Inflammation and dyslipidaemia in combined diabetes and tuberculosis; a cohort study
Bibliographic record
Abstract
= 91), we measured 92 inflammatory proteins and 250 primarily lipid-related metabolites, repeating measurements after two months of TB treatment. Inflammation was primarily driven by TB, but higher in TB-DM. In TB-DM, the proteins osteoprotegerin (OPG), signaling lymphocytic activation molecule (SLAMF1), adenosine deaminase (ADA), interleukin-10 receptor subunit beta (IL-10RB), and tumor necrosis factor receptor superfamily member 9 (TNFSR9) were differentially abundant, and IL-17A/C predicted treatment failure. Disease severity correlated with inflammation and dyslipidaemia. Inflammation decreased with TB treatment, both in TB and TB-DM. Dyslipidaemia was primarily driven by DM, but more pro-atherogenic in TB-DM, with elevated VLDL and apolipoprotein B (ApoB). Despite TB treatment, pro-atherogenicity persisted. Stronger inflammation and dyslipidaemia may account for worse disease outcomes in TB-DM and warrant further action to prevent cardiovascular events.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".