Clinical course of untreated cerebral cavernous malformations: individual patient data meta-analysis
Bibliographic record
Abstract
The clinical course of untreated cerebral cavernous malformations (CCM) remains uncertain, partly due to small sample sizes and the infrequency of outcome events in previous studies. The dilemma about whether, when and how to treat patients would be informed by a more precise estimation of clinical course, identification of prognostic factors and derivation of prognostic models. From a systematic review, we identified three prospective or retrospective hospital-based cohorts (Mayo Clinic, Rochester, MN; Toronto Western Hospital, Toronto; and Hôpital Lariboisière, Paris) and one prospective population-based cohort (Scotland) that could provide detailed data regarding clinical outcome between diagnosis and CCM treatment or last follow-up in adults with CCM. We will describe baseline characteristics and use survival analysis to calculate the risks of outcomes at specific times and identify their predictors using adjusted hazard ratios. We will pool the estimates from each study in meta-analyses using random-effects models, and quantify and investigate any heterogeneity between studies. In three cohorts providing data to date ( n = 745), between 29% and 46% of patients presented incidentally, 20-29% with seizure, 13-34% with haemorrhage, and 11-17% with focal neurological deficit. In follow-up these cohorts identified 105 symptomatic events, including 46 haemorrhages.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.005 | 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 teacher head, 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".