Mycobacterium w Immunotherapy for Treating Pulmonary Tuberculosis - a Systematic Review
Bibliographic record
Abstract
BACKGROUND: Tuberculosis (TB) remains a global health catastrophe. Mycobacterium w is a heat-killed immune-modulating vaccine designed to attenuate the effects of TB, reduce time to sputum conversion, and thereby decrease transmission and improve cure rates. OBJECTIVES: To evaluate Mycobacterium w (M w) immunotherapy as an adjunct to chemotherapy in participants with pulmonary TB (PTB). SEARCH STRATEGY: In January 2012, we performed both a database search, a handsearch and corresponded with experts in the field. SELECTION CRITERIA: Randomised and quasi-randomised controlled trials of M w immunotherapy versus placebo (or no control) for participants with PTB. DATA COLLECTION AND ANALYSIS: Two of the authors (SP and ZK) independently extracted data. Dichotomous outcomes were analysed using risk ratios (RR) and 95% confidence intervals (CI). OUTCOMES: The primary outcome was to determine the effect of M w therapy on sputum conversion. Secondary outcomes were to determine the frequency of adverse reactions. MAIN RESULTS: Three trials (four papers) involving 368 participants were included. All four papers had methodological flaws. Overall, 173 participants received M w and 168 participants received placebo or no control. M w immunotherapy was effective at reducing time to sputum conversion at days 15 (RR 2.31; 95% CI 1.75 to 3.06; P < 0.001) and 30 (RR 1.83; 95% CI 1.12 to 2.98; P = 0.02). After day 30, benefit was only demonstrated in the category II TB (re-treatment). CONCLUSIONS: The meta-analysis suggests benefit as regards the time to sputum conversion. The available data on M w immunotherapy for participants with PTB are however methodologically flawed. We advise that M w be investigated in a well-structured, randomised controlled trial.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".