Serial interferon-gamma release assays for latent tuberculosis in dialysis patients with end stage renal disease in a Korean population
Bibliographic record
Abstract
BACKGROUND: Serial interferon-gamma-release-assay (IGRA) result can show variance due to within-subject variation and difference in host immune status, and may be affected by latent tuberculosis infection (LTBI) treatment. We aimed to know the changes in QFT-IT (QuantiFERON-TB Gold In-Tube) results measured at a 4 month interval in end stage renal disease patients and whether these changes were influenced by dialysis method or LTBI treatment. METHODS: We prospectively performed serial QFT-IT tests at 4 month interval in 93 end stage renal disease (ESRD) patients on HD (hemodialysis) or PD (peritoneal dialysis). LTBI treatment was given to 18 of 39 patients with initial positive QFT-IT result. Agreement between the two results was estimated for all 93 patients and reversion rates were estimated among the 39 patients with initial positive QFT-IT. RESULTS: Positive QFT-IT at the first and 2(nd) tests were 41.9 and 34.4 %, respectively. The concordance rate between baseline QFT-IT and 2(nd) QFT in 93 ESRD patients was excellent (90.3 %, kappa = 0.80, p < 0.001). Agreement between the first QFT-IT and 2(nd) QFT-IT in HD (95.3 %, kappa = 0.91, p < 0.001) was higher than in PD patients (86.0 %, kappa = 0.69, p < 0.001). Among all ESRD patients, the odds of reversion of QFT-IT was not different in those who were, or were not treated for LTBI [odds ratio = 2.3 (0.5-11.4), p = 0.43]. CONCLUSIONS: In a group of 93 dialyzed ESRD patients 8.6 % showed reversion of initial positive QFT to negative within 4 months. Reversion seemed not to be associated with LTBI treatment. Further study with larger numbers of patients is needed to investigate the variation of QFT-IT tests in dialyzed ESRD patients.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.000 | 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 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".