Risk Factors and Characteristics of Intraoperative Seizures During Awake Craniotomy: A Retrospective Cohort Study of 562 Consecutive Patients With a Space-occupying Brain Lesion
Bibliographic record
Abstract
INTRODUCTION: Intraoperative seizures (IOSs) during awake craniotomy (AC) are associated with significant morbidity. The reported incidence of IOS is between 3% and 30%. The aim of this study was to identify risk factors for IOS during AC for elective resection or biopsy of a space-occupying brain lesion. METHODS: In this retrospective study, we reviewed the records of all awake craniotomies performed by a single neurosurgeon at a single university hospital between July 2006 and December 2018. IOS was defined as a clinically apparent seizure that occurred in the operating room and was documented in the medical records. Explanatory variables were chosen based on previously published literature on risk factors for IOS. RESULTS: Five hundred and sixty-two patients had a total of 607 AC procedures during the study period; 581 cases with complete anesthesia records were included in analysis. Twenty-nine (5.0%) IOS events were reported during 29 (5%) awake craniotomies. Most seizures (27/29; 93%) were focal in nature and did not limit planned intraoperative stimulation mapping. Variables associated with IOS at a univariate P -value <0.1 (frontal location of tumor, preoperative radiotherapy, preoperative use of antiepileptic drugs, intraoperative use of dexmedetomidine, and intraoperative stimulation mapping) were included in a multivariable logistic regression. Frontal location of tumor (adjusted odds ratio: 5.68, 95% confidence interval: 2.11-15.30) and intraoperative dexmedetomidine use (adjusted odds ratio: 2.724, 95% confidence interval: 1.24-6.00) were independently associated with IOS in the multivariable analysis. CONCLUSIONS: This study identified a low incidence (5%) of IOS during AC. The association between dexmedetomidine and IOS should be further studied in randomized trials as this is a modifiable risk factor.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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".