Risk of Tuberculosis Disease in People With Chronic Kidney Disease Without Kidney Failure: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Kidney failure is an established risk factor for tuberculosis (TB), but little is known about TB risk in people with chronic kidney disease (CKD) who have not initiated kidney replacement therapy (CKD without kidney failure). Our primary objective was to estimate the pooled relative risk of TB disease in people with CKD stages 3-5 without kidney failure compared with people without CKD. Our secondary objectives were to estimate the pooled relative risk of TB disease for all stages of CKD without kidney failure (stages 1-5) and by each CKD stage. METHODS: This review was prospectively registered (PROSPERO CRD42022342499). We systematically searched MEDLINE, Embase, and Cochrane databases for studies published between 1970 and 2022. We included original observational research estimating TB risk among people with CKD without kidney failure. Random-effects meta-analysis was performed to obtain the pooled relative risk. RESULTS: Of the 6915 unique articles identified, data from 5 studies were included. The estimated pooled risk of TB was 57% higher in people with CKD stages 3-5 than in people without CKD (adjusted hazard ratio: 1.57; 95% CI: 1.22-2.03; I2 = 88%). When stratified by CKD stage, the pooled rate of TB was highest in stages 4-5 (incidence rate ratio: 3.63; 95% CI: 2.25-5.86; I2 = 89%). CONCLUSIONS: People with CKD without kidney failure have an increased relative risk of TB. Further research and modeling are required to understand the risks, benefits, and CKD cutoffs for screening people for TB with CKD prior to kidney replacement therapy.
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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 | 0.012 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.042 |
| Bibliometrics | 0.007 | 0.007 |
| 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".