Procalcitonin in Takayasu Arteritis
Bibliographic record
Abstract
To the Editor: Procalcitonin (PCT) is an acute-phase protein, a precursor of the hormone calcitonin1. Microbial constituents and proinflammatory mediators such as tumor necrosis factor-α (TNF), interleukin 6 (IL-6), and interferon-γ induce ubiquitous PCT expression during bacterial, parasitic, or fungal infections1,2. PCT enhances inflammatory response during sepsis, when excessive PCT production can be toxic, increasing mortality in animal models1. In humans, PCT has been demonstrated to be a more accurate marker of systemic bacterial infections than C-reactive protein (CRP)3, and it correlates with the severity of sepsis and mortality risk1. For these reasons, PCT is increasingly used for diagnosis, prognostic stratification, and treatment of patients with systemic bacterial or fungal infections. However, PCT elevation has been reported in noninfectious conditions, including inflammatory states associated with antineutrophil cytoplasmic antibodies-associated vasculitis, Kawasaki disease, and Goodpasture syndrome2. The clinical usefulness of PCT as a biomarker in patients with systemic autoimmune diseases has not been fully defined2. One metaanalysis showed that PCT had higher specificity but lower sensitivity than … Address correspondence to Dr. E. Tombetti, San Raffaele University Hospital, Unit of Internal Medicine and Clinical Immunology, Via Olgettina 60, 20132 Milan, Italy. E-mail: tombetti.enrico{at}hsr.it
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".