Higher plasma interleukin − 6 levels are associated with lung cavitation in drug-resistant tuberculosis
Bibliographic record
Abstract
BACKGROUND: Lung cavitation is associated with heightened TB transmission and poor treatment outcomes. This study aimed to determine the relationship between systemic inflammation and lung cavitation in drug-resistant TB patients with and without HIV co-infection. METHODS: Plasma samples were obtained from 128 participants from the CAPRISA 020 Individualized M(X)drug-resistant TB Treatment Strategy Study (InDEX) prior to treatment initiation. Lung cavitation was present in 61 of the 128 drug-resistant TB patients with 93 being co-infected with HIV. The plasma cytokine and chemokine levels were measured using the 27-Plex Human Cytokine immunoassay. Modified Poisson regression models were used to determine the association between plasma cytokine/chemokine expression and lung cavitation in individuals with drug-resistant TB. RESULTS: Higher Interleukin-6 plasma levels (adjusted risk ratio [aRR] 1.405, 95% confidence interval [CI] 1.079-1.829, p = 0.011) were associated with a higher risk of lung cavitation in the multivariable model adjusting for age, sex, body mass index, HIV status, smoking and previous history of TB. Smoking was associated with an increased risk of lung cavitation (aRR 1.784, 95% CI 1.167-2.729, p = 0.008). An HIV positive status and a higher body mass index, were associated with reduced risk of lung cavitation (aRR 0.537, 95% CI 0.371-0.775, p = 0.001 and aRR 0.927, 95% CI 0.874-0.983, p = 0.012 respectively). CONCLUSION: High plasma interleukin-6 levels are associated with an increased risk of cavitary TB highlighting the role of interleukin-6 in the immunopathology of drug-resistant TB.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".