Health‐related quality of life, comorbidities and mortality in pulmonary nontuberculous mycobacterial infections: A systematic review
Bibliographic record
Abstract
Nontuberculous mycobacterial (NTM) infections are increasing in disease frequency worldwide. This systematic review examines health-related quality of life (HRQOL), comorbidities and mortality associated with pulmonary NTM disease. We searched MEDLINE, EMBASE, CINAHL, Scopus Life Sciences, conference proceedings and Google (earliest date available to February 2015) for primary studies. Eligible studies compared populations with and without pulmonary NTM disease in high-income jurisdictions. We excluded studies on HIV/AIDS. All languages were accepted. Two reviewers followed MOOSE and PRISMA reporting guidelines and independently appraised quality using STROBE. All studies were summarized qualitatively regardless of quality. Of 3193 citations screened, we included 17 studies mostly from Taiwan (n = 5) and the USA (n = 4). Two studies assessed HRQOL; one assessed comorbidities, 11 assessed mortality, and three assessed multiple outcomes. Populations with pulmonary NTM reported significantly worse or similar HRQOL than the general population, depending on the instruments used. Some suggested greater prevalence of having bronchiectasis (n = 2) and greater risk of developing pulmonary tuberculosis (n = 1). Most (n = 7) suggested no difference in mortality, although only one was age-matched and gender-matched to the general population. Four suggested NTM populations had higher mortality-two of which compared with the general population and were deemed of high quality, while two compared with non-NTM patients from hospital. High clinical heterogeneity in study design may explain discordant results. Bias assessments and controlling for confounding were carried out poorly. No consistent trends were observed although there is suggestion of an increased health burden from respiratory diseases and increased mortality associated with pulmonary NTM disease.
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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 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".