Xpert MTB/RIF and Xpert Ultra assays for screening for pulmonary tuberculosis and rifampicin resistance in adults, irrespective of signs or symptoms

Background Tuberculosis is a leading cause of infectious disease‐related death and is one of the top 10 causes of death worldwide. The World Health Organization (WHO) recommends the use of specific rapid molecular tests, including Xpert MTB/RIF or Xpert Ultra, as initial diagnostic tests for the detection of tuberculosis and rifampicin resistance in people with signs and symptoms of tuberculosis. However, the WHO estimates that nearly one‐third of all active tuberculosis cases go undiagnosed and unreported. We were interested in whether a single test, Xpert MTB/RIF or Xpert Ultra, could be useful as a screening test to close this diagnostic gap and improve tuberculosis case detection. Objectives To estimate the accuracy of Xpert MTB/RIF and Xpert Ultra for screening for pulmonary tuberculosis in adults, irrespective of signs or symptoms of pulmonary tuberculosis in high‐risk groups and in the general population. Screening "irrespective of signs or symptoms" refers to screening of people who have not been assessed for the presence of tuberculosis symptoms (e.g. cough). To estimate the accuracy of Xpert MTB/RIF and Xpert Ultra for detecting rifampicin resistance in adults screened for tuberculosis, irrespective of signs and symptoms of pulmonary tuberculosis in high‐risk groups and in the general population. Search methods We searched 12 databases including the Cochrane Infectious Diseases Group Specialized Register, MEDLINE and Embase, on 19 March 2020 without language restrictions. We also reviewed reference lists of included articles and related Cochrane Reviews, and contacted researchers in the field to identify additional studies. Selection criteria Cross‐sectional and cohort studies in which adults (15 years and older) in high‐risk groups (e.g. people living with HIV, household contacts of people with tuberculosis) or in the general population were screened for pulmonary tuberculosis using Xpert MTB/RIF or Xpert Ultra. For tuberculosis detection, the reference standard was culture. For rifampicin resistance detection, the reference standards were culture‐based drug susceptibility testing and line probe assays. Data collection and analysis Two review authors independently extracted data using a standardized form and assessed risk of bias and applicability using QUADAS‐2. We used a bivariate random‐effects model to estimate pooled sensitivity and specificity with 95% credible intervals (CrIs) separately for tuberculosis detection and rifampicin resistance detection. We estimated all models using a Bayesian approach. For tuberculosis detection, we first estimated screening accuracy in distinct high‐risk groups, including people living with HIV, household contacts, people residing in prisons, and miners, and then in several high‐risk groups combined. Main results We included a total of 21 studies: 18 studies (13,114 participants) evaluated Xpert MTB/RIF as a screening test for pulmonary tuberculosis and one study (571 participants) evaluated both Xpert MTB/RIF and Xpert Ultra. Three studies (159 participants) evaluated Xpert MTB/RIF for rifampicin resistance. Fifteen studies (75%) were conducted in high tuberculosis burden and 16 (80%) in high TB/HIV‐burden countries. We judged most studies to have low risk of bias in all four QUADAS‐2 domains and low concern for applicability. Xpert MTB/RIF and Xpert Ultra as screening tests for pulmonary tuberculosis In people living with HIV (12 studies), Xpert MTB/RIF pooled sensitivity and specificity (95% CrI) were 61.8% (53.6 to 69.9) (602 participants; moderate‐certainty evidence) and 98.8% (98.0 to 99.4) (4173 participants; high‐certainty evidence). Of 1000 people where 50 have tuberculosis on culture, 40 would be Xpert MTB/RIF‐positive; of these, 9 (22%) would not have tuberculosis (false‐positives); and 960 would be Xpert MTB/RIF‐negative; of these, 19 (2%) would have tuberculosis (false‐negatives). In people living with HIV (1 study), Xpert Ultra sensitivity and specificity (95% CI) were 69% (57 to 80) (68 participants; very low‐certainty evidence) and 98% (97 to 99) (503 participants; moderate‐certainty evidence). Of 1000 people where 50 have tuberculosis on culture, 53 would be Xpert Ultra‐positive; of these, 19 (36%) would not have tuberculosis (false‐positives); and 947 would be Xpert Ultra‐negative; of these, 16 (2%) would have tuberculosis (false‐negatives). In non‐hospitalized people in high‐risk groups (5 studies), Xpert MTB/RIF pooled sensitivity and specificity were 69.4% (47.7 to 86.2) (337 participants, low‐certainty evidence) and 98.8% (97.2 to 99.5) (8619 participants, moderate‐certainty evidence). Of 1000 people where 10 have tuberculosis on culture, 19 would be Xpert MTB/RIF‐positive; of these, 12 (63%) would not have tuberculosis (false‐positives); and 981 would be Xpert MTB/RIF‐negative; of these, 3 (0%) would have tuberculosis (false‐negatives). We did not identify any studies using Xpert MTB/RIF or Xpert Ultra for screening in the general population. Xpert MTB/RIF as a screening test for rifampicin resistance Xpert MTB/RIF sensitivity was 81% and 100% (2 studies, 20 participants; very low‐certainty evidence), and specificity was 94% to 100%, (3 studies, 139 participants; moderate‐certainty evidence). Authors' conclusions Of the high‐risks groups evaluated, Xpert MTB/RIF applied as a screening test was accurate for tuberculosis in high tuberculosis burden settings. Sensitivity and specificity were similar in people living with HIV and non‐hospitalized people in high‐risk groups. In people living with HIV, Xpert Ultra sensitivity was slightly higher than that of Xpert MTB/RIF and specificity similar. As there was only one study of Xpert Ultra in this analysis, results should be interpreted with caution. There were no studies that evaluated the tests in people with diabetes mellitus and other groups considered at high‐risk for tuberculosis, or in the general population

Diversity of HIV-1 Subtypes and Transmitted Drug-resistance Mutations Among Minority HIV-1 Variants in a Turkish Cohort

Background: The World Health Organization (WHO) recommends the surveillance of transmitted drug resistance mutations (TDRMs) to ensure the effectiveness and sustainability of HIV treatment programs. Objective: Our aim was to determine the TDRMs and evaluate the distribution of HIV-1 subtypes using and compared next-generation sequencing (NGS) and Sanger-based sequencing (SBS) in a cohort of 44 antiretroviral treatment-naïve patients. Methods: All samples that were referred to the microbiology laboratory for HIV drug resistance analysis between December 2016 and February 2018 were included in the study. After exclusions, 44 treatment-naive adult patients with a viral load of &gt;1000 copies/mL were analyzed. DNA sequencing for reverse transcriptase and protease regions was performed using both DeepChek ABL single round kit and Sanger-based ViroSeq HIV-1 Genotyping System. The mutations and HIV-1 subtypes were analyzed using the Stanford HIVdb version 8.6.1 Genotypic Resistance software, and TDRMs were assessed using the WHO surveillance drug-resistance mutation database. HIV-1 subtypes were confirmed by constructing a maximum-likelihood phylogenetic tree using Los Alamos IQ-Tree software. Results: NGS identified nucleos(t)ide reverse transcriptase inhibitor (NRTI)-TDRMs in 9.1 % of the patients, non-nucleos(t)ide reverse transcriptase inhibitor (NNRTI)-TDRMs in 6.8 % of the patients, and protease inhibitor (PI)-TDRMs in 18.2 % of the patients at a detection threshold of ≥ 1 %. Using SBS, 2.3 % and 6.8 % of the patients were found to have NRTI- and NNRTI-TDRMs, respectively, but no major PI mutations were detected. M41L, L74I, K65R, M184V, and M184I related to NRTI, K103N to NNRTI, and N83D, M46I, I84V, V82A, L24I, L90M, I54V to the PI sites were identified using NGS. Most mutations were found in low-abundance (frequency range: 1.0 % - 4.7 %) HIV-1 variants, except M41L and K103N. The subtypes of the isolates were found as follows; 61.4 % subtype B, 18.2 % subtype B/CRF02_AG recombinant, 13.6 % subtype A, 4.5 % CRF43_ 02G, and 2.3 % CRF02_AG. All TDRMs, except K65R, were detected in HIV-1 subtype B isolates. Conclusion: The high diversity of protease site TDRMs in the minority HIV-1 variants and prevalence of CRFs were remarkable in this study. All minority HIV-1 variants were missed by conventional sequencing. TDRM prevalence among minority variants appears to be decreasing over time at our center. </jats:sec

One-Year Post-Vaccination Longitudinal Follow-Up of Quantitative SARS-CoV-2 Anti-Spike Total Antibodies in Health Care Professionals and Evaluation of Correlation with Surrogate Neutralization Test

Numerous vaccines have been generated to decrease the morbidity and mortality of COVID-19. This study aims to evaluate the immunogenicity of the heterologous boosts by BioNTech against homologous boosts by CoronaVac at three-month intervals in two health care worker (HCW) cohorts, with or without prior COVID-19, for one year post-vaccination. This is a prospective cohort study in which the humoral responses of 386 HCWs were followed-up longitudinally in six main groups according to their previous COVID-19 exposure and vaccination status. Anti-SARS-CoV-2 spike-RBD total antibody levels were measured and SARS-CoV-2 neutralization antibody (NAbs) responses against the ancestral Wuhan and the Omicron variant were evaluated comparatively using international standard serum for Wuhan and Omicron, as well as with the aid of a conversion tool. The anti-SARS-CoV-2 spike-RBD total Ab and Nab difference between with and without prior COVID-19, three months after two-dose primary vaccination with CoronaVac, was statistically significant (p = 0.001). In the subsequent follow-ups, this difference was not observed between the groups. Those previously infected (PI) and non-previously infected (NPI) groups receiving BioNTech as the third dose had higher anti-SARS-CoV-2 spike total Ab levels (14.2-fold and 17.4-fold, respectively, p = 0.001) and Nab responses (against Wuhan and Omicron) than those receiving CoronaVac. Ab responses after booster vaccination decreased significantly in all groups at the ninth-month follow-up (p < 0.05); however, Abs were still higher in all booster received groups than that in the primary vaccination. Abs were above the protective level at the twelfth-month measurement in the entire of the second BioNTech received group as the fourth dose of vaccination. In the one-year follow-up period, the increased incidence of COVID-19 in the groups vaccinated with two or three doses of CoronaVac compared with the groups vaccinated with BioNTech as a booster suggested that continuing the heterologous CoronaVac/BioNTech vaccination, revised according to current SARS-CoV-2 variants and with at least a six-month interval booster would be an effective and safe strategy for protection against COVID-19, particularly in health care workers

Evaluation of the Two Different Real Time Polymerase Chain Reaction Methods Used for BK Virus (BKV) Quantification and BKV Genotype Assignment

BK virus (BKV) viral load quantification has a distinct role in the clinical control of BKV nephropathy and organ rejection among renal transplant recipients. In this study, it was aimed to compare BKV DNA measurement values performed with two different real-time polymerase chain reaction (PCR) methods and to determine BKV genotypes in renal transplant recipients. Totally, 150 clinical samples tested previously in two different laboratories (Lab-1 and Lab-2) from adult and pediatric renal transplantation patients were included in the study. Fifty plasma samples of 50 different patients from Lab-1, 50 plasma and 50 urine samples of 58 different patients from Lab-2 were included in the study. Viral nucleic acid extraction was performed with automatized systems in Lab-1 and Lab-2 (EZ1, Qiagen, Germany and MagNA Pure 96, Roche Diagnostics, Germany; respectively;). Real-time PCR procedure was carried out in Lab-1 with an amplification mixture of primer, probe sequences targeting VP-1 gene region using RotorGene (Qiagen, Germany) and in Lab-2 with an amplification mixture of primer, probe sequences targeting VP-2 gene region using ABI Prism 7500 (Applied Biosystems, USA). BKV genotyping was performed with multiplex PCR using primer, probe sequences for BKV genotypes I-IV. In both of the laboratories, 82 (54.6%) of the samples were found as positive, 37(24.6%) samples were found as negative and a moderate agreement was found between qualitative results of two real-time PCR methods (k= 0.56, p<0.001). Median viral load values were 4.1 x 10(4) copies/ml (321-6 x 10(9)) in Lab-1 and 3.3 x 10(5) copies/ml (224-8.3 x 10(10)) in Lab-2 for positive samples. According to the lineer regression analysis of quantitative results, moderate (R-2 = 0.52, p<0.001) and high (R-2 = 0.88, p<0.001) correlation was found for plasma (n= 52) and urine (n= 30) samples, respectively. Bland-Altman analysis yielded a mean difference of -0.58 log(10) for all samples. For plasma samples mean difference was -0.29 log(10), while it was -1.1 log(10 )for urine samples. In all samples, Lab-1 measurements were lower than Lab-2 measurements. A mean difference of -1.1 log(10) indicated that the measurement values of Lab-2 were more higher than Lab-1 measurments with an average of 1.1 log(10). Supporting this result, 71.9% of the samples had a measurement difference more than 0.5 log 10 and 29.2% of the samples had a measurement difference more than 1 log(10). Only 28.1% of the samples were measured within clinically acceptable log difference range (less than 0.5 log(10)). BKV genotyping was performed only for 74 different patient samples with sufficient copy numbers and genotype I (81.7%), IV (15.5%), II (1.4%), I+IV (1.4%) were detected. When the results were compared; 66.6% (n= 12) of the genotype IV samples had more than 1 log(10) and 83.3% of them had more than 0.5 log(10) viral load measurement difference. Correlation and linear regression analyzes were insufficient for the comparison of the results of the two different tests. It will be appropriate for each center to monitor patients with the same test until the international BKV standard developed by the World Health Organization is optimized. The clinical correlation of the tests is limited to the currently used test. The result of incorrect BKV quantification affects the clinical decision. Measurements less than the actual value will lead to the development of BKV nephropathy, and higher measurements will lead to unnecessary allograft biopsy and unnecessary reduction of immunosuppression