The critical clock – re-evaluating optimal timing of surgery for brainstem cavernous malformations
Bibliographic record
Abstract
Brainstem cavernous malformations (BSCMs) often present with haemorrhage, but the optimal timing for microsurgical intervention remains unclear. This study aims to explore how intervention timing relates to neurological outcomes in haemorrhagic BSCM patients undergoing microsurgery, offering insights for clinical decisions. Methods: A total of 293 consecutive patients diagnosed with BSCMs, who underwent microsurgery were identified between March 2011 and January 2023 at two comprehensive centres in China, with a postoperative follow-up duration exceeding 6 months. Utilizing logistic regression models with restricted cubic splines, distinct time groups were identified. Subsequently, matching weight analysis compared these groups in terms of outcomes, new haemorrhage rates, cranial nerve deficits, and perioperative complications. The primary outcome was an unfavourable outcome, which was defined as a mRS score greater than 2 at the latest follow-up. Results: Among the 293 patients, 48.5% were female, median age was (39.9 ± 14.3) years, and median haemorrhage-to-treatment time was 42 days. Patients were categorized into acute (≤21 days), subacute (22–42 days), and delay (>42 days) intervention groups. After matching, 186 patients were analyzed. Adjusted analysis showed lower unfavourable outcome rates for acute [adjusted odds ratio (OR), 0.73; 95% CI, 0.65–0.82; P<0.001] and subacute (adjusted OR, 0.83; 95% CI, 0.72–0.95; P = 0.007) groups compared to the delay group. Subacute intervention led to fewer cranial nerve deficits (adjusted OR, 0.76; 95% CI, 0.66–0.88, P<0.001). New haemorrhage incidence didn’t significantly differ among groups. Conclusions: For haemorrhagic BSCMs patients, delayed microsurgical intervention that exceeded 42 days after a prior haemorrhage were associated with an increased risk of unfavourable neurological outcomes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.000 | 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".