Rho Kinase Expression in Giant Cell Arteritis: Validating Phosphorylated Ezrin/Radixin/Moesin Intensity Score to Increase Sensitivity of Temporal Artery Biopsy
Bibliographic record
Abstract
Objective Aberrant Rho-associated protein kinase (ROCK) activity is implicated in several vascular and immunologic disorders. We previously demonstrated increased ROCK activity in histopathologically negative temporal artery biopsies (TABs) in subjects with clinical giant cell arteritis (GCA) compared to those without GCA. This current study aimed to examine ROCK activity in a larger cohort of biopsy-negative GCA subjects and to validate the prior findings. Methods. Based on clinical data 6 months after TAB, subjects were categorized into 2 groups: biopsy-negative GCA and controls without GCA. Paraffin-embedded TABs were stained for phosphorylated ezrin/radixin/ moesin (pERM), a surrogate of ROCK activity, and scored by 2 pathologists blinded to clinical diagnosis using a previously derived scoring system measuring staining intensity in 3 areas of the vessel. Results. Thirty-six subjects with biopsy-negative GCA and 43 controls were analyzed. The mean (SD) pERM intensity score in non-GCA subjects was 3.9 (1.4), compared to 5.0 (1.4) in those with GCA (P = 0.002). Using the predetermined cut-off of 4 to define high pERM intensity, subjects with GCA were significantly more likely to have a high pERM intensity score compared to non-GCA (odds ratio 3.67, 95% CI 1.19-11.36; P = 0.02. The sensitivity of high pERM intensity score for diagnosis of GCA in histologically negative TABs was 86% (95% CI 70-95). Conclusion. In this well-characterized cohort, those with biopsy-negative GCA had significantly higher pERM intensity scores compared to subjects without GCA. pERM staining has diagnostic significance in enhancing the sensitivity of TAB and may help to define the clinically important group of biopsy-negative GCA.
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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 | 0.005 | 0.007 |
| 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 | 0.001 |
| Research integrity | 0.001 | 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".