[Effectiveness of interferon-gamma release assays in the tuberculosis contact investigation of elderly people].
Bibliographic record
Abstract
PURPOSE: To confirm the effectiveness of interferon-gamma release assays (IGRAs) in the tuberculosis (TB) contact investigation of elderly people, we analyzed the results of the QuantiFERON TB Gold in tube (QFT-3G) test, which is a commercially available IGRA. METHODS: We analyzed the results of the QFT-3G test in 2,420 subjects who were in close contact with TB patients. We investigated subjects with latent TB infection and those showing the onset of TB among the QFT-3G-positive subjects. RESULTS: The QFT-3G-positive rate was 7.3% (95% confidence interval, 6.2%-8.3%). In addition, we demonstrated that the QFT-3G-positive rate increased with age (P < 0.001). DISCUSSION: The QFT-3G-positive rate was high, particularly in elderly people (> or = 60 years), but the rate was significantly lower than the predicted prevalence of TB infection. Therefore, it was assumed that the QFT-3G test does not always provide a positive result, even in cases of subjects with a previous TB infection. Furthermore, data from the QFT-3G-positive subjects indicated that approximately one half of subjects aged 60-69 years, approximately one-third of those aged 70-79 years, and approximately one-quarter of those aged over 80 years have had recent TB infections. In conclusion, the results of the QFT-3G test in elderly people need to be carefully evaluated according to the contact situation with TB patients; nevertheless, the QFT-3G test is useful for the screening of latent TB infection in elderly people who were in close contact with TB patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".