The incidence of pulmonary non-tuberculous mycobacteria in British Columbia, Canada.
Bibliographic record
Abstract
SETTING: British Columbia Centre for Disease Control (BCCDC), Vancouver, Canada. OBJECTIVE: To determine the incidence of non-tuberculous mycobacteria (NTM) and to assess the impact of new laboratory techniques. DESIGN: Population-based study of all subjects with positive cultures for NTM from 1990 to 2006. RESULTS: Mycobacterium avium complex (MAC) was the most common NTM isolate (77%). The median incidence rates per 100 000 population in the total sample were respectively 6.7, 4.5 and <0.7 for all NTMs, MAC and all non-MAC species; for NTM-treated subjects the rates were respectively 1.6, 1.4 and <0.08; and for the NTM-colonised they were respectively 4.7, 2.7 and <0.5. In the period after the introduction of new laboratory techniques, all NTM isolates, the overall MAC rate and the MAC-colonised rate increased by respectively 24%, 35.4% and 76% (P < 0.05). All NTM isolates and rates for all NTMs, NTM-treated and M. tuberculosis subjects (used as comparison group) decreased over time (P < 0.05). CONCLUSION: The most common NTM species was MAC. Episodic increases in the number of isolates and incidence rates of subjects colonised with MAC are likely to be associated with the implementation of new laboratory techniques, which may represent an artefact. The decrease in rates of NTM-treated subjects is reassuring.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".