Challenging the Diagnosis of Primary Angiitis of the Central Nervous System: A Single-center Retrospective Study
Bibliographic record
Abstract
OBJECTIVE: (1) To describe a series of adults assessed for suspected primary angiitis of the central nervous system (PACNS) and their final diagnosis; (2) to describe and compare presenting features of PACNS and reversible cerebral vasoconstriction syndrome (RCVS); and (3) to evaluate the specificity of the presenting features of RCVS. METHODS: Patients evaluated at our institution between 2000 and 2008 for a possible CNS vasculitis and investigated by conventional angiography and/or brain biopsy were retrospectively analyzed. The inclusion criteria were a clinicoradiological presentation and cerebral angiography and/or brain biopsy raising the hypothesis of isolated cerebral vasculitis; and absence of identifiable etiology at the time of conventional angiogram and/or brain biopsy. RESULTS: Among 58 cases evaluated, 37 met the inclusion criteria and 33 were included in the study. Thirteen patients had RCVS. Thunderclap headaches, the absence of a focal neurological deficit, a convexal subarachnoid hemorrhage and/or normal brain parenchyma on magnetic resonance imaging, and "string of beads" appearance on conventional angiography had high diagnostic value. Six patients had other noninflammatory vascular disorders (intracranial atherosclerosis, cryptogenic embolism, and genetic vasculopathy). Six patients had infection or malignancy. Eight patients were diagnosed with PACNS; their clinical presentation and disease course were heterogeneous. Brain biopsy was performed in 3 cases (positive in 1). CONCLUSION: RCVS is an important differential diagnosis of CNS vasculitis. Its particular presentation should allow rapid identification in order to avoid pointless investigations and treatment. The frequent lack of histological proof and heterogeneous presentation of PACNS illustrated the nosological uncertainties of this label.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".