Baseline features and functional outcomes in primary central nervous system vasculitis: development and validation of a prognostic model
Bibliographic record
Abstract
OBJECTIVES: Few data are available regarding the functional prognosis of adults with primary central nervous system vasculitis (PCNSV). We developed and validated a prognostic model for 12-month functional independence in adults with PCNSV. METHODS: We conducted a multicentre, international cohort study of adults with PCNSV (COVAC'). The primary end point was functional independence 12 months after the start of corticosteroids or immunosuppressants, defined as a modified Rankin Scale of 0-2. We identified baseline features independently associated with functional independence using multivariable analyses. We assessed discrimination using AUC-ROC and externally validated the model in a geographically distinct, single-centre cohort from India. RESULTS: Among the 206 patients included with PCNSV (mean age: 48 years; 41% female), 67 (33%) were diagnosed based on a positive biopsy. At 12 months, 135 (66%) patients were functionally independent and 12 (6%) had died. Favourable prognostic factors were ≥1 intracranial stenosis on CT- or MR-angiogram (OR = 2.99, 95% CI: 1.23-7.68) and headache (OR = 2.67, 95% CI: 1.31-5.59). Unfavourable prognostic factors were an altered level of consciousness (OR = 0.09, 95% CI: 0.02-0.31), ≥1 acute brain infarct (OR = 0.12, 95% CI: 0.04-0.33) and cognitive impairment (OR = 0.22, 95% CI: 0.10-0.46). A prognostic model including these five variables had an AUC of 0.80 (95% CI: 0.74-0.87) in the derivation cohort and 0.67 (95% CI: 0.54-0.81) in the validation cohort. CONCLUSIONS: Baseline clinical and imaging variables may predict 12-month functional independence in adults with PCNSV. These results may support physicians in prognostication and risk stratification of adults with PCNSV.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".