Function of N-Terminal Pro-Brain Natriuretic Peptide in Takayasu Arteritis Disease Monitoring
Bibliographic record
Abstract
OBJECTIVE: Increased levels of N-terminal pro-brain natriuretic peptide (NT-proBNP) are associated with cardiovascular morbidity and mortality. Inflammation may also affect levels of NT-proBNP. We investigated the relationship of NT-proBNP with inflammation, disease activity, disease severity, and progression of Takayasu arteritis (TA). METHODS: Plasma levels of NT-proBNP were determined in 68 patients with TA and in 90 control subjects. Disease activity and disease severity in patients with TA were defined according to the National Institutes of Health and Ishikawa's criteria, respectively. RESULTS: NT-proBNP levels were higher in patients with active disease (915.0 ± 328.0 pmol/l) and patients in remission (618.2 ± 243.4 pmol/l) than in controls (427.2 ± 81.4 pmol/l) (p < 0.001). Patients with severe TA showed significantly higher NT-proBNP levels than those with mild-moderate TA (924.0 ± 332.4 pmol/l vs 653.8 ± 269.1 pmol/l; p = 0.001). In patients with longitudinal data, NT-proBNP levels at the active phase were significantly higher than those at the stable phase (944.1 ± 216.7 pmol/l vs 552.1 ± 178.2 pmol/l; p = 0.001). Inflammatory markers, including C-reactive protein, erythrocyte sedimentation rate, and white blood cell count, were independently associated with NT-proBNP levels after adjustment for other confounding factors (R(2) adjusted = 0.307, p = 0.001). CONCLUSION: NT-proBNP levels were significantly increased in patients with active TA exhibiting complications. NT-proBNP levels were independently associated with inflammation. These results indicate that NT-proBNP may be a useful marker to assess the status, severity, and progression of TA.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".