Co-Recovery of Mycobacterium avium Complex and Mycobacterium tuberculosis in Patients With Pulmonary Tuberculosis
Bibliographic record
Abstract
Background Patients eventually shown to have pulmonary tuberculosis often grow both Mycobacterium avium complex (MAC) and Mycobacterium tuberculosis (MTB) from sputum. If the MAC grows first, patients may erroneously be assumed to have MAC disease, with discontinuation of isolation, contact investigation and alterations in chemotherapy. In patient with compatible disease, it would be helpful to know the likelihood of recovering both MAC and MTB as well as the predictive value of a positive sputum smear. Methods During 2012 and 2013 the Tuberculosis Control Program of the Philadelphia Department of Public health evaluated the relative incidence of MAC versus MTB in patients with suspected pulmonary tuberculosis, the time to culture growth from the initial smear for MTB and MAC, and determined the positive predictive value of a positive acid fast smear. Results In this setting, 22% of patients that were culture positive for MTB also grew MAC, with 78% of them growing MAC before MTB. The positive predictive value of a positive acid fast smear was 89% for MTB versus MAC. Conclusions There is a relatively high frequency of recovering MAC in TB patients Therefore, the recovery of MAC in a patient with a positive acid fast smear and compatible disease should not rule out MTB until cultures are final.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".