Global survey of physician testing practices for nontuberculous mycobacteria
Bibliographic record
Abstract
Background: Certain patients are at greater risk of developing nontuberculous mycobacterial pulmonary disease (NTM-PD), including those with lung conditions such as bronchiectasis. Testing for nontuberculous mycobacteria (NTM) in patients at risk is necessary to identify NTM-PD and start appropriate management. The aim of this survey was to evaluate current testing practices for NTM and identify testing triggers. Methods: Physicians (n=455) who see at least one patient with NTM-PD in a typical 12-month period and test for NTM as part of practice from Europe, USA, Canada, Australia, New Zealand and Japan participated in a 10-min anonymised survey on NTM testing practices. Results: Bronchiectasis, COPD and use of immunosuppressants were the factors most likely to prompt testing among physicians in this survey (90%, 64% and 64%, respectively), with radiological findings the most common reason leading to considering NTM testing in patients with bronchiectasis and COPD (62% and 74%, respectively). Macrolide monotherapy in patients with bronchiectasis and inhaled corticosteroid use in patients with COPD were not important triggers for testing (15% and 9% of physicians, respectively). Persistent cough and weight loss triggered testing in >75% of physicians. Testing triggers were markedly different for physicians in Japan, with cystic fibrosis prompting testing in fewer physicians compared with other regions. Conclusions: Testing for NTM is influenced by underlying disease, clinical symptoms or radiological changes, but clinical practice varies considerably. Adherence to guideline recommendations for NTM testing is limited in certain patient subgroups and varies across regions. Clear recommendations on NTM testing are 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 | 0.009 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".