A systematic review and meta-analysis of the impact of tuberculosis on health-related quality of life
Bibliographic record
Abstract
PURPOSE: To summarize the impact of tuberculosis (TB) on quantitative measures on self-reported health-related quality of life (HRQOL). METHODS: We searched eight databases to retrieve all peer-reviewed publications reporting original HRQOL data for persons with TB. All retrieved abstracts were considered for full-text review if HRQOL was quantitatively assessed among subjects with TB. Full-text articles were reviewed by two independent reviewers using a standardized abstraction form to collect data on socio-demographic characteristics, questionnaire administration, and mean HRQOL scores. Meta-analyses were performed for standardized mean differences in HRQOL scores, comparing subjects treated for active TB with subjects treated for latent TB infection (LTBI), or with healthy controls, at similar time points with respect to diagnosis and/or treatment. RESULTS: From over 15,000 abstracts retrieved, 76 full-text articles were reviewed, which represented 28 unique cohorts (6,028 subjects) reporting HRQOL among subjects with active TB; 42 % were women and mean age was 42 years. Data on key social and behavioral determinants were limited. Within individual studies and in meta-analyses, subjects with active TB disease consistently reported worse HRQOL than concurrently evaluated subjects treated for LTBI. However, meaningful improvements in HRQOL throughout active TB treatment were reported by longitudinal studies. CONCLUSIONS: In a variety of studies, in different settings and using different instruments, subjects with active TB consistently reported poorer HRQOL than persons treated for LTBI. Future research on HRQOL and TB should better address social and behavioral health determinants which may also affect HRQOL.
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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 | 0.020 | 0.057 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.032 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".