Temporal Small-Vessel Inflammation in Patients with Giant Cell Arteritis: Clinical Course and Preliminary Immunohistopathologic Characterization
Bibliographic record
Abstract
OBJECTIVE: To investigate the occurrence, clinical correlates, and immunohistochemical phenotype of temporal small-vessel inflammation (TSVI) in temporal artery biopsies from patients presenting with clinical features of giant cell arteritis (GCA). METHODS: We retrospectively reviewed 41 temporal artery biopsy specimens for the presence of inflammatory infiltrates in small vessels external to the temporal artery adventitia (TSVI); 33 had sufficient clinical and pathological data for detailed analysis. Clinical and laboratory features at presentation and corticosteroid treatment patterns of patients with isolated TSVI were compared to those of patients with positive and negative biopsies. The cellular composition of the infiltrates was further characterized by immunohistochemistry. RESULTS: Twenty-three (70%) specimens had evidence of TSVI including 10 with concurrent GCA and 13 (39%) with isolated TSVI. TSVI was found in all positive temporal artery biopsies. The proportion of macrophages and of lymphocyte subpopulations differed between infiltrates observed in TSVI and those of the main temporal artery wall. Initial erythrocyte sedimentation rate (ESR) was similar in the TSVI and positive biopsy groups and was significantly higher than in the negative biopsy group. Patients with isolated TSVI more often had symptoms of polymyalgia rheumatica compared to the positive biopsy group. Patients with TSVI received corticosteroid doses that were intermediate between patients with positive and those with negative biopsies. CONCLUSION: A significant number of patients with clinical features of GCA demonstrated isolated TSVI. Differences in the clinical presentation and cellular composition suggest that TSVI may represent a subset of GCA and should be considered in the interpretation of temporal artery biopsies and treatment decisions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".