Detecting Latent Tuberculosis Infection in Hemodialysis Patients
Bibliographic record
Abstract
Current guidelines advocate screening hemodialysis patients for latent tuberculosis infection; however, the tuberculin skin test (TST) is believed to be insensitive in this population. This study compared the diagnostic utility of the TST with that of an IFN-gamma assay (T-SPOT.TB) and the clinical consensus of an expert physician panel. A total of 203 patients with ESRD were evaluated for latent tuberculosis infection with the TST, T-SPOT.TB test, and an expert physician panel. Test results were compared with respect to their association with established tuberculosis risk factors. Tuberculosis infection, as estimated by the tuberculin test, T-SPOT.TB test, and expert physician panel, was detected in 12.8%, 35.5, and 26.1 of patients respectively. Among patients with a history of active tuberculosis and radiographic markers of previous infection, 78.6 and 72.7% had positive T.SPOT.TB results, compared with 21.4 and 18.2% who had positive tuberculin tests. The physician panel unanimously declared infection in these two groups. On multivariate analysis, a positive T-SPOT.TB test was associated with a history of active tuberculosis, radiographic markers of previous infection, and birth in an endemic country, whereas a physician panel diagnosis also was associated with a history of previous tuberculosis contact. The TST is insensitive in hemodialysis patients and is not recommended to be used in isolation to diagnose latent tuberculosis infection. It is suggested that a combination of T-SPOT.TB testing and medical assessment may be the most accurate screening method.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".