Potential Application of Digitally Linked Tuberculosis Diagnostics for Real-Time Surveillance of Drug-Resistant Tuberculosis Transmission: Validation and Analysis of Test Results
Bibliographic record
Abstract
BACKGROUND: Tuberculosis (TB) is the highest-mortality infectious disease in the world and the main cause of death related to antimicrobial resistance, yet its surveillance is still paper-based. Rifampicin-resistant TB (RR-TB) is an urgent public health crisis. The World Health Organization has, since 2010, endorsed a series of rapid diagnostic tests (RDTs) that enable rapid detection of drug-resistant strains and produce large volumes of data. In parallel, most high-burden countries have adopted connectivity solutions that allow linking of diagnostics, real-time capture, and shared repository of these test results. However, these connected diagnostics and readily available test results are not used to their full capacity, as we have yet to capitalize on fully understanding the relationship between test results and specific rpoB mutations to elucidate its potential application to real-time surveillance. OBJECTIVE: We aimed to validate and analyze RDT data in detail, and propose the potential use of connected diagnostics and associated test results for real-time evaluation of RR-TB transmission. METHODS: We selected 107 RR-TB strains harboring 34 unique rpoB mutations, including 30 within the rifampicin resistance-determining region (RRDR), from the Belgian Coordinated Collections of Microorganisms, Antwerp, Belgium. We subjected these strains to Xpert MTB/RIF, GenoType MTBDRplus v2.0, and Genoscholar NTM + MDRTB II, the results of which were validated against the strains' available rpoB gene sequences. We determined the reproducibility of the results, analyzed and visualized the probe reactions, and proposed these for potential use in evaluating transmission. RESULTS: The RDT probe reactions detected most RRDR mutations tested, although we found a few critical discrepancies between observed results and manufacturers' claims. Based on published frequencies of probe reactions and RRDR mutations, we found specific probe reactions with high potential use in transmission studies: Xpert MTB/RIF probes A, Bdelayed, C, and Edelayed; Genotype MTBDRplus v2.0 WT2, WT5, and WT6; and Genoscholar NTM + MDRTB II S1 and S3. Inspection of probe reactions of disputed mutations may potentially resolve discordance between genotypic and phenotypic test results. CONCLUSIONS: We propose a novel approach for potential real-time detection of RR-TB transmission through fully using digitally linked TB diagnostics and shared repository of test results. To our knowledge, this is the first pragmatic and scalable work in response to the consensus of world-renowned TB experts in 2016 on the potential of diagnostic connectivity to accelerate efforts to eliminate TB. This is evidenced by the ability of our proposed approach to facilitate comparison of probe reactions between different RDTs used in the same setting. Integrating this proposed approach as a plug-in module to a connectivity platform will increase usefulness of connected TB diagnostics for RR-TB outbreak detection through real-time investigation of suspected RR-TB transmission cases based on epidemiologic linking.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".