Isolation Prevalence of Pulmonary Nontuberculous Mycobacteria in Ontario in 2007
Bibliographic record
Abstract
BACKGROUND: The reported prevalence of pulmonary nontuberculous mycobacteria (NTM) infections is increasing. OBJECTIVE: To determine the 'isolation prevalence' of NTM in 2007 and compare it with previously published research that examined the increasing rates of isolation of NTM from clinical pulmonary specimens between 1997 and 2003. METHODS: Isolation prevalence was investigated retrospectively by reviewing a cohort of all positive pulmonary NTM culture results from the Tuberculosis and Mycobacteriology Laboratory, Public Health Laboratory (Toronto, Ontario) in 2007, which identifies at least 95% of NTM isolates in Ontario. Isolation prevalence was calculated as the number of persons with a pulmonary isolate in a calendar year divided by the contemporary population and expressed per 100,000 population. Changes in isolation prevalence from previous years were assessed for statistical significance using generalized linear models with a negative binomial distribution. RESULTS: In 2007, 4160 pulmonary isolates of NTM were collected from 2463 patients. The isolation prevalence of all species (excluding Mycobacterium gordonae) was 19 per 100,000 population in 2007 - an increase from previous observations reported for Ontario - corresponding to an average annual increase of 8.5% from 1997 to 2007 (P<0.0001). Average annual increases in isolation prevalence of Mycobacterium avium complex (8.8%, P<0.0001) and Mycobacterium xenopi (7.3%, P=0.0005) were largely responsible for the overall increase, while prevalence rates of rapidly growing mycobacteria remained relatively stable. CONCLUSION: The isolation prevalence of pulmonary NTM continues to increase significantly in Ontario, supporting the belief that pulmonary NTM disease is increasingly common.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".