Performance of Xpert MTB/RIF and sputum microscopy compared to sputum culture for diagnosis of tuberculosis in seven hospitals in Indonesia

IntroductionTuberculosis (TB) is a major public health concern in Indonesia, where the incidence was 301 cases per 100,000 inhabitants in 2020 and the prevalence of multi-drug resistant (MDR) TB is increasing. Diagnostic testing approaches vary across Indonesia due to resource limitations. Acid-fast bacilli (AFB) smear is widely used, though Xpert MTB/RIF has been the preferred assay for detecting TB and rifampicin resistance since 2012 due to higher sensitivity and ability to rapidly identify rifampicin resistance. However, <1,000 Xpert instruments were available in Indonesia as of 2020 and the Xpert supply chain has suffered interruptions.MethodsWe compared the performance of Xpert MTB/RIF and AFB smear to facilitate optimization of TB case identification. We analyzed baseline data from a cohort study of adults with pulmonary TB conducted at seven hospitals across Indonesia. We evaluated sensitivity and specificity of AFB smear and Xpert MTB/RIF using Mycobacterium tuberculosis (Mtb) culture as the gold standard, factors associated with assay results, and consistency of Xpert MTB/RIF with drug susceptibility test (DST) in detecting rifampicin resistance.ResultsSensitivity of AFB smear was significantly lower than Xpert MTB/RIF (86.2 vs. 97.4%, p-value <0.001), but specificity was significantly better (86.7 vs. 73.3%, p-value <0.001). Performance varied by hospital. Positivity rate for AFB smear and Mtb culture was higher in subjects with pulmonary cavities and in morning sputum samples. Consistency of Xpert MTB/RIF with DST was lower in those with rifampicin- sensitive TB by DST.DiscussionAdditional evaluation using sputa from primary and secondary Indonesian health centers will increase the generalizability of the assessment of AFB smear and Xpert MTB/RIF performance, and better inform health policy.Clinical trial registration[https://clinicaltrials.gov/], identifier [NCT027 58236]

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use