Effective screening tool to triage recovery rooms for possible tuberculosis patients undergoing bronchoscopy
Bibliographic record
Abstract
SETTING: In 2005, tuberculin skin test conversions were observed following exposure to a patient with active pulmonary tuberculosis (TB) who recovered post-bronchoscopy in an open area at The Ottawa Hospital, Canada. In response, we implemented a screening tool to triage patients to an airborne infection isolation (AII) room pre- and post-bronchoscopy. OBJECTIVE: To evaluate the performance of the screening tool in detecting patients with culture-confirmed TB. DESIGN: All bronchoscopies performed between 1 March 2006 and 31 March 2010 were retrospectively reviewed. RESULTS: Of 1839 patients included (55.3% of bronchoscopies), 210 screened positive, capturing 28 culture-confirmed TB cases. Three patients with positive TB cultures screened negative. The sensitivity of the screening tool was 90.3%; the negative predictive value was 99.8%. A positive screening result was strongly predictive of a positive TB culture. CONCLUSIONS: The screening tool is effective for identifying high-risk patients and triaging them to AII rooms. The pre-bronchoscopy screening tool is simple and inexpensive to implement and has the potential to reduce intra-institutional spread of TB.
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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 | 0.002 | 0.012 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".