Clinical Profile of HIV/AIDS-infected Patients Admitted to a New Specialist Unit in Dhaka, Bangladesh\u2014A Low-prevalence Country for HIV

This paper describes the clinical features of a series of patients admitted to the specialist HIV/AIDS unit (Jagori) of the Dhaka Hospital, ICDDR,B (International Centre for Diarrhoeal Disease Research, Bangladesh) during May 2008\u2013February 2010. Data were collected from a review of documents and electronic case-records and collation of laboratory results with respect to CD4 counts. One hundred and nine patients were admitted during this period. Their mean age was 33.4 years, and 62% were male. On admission, the mean CD4 count\ub1standard deviation (SD) was 244\ub1245 (range 2-1,549). The death rate was 12%. The patients were classified as World Health Organization clinical stage 1: 23%, stage 2: 30%, stage 3: 23%, and stage 4: 24% during the admission. The commonest diagnosis recorded was tuberculosis (TB) (23%), which was also the commonest cause of death (38%). Even for those clinicians with limited experience of managing AIDS cases, the commonest problem encountered in this patient group was TB, reflecting the continued high burden of TB on health services in Bangladesh. Additional challenges to managing TB/HIV co-infection include atypical presentations in HIV-infected persons and the complex drug interaction with antiretroviral therapy

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 pre-defined targets supporting the current recommendations for ETA deprioritization

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

Genomics, social media and mobile phone data enable mapping of SARS-CoV-2 lineages to inform health policy in Bangladesh.

Genomics, combined with population mobility data, used to map importation and spatial spread of SARS-CoV-2 in high-income countries has enabled the implementation of local control measures. Here, to track the spread of SARS-CoV-2 lineages in Bangladesh at the national level, we analysed outbreak trajectory and variant emergence using genomics, Facebook 'Data for Good' and data from three mobile phone operators. We sequenced the complete genomes of 67 SARS-CoV-2 samples (collected by the IEDCR in Bangladesh between March and July 2020) and combined these data with 324 publicly available Global Initiative on Sharing All Influenza Data (GISAID) SARS-CoV-2 genomes from Bangladesh at that time. We found that most (85%) of the sequenced isolates were Pango lineage B.1.1.25 (58%), B.1.1 (19%) or B.1.36 (8%) in early-mid 2020. Bayesian time-scaled phylogenetic analysis predicted that SARS-CoV-2 first emerged during mid-February in Bangladesh, from abroad, with the first case of coronavirus disease 2019 (COVID-19) reported on 8 March 2020. At the end of March 2020, three discrete lineages expanded and spread clonally across Bangladesh. The shifting pattern of viral diversity in Bangladesh, combined with the mobility data, revealed that the mass migration of people from cities to rural areas at the end of March, followed by frequent travel between Dhaka (the capital of Bangladesh) and the rest of the country, disseminated three dominant viral lineages. Further analysis of an additional 85 genomes (November 2020 to April 2021) found that importation of variant of concern Beta (B.1.351) had occurred and that Beta had become dominant in Dhaka. Our interpretation that population mobility out of Dhaka, and travel from urban hotspots to rural areas, disseminated lineages in Bangladesh in the first wave continues to inform government policies to control national case numbers by limiting within-country travel

Pulmonary Tuberculosis and Drug Resistance in Dhaka Central Jail, the Largest Prison in Bangladesh

There are limited data on TB among prison inmates in Bangladesh. The aim of the study was to determine the prevalence of pulmonary tuberculosis (TB), its drug resistance and risk factors in Dhaka Central Jail, the largest prison in Bangladesh.Cross sectional survey with, active screening of a total number of 11,001 inmates over a period of 2 years. Sputum samples from TB suspects were taken for acid- fast bacilli (AFB) microscopy, culture and drug susceptibility testing. (5.37, 4.02–7.16).The study results revealed a very high prevalence of TB in the prison population in Dhaka Central Jail. Entry examinations and active symptom screening among inmates are important to control TB transmission inside the prison. Identifying undiagnosed smear-negative TB cases remains a challenge to combat this deadly disease in this difficult setting

Estimating the contribution of subclinical tuberculosis disease to transmission: An individual patient data analysis from prevalence surveys.

BACKGROUND: Individuals with bacteriologically confirmed pulmonary tuberculosis (TB) disease who do not report symptoms (subclinical TB) represent around half of all prevalent cases of TB, yet their contribution to Mycobacterium tuberculosis (Mtb) transmission is unknown, especially compared to individuals who report symptoms at the time of diagnosis (clinical TB). Relative infectiousness can be approximated by cumulative infections in household contacts, but such data are rare. METHODS: We reviewed the literature to identify studies where surveys of Mtb infection were linked to population surveys of TB disease. We collated individual-level data on representative populations for analysis and used literature on the relative durations of subclinical and clinical TB to estimate relative infectiousness through a cumulative hazard model, accounting for sputum-smear status. Relative prevalence of subclinical and clinical disease in high-burden settings was used to estimate the contribution of subclinical TB to global Mtb transmission. RESULTS: We collated data on 414 index cases and 789 household contacts from three prevalence surveys (Bangladesh, the Philippines, and Viet Nam) and one case-finding trial in Viet Nam. The odds ratio for infection in a household with a clinical versus subclinical index case (irrespective of sputum smear status) was 1.2 (0.6-2.3, 95% confidence interval). Adjusting for duration of disease, we found a per-unit-time infectiousness of subclinical TB relative to clinical TB of 1.93 (0.62-6.18, 95% prediction interval [PrI]). Fourteen countries across Asia and Africa provided data on relative prevalence of subclinical and clinical TB, suggesting an estimated 68% (27-92%, 95% PrI) of global transmission is from subclinical TB. CONCLUSIONS: Our results suggest that subclinical TB contributes substantially to transmission and needs to be diagnosed and treated for effective progress towards TB elimination. FUNDING: JCE, KCH, ASR, NS, and RH have received funding from the European Research Council (ERC) under the Horizon 2020 research and innovation programme (ERC Starting Grant No. 757699) KCH is also supported by UK FCDO (Leaving no-one behind: transforming gendered pathways to health for TB). This research has been partially funded by UK aid from the UK government (to KCH); however, the views expressed do not necessarily reflect the UK government's official policies. PJD was supported by a fellowship from the UK Medical Research Council (MR/P022081/1); this UK-funded award is part of the EDCTP2 programme supported by the European Union. RGW is funded by the Wellcome Trust (218261/Z/19/Z), NIH (1R01AI147321-01), EDTCP (RIA208D-2505B), UK MRC (CCF17-7779 via SET Bloomsbury), ESRC (ES/P008011/1), BMGF (OPP1084276, OPP1135288 and INV-001754), and the WHO (2020/985800-0)

Development of treatment-decision algorithms for children evaluated for pulmonary tuberculosis: an individual participant data meta-analysis.

Background: Many children with pulmonary tuberculosis remain undiagnosed and untreated with related high morbidity and mortality. Recent advances in childhood tuberculosis algorithm development have incorporated prediction modelling, but studies so far have been small and localised, with limited generalisability. We aimed to evaluate the performance of currently used diagnostic algorithms and to use prediction modelling to develop evidence-based algorithms to assist in tuberculosis treatment decision making for children presenting to primary health-care centres. Methods: For this meta-analysis, we identified individual participant data from a WHO public call for data on the management of tuberculosis in children and adolescents and referral from childhood tuberculosis experts. We included studies that prospectively recruited consecutive participants younger than 10 years attending health-care centres in countries with a high tuberculosis incidence for clinical evaluation of pulmonary tuberculosis. We collated individual participant data including clinical, bacteriological, and radiological information and a standardised reference classification of pulmonary tuberculosis. Using this dataset, we first retrospectively evaluated the performance of several existing treatment-decision algorithms. We then used the data to develop two multivariable prediction models that included features used in clinical evaluation of pulmonary tuberculosis-one with chest x-ray features and one without-and we investigated each model's generalisability using internal-external cross-validation. The parameter coefficient estimates of the two models were scaled into two scoring systems to classify tuberculosis with a prespecified sensitivity target. The two scoring systems were used to develop two pragmatic, treatment-decision algorithms for use in primary health-care settings. Findings: Of 4718 children from 13 studies from 12 countries, 1811 (38·4%) were classified as having pulmonary tuberculosis: 541 (29·9%) bacteriologically confirmed and 1270 (70·1%) unconfirmed. Existing treatment-decision algorithms had highly variable diagnostic performance. The scoring system derived from the prediction model that included clinical features and features from chest x-ray had a combined sensitivity of 0·86 [95% CI 0·68-0·94] and specificity of 0·37 [0·15-0·66] against a composite reference standard. The scoring system derived from the model that included only clinical features had a combined sensitivity of 0·84 [95% CI 0·66-0·93] and specificity of 0·30 [0·13-0·56] against a composite reference standard. The scoring system from each model was placed after triage steps, including assessment of illness acuity and risk of poor tuberculosis-related outcomes, to develop treatment-decision algorithms. Interpretation: We adopted an evidence-based approach to develop pragmatic algorithms to guide tuberculosis treatment decisions in children, irrespective of the resources locally available. This approach will empower health workers in primary health-care settings with high tuberculosis incidence and limited resources to initiate tuberculosis treatment in children to improve access to care and reduce tuberculosis-related mortality. These algorithms have been included in the operational handbook accompanying the latest WHO guidelines on the management of tuberculosis in children and adolescents. Future prospective evaluation of algorithms, including those developed in this work, is necessary to investigate clinical performance. Funding: WHO, US National Institutes of Health

Comparative genomic and phylogeographic analysis of Mycobacterium leprae

Reductive evolution and massive pseudogene formation have shaped the 3.31-Mb genome of Mycobacterium leprae, an unculturable obligate pathogen that causes leprosy in humans. The complete genome sequence of M. leprae strain Br4923 from Brazil was obtained by conventional methods (6 x coverage), and Illumina resequencing technology was used to obtain the sequences of strains Thai53 (38 x coverage) and NHDP63 (46 x coverage) from Thailand and the United States, respectively. Whole-genome comparisons with the previously sequenced TN strain from India revealed that the four strains share 99.995% sequence identity and differ only in 215 polymorphic sites, mainly SNPs, and by 5 pseudogenes. Sixteen interrelated SNP subtypes were defined by genotyping both extant and extinct strains of M. leprae from around the world. The 16 SNP subtypes showed a strong geographical association that reflects the migration patterns of early humans and trade routes, with the Silk Road linking Europe to China having contributed to the spread of leprosy

Comparison of three mycobacterial DNA extraction methods from extrapulmonary samples for PCR assay

Sensitivity of the molecular diagnostic tests of extrapulmonary tuberculosis largely depends upon the efficiency of DNA extraction methods. The objective of our study was to compare three methods of extracting DNA of Mycobacterium tuberculosis for testing by polymerase chain reaction. All three methods; heating, heating with sonication and addition of lysis buffer with heating and sonication were implicated on 20 extrapulmonary samples. PCR positivity was 2 (10%), 4 (20%) and 7 (35%) in the samples extracted by heating, heat+sonication and heat+sonication+lysis buffer method respectively. Of the extraction methods evaluated, maximum PCR positive results were achieved by combined heat, sonication and lysis buffer method which can be applied in routine clinical practice. Ibrahim Med. Coll. J. 2012; 6(1): 9-1

Clinical Profile of HIV/AIDS-infected Patients Admitted to a New Specialist Unit in Dhaka, Bangladesh—A Low-prevalence Country for HIV

This paper describes the clinical features of a series of patients admitted to the specialist HIV/AIDS unit (Jagori) of the Dhaka Hospital, ICDDR,B (International Centre for Diarrhoeal Disease Research, Bangladesh) during May 2008–February 2010. Data were collected from a review of documents and electronic case-records and collation of laboratory results with respect to CD4 counts. One hundred and nine patients were admitted during this period. Their mean age was 33.4 years, and 62% were male. On admission, the mean CD4 count±standard deviation (SD) was 244±245 (range 2-1,549). The death rate was 12%. The patients were classified as World Health Organization clinical stage 1: 23%, stage 2: 30%, stage 3: 23%, and stage 4: 24% during the admission. The commonest diagnosis recorded was tuberculosis (TB) (23%), which was also the commonest cause of death (38%). Even for those clinicians with limited experience of managing AIDS cases, the commonest problem encountered in this patient group was TB, reflecting the continued high burden of TB on health services in Bangladesh. Additional challenges to managing TB/HIV co-infection include atypical presentations in HIV-infected persons and the complex drug interaction with antiretroviral therapy