Needle in a haystack: Looking for tuberculosis in a low-incidence setting
Bibliographic record
Abstract
Background: Canada is a low-incidence country for tuberculosis (TB). The BC Public Health Laboratory diagnostic algorithm for pulmonary TB includes acid fast bacilli (AFB) smear and mycobacterial culture of all submitted sputa. TB nucleic acid amplification testing (NAT) is routinely performed on AFB-smear-positive (AFB+) sputa only. We assessed the laboratory-associated costs of implementing the international recommendations for TB NAT on AFB-smear-negative (AFB-) sputa. Methods: Two data sets were obtained: (1) all AFB- samples for a 3-year period (October 1, 2014-September 30, 2017) and (2) all AFB-, TB-culture-positive samples for the same period. One AFB- sample/patient from each defined diagnostic set of sputa was deemed eligible for TB NAT. To stratify patients by ordering location, a 1-year subset of data (October 1, 2016-September 30, 2017) was examined. Results: In the 3-year period, 0.7% of all diagnostic sets were AFB- and culture-positive. In the 1-year period, the provincial TB Services clinics submitted 26% of all AFB- samples received, but these constituted 78% of AFB-, culture-positive samples. Conclusions: The annual cost of TB NAT on one AFB- sputum sample from each eligible diagnostic set would total approximately $247,000. Targeting only TB Services clinic patients would reduce this cost to approximately $64,000/year while capturing more than 75% of AFB-, culture-positive patients. On the basis of our provincial positivity rate, it would cost approximately $6,000 to provide an early TB diagnosis for an AFB-, culture-positive patient. The cost-effectiveness to public health of this approach in a TB low-incidence setting needs to be carefully evaluated.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".