Rapid Ventricular Pacing for Clipping of Intracranial Aneurysms: A Single-centre Retrospective Case Series
Bibliographic record
Abstract
OBJECTIVE: Multiple strategies exist to facilitate microdissection and obliteration of intracranial aneurysms during microsurgical clipping. Rapid ventricular pacing (RVP) can be used to induce controlled transient hypotension to facilitate aneurysm manipulation. We report the indications and outcomes of intraoperative RVP for clipping of ruptured and unruptured complex aneurysms. METHODS: We completed a retrospective review of adult patients who underwent RVP-facilitated elective and emergent microsurgical aneurysm clipping by a single senior neurosurgeon between 2016 and 2023. Intraoperative RVP was performed at a rate of 150 to 200 beats per minute through a transvenous pacing wire and repeated as needed based on surgical requirements. Intraoperative procedural and pacing data and perioperative cardiac and neurosurgical variables were collected. RESULTS: Forty patients were included in this study. The median (interquartile range) number of pacing episodes per patient was 8 (5 to 14), resulting in a median mean arterial pressure of 37 (30 to 40) mm Hg during RVP. One patient developed wide complex tachycardia intraoperatively, which resolved after cardioversion. Fifteen out of 36 (42%) patients who had postoperative troponin measurements had at least one troponin value above the 99th percentile upper reference limit. One patient had markedly elevated troponin with anterolateral ischemia in the context of massive postoperative intracranial hemorrhage. There were no other documented intraoperative or postoperative cardiac events. CONCLUSIONS: This retrospective case series suggests that RVP could be an effective adjunct for clipping of complex ruptured and unruptured aneurysms, associated with transient troponin rise but rare postoperative cardiac complications.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".