Diagnostic accuracy of Truenat MTB Ultima on sputum for pulmonary tuberculosis diagnosis in an HIV-endemic setting
Bibliographic record
Abstract
OBJECTIVES: Assess Truenat MTB Ultima (Ultima) diagnostic accuracy, alongside standard-of-care Truenat MTB Plus (MTB Plus) and Xpert MTB/RIF Ultra (Ultra) tests, for pulmonary tuberculosis (TB) diagnosis in a high-burden setting. We secondarily evaluated Truenat MTB-RIF Dx (MTB-RIF Dx) on Ultima- or MTB Plus-positive samples for rifampicin susceptibility diagnosis. METHODS: Adults (≥18 years; n = 498) with presumptive TB self-presenting to primary care clinics in Cape Town, South Africa (19/02/2016-22/02/2023) provided sputa. The microbiological reference standard was a single culture for TB and MTBDRplus on an isolate for rifampicin susceptibility. RESULTS: In total, 54% (n = 269) of the participants had HIV, and 42% (n = 210) had previous TB. The proportion of Ultima and MTB Plus unsuccessful results was 14% (95% CI 11, 16) and 20% (17, 23), respectively, with at least half resolving upon retesting the same eluate. In a three-way analysis, Ultima, MTB Plus, and Ultra had TB sensitivities of 90% (85, 93), 84% (78, 88), and 92% (87, 95) and specificities of 85% (80, 88), 95% (92, 97), and 95% (92, 97). Ultima specificity did not improve with Ultra in the reference standard. MTB-RIF Dx had high unsuccessful result rates that varied if done on the day of DNA extraction or on Ultima- [18% (10, 26) vs. 44% (35, 51) if after day of extraction] or MTB Plus-positive eluates [9% (3, 16) vs. 27% (18, 35)]. Same day rifampicin susceptibility testing was often unsuccessful in samples with the "very low" semiquantitation category reported by Ultima [75% (65, 86)] or MTB Plus [73% (58, 89)] but had 100% (40, 100) sensitivity and 99% (96, 100) specificity (on both MTB Plus- or Ultima-positive DNA). Reagent lot variation in unsuccessful and false positive results was observed. DISCUSSION: Ultima met the minimum sensitivity recommended by the WHO for TB detection, but specificity, reagent lot variation, and unsuccessful results were suboptimal.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".