Association of Pluslife MiniDock MTB time-to-positivity with tuberculosis bacterial load: a diagnostic study in Indonesia
Korompis, M.; Veeken, L. D.; Hartati, S.; Fatma, Z. H.; Chaidir, L.; Eristiana, N.; Setiabudiawan, T.; van Ingen, J.; van Crevel, R.; Hill, P. C.; Houben, R. M. G. J.; Alisjahbana, B.; Koesoemadinata, R. C.
Show abstract
Objectives: The near point-of-care (nPOC) Pluslife MiniDock MTB (MiniDock) assay does not report semiquantitative values. We evaluated whether categorized MiniDock time-to-positivity (TTP) serves as a quantitative proxy for Mycobacterium tuberculosis (Mtb) bacterial load. Methods: Presumptive tuberculosis (TB) patients enrolled across 27 health facilities in Indonesia were tested with sputum GeneXpert MTB/RIF Ultra (Xpert), MiniDock sputum swabs, and tongue swabs. Positive results were categorized using a median split at 13 minutes ([≤]13, 13-25, and 25 minute). MiniDock TTP categories were evaluated against Xpert semiquantitative grades and BACTEC MGIT 960 liquid culture TTP (days). Results: Of 2974 presumptive TB participants tested with sputum Xpert, 426 (14.3%) were sputum Xpert-positive. MiniDock detected Mtb in 248/299 (83.0%) sputum and 263/382 (68.8%) tongue swab. Among 248 Minidock sputum-positive results, 99 (39.9%) turned positive [≤]13 minutes, 107 (43.1%) between 13 and 25 minutes, and 42 (16.9%) at 25 minutes. Minidock TTP categories correlated with sputum and tongue swab semiquantitative results as well as with culture time to positivity (p<0.001). Conclusions: MiniDock TTP categories ([≤]13, 13-25, 25 minutes) provide meaningful stratification which correlates with both Xpert semiquantitative and culture TTP. Time to Positivity from nPOC could thus serve as a proxy for bacterial burden and infectiousness, strongly increasing its utility for clinical care, public health and research.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Comparison of tests done, and Tuberculosis cases detected by Xpert® MTB/RIF and Xpert® MTB/RIF-Ultra in Uganda 96%
- High Proportion of RR-TB and mutations conferring RR outside of the RRDR of the rpoB gene detected in GeneXpert MTB/RIF assay positive pulmonary tuberculosis cases, in Addis Ababa, Ethiopia 96%
- The Pattern of rpoB gene mutation of Mycobacterium tuberculosis and predictors of rifampicin resistance detected by gene Xpert MTB/Rif in Tanzania 96%
Similar papers in this journal
- Diagnostic accuracy study of a novel blood-based assay for identification of TB in people living with HIV 96%
- Direct thin-layer agar for bedaquiline-susceptibility testing of Mycobacterium tuberculosis at BSL2 level yields high accuracy in 15 days from sputum processing. 95%
- Accuracy of tongue swab testing using Xpert MTB-RIF Ultra for tuberculosis diagnosis 95%
Similar papers in this journal
- Diagnostic accuracy study of the multiplex Truenat MTB Ultima/COVID-19 assay for simultaneous detection of Tuberculosis and SARS-CoV2 (COVID-19) 95%
- Association of Human Cytomegalovirus exposure with tuberculosis disease in South African adults with presumptive tuberculosis 94%
- Healthcare seeking behavior and delays in case of drug-resistant Tuberculosis patients in Bangladesh: Findings from a cross-sectional survey 94%
Similar papers in this journal
- Feasibility and Sensitivity of Saliva GeneXpert MTB/RIF Ultra for Tuberculosis Diagnosis in Adults in Uganda 95%
- Development of a multiplex real-time PCR assay for BCG and validation in a clinical laboratory 94%
- Distribution, Prevalence of Non-Tuberculous Mycobacteria in Hainan Island and Antibiotic Resistance of Mycobacterium abscessus 93%
Similar papers in this journal
- Acceptable Performance of the Abbott ID NOW Among Symptomatic Individuals with Confirmed COVID-19 91%
- Microcolonies: a novel morphological form of pathogenic Mycoplasma spp 91%
- False-positive detection of Group B Streptococcus (GBS) in chromogenic media due to presence of Enterococcus faecalis in High Vaginal Swabs 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.