Patients with Glomerular Disease Are at Very High Risk of TB Infection Compared to the General Population
Bibliographic record
Abstract
Background: Advanced kidney disease is a known risk factor for active TB disease; however this risk has not been studied in patients with glomerular disease (GN). We sought to determine the incidence of TB disease in patients with GN and to explore the risk associated with immunosuppression (IS) treatment. Methods: A population-level cohort was created using a centralized kidney biopsy registry (2000-2012) of all GN cases in British Columbia, Canada: IgA nephropathy (IgAN) n=857, focal segmental glomerulosclerosis (FSGS) n=564, ANCA-GN n=404, lupus nephritis (LN) n=360, membranous nephropathy (MN) n=398, minimal change disease (MCD) n=191, and other GN (n=305). TB disease was ascertained by linkage to administrative databases. High TB incidence was defined as >30/100,000 person years (PY) consistent with the definition used in first-world countries. Incidence rates were standardized to the general population to generate standardized incidence ratios (SIR, 95% CI). Hazard ratios were calculated using Cox proportional hazards regression. Results: During a median follow-up 6.2 years, there were 41 cases of TB disease. TB incident rate was 197.4/100,000PY, and was higher in patients with LN vs. other types of GN (403.0/100,000PY, p<0.05). TB incidence in patients with GN was 23-fold higher than the general population (SIR 23.4, 16.8-31.7), and was high in both Canadian and foreign-born patients (range 124.1-579.6/100,000PY). TB incidence was higher during periods of IS use (282.4 vs. 147.9 per 100,000PY, p<0.05), and most cases (80.5%) had IS exposure prior to TB diagnosis. Time from IS to TB disease was highly variable, with median 3.9 years but 24% of TB cases occurred within 1 year. Reduced kidney function and higher proteinuria were also associated with increased TB risk (Table). Conclusions: Patients with GN have a high risk of TB disease, irrespective of GN type or country of origin. TB disease can occur within months of starting IS, suggesting that all GN patients should be screened for latent TB early in their disease course.Risk Factors for TB in GN
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".