Pediatric tuberculosis detection using trained African giant pouched rats
Bibliographic record
Abstract
BACKGROUND: Tuberculosis (TB) diagnosis in children is a challenge with up to 94% of children with TB treated empirically in TB high-burden countries. Therefore, new diagnostic tests are needed for TB diagnosis. We determined the performance of trained rats in the diagnosis of pediatric TB and whether they can improve detection rate compared to the standard of care. METHODS: Presumptive TB patients in 24 TB clinics in Tanzania were tested. Samples indicated as TB-positive by rats underwent confirmation by concentrated smear microscopy. TB yield of bacteriologically confirmed pediatric TB patients (≤5 years) was compared with yield of standard of care. RESULTS: Sputum samples from 55,148 presumptive TB patients were tested. Nine hundred eighty-two (1.8%) were the children between 1 and 5 years. Clinics detected 34 bacteriologically positive children, whereas rats detected additional 23 children yielding 57 bacteriologically TB-positive children. Rats increased pediatric TB detection by 67.6%. Among 1-14-year-old children, clinics detected 331 bacteriologically positive TB whereas rats found the additional 208 children with TB that were missed by clinics. Relative increase in TB case detection by rats decreased with the increase in age (P<0.0001). CONCLUSION: Trained rats increase pediatric TB detection significantly and could help address the pediatric TB diagnosis challenges. Further determination of accuracy of rats involving other sample types is still needed.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".