Risk of active tuberculosis among people with diabetes mellitus: systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Objective To assess the risk of activeTBin people withDMand the factors associated with this risk. Methods Systematic review and meta‐analysis. We searched the literature for studies that reported the effect ofDMonTBcontrolled for the effect of age. Studies that had not established the diagnosis ofDMprior to detecting activeTBwere excluded. Study quality was assessed by Newcastle‐Ottawa scale and we conducted a meta‐analysis using random‐effects models. Results Of 14 studies (eight cohort and six case–control studies) that involved 22 616 623 participants met the selection criteria and were included in the analysis. There was substantial variation between studies in the estimates of the effect ofDMonTB. However, the pooled estimates from seven high‐quality studies showed that diabetic people have a 1.5‐fold increased risk of developing activeTBvs. those withoutDM(95%CI1.28–1.76), with relatively small heterogeneity (I2 = 44%). The increased risk ofTBwas observed predominantly amongDMpopulations with poor glycaemic control. Conclusion There is evidence suggesting an increased risk of developingTBamong people withDM, and that improving glycaemic control inDMpatients would reduce the risk of developingTB. An integrated approach is needed to control the dual burden ofDMandTB.
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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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.025 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".