Primary angiitis of the central nervous system: Clinical profiles and outcomes of 45 patients
Bibliographic record
Abstract
OBJECTIVE: To describe the clinical profile, treatment response and predictors of outcome in patients with primary angiitis of the central nervous system (PACNS) from a single tertiary care center. METHODOLOGY: Retrospective analysis of consecutive patients diagnosed with PACNS from January 2000 to December 2015. Outcome was defined as poor when the 6-month modified Rankin scale (mRS) was ≥3. RESULTS: The median age of the 45 patients included in this study was 36 (range 19-70) years at disease onset and 31 (68.9%) were males. The initial presentation was ischemic stroke in 15 (33.3%), hemorrhagic stroke in 4 (8.9%), headache in 11 (24.4%), seizures in 8 (17.8%) and cognitive dysfunction in 5 (11.1%) patients. Diagnosis was confirmed by a four vessel cerebral digital subtraction angiogram (DSA), biopsy and by both biopsy and DSA in 26 (57.8%), 15 (33.3%) and 4 (8.9%) patients, respectively. All patients received glucocorticoids and 14 patients received in addition either cyclophosphamide or azathioprine as their first treatment. The median duration of follow-up was 33.1 (0.7-356) months. A poor 6-month outcome was observed in 12 (26.7%) patients. Relapse occurred in 25 (55.6%) patients and 7 (15.6%) died. Predictors of a poor outcome consisted of cognitive dysfunction at diagnosis (80% vs 20%; P = 0.014) and NIHSS ≥5 (62.5% vs 37.5%; P <.0005). None of the patients with a normal EEG had a poor outcome (P = 0.046). Predictors of relapse were a higher NIHSS at admission (P =.032) and a normal DSA (P = 0.002). CONCLUSION: In this cohort, severe deficits and cognitive symptoms at onset and an abnormal EEG were associated with a poor 6-month outcome.
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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 | 0.001 |
| 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".