Costs of Digital Adherence Technologies for Tuberculosis Treatment Support, 2018-2021.

Digital adherence technologies are increasingly used to support tuberculosis (TB) treatment adherence. Using microcosting, we estimated healthcare system costs (in 2022 US dollars) of 2 digital adherence technologies, 99DOTS medication sleeves and video-observed therapy (VOT), implemented in demonstration projects during 2018-2021. We also obtained cost estimates for standard directly observed therapy (DOT). Estimated per-person costs of 99DOTS for drug-sensitive TB were $98 in Bangladesh (n = 719), $119 in the Philippines (n = 396), and $174 in Tanzania (n = 976). Estimated per-person costs of VOT were $1,154 in Haiti (87 drug-sensitive), $304 in Moldova (173 drug-sensitive), $452 in Moldova (135 drug-resistant), and $661 in the Philippines (110 drug-resistant). 99DOTS costs may be similar to or less expensive than standard DOT. VOT is more expensive, although in some settings, labor cost offsets or economies of scale may yield savings. 99DOTS and VOT may yield savings to local programs if donors cover infrastructure costs.

Pharmacokinetic-Pharmacodynamic Determinants of Clinical Outcomes for Rifampin-Resistant Tuberculosis: A Multisite Prospective Cohort Study.

BACKGROUND: Rifampin-resistant and/or multidrug-resistant tuberculosis (RR/MDR-TB) treatment requires multiple drugs, and outcomes remain suboptimal. Some drugs are associated with improved outcome. It is unknown whether particular pharmacokinetic-pharmacodynamic relationships predict outcome. METHODS: Adults with pulmonary RR/MDR-TB in Tanzania, Bangladesh, and the Russian Federation receiving local regimens were enrolled from June 2016 to July 2018. Serum was collected after 2, 4, and 8 weeks for each drug's area under the concentration-time curve over 24 hours (AUC0-24). Quantitative susceptibility of the M. tuberculosis isolate was measured by minimum inhibitory concentrations (MICs). Individual drug AUC0-24/MIC targets were assessed by adjusted odds ratios (ORs) for favorable treatment outcome, and hazard ratios (HRs) for time to sputum culture conversion. K-means clustering algorithm separated the cohort of the most common multidrug regimen into 4 clusters by AUC0-24/MIC exposures. RESULTS: Among 290 patients, 62 (21%) experienced treatment failure, including 30 deaths. Moxifloxacin AUC0-24/MIC target of 58 was associated with favorable treatment outcome (OR, 3.75; 95% confidence interval, 1.21-11.56; P = .022); levofloxacin AUC0-24/MIC of 118.3, clofazimine AUC0-24/MIC of 50.5, and pyrazinamide AUC0-24 of 379 mg × h/L were associated with faster culture conversion (HR >1.0, P < .05). Other individual drug exposures were not predictive. Clustering by AUC0-24/MIC revealed that those with the lowest multidrug exposures had the slowest culture conversion. CONCLUSIONS: Amidst multidrug regimens for RR/MDR-TB, serum pharmacokinetics and M. tuberculosis MICs were variable, yet defined parameters to certain drugs-fluoroquinolones, pyrazinamide, clofazimine-were predictive and should be optimized to improve clinical outcome. CLINICAL TRIALS REGISTRATION: NCT03559582.

A molecular modelling approach for identifying antiviral selenium-containing heterocyclic compounds that inhibit the main protease of SARS-CoV-2: an in silico investigation.

Coronavirus disease 2019 (COVID-19), an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been declared a global pandemic by the World Health Organization, and the situation worsens daily, associated with acute increases in case fatality rates. The main protease (Mpro) enzyme produced by SARS-CoV-2 was recently demonstrated to be responsible for not only viral reproduction but also impeding host immune responses. The element selenium (Se) plays a vital role in immune functions, both directly and indirectly. Thus, we hypothesised that Se-containing heterocyclic compounds might curb the activity of SARS-CoV-2 Mpro. We performed a molecular docking analysis and found that several of the selected selenocompounds showed potential binding affinities for SARS-CoV-2 Mpro, especially ethaselen (49), which exhibited a docking score of -6.7 kcal/mol compared with the -6.5 kcal/mol score for GC376 (positive control). Drug-likeness calculations suggested that these compounds are biologically active and possess the characteristics of ideal drug candidates. Based on the binding affinity and drug-likeness results, we selected the 16 most effective selenocompounds as potential anti-COVID-19 drug candidates. We also validated the structural integrity and stability of the drug candidate through molecular dynamics simulation. Using further in vitro and in vivo experiments, we believe that the targeted compound identified in this study (ethaselen) could pave the way for the development of prospective drugs to combat SARS-CoV-2 infections and trigger specific host immune responses.

Community based peer-led TB screening intervention: an innovative approach to increase TB knowledge, presumptive case identification, and referral among sexual minority people in urban Bangladesh.

INTRODUCTION: One of the contributors to tuberculosis (TB) burden among vulnerable populations, such as sexual minority people, is the delay in case finding and notification. Given their socially excluded, hard-to-reach nature, community-led approaches need to be introduced to facilitate their screening of TB symptoms and their subsequent referral to TB healthcare providers. This article aimed to explore the existing challenges surrounding TB screening and referral, and the implementation facilitators and barriers of the proposed community-based TB screening model for sexual minority people in Dhaka, Bangladesh. METHODS: This study followed the quasi-experimental design using mixed methods (i.e., qualitative and quantitative) approach. The study participants who were also a part of the community-led TB screening model included sexual minority people enrolled in HIV prevention interventions. In addition to quantitative inquiry, in-depth interviews were conducted on sexual minority people, focus group discussions were also conducted on them and HIV prevention service providers, and key-informant interviews were conducted on service providers, programmatic experts and TB researchers. Data were analyzed using content, contextual and thematic approaches. RESULTS: The 'Six Steps in Quality Intervention Development' framework was used to guide the development of the community-based TB screening model. In Step 1 (identifying the problem), findings revealed low rates of TB screening among sexual minority people enrolled in the HIV prevention intervention. In Step 2 (identifying contextual factors for change), various individual, and programmatic factors were identified, which included low knowledge, low-risk perception, prioritization of HIV services over TB, and stigma and discrimination towards these populations. In Step 3 (deciding change mechanism), community-based screening approaches were applied, thus leading to Step 4 (delivery of change mechanism) which designed a community-based approach leveraging the peer educators of the HIV intervention. Step 5 (testing intervention) identified some barriers and ways forward for refining the intervention, such as home-based screening and use of social media. Step 6 (collecting evidence of effectiveness) revealed that the main strength was its ability to engage peer educators. CONCLUSION: This study indicates that a community-based peer-led TB screening approach could enhance TB screening, presumptive TB case finding and referral among these populations. Therefore, this study recommends that this approach should be incorporated to complement the existing TB program.

Xpert Ultra Assay on Stool to Diagnose Pulmonary Tuberculosis in Children.

BACKGROUND: The World Health Organization recommends the Xpert MTB/RIF Ultra assay for diagnosing pulmonary tuberculosis (PTB) in children. Though stool is a potential alternative to respiratory specimens among children, the diagnostic performance of Xpert Ultra on stool is unknown. Thus, we assessed the diagnostic performance of Xpert Ultra on stool to diagnose PTB in children. METHODS: We conducted a cross-sectional study among consecutively recruited children (< 15 years of age) with presumptive PTB admitted in 4 tertiary care hospitals in Dhaka, Bangladesh, between January 2018 and April 2019. Single induced sputum and stool specimens were subjected to culture, Xpert, and Xpert Ultra. We considered children as bacteriologically confirmed on induced sputum if any test performed on induced sputum was positive for Mycobacterium tuberculosis and bacteriologically confirmed if M. tuberculosis was detected on either induced sputum or stool. RESULTS: Of 447 children, 29 (6.5%) were bacteriologically confirmed on induced sputum and 72 (16.1%) were bacteriologically confirmed. With "bacteriologically confirmed on induced sputum" as a reference, the sensitivity and specificity of Xpert Ultra on stool were 58.6% and 88.1%, respectively. Xpert on stool had sensitivity and specificity of 37.9% and 100.0%, respectively. Among bacteriologically confirmed children, Xpert Ultra on stool was positive in 60 (83.3%), of whom 48 (80.0%) had "trace call." CONCLUSIONS: In children, Xpert Ultra on stool has better sensitivity but lesser specificity than Xpert. A high proportion of Xpert Ultra assays positive on stool had trace call. Future longitudinal studies on clinical evolution are required to provide insight on the management of children with trace call.

Identifying Insomnia From Social Media Posts: Psycholinguistic Analyses of User Tweets.

BACKGROUND: Many people suffer from insomnia, a sleep disorder characterized by difficulty falling and staying asleep during the night. As social media have become a ubiquitous platform to share users' thoughts, opinions, activities, and preferences with their friends and acquaintances, the shared content across these platforms can be used to diagnose different health problems, including insomnia. Only a few recent studies have examined the prediction of insomnia from Twitter data, and we found research gaps in predicting insomnia from word usage patterns and correlations between users' insomnia and their Big 5 personality traits as derived from social media interactions. OBJECTIVE: The purpose of this study is to build an insomnia prediction model from users' psycholinguistic patterns, including the elements of word usage, semantics, and their Big 5 personality traits as derived from tweets. METHODS: In this paper, we exploited both psycholinguistic and personality traits derived from tweets to identify insomnia patients. First, we built psycholinguistic profiles of the users from their word choices and the semantic relationships between the words of their tweets. We then determined the relationship between a users' personality traits and insomnia. Finally, we built a double-weighted ensemble classification model to predict insomnia from both psycholinguistic and personality traits as derived from user tweets. RESULTS: Our classification model showed strong prediction potential (78.8%) to predict insomnia from tweets. As insomniacs are generally ill-tempered and feel more stress and mental exhaustion, we observed significant correlations of certain word usage patterns among them. They tend to use negative words (eg, "no," "not," "never"). Some people frequently use swear words (eg, "damn," "piss," "fuck") with strong temperament. They also use anxious (eg, "worried," "fearful," "nervous") and sad (eg, "crying," "grief," "sad") words in their tweets. We also found that the users with high neuroticism and conscientiousness scores for the Big 5 personality traits likely have strong correlations with insomnia. Additionally, we observed that users with high conscientiousness scores have strong correlations with insomnia patterns, while negative correlation between extraversion and insomnia was also found. CONCLUSIONS: Our model can help predict insomnia from users' social media interactions. Thus, incorporating our model into a software system can help family members detect insomnia problems in individuals before they become worse. The software system can also help doctors to diagnose possible insomnia in patients.

Ethionamide Population Pharmacokinetic Model and Target Attainment in Multidrug-Resistant Tuberculosis.

Ethionamide (ETA), an isonicotinic acid derivative, is part of the multidrug-resistant tuberculosis (MDR-TB) regimen. The current guidelines have deprioritized ETA because it is potentially less effective than other agents. Our aim was to develop a population pharmacokinetic (PK) model and simulate ETA dosing regimens in order to assess target attainment. This study included subjects from four different sites, including healthy volunteers and patients with MDR-TB. The TB centers included were two in the United States and one in Bangladesh. Patients who received ETA and had at least one drug concentration reported were included. The population PK model was developed, regimens with a total of 1,000 to 2,250 mg daily were simulated, and target attainment using published MICs and targets of 1.0-log kill and resistance suppression was assessed with the Pmetrics R package. We included 1,167 ethionamide concentrations from 94 subjects. The final population model was a one-compartment model with first-order elimination and absorption with a lag time. The mean (standard deviation [SD]) final population parameter estimates were as follows: absorption rate constant, 1.02 (1.11) h-1; elimination rate constant, 0.69 (0.46) h-1; volume of distribution, 104.16 (59.87) liters; lag time, 0.43 (0.32) h. A total daily dose of 1,500 mg or more was needed for ≥90% attainment of the 1.0-log kill target at a MIC of 1 mg/liter, and 2,250 mg/day led to 80% attainment of the resistance suppression target at a MIC of 0.5 mg/liter. In conclusion, we developed a population PK model and assessed target attainment for different ETA regimens. Patients may not be able to tolerate the doses needed to achieve the predefined targets supporting the current recommendations for ETA deprioritization.

Pharmacological studies on the antinociceptive, anxiolytic and antidepressant activity of Tinospora crispa.

Pharmacological studies were performed in mice on the methanol extract of Tinospora crispa (TC), and of its hexane (HF) and chloroform (CF) fractions. Significant antinociceptive activity was observed for TC, HF, and CF in the acetic acid-induced writhing and formalin-induced paw licking tests. Anxiolytic and antidepressant activities were assessed using the open field, hole board, and elevated plus maze (EPM) tests. TC, HF, and CF demonstrated a significant decrease in spontaneous locomotor activity. They also showed an increase in the number of head-dippings in the hole-board test, suggesting decreased fearfulness. TC, and most of its fractions, showed a significant increase of the time spent in the opened arm of the EPM, indicating reduced anxiety. This study provides some support to explain the traditional use of T. crispa as a remedy for pain.

Epitope-Based Immunoinformatics Approach on Nucleocapsid Protein of Severe Acute Respiratory Syndrome-Coronavirus-2.

With an increasing fatality rate, severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has emerged as a promising threat to human health worldwide. Recently, the World Health Organization (WHO) has announced the infectious disease caused by SARS-CoV-2, which is known as coronavirus disease-2019 (COVID-2019), as a global pandemic. Additionally, the positive cases are still following an upward trend worldwide and as a corollary, there is a need for a potential vaccine to impede the progression of the disease. Lately, it has been documented that the nucleocapsid (N) protein of SARS-CoV-2 is responsible for viral replication and interferes with host immune responses. We comparatively analyzed the sequences of N protein of SARS-CoV-2 for the identification of core attributes and analyzed the ancestry through phylogenetic analysis. Subsequently, we predicted the most immunogenic epitope for the T-cell and B-cell. Importantly, our investigation mainly focused on major histocompatibility complex (MHC) class I potential peptides and NTASWFTAL interacted with most human leukocyte antigen (HLA) that are encoded by MHC class I molecules. Further, molecular docking analysis unveiled that NTASWFTAL possessed a greater affinity towards HLA and also available in a greater range of the population. Our study provides a consolidated base for vaccine design and we hope that this computational analysis will pave the way for designing novel vaccine candidates.

Cycloserine Population Pharmacokinetics and Pharmacodynamics in Patients with Tuberculosis.

Limited pharmacokinetic/pharmacodynamic (PK/PD) data exist on cycloserine in tuberculosis (TB) patients. We pooled several studies into a large PK data set to estimate the population PK parameters for cycloserine in TB patients. We also performed simulations to provide insight into optimizing the dosing of cycloserine. TB patients were included from Georgia, Bangladesh, and four U.S. sites. Monolix and mlxR package were used for population PK modeling and simulation. We used PK/PD targets for time above MIC of ≥30% and ≥64%, representing bactericidal activity and 80% of the maximum kill, to calculate the probability of target attainment (PTA). Optimal PK/PD breakpoints were defined as the highest MIC to achieve ≥90% of PTA. Data from 247 subjects, including 205 patients with drug-resistant TB, were included. The data were best described by a one-compartment model. In most cases, the PK/PD breakpoints for the simulated regimens were similar for both PK/PD targets. Higher PTA were achieved as the total daily dose was increased. The highest PK/PD breakpoint that resulted from the use of 250 mg dosages was 16 mg/liter. For MICs of >16 mg/liter, doses of at least 500 mg three times daily or 750 mg twice daily were needed. In conclusion, the current dosing for cycloserine, 250 to 500 mg once or twice daily, is not sufficient for MICs of >16mg/liter. Further studies are needed regarding the efficacy and tolerability of daily doses of >1,000 mg. Dividing the dose minimally affected the PK/PD breakpoints while optimizing exposure, which can potentially reduce adverse drug effects.

Fluoroquinolones in Drug-Resistant Tuberculosis: Culture Conversion and Pharmacokinetic/Pharmacodynamic Target Attainment To Guide Dose Selection.

Fluoroquinolones are group A drugs in tuberculosis guidelines. We aim to compare the culture conversion between new-generation (levofloxacin and moxifloxacin) and old-generation (ciprofloxacin and ofloxacin) fluoroquinolones, develop pharmacokinetic models, and calculate target attainment for levofloxacin and moxifloxacin. We included three U.S. tuberculosis centers. Patients admitted between 1984 and 2015, infected with drug-resistant tuberculosis, and who had received fluoroquinolones for ≥28 days were included. Demographics, sputum cultures and susceptibility, treatment regimens, and serum concentrations were collected. A time-to-event analysis was conducted, and Cox proportional hazards model was used to compare the time to culture conversion. Using additional data from ongoing studies, pharmacokinetic modelling and Monte Carlo simulations were performed to assess target attainment for different doses. Overall, 124 patients received fluoroquinolones. The median age was 40 years, and the median weight was 60 kg. Fifty-six patients (45%) received old-generation fluoroquinolones. New-generation fluoroquinolones showed a faster time to culture conversion (median 16 versus 40 weeks, P = 0.012). After adjusting for isoniazid and clofazimine treatment, patients treated with new-generation fluoroquinolones were more likely to have culture conversion (adjusted hazards ratio, 2.16 [95% confidence interval, 1.28 to 3.64]). We included 178 patients in the pharmacokinetic models. Levofloxacin and moxifloxacin were best described by a one-compartment model with first-order absorption and elimination. At least 1,500 to 1,750 mg levofloxacin and 800 mg moxifloxacin may be needed for maximum kill at the current epidemiologic cutoff values. In summary, new-generation fluoroquinolones showed faster time to culture conversion compared to the old generation. For optimal target attainment at the current MIC values, higher doses of levofloxacin and moxifloxacin may be needed.

Pyrazinamide Susceptibility and pncA Mutation Profiles of Mycobacterium tuberculosis among Multidrug-Resistant Tuberculosis Patients in Bangladesh.

Pyrazinamide (PZA) is a frontline antituberculosis (anti-TB) drug used in both first- and second-line treatment regimens. However, due to complex laboratory requirements, the PZA susceptibility test is rarely performed, leading to a scarcity of data on susceptibility to PZA. Bangladesh is a country with a burden of high rates of both TB and multidrug-resistant TB (MDR-TB), but to our knowledge, published data on rates of PZA susceptibility (PZAs), especially among MDR-TB patients, are limited. We aimed to analyze the PZA susceptibility patterns of Mycobacterium tuberculosis isolates from MDR-TB patients and to correlate the pncA mutation with PZA resistance in Bangladesh. A total of 169 confirmed MDR M. tuberculosis isolates from a pool of specimens collected in a nationwide surveillance study were included in this analysis. All the isolates were tested for phenotypic PZA susceptibility in Bactec mycobacterial growth indicator tube (MGIT) culture medium, and the pncA gene was sequenced. We also correlated different types of clinical information and treatment outcomes with PZA susceptibility. We found that 45% of isolates were phenotypically PZA resistant. Sequencing of the pncA gene revealed a high concordance (82.2%) between the pncA gene sequence and the phenotypic assay results. A total of 64 different mutations were found, and 9 isolates harbored multiple mutations. We detected 27 new pncA mutations. We did not find any significant correlation between the different clinical categories, the genetic lineage, or treatment outcome group and PZA susceptibility. Considering the turnaround time, sequencing would be the more feasible option to determine PZA susceptibility, and further studies to investigate the MIC of PZA should be conducted to determine an effective dose of the drug.

Evaluation of community-based treatment for drug-resistant tuberculosis in Bangladesh.

OBJECTIVE: Drug-resistant tuberculosis (TB) threatens global TB control because it is difficult to diagnose and treat. Community-based programmatic management of drug-resistant TB (cPMDT) has made therapy easier for patients, but data on these models are scarce. Bangladesh initiated cPMDT in 2012, and in 2013, we sought to evaluate programme performance. METHODS: In this retrospective review, we abstracted demographic, clinical, microbiologic and treatment outcome data for all patients enrolled in the cPMDT programme over 6 months in three districts of Bangladesh. We interviewed a convenience sample of patients about their experience in the programme. RESULTS: Chart review was performed on 77 patients. Sputum smears and cultures were performed, on average, once every 1.35 and 1.36 months, respectively. Among 74 initially culture-positive patients, 70 (95%) converted their cultures and 69 (93%) patients converted the cultures before the sixth month. Fifty-two (68%) patients had evidence of screening for adverse events. We found written documentation of musculoskeletal complaints for 16 (21%) patients, gastrointestinal adverse events for 16 (21%), hearing loss for eight (10%) and psychiatric events for four (5%) patients; conversely, on interview of 60 patients, 55 (92%) reported musculoskeletal complaints, 54 (90%) reported nausea, 36 (60%) reported hearing loss, and 36 (60%) reported psychiatric disorders. CONCLUSIONS: The cPMDT programme in Bangladesh appears to be programmatically feasible and clinically effective; however, inadequate monitoring of adverse events raises some concern. As the programme is brought to scale nationwide, renewed efforts at monitoring adverse events should be prioritised.

Discordance across several methods for drug susceptibility testing of drug-resistant Mycobacterium tuberculosis isolates in a single laboratory.

Given the increases in drug-resistant tuberculosis, laboratory capacities for drug susceptibility testing are being scaled up worldwide. A laboratory must decide among several endorsed methodologies. We evaluated 87 Mycobacterium tuberculosis isolates for concordance of susceptibility results across six methods: the L-J proportion method, MGIT 960 SIRE AST, Gene/Xpert MTB/RIF, GenoType MTBDRplus line probe assay, MycoTB MIC plate, and a laboratory-developed mycobacteriophage quantitative PCR (qPCR)-based method. Most (80%) isolates were multidrug resistant. Of the culture-based methods, the mycobacteriophage qPCR method was fastest, the L-J proportion method was the slowest, and the MGIT method required the most repeat testing (P < 0.05). For isoniazid (INH), 82% of isolates were susceptible by all methods or resistant by all methods, whereas for rifampin (RIF), ethambutol (EMB), and streptomycin (STR), such complete concordance was observed in 77%, 50%, and 51% of isolates, respectively (P < 0.05 for INH or RIF versus EMB or STR). The discrepancies of EMB and STR stemmed largely from diminished concordance of the MGIT EMB results (kappa coefficient range, 0.26 to 0.30) and the L-J STR result (kappa range, 0.35 to 0.45) versus other methods. Phage qPCR and the MycoTB MIC plate were the only methods that yielded second-line susceptibilities and revealed significant quantitative correlations for all drugs except cycloserine, as well as moderate to excellent kappa coefficients for all drugs except for para-aminosalicylic acid. In summary, the performance of M. tuberculosis susceptibility testing differs by platform and by drug. Laboratories should carefully consider these factors before choosing one methodology, particularly in settings where EMB and STR results are clinically important.

Thermal imaging and computer vision technologies for the enhancement of pig husbandry: a review.

Pig farming, a vital industry, necessitates proactive measures for early disease detection and crush symptom monitoring to ensure optimum pig health and safety. This review explores advanced thermal sensing technologies and computer vision-based thermal imaging techniques employed for pig disease and piglet crush symptom monitoring on pig farms. Infrared thermography (IRT) is a non-invasive and efficient technology for measuring pig body temperature, providing advantages such as non-destructive, long-distance, and high-sensitivity measurements. Unlike traditional methods, IRT offers a quick and labor-saving approach to acquiring physiological data impacted by environmental temperature, crucial for understanding pig body physiology and metabolism. IRT aids in early disease detection, respiratory health monitoring, and evaluating vaccination effectiveness. Challenges include body surface emissivity variations affecting measurement accuracy. Thermal imaging and deep learning algorithms are used for pig behavior recognition, with the dorsal plane effective for stress detection. Remote health monitoring through thermal imaging, deep learning, and wearable devices facilitates non-invasive assessment of pig health, minimizing medication use. Integration of advanced sensors, thermal imaging, and deep learning shows potential for disease detection and improvement in pig farming, but challenges and ethical considerations must be addressed for successful implementation. This review summarizes the state-of-the-art technologies used in the pig farming industry, including computer vision algorithms such as object detection, image segmentation, and deep learning techniques. It also discusses the benefits and limitations of IRT technology, providing an overview of the current research field. This study provides valuable insights for researchers and farmers regarding IRT application in pig production, highlighting notable approaches and the latest research findings in this field.

SalivaDirect: an alternative to a conventional RNA extraction protocol for molecular detection of SARS-CoV-2 in a clinical setting.

IMPORTANCE: Affordable and accessible tests for COVID-19 allow for timely disease treatment and pandemic management. SalivaDirect is a faster and easier method to implement than NPS sampling. Patients can self-collect saliva samples at home or in other non-clinical settings without the help of a healthcare professional. Sample processing in SalivaDirect is less complex and more adaptable than in conventional nucleic acid extraction methods. We found that SalivaDirect has good diagnostic performance and is ideal for large-scale testing in settings where supplies may be limited or trained healthcare professionals are unavailable.

Expanding molecular diagnostic coverage for tuberculosis by combining computer-aided chest radiography and sputum specimen pooling: a modeling study from four high-burden countries.

Background: In 2022, fewer than half of persons with tuberculosis (TB) had access to molecular diagnostic tests for TB due to their high costs. Studies have found that the use of artificial intelligence (AI) software for chest X-ray (CXR) interpretation and sputum specimen pooling can each reduce the cost of testing. We modeled the combination of both strategies to estimate potential savings in consumables that could be used to expand access to molecular diagnostics. Methods: We obtained Xpert testing and positivity data segmented into deciles by AI probability scores for TB from the community- and healthcare facility-based active case finding conducted in Bangladesh, Nigeria, Viet Nam, and Zambia. AI scores in the model were based on CAD4TB version 7 (Zambia) and qXR (all other countries). We modeled four ordinal screening and testing approaches involving AI-aided CXR interpretation to indicate individual and pooled testing. Setting a false negative rate of 5%, for each approach we calculated additional and cumulative savings over the baseline of universal Xpert testing, as well as the theoretical expansion in diagnostic coverage. Results: In each country, the optimal screening and testing approach was to use AI to rule out testing in deciles with low AI scores and to guide pooled vs individual testing in persons with moderate and high AI scores, respectively. This approach yielded cumulative savings in Xpert tests over baseline ranging from 50.8% in Zambia to 57.5% in Nigeria and 61.5% in Bangladesh and Viet Nam. Using these savings, diagnostic coverage theoretically could be expanded by 34% to 160% across the different approaches and countries. Conclusions: Using AI software data generated during CXR interpretation to inform a differentiated pooled testing strategy may optimize TB diagnostic test use, and could extend molecular tests to more people who need them. The optimal AI thresholds and pooled testing strategy varied across countries, which suggests that bespoke screening and testing approaches may be needed for differing populations and settings. Supplementary Information: The online version contains supplementary material available at 10.1186/s44263-024-00081-2.

Xpert MTB/RIF Ultra for the rapid diagnosis of extrapulmonary tuberculosis in a clinical setting of high tuberculosis prevalence country and interpretation of 'trace' results.

To evaluate the diagnostic performance of Xpert MTB/RIF Ultra (Ultra) for the diagnosis of extrapulmonary tuberculosis (EPTB) from different types of extrapulmonary specimens in comparison with culture and composite microbiological reference standard (CRS). A total of 240 specimens were prospectively collected from presumptive EPTB patients between July 2021-January 2022 and tested by Ultra, Xpert, culture and acid-fast bacilli (AFB) smear microscopy. Out of 240 specimens, 35.8 %, 20.8 %, 11.3 %, and 7.1 % were detected as Mycobacterium tuberculosis complex by Ultra, Xpert, culture and AFB microscopy, respectively. An additional 15.0 % cases were detected by Ultra compared to Xpert MTB/RIF (Xpert) assay. A total of 28 (11.7 %) cases were identified as 'trace' category by Ultra with indeterminate rifampicin resistance result; of which 36.4 % were clinically confirmed as EPTB. Compared to culture, the sensitivity and specificity of Ultra and Xpert were 100 % and 72.3 %; 92.6 % and 88.3 %, respectively. In comparison with CRS, these were respectively: 98.9 % and 100 %; 57.5 % and 100 %. For individual category of specimens, sensitivity of Ultra was 100 % with varying specificity. We found that Ultra was highly sensitive for the rapid diagnosis of EPTB and has extensive potential over current diagnostics in high TB burden countries, but 'trace' results should be interpreted with caution.

Targeted next-generation sequencing of Mycobacterium tuberculosis from patient samples: lessons learned from high drug-resistant burden clinical settings in Bangladesh.

Lack of appropriate early diagnostic tools for drug-resistant tuberculosis (DR-TB) and their incomplete drug susceptibility testing (DST) profiling is concerning for TB disease control. Existing methods, such as phenotypic DST (pDST), are time-consuming, while Xpert MTB/RIF (Xpert) and line probe assay (LPA) are limited to detecting resistance to few drugs. Targeted next-generation sequencing (tNGS) has been recently approved by WHO as an alternative approach for rapid and comprehensive DST. We aimed to investigate the performance and feasibility of tNGS for detecting DR-TB directly from clinical samples in Bangladesh. pDST, LPA and tNGS were performed among 264 sputum samples, either rifampicin-resistant (RR) or rifampicin-sensitive (RS) TB cases confirmed by Xpert assay. Resistotypes of tNGS were compared with pDST, LPA and composite reference standard (CRS, resistant if either pDST or LPA showed a resistant result). tNGS results revealed higher sensitivities for rifampicin (RIF) (99.3%), isoniazid (INH) (96.3%), fluoroquinolones (FQs) (94.4%), and aminoglycosides (AMGs) (100%) but comparatively lower for ethambutol (76.6%), streptomycin (68.7%), ethionamide (56.0%) and pyrazinamide (50.7%) when compared with pDST. The sensitivities of tNGS for INH, RIF, FQs and AMGs were 93.0%, 96.6%, 90.9%, and 100%, respectively and the specificities ranged from 91.3 to 100% when compared with CRS. This proof of concept study, conducted in a high-burden setting demonstrated that tNGS is a valuable tool for identifying DR-TB directly from the clinical specimens. Its feasibility in our laboratory suggests potential implementation and moving tNGS from research settings into clinical settings.