Meta-analysis on mortality of pulmonary disease caused by Mycobacterium avium complex
Bibliographic record
Abstract
Objective To investigate the mortality of pulmonary disease caused by Mycobacterium avium complex (MAC). Methods Relevant publications were collected by literature retrieval from Medline, Cochrane, Embase and Web of Science between January 1, 1941 and January 1, 2020. Two investigators screened 1 622 articles, and 48 articles were finally included according to the inclusion and exclusion criteria. Quality of included researches was evaluated by using Newcastle-Ottawa scale (NOS) and Cochrane risk of bias tool. Meta-analysis was performed on the original data by using RevMan5.3 and Stata14.0. Results Forty eight studies, including 45 cohort studies and 3 random clinical trials and involving 6 933 cases of MAC pulmonary disease, were used, in which 31 studies reported causative mortality rate of MAC pulmonary diseases and 14 studies reported five-year all-cause mortality of MAC pulmonary diseases. This Meta-analysis indicated that all-cause mortality rate of MAC pulmonary diseases was 20.00% (I2=95.00%), five-year all-cause mortality rate was 26.00%(I2=94.00%), and the causative mortality rate was 5.00% (I2=87.00%). The prognostic factors included cavity type in radiography, age ≥65 years, being male, comorbidities, BMI ≤18.50 kg/m2 and ALB Conclusion This meta-analysis revealed that all-cause mortality rate of MAC pulmonary diseases was high and the patients had poor prognosis. The patients with HIV infection, cavity and comorbidities had increased risk of death.
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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 | 0.017 | 0.030 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.060 |
| Bibliometrics | 0.007 | 0.005 |
| 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) | 0.003 | 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".