A retrospective review of non-tuberculous Mycobacterium treatment in Montreal
Bibliographic record
Abstract
Introduction The detection of non-tuberculous mycobacteria (NTM) is rising on a global scale and clinicians are becoming more aware of NTM-pulmonary disease (NTM-PD). While guidelines exist to help clinicians with management of this disease, there is uncertainty around who may benefit from treatment. This study examined disease course and survival of patients with NTM-PD.Methods A retrospective analysis of all adult patients between January 2017 to June 2022 with 1 or more respiratory samples identified from the McGill University Health Center Clinical Laboratory positive for NTM was performed. Medical records were reviewed to assess if they met ATS/IDSA criteria for NTM-PD.Results A total of 434 patients with a first culture positive for NTM were identified after screening 29,530 samples sent for mycobacterial culture. Of these patients, 16% were considered to meet the diagnostic criteria of NTM-PD, 68% were determined to not meet the NTM-PD criteria, and 16% had insufficient information to determine which group they were in. M. avium was the most commonly isolated organism of the adults considered to have NTM-PD, 56% were treated. There was no difference in survival or disease course between those who were treated or not. Adverse events leading to a regimen change occurred in 42% of those treated.Conclusions A low percentage of patients with positive NTM cultures met criteria for disease and of those, less than half were treated. Treated patients had frequent side effects and high mortality. This study suggests there is equipoise on the issue of identification of patients with pulmonary NTM disease who will benefit from current treatment, supporting the development of trials to address this.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".