected as potential molecular markers for distinguishing between MDR-TB and drug-susceptible tuberculosis (DS-TB). These markers were subsequently validated using the GSE147690 dataset. The findings suggested that A4GALT exhibited area under the curve (AUC) values of 0.8571 and 0.7121 in the training and test datasets, respectively, for distinguishing between MDR-TB and DS-TB. S1PR1 demonstrated AUC values of 0.8163 and 0.5404 in the training and test datasets, respectively. When A4GALT and S1PR1 were combined, the AUC values in the training and test datasets were 0.881 and 0.7551, respectively. The relationship between hub genes and 28 immune cells infiltrating MDR-TB was investigated using single sample gene enrichment analysis (ssGSEA). The findings indicated that MDR-TB samples exhibited a higher proportion of type 1T helper cells and a lower proportion of activated dendritic cells in contrast to DS-TB samples. A negative correlation was observed between A4GALT and type 1T helper cells, whereas a positive correlation was found with activated dendritic cells. S1PR1 exhibited a positive correlation with type 1T helper cells and a negative correlation with activated dendritic cells. Furthermore, our study utilized connectivity map analysis to identify nine potential medications, including verapamil, for treating MDR-TB. In conclusion, our research identified two molecular indicators for the differentiation between MDR-TB and DS-TB and identified a total of nine potential medications for MDR-TB.

Evaluation of WHO catalog of mutations and five WGS analysis tools for drug resistance prediction of Mycobacterium tuberculosis isolates from China.

The continuous advancement of molecular diagnostic techniques, particularly whole-genome sequencing (WGS), has greatly facilitated the early diagnosis of drug-resistant tuberculosis patients. Nonetheless, the interpretation of results from various types of mutations in drug-resistant-associated genes has become the primary challenge in the field of molecular drug-resistance diagnostics. In this study, our primary objective is to evaluate the diagnosis accuracy of the World Health Organization (WHO) catalog of mutations and five WGS analysis tools (PhyResSE, Mykrobe, TB Profiler, Gen-TB, and SAM-TB) in drug resistance to 10 anti-Mycobacterium tuberculosis (MTB) drugs. We utilized the data of WGS collected between 2014 and 2017 in Zhejiang Province, consisting of 110 MTB isolates as detailed in our previous study. Based on phenotypic drug susceptibility testing (DST) results using the proportion method on Löwenstein-Jensen medium with antibiotics, we evaluated the predictive accuracy of genotypic DST obtained by these tools. The results revealed that the WHO catalog of mutations and five WGS analysis tools exhibit robust predictive capabilities concerning resistance to isoniazid, rifampicin, ethambutol, streptomycin, amikacin, kanamycin, and capreomycin. Notably, Mykrobe, SAM-TB, and TB Profiler demonstrate the most accurate predictions for resistance to pyrazinamide, prothionamide, and para-aminosalicylic acid, respectively. These findings are poised to significantly guide and influence future clinical treatment strategies and resistance monitoring protocols.IMPORTANCEWhole-genome sequencing (WGS) has the potential for the early diagnosis of drug-resistant tuberculosis. However, the interpretation of mutations of drug-resistant-associated genes represents a significant challenge as the amount and complexity of WGS data. We evaluated the accuracy of the World Health Organization catalog of mutations and five WGS analysis tools in predicting drug resistance to first-line and second-line anti-TB drugs. Our results offer clinicians guidance on selecting appropriate WGS analysis tools for predicting resistance to specific anti-TB drugs.

Beyond the diagnosis of drug-resistant Tuberculosis in Norway: patients’ experiences before, during and after treatment

BackgroundThis study aims to explore the varied experiences of patients with drug-resistant tuberculosis in Norway. The study emphasizes challenges and implications of being diagnosed with drug-resistant tuberculosis, including the impact on psychosocial health during the diagnosis, disease, treatment, isolation and recovery phases.Norway is a low endemic country of tuberculosis. Most patients are immigrants, and some of them have recently arrived in the country. Patients undergoing treatment for drug-resistant tuberculosis endure prolonged and demanding treatment that could affect their psychosocial health.MethodsThis qualitative study conducted 16 in-depth interviews with individuals aged 18 years and above who were diagnosed with drug-resistant tuberculosis. All participants completed the treatment between 2008 and 2020. Fourteen participants were immigrants, and eight of them had resided in Norway for less than four years before diagnosis. Data analysis followed the six-phase reflexive thematic analysis framework, focusing on identifying patterns in participants’ experiences, thoughts, expectations and attitudes.ResultsThe narratives of the participants highlighted the complexities of navigating the diagnosis of drug-resistant tuberculosis, treatment, side effects and life after treatment. Immigrants encountered additional challenges, including language barriers and adapting to new social environments. All participants reported experiencing physical health issues that additionally affected their mental health and social activity. Several participants had a delayed or prolonged diagnosis that complicated their disease trajectory. Participants with suspected or confirmed contagious pulmonary tuberculosis underwent hospital isolation for periods ranging from weeks to six months. The participants reported mental health issues, social isolation and stigma, however few were offered follow-up by a psychologist. Many participants had persistent problems at the time of the interviews. Three main themes emerged from the analysis: Delayed and prolonged diagnosis; Psychosocial impact of isolation during treatment; The life after tuberculosis.ConclusionThis study highlights the enduring impact of drug-resistant tuberculosis on patients and the significance of timely diagnosis, psychosocial support and post-treatment follow-up. The participants universally faced serious implications of the disease, including stigma and isolation. Participants who experienced delayed diagnosis, reflected on missed early intervention opportunities. We recommend further research in low endemic countries to evaluate the international and local recommendations on psychosocial support.

Evaluation of AAICare®-TB sequence analysis tool for accurate diagnosis of drug-resistant tuberculosis: A comparative study with TB-Profiler and Mykrobe

A rapid and comprehensive drug susceptibility test is essential for eliminating drug resistant tuberculosis. Next generation sequencing (NGS) based susceptibility testing is being explored as a potential substitute for the conventional phenotypic and genotypic testing methods. However, the adoption of NGS based genotypic susceptibility testing depends on the availability of simple, accurate and efficient analysis tools. This preliminary study aimed to evaluate the performance of a Mycobacterium tuberculosis (Mtb) genome analysis pipeline, AAICare®-TB, for susceptibility prediction, in comparison to two widely used gDST prediction tools, TB-Profiler and Mykrobe. This study was performed in a National Reference Laboratory in India on presumptive drug-resistant tuberculosis (DR-TB) isolates. Whole genome sequences of the 120 cultured isolates were obtained through Illumina sequencing on a MiSeq platform. Raw sequences were simultaneously analysed using the three tools. Susceptibility prediction reports thus generated, were compared to estimate the total concordance and discordance. WHO mutation catalogue (1st edition, 2021) was used as the reference standard for categorizing the mutations. In this study, AAICare®-TB was able to predict drug resistance status for First Line (Streptomycin, Isoniazid, Rifampicin, Ethambutol and Pyrazinamide) and Second Line drugs (Fluoroquinolones, Second Line Injectables and Ethionamide) in 93 samples along with lineage and hetero-resistance as per the WHO guidelines.

Rapid detection of multidrug resistance in tuberculosis using nanopore-based targeted next-generation sequencing: a multicenter, double-blind study.

Resistance to anti-tuberculous drugs is a major challenge in the treatment of tuberculosis (TB). We aimed to evaluate the clinical availability of nanopore-based targeted next-generation sequencing (NanoTNGS) for the diagnosis of drug-resistant tuberculosis (DR-TB). This study enrolled 253 patients with suspected DR-TB from six hospitals. The diagnostic efficacy of NanoTNGS for detecting Mycobacterium tuberculosis and its susceptibility or resistance to first- and second-line anti-tuberculosis drugs was assessed by comparing conventional phenotypic drug susceptibility testing (pDST) and Xpert MTB/RIF assays. NanoTNGS can be performed within 12 hours from DNA extraction to the result delivery. NanoTNGS showed a remarkable concordance rate of 99.44% (179/180) with the culture assay for identifying the Mycobacterium tuberculosis complex. The sensitivity of NanoTNGS for detecting drug resistance was 93.53% for rifampicin, 89.72% for isoniazid, 85.45% for ethambutol, 74.00% for streptomycin, and 88.89% for fluoroquinolones. Specificities ranged from 83.33% to 100% for all drugs tested. Sensitivity for rifampicin-resistant tuberculosis using NanoTNGS increased by 9.73% compared to Xpert MTB/RIF. The most common mutations were S531L (codon in E. coli) in the rpoB gene, S315T in the katG gene, and M306V in the embB gene, conferring resistance to rifampicin, isoniazid, and ethambutol, respectively. In addition, mutations in the pncA gene, potentially contributing to pyrazinamide resistance, were detected in 32 patients. Other prevalent variants, including D94G in the gyrA gene and K43R in the rpsL gene, conferred resistance to fluoroquinolones and streptomycin, respectively. Furthermore, the rv0678 R94Q mutation was detected in one sample, indicating potential resistance to bedaquiline. NanoTNGS rapidly and accurately identifies resistance or susceptibility to anti-TB drugs, outperforming traditional methods. Clinical implementation of the technique can recognize DR-TB in time and provide guidance for choosing appropriate antituberculosis agents.

Deep learning for precise diagnosis and subtype triage of drug-resistant tuberculosis on chest computed tomography.

Deep learning, transforming input data into target prediction through intricate network structures, has inspired novel exploration in automated diagnosis based on medical images. The distinct morphological characteristics of chest abnormalities between drug-resistant tuberculosis (DR-TB) and drug-sensitive tuberculosis (DS-TB) on chest computed tomography (CT) are of potential value in differential diagnosis, which is challenging in the clinic. Hence, based on 1176 chest CT volumes from the equal number of patients with tuberculosis (TB), we presented a Deep learning-based system for TB drug resistance identification and subtype classification (DeepTB), which could automatically diagnose DR-TB and classify crucial subtypes, including rifampicin-resistant tuberculosis, multidrug-resistant tuberculosis, and extensively drug-resistant tuberculosis. Moreover, chest lesions were manually annotated to endow the model with robust power to assist radiologists in image interpretation and the Circos revealed the relationship between chest abnormalities and specific types of DR-TB. Finally, DeepTB achieved an area under the curve (AUC) up to 0.930 for thoracic abnormality detection and 0.943 for DR-TB diagnosis. Notably, the system demonstrated instructive value in DR-TB subtype classification with AUCs ranging from 0.880 to 0.928. Meanwhile, class activation maps were generated to express a human-understandable visual concept. Together, showing a prominent performance, DeepTB would be impactful in clinical decision-making for DR-TB.

Chinese expert consensus on imaging diagnosis of drug-resistant pulmonary tuberculosis.

Tuberculosis (TB) remains one of the major infectious diseases in the world with a high incidence rate. Drug-resistant tuberculosis (DR-TB) is a key and difficult challenge in the prevention and treatment of TB. Early, rapid, and accurate diagnosis of DR-TB is essential for selecting appropriate and personalized treatment and is an important means of reducing disease transmission and mortality. In recent years, imaging diagnosis of DR-TB has developed rapidly, but there is a lack of consistent understanding. To this end, the Infectious Disease Imaging Group, Infectious Disease Branch, Chinese Research Hospital Association; Infectious Diseases Group of Chinese Medical Association of Radiology; Digital Health Committee of China Association for the Promotion of Science and Technology Industrialization, and other organizations, formed a group of TB experts across China. The conglomerate then considered the Chinese and international diagnosis and treatment status of DR-TB, China's clinical practice, and evidence-based medicine on the methodological requirements of guidelines and standards. After repeated discussion, the expert consensus of imaging diagnosis of DR-PB was proposed. This consensus includes clinical diagnosis and classification of DR-TB, selection of etiology and imaging examination [mainly X-ray and computed tomography (CT)], imaging manifestations, diagnosis, and differential diagnosis. This expert consensus is expected to improve the understanding of the imaging changes of DR-TB, as a starting point for timely detection of suspected DR-TB patients, and can effectively improve the efficiency of clinical diagnosis and achieve the purpose of early diagnosis and treatment of DR-TB.

Rapid Diagnosis of Drug-Resistant Tuberculosis-Opportunities and Challenges.

Global tuberculosis (TB) eradication is undermined by increasing prevalence of emerging resistance to available drugs, fuelling ongoing demand for more complex diagnostic and treatment strategies. Early detection of TB drug resistance coupled with therapeutic decision making guided by rapid characterisation of pre-treatment and treatment emergent resistance remains the most effective strategy for averting Drug-Resistant TB (DR-TB) transmission, reducing DR-TB associated mortality, and improving patient outcomes. Solid- and liquid-based mycobacterial culture methods remain the gold standard for Mycobacterium tuberculosis (MTB) detection and drug susceptibility testing (DST). Unfortunately, delays to result return, and associated technical challenges from requirements for specialised resource and capacity, have limited DST use and availability in many high TB burden resource-limited countries. There is increasing availability of a variety of rapid nucleic acid-based diagnostic assays with adequate sensitivity and specificity to detect gene mutations associated with resistance to one or more drugs. While a few of these assays produce comprehensive calls for resistance to several first- and second-line drugs, there is still no endorsed genotypic drug susceptibility test assay for bedaquiline, pretomanid, and delamanid. The global implementation of regimens comprising these novel drugs in the absence of rapid phenotypic drug resistance profiling has generated a new set of diagnostic challenges and heralded a return to culture-based phenotypic DST. In this review, we describe the available tools for rapid diagnosis of drug-resistant tuberculosis and discuss the associated opportunities and challenges.

Drug-resistant Tuberculosis in Pediatric

Introduction: Drug-resistant tuberculosis (DR TB) is a condition where Mycobacterium tuberculosis is resistant to isoniazid, rifampicin or resistant to isoniazid and rifampin as well as other first-line anti-tuberculosis drugs (OAT). Tuberculosis (TB) is a contagious infectious disease, caused by Mycobacterium tuberculosis germs where the source of transmission is through droplets containing TB germs. Case Report: A 10 years 7 months girl, came to the MDR Polyclinic at the Haji Adam Malik Medan Central General Hospital (RSUP HAM Medan) on March 21 2023 bringing the results of the TB Molecular Rapid Test (TCM-TB) examination from the Teladan Barat Health Center with Rifampicin results were resistant and on March 24 2023 the patient was hospitalized. Currently, the patient is complaining of a cough that has been experiencing for ± 3 weeks. Cough with the impression of a dry cough and is continuous so that it interferes with daily activities. The cough does not improve even though the patient has taken cough medicine. There is no fever, there is also no history of previous fever. According to the anamnesis from the patient's parents, there has been a weight loss in the last 2 months, around ± 4 kg. There is no family history of long-term cough, but according to parents, there is a neighbor of the patient who suffers from pulmonary TB and is undergoing treatment. Discussion: After the diagnosis of drug-resistant tuberculosis is confirmed, an evaluation is carried out whether the patient meets the criteria for drug-resistant TB treatment guided by short-term or long-term oral drug-resistant tuberculosis. Patients who meet the evaluation criteria for treatment can immediately be given short-term oral drug-resistant tuberculosis therapy. If the patient does not meet the criteria for short-term treatment, long-term drug-resistant tuberculosis treatment is given. Routine evaluations are carried out during treatment and when the results of drug sensitivity tests are available, treatment is adjusted according to the examination results. Conclusion: A case of drug-resistant tuberculosis in a girl aged 10 years 7 months has been reported which was diagnosed based on anamnesis, physical examination, and supporting examinations, there was also a history of close contact with TB sufferers, and the results of TCM examination of sputum fluid showed rifampicin resistant MTB growth. Patients are treated as drug-resistant TB cases with a short-term regimen with regular monitoring of treatment response and side effects.

Strengthening the Diagnosis of Drug-Resistant Tuberculosis Using NGS-Based Approaches and Bioinformatics Pipelines for Data Analysis in India.

In India, drug-resistant tuberculosis (DR-TB) is a major public health issue and a significant challenge to stop TB program. An estimated 27% of new TB cases and 44% of previously treated TB cases are resistant to at least one anti-TB drug. The conventional methods for DR-TB diagnosis are time-consuming and have limitations, leading to delays in treatment initiation and the spread of the disease. Next-generation sequencing (NGS) based approaches have emerged as a promising tool for diagnosing DR-TB, simultaneously offering rapid and accurate detection of resistance mutations in multiple genes. NGS-based approaches generate a large amount of data, which requires efficient and reliable bioinformatics pipelines for data analysis. TBProfiler and Mykrobe are the bioinformatics pipelines that have been created to analyze NGS data for the diagnosis of DR-TB. These pipelines use reference-based and machine-learning approaches to detect resistance mutations and predict drug susceptibility, enabling clinicians to make informed treatment decisions. Implementing NGS-based approaches and bioinformatics pipelines for DR-TB diagnosis can potentially improve patient outcomes by facilitating early detection of drug resistance and guiding personalized treatment regimens. However, the widespread adoption of these approaches in India faces several challenges, including high costs, limited infrastructure, and a lack of trained personnel. Addressing these challenges requires concerted effort to ensure equitable access to and effective implementation of these innovative technologies.

Comparison of the MeltPro TB assay and whole-genome sequencing assay for rapid molecular diagnosis of drug resistant tuberculosis in guangdong province

BackgroundRifampicin (RIF) and multidrug-resistant tuberculosis (TB) are major public health threats. As conventional phenotypic drug susceptibility testing requires two–eight weeks, molecular diagnostic assays are widely used to determine drug resistance. MethodsClinical Mycobacterium tuberculosis isolates with consistent drug susceptibility results, tested using microbroth dilution and proportion methods in Löwenstein-Jensen medium from patients with TB in Guangdong province were utilized to evaluate MeltPro TB and whole-genome sequencing (WGS) assays in detecting resistance to RIF, isoniazid (INH), ethambutol (EMB), fluoroquinolones (FQ), and streptomycin (SM). Solid phenotypic drug susceptibility testing was used as the gold standard to evaluate the detection capacity of MeltPro TB on clinical sputum samples of patients with TB. ResultsSimilar to WGS, MeltPro TB successfully detected RIF, INH, and SM resistance with sensitivities of 86.3, 84.8, and 86.6 %, respectively. However, the resistant isolate detection rates were only 58.1 and 69.6 % for EMB and FQ-resistant strains. For clinical specimens, MeltPro TB still showed good detectable rates of RIF and INH resistance, with sensitivities of 82.4 % and 95.2 %, respectively. Detectable rates of FQ and EMB resistance were low: 77.8 % and 35.3 %, respectively. ConclusionsMeltPro TB can detect known DNA mutations associated with drug resistance in Mycobacterium tuberculosis strains with comparable efficacy to WGS. For FQ and EMB resistance testing, MeltPro TB requires optimization and is unsuitable for general use. MeltPro TB can be used for diagnosis of RIF and multidrug-resistant tuberculosis to rapidly initiate appropriate anti-TB drug therapy.

Coping with drug resistant tuberculosis alongside COVID-19 and other stressors in Zimbabwe: A qualitative study.

Households in low-resource settings are more vulnerable to events which adversely affect their livelihoods, including shocks e.g. death of family members, droughts and more recently COVID-19. Drug Resistant Tuberculosis (DR-TB) is another shock that inflicts physical, psychological and socioeconomic burden on individuals and households. We describe experiences and coping strategies among people affected by DR-TB and their households in Zimbabwe during the COVID-19 pandemic, 2020-2021. We purposively selected 16 adults who had just completed or were completing treatment for DR-TB for in-depth interviews. We transcribed audio-recordings verbatim and translated the transcripts into English. Data were coded both manually and using NVivo 12 (QSR International), and were analysed thematically. Health seeking from providers outside the public sector, extra-pulmonary TB and health system factors resulted in delayed DR-TB diagnosis and treatment and increased financial drain on households. DR-TB reduced productive capacity and narrowed job opportunities leading to income loss that continued even after completion of treatment. Household livelihood was further adversely affected by lockdowns due to COVID-19, outbreaks of bird flu and cattle disease. Stockouts of DR-TB medicines, common during COVID-19, exacerbated loss of productive time and transport costs as medication had to be accessed from other clinics. Reversible coping strategies included: reducing number of meals; relocating in search of caregivers and/or family support; spending savings; negotiating with school authorities to keep children in school. Some households adopted irreversible coping strategies e.g. selling productive assets and withdrawing children from school. DR-TB combined with COVID-19 and other stressors and pushed households into deeper poverty and vulnerability. Multisectoral approaches that combine health systems and socioeconomic interventions are crucial to mitigate diagnostic delays and suffering, and meaningfully support people with DR-TB and their households to compensate the loss of livelihoods during and post DR-TB treatment.

Implementation of targeted next-generation sequencing for the diagnosis of drug-resistant tuberculosis in low-resource settings: a programmatic model, challenges, and initial outcomes.

Targeted next-generation sequencing (tNGS) from clinical specimens has the potential to become a comprehensive tool for routine drug-resistance (DR) prediction of Mycobacterium tuberculosis complex strains (MTBC), the causative agent of tuberculosis (TB). However, TB mainly affects low- and middle-income countries, in which the implementation of new technologies have specific needs and challenges. We propose a model for programmatic implementation of tNGS in settings with no or low previous sequencing capacity/experience. We highlight the major challenges and considerations for a successful implementation. This model has been applied to build NGS capacity in Namibia, an upper middle-income country located in Southern Africa and suffering from a high-burden of TB and TB-HIV, and we describe herein the outcomes of this process.

Time-to-Treatment Initiation in a Decentralised Community-Care Model of Drug-Resistant Tuberculosis Management in the OR Tambo District Municipality of South Africa.

Drug-resistant tuberculosis (DR-TB) continues to challenge global efforts toward eradicating and having a tuberculosis-free world. Considering the high early mortality, especially among HIV-infected individuals, early diagnosis and prompt initiation of effective treatment are needed to significantly reduce mortality and halt transmission of DR-TB in the community. This study aims to assess the effectiveness of a community DR-TB care model with the specific objective of determining the Time-to-treatment initiation of DR-TB among patients in the OR Tambo district municipality. A prospective cohort study of patients with DR-TB was conducted in the OR Tambo district municipality of Eastern Cape Province, South Africa. Patients were enrolled as they presented for treatment initiation at the decentralised facilities following a diagnosis of DR-TB and compared with a centralised site. A total of 454 DR-TB patients from six facilities between 2018 and 2020 were included in the analysis. The mean age was 37.54 (SD = 14.94) years. There were slightly more males (56.2%) than females (43.8%). Most of the patients were aged 18-44 years (67.5%), without income (82.3%). Results showed that slightly over thirteen percent (13.4%) of patients initiated treatment the same day they were diagnosed with DR-TB, while 36.3% were on the time-to-treatment target of being initiated within 5 days. However, about a quarter (25.8%) of patients failed to initiate treatment two weeks after diagnosis. Time-to-treatment initiation (TTTI) varied according to the decentralised sites, with progressive improvement with each successive year between 2018 and 2021. No demographic factor was significantly associated with TTTI. Despite rapid diagnosis, only 36% of patients were initiated on treatment promptly. Operational challenges remained, and services needed to be reorganised to maximise the exceptional potentials that a decentralised community DR-TB care model brings.

Resistant Tuberculosis in HIV-Positive Patients: A Growing Public Health Threat

<i>Introduction: </i>Tuberculosis (TB) is a pathology considered one of the main causes of death by single infectious agent, ranking just after HIV / AIDS. Indeed, its emergence and the difficulty of its treatment, especially in the resistant form, in patients with co-infection with other diseases immundéprimante as HIV.<i> Observation 1:</i> 31 years old presented with febrile headaches complicated by epileptic seizures. The MRI scan showed 3 cockeyed and multilocular lesions suggesting neuromeningeal tuberculosis. HIV serology came back positive and during the first line treatment he relapsed and the resistance test was positive.<i> Observation 2:</i> 45 progressive alteration of the state associated with signs of tuberculosis impregnation and a meningeal syndrome. BK in the CSF and in the sputum was positive and brain imaging allowed us to retain the diagnosis of a neuromeningeal tuberculosis. The patient was put on anti-bacillary ERIP k4 and a corticotherapy. The workup for co-infection was able to establish an HIV infection. After 3 weeks of anti-bacillary treatment, the patient had a bad evolution and the search for resistance came back positive. <i>Observation 3: </i>25 years old, pulmonary tuberculosis manifested by a hemoptysis of small abundance associated with a deep alteration of the general state, 3 BK positive sputum, as well as the image of a tuberculous cavern on the thoracic CT. Bad evolution after 2 months of treatment of first worsening of symptoms neuro and systemic involvement the search for resistance came back positive. <i>Discussion:</i> Drug-resistant tuberculosis is a major global public health challenge. In this article, we present three cases of drug-resistant TB in HIV-coinfected patients, highlighting the emergence and increasing prevalence of multidrug-resistant TB (MDR-TB) strains worldwide. In order to control the spread of this dreaded disease, it is essential to improve treatment regimens, promote vaccination, educate affected patients, and promote adherence to treatment. <i>conclusion: </i>Diagnosis of drug-resistant tuberculosis should be prompt and considered if there is a delay or lack of improvement with conventional tuberculosis treatment.

Clinical value of the MeltPro MTB assays in detection of drug-resistant tuberculosis in paraffin-embedded tissues

Objective: To evaluate the clinical value of the MeltPro MTB assays in the diagnosis of drug-resistant tuberculosis. Methods: A cross-sectional study design was used to retrospectively collect all 4 551 patients with confirmed tuberculosis between January 2018 and December 2019 at Beijing Chest Hospital, Capital Medical University. Phenotypic drug sensitivity test and GeneXpert MTB/RIF (hereafter referred to as "Xpert") assay were used as gold standards to analyze the accuracy of the probe melting curve method. The clinical value of this technique was also evaluated as a complementary method to conventional assays of drug resistance to increase the detective rate of drug-resistant tuberculosis. Results: By taking the phenotypic drug susceptibility test as the gold standard, the sensitivity of the MeltPro MTB assays to detect resistance to rifampicin, isoniazid, ethambutol and fluoroquinolone was 14/15, 95.7%(22/23), 2/4 and 8/9,respectively; and the specificity was 92.0%(115/125), 93.2%(109/117), 90.4%(123/136) and 93.9%(123/131),respectively; the overall concordance rate was 92.1%(95%CI:89.6%-94.1%),and the Kappa value of the consistency test was 0.63(95%CI:0.55-0.72).By taking the Xpert test results as the reference, the sensitivity of this technology to the detection of rifampicin resistance was 93.6%(44/47), the specificity was100%(310/310), the concordance rate was 99.2%(95%CI:97.6%-99.7%), and the Kappa value of the consistency test was 0.96(95%CI:0.93-0.99). The MeltPro MTB assays had been used in 4 551 confirmed patients; the proportion of patients who obtained effective drug resistance results increased from 83.3% to 87.8%(P<0.01); and detection rate of rifampicin, isoniazid, ethambutol, fluoroquinolone resistance, multidrug and pre-extensive drug resistance cases were increased by 3.2%, 14.7%, 22.2%, 13.7%, 11.2% and 12.5%, respectively. Conclusion: The MeltPro MTB assays show satisfactory accuracy in the diagnosis of drug-resistant tuberculosis. This molecular pathological test is an effective complementary method in improving test positivity of drug-resistant tuberculosis.

A rapid, accurate, and low-cost method for detecting Mycobacterium tuberculosis and its drug-resistant genes in pulmonary tuberculosis: Applications of MassARRAY DNA mass spectrometry.

Mycobacterium tuberculosis (MTB) identification and drug resistance diagnosis are very important for treatment of drug-resistant tuberculosis (DR-TB). Therefore, high throughput, accurate and low-cost molecular detection techniques are urgently needed. This study aimed to evaluate the clinical application value of MassARRAY in tuberculosis diagnosis and drug resistance screening. The limit of detection (LOD) and clinical application value of MassARRAY were evaluated using reference strains and clinical isolates. MTB in bronchoalveolar lavage fluid (BALF) and sputum samples were detected using MassARRAY, quantitative real-time polymerase chain reaction (qPCR) and MGIT960 liquid culture (culture). Using culture as the standard, the efficacy of MassARRAY and qPCR for the detection of TB was analyzed. Mutation of drug resistance genes in MTB clinical isolates was tested using MassARRAY, high-resolution melting curve (HRM), and Sanger sequencing. Using sequencing as the standard, the efficacy of MassARRAY, and HRM for the detection of each drug resistance site of MTB was analyzed. Simultaneously, the mutation of drug resistance genes by the MassARRAY method was compared with the results of drug susceptibility testing (DST), and the genotype-phenotype relationship was analyzed. The ability of MassARRAY to discriminate mixed infections was detected using mixtures of standard strains (M. tuberculosis H37Rv) and drug-resistant clinical isolates and mixtures of wild-type and mutant plasmids. In MassARRAY, 20 related gene mutations could be detected by two PCR systems. All genes could be accurately detected when the bacterial load was 104 CFU/mL. When the load of wild-type and drug-resistant MTB mixture was 105 CFU/mL (respectively reached 104 CFU/mL), variants and wild-type genes could be detected simultaneously. The sensitivity of MassARRAY (96.9%) for identification was higher than that of qPCR (87.5%) (p < 0.001). The sensitivity and specificity of MassARRAY for all drug resistance gene mutations were 100.0%, with higher accuracy and consistency than HRM (sensitivity = 89.3% and specificity = 96.9%, p = 0.001). Analyzing the relationship between MassARRAY genotype and DST phenotype, the accuracy of katG_315, rpoB_531, rpsL_43, rpsL_88, and rrs_513 sites was 100.0%, and embB_306 and rpoB_526 were inconsistent with the DST results when the base changes were different. MassARRAY can obtain base mutation information and identify heteroresistance infections simultaneously when the mutant proportion was at least 5-25%. It has good application prospects in the diagnosis of DR-TB with high throughput, accurate and low-cost.

Distribution of Rifampicin-Resistant Tuberculosis Patients based on Presumptive Drug-Resistant Tuberculosis Criteria at Dr. Hasan Sadikin Hospital 2016–2019

Background: Diagnosis of drug-resistant tuberculosis (DR-TB) begins with identifying presumptive DR-TB patients using Xpert MTB/RIF, as a diagnostic test to detect resistance to rifampicin. The study aimed to identify the distribution of rifampicin-resistant tuberculosis (RR-TB) patients based on presumptive DR-TB criteria at Dr. Hasan Sadikin General Hospital Bandung. Moreover, this study also explored the Xpert MTB/RIF Ct values.Methods: This was a descriptive-retrospective study from 570 medical records of DR-TB patients collected at the Multidrug-resistant tuberculosis (MDR-TB) clinic of Dr. Hasan Sadikin General Hospital from 2016 to 2019. The inclusion criteria were suspected patients with the Xpert MTB/RIF Ct values in the very low-low and medium-high categories. Data were analyzed using frequency distribution. Results: The most common presumptive DR-TB criteria among DR-TB patients were relapse cases (52.3%). Presumptive DR-TB criteria, with a high percentage result of medium-high Ct values, were category II treatment failure (80.9%).Conclusion: Relapse case and category II treatment failure are presumptive DR-TB criteria, which need more attention from clinicians.

Progress on diagnosis and treatment of drug-resistant tuberculosis in line with World Health Organization recommendations in six priority countries in the Western Pacific Region.

Diagnosis and treatment of drug-resistant tuberculosis (DR-TB) have radically changed in accordance with recommendations from the World Health Organization (WHO) in the past decade, allowing rapid and simple diagnosis and shorter treatment duration with new and repurposed drugs. A descriptive analysis of the status and progress of DR-TB diagnosis and treatment in six priority countries in the Western Pacific Region was conducted using information from interviews with countries and the WHO TB database. Over the past decade, the use of Xpert MTB/RIF has increased in the six priority countries, in parallel with implementation of national policies and algorithms to use Xpert MTB/RIF as an initial diagnostic test for TB and detection of rifampicin resistance. This has resulted in increases in the number of people diagnosed with multidrug-resistant or rifampicin-resistant TB (MDR/RR-TB). Shorter treatment regimens with new and repurposed drugs have also been adopted for MDR/RR-TB cases, alongside a decentralized model of care, leading to improved treatment outcomes. The Western Pacific Region has achieved considerable progress in the diagnosis and treatment of DR-TB, in line with the evolving WHO recommendations in the past decade. The continued commitment of Member States is needed to address remaining challenges, such as the impact of the coronavirus disease pandemic, suboptimal management and health system issues.

CRISPR-Based Diagnostics: A Potential Tool to Address the Diagnostic Challenges of Tuberculosis.

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis, which infects more than 23% of the world’s population. With the emergence of drug-resistant TB (DR-TB) and latent TB infection (LTBI), rapid diagnosis of DR-TB and LTBI has become a challenge for the prevention and control of TB. Herein, we highlight these challenges and discuss emerging clustered regularly interspaced short palindromic repeats (CRISPR)-based diagnostics in TB detection. Currently, the clinical diagnosis of M. tuberculosis infection mainly depends on pathogenic and molecular biological methods, including sputum smear, sputum culture, and Xpert. Although CRISPR-based diagnostics have not been applied to the clinical diagnosis of TB, they have shown exciting preponderances in TB diagnosis compared with traditional methods, including higher sensitivity, less sample input, and shorter turnaround time. CRISPR-based diagnostics represent a potential tool to address the challenges and natural weaknesses associated with traditional TB diagnosis methods. Based on the currently available data, we suggest that future CRISPR-based TB diagnostics should be developed in the direction of automation, modularization, diversification, and intelligence. By combining the CRISPR platform with various systems, such as microfluidic chips, droplet microfluidics, electrochemical techniques, and optical systems, the specificity and sensitivity of TB diagnosis may be revolutionized.