Effectiveness and Costs of Identification Pathways for Tuberculosis: Modelling the Impact of Dual Energy X-Ray Technology
Bibliographic record
Abstract
Abstract Background Existing screening methods for TB involve trade-offs among sensitivity, specificity and cost. Recent advances mean that dual-energy X-ray is more sensitive and only slightly more costly than conventional chest X-ray and could be a high-performing alternative for TB screening, particularly if associated computer-aided diagnostic (CAD) software were developed. Methods Existing data on sensitivity,specificity and cost were used for six screening methods (sputum testing, conventional chest X-ray with and without CAD software, dual-energy X-ray with and without CAD software, and nucleic acid amplification testing (NAAT), used in various sequences. Cost and effectiveness of 20 different screening pathwayswere examined using data for Pakistan. Monte-carlo based sensitivity analysis focused on parameters for dual-energy X-ray. Results Sputum followed by NAAT is the best pathway when government budgets are low, and NAAT alone is the best when budgets are unlimited. With intermediate budgets, pathways including dual-energy X-ray dominate those including conventional X-rays, particularly if CAD software is developed for dual-energy X-ray. Conclusions Dual-energy X-ray can be a valuable addition to the screening options for TB. Our study provides different TB screening options for policy makers and TB program managers, which could be used as a guide for planning and implementation of TB screening programs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".