Complications of invasive subdural grid monitoring in children with epilepsy
Bibliographic record
Abstract
OBJECT: This study was performed to evaluate the complications of invasive subdural grid monitoring during epilepsy surgery in children. METHODS: The authors retrospectively reviewed the records of 35 consecutive children with intractable localization-related epilepsy who underwent invasive video electroencephalography (EEG) with subdural grid electrodes at The Hospital for Sick Children between 1996 and 2001. After subdural grid monitoring and identification of the epileptic regions, cortical excisions and/or multiple subpial transections (MSTs) were performed. Complications after these procedures were then categorized as either surgical or neurological. There were 17 male and 18 female patients whose mean age was 11.7 years. The duration of epilepsy before surgery ranged from 2 to 17 years (mean 8.3 years). Fifteen children (43%) had previously undergone surgical procedures for epilepsy. The number of electrodes on the grids ranged from 40 to 117 (mean 95). During invasive video EEG, cerebrospinal fluid leaks occurred in seven patients. Also, cerebral edema (five patients), subdural hematoma (five patients), and intracerebral hematoma (three patients) were observed on postprocedural imaging studies but did not require surgical intervention. Hypertrophic scars on the scalp were observed in nine patients. There were three infections, including one case of osteomyelitis and two superficial wound infections. Blood loss and the amounts of subsequent transfusions correlated directly with the size and number of electrodes on the grids (p < 0.001). Twenty-eight children derived significant benefit from cortical resections and MSTs, with a more than 50% reduction of seizures and a mean follow-up period of 30 months. CONCLUSIONS: The results of this study indicate that carefully selected pediatric patients with intractable epilepsy can benefit from subdural invasive monitoring procedures that entail definite but acceptable risks.
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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 | 0.004 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".