Cerebral Cavernous Malformation: The Impact of Associated Developmental Venous Anomaly on Surgical Treatment Outcome
Bibliographic record
Abstract
BACKGROUND: The goal of this study was to analyze retrospectively the course of patients with cerebral cavernous malformation (CCM) and associated developmental venous anomaly (DVA) concerning neurological outcome and formation of CCM recurrence or de-novo formation after surgical removal of the lesion. METHODS: 1469 patients diagnosed with CCM were referred to our institution from 2003 to 2022. Adult patients with sporadic CCM, complete magnetic resonance imaging dataset, and ≥2 follow-up (FU) investigations after surgical resection were analyzed. Patient's clinical data, surgical, and radiological reports were retrospectively assessed. Multiple factors regarding functional outcome were scanned using logistic regression analyses with P < 0.05. Preoperative and postoperative neurological function was assessed using the modified Rankin Scale (mRS). RESULTS: 183 patients were included in this study; 59 of 183 presented associated DVA. Mean preoperative mRS in the CCM + DVA group was 1.7 (±0.9), and in the CCM-DVA group was 1.97 (±0.8), while mean mRS at the last FU was 0.65 (±0.89) in the CCM + DVA group and 0.93 (±0.92) in the CCM-DVA group. Recurrence of CCM lesion was seen in 1 case in the CCM + DVA group and in 2 cases in the CCM-DVA group. Significant differences in the neurological status preoperatively (P = 0.046) and at the last FU (P = 0.049) could be detected for the benefit of the CCM + DVA group. CONCLUSIONS: DVA does not represent an additional risk for neurological deterioration in the surgical resection of CCM. Postoperative CCM recurrence is negligible.
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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 | 0.002 |
| 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) | 0.002 | 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".