Evaluation of <i>Mycobacterium Avium</i> Complex Pulmonary Disease Treatment Completion and Adherence to ATS/IDSA Guidelines
Bibliographic record
Abstract
BACKGROUND: Nontuberculous mycobacteria are environmental organisms that cause infections leading to chronic, debilitating pulmonary disease, among which Mycobacterium avium complex (MAC) is the most common species. METHODS: We described patterns of macrolide-based multidrug antibiotic therapies for MAC pulmonary disease (MAC-PD) in US Medicare beneficiaries with bronchiectasis between January 2006 and December 2014. MAC therapy was defined as a multidrug regimen containing a macrolide plus ≥1 other drug targeting MAC-PD (rifamycin, ethambutol, fluoroquinolone, or amikacin) prescribed concomitantly for >28 days. RESULTS: We identified 9189 new MAC therapy users, with a mean age (standard deviation) of 74 (6 years) at the start of therapy; 75% female and 87% non-Hispanic white. A guideline-based regimen (a macrolide, ethambutol, and rifamycin, with or without amikacin) was prescribed for 51% of new MAC therapy users at treatment start, of whom 41% were continuing guideline-based therapy at 6 months, and only 18% at 12 months. Of all new MAC therapy users, by 18 months only 11% were still receiving MAC treatment, 55% had discontinued therapy, and 34% were censored owing to death or the end of the study period. CONCLUSIONS: Overall, nearly half of new MAC therapy users were prescribed a non-guideline-recommended macrolide-based therapy, including regimens commonly associated with promoting macrolide resistance. Treatment discontinuation was common, and once discontinued, only a few beneficiaries resumed therapy at a later time. Our study adds important data to the current literature on treatment patterns for MAC-PD among older US populations. Future research should examine treatment patterns using more contemporary data sources.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".