TIPIC Syndrome: Beyond the Myth of Carotidynia, a New Distinct Unclassified Entity
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The differential diagnosis of acute cervical pain includes nonvascular and vascular causes such as carotid dissection, carotid occlusion, or vasculitis. However, some patients present with unclassified vascular and perivascular changes on imaging previously reported as carotidynia. The aim of our study was to improve the description of this as yet unclassified clinico-radiologic entity. MATERIALS AND METHODS: From January 2009 through April 2016, 47 patients from 10 centers presenting with acute neck pain or tenderness and at least 1 cervical image showing unclassified carotid abnormalities were included. We conducted a systematic, retrospective study of their medical charts and diagnostic and follow-up imaging. Two neuroradiologists independently analyzed the blinded image datasets. RESULTS: The median patient age was 48 years. All patients presented with acute neck pain, and 8 presented with transient neurologic symptoms. Imaging showed an eccentric pericarotidian infiltration in all patients. An intimal soft plaque was noted in 16 patients, and a mild luminal narrowing was noted in 16 patients. Interreader reproducibility was excellent. All patients had complete pain resolution within a median of 13 days. At 3-month follow-up, imaging showed complete disappearance of vascular abnormalities in 8 patients, and a marked decrease in all others. CONCLUSIONS: Our study improved the description of an unclassified, clinico-radiologic entity, which could be described by the proposed acronym: TransIent Perivascular Inflammation of the Carotid artery (TIPIC) syndrome.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".