Surgical outcomes in children with bottom-of-sulcus dysplasia and drug-resistant epilepsy: a retrospective cohort study
Bibliographic record
Abstract
OBJECTIVE: Bottom-of-sulcus dysplasia (BOSD) is challenging to identify radiologically. The aim of this study was to explore seizure outcomes after resective surgery or MR-guided laser interstitial thermal therapy (MRgLITT) in children with BOSD. METHODS: Children with radiologically defined BOSD who underwent resective surgery or MRgLITT, with at least 1 year of follow-up were included. Clinical, radiological, neurophysiological, and histological data were extracted from medical records. Invasive video EEG (IVEEG) was used to evaluate the ictal onset zone or motor/language mapping, wherever appropriate. Histology of MRI-visible BOSD, including the overlying and adjacent cortex, was also evaluated. RESULTS: Forty-one children with BOSD underwent surgical treatment. The lesion was initially overlooked on MRI in 20 patients (48.8%). Of 34 patients who underwent IVEEG and who had available ictal data, the ictal onset zone extended beyond the MRI-visible BOSD in 23 patients (67.6%). Surgical treatment included lesionectomy (24 patients), extended lesionectomy (12 patients), lobectomy (1 patient), and ablation of BOSD (4 patients). The pathology in 37 patients who underwent resection showed focal cortical dysplasia type IIB and type IIA in 21 (53.8%) and 16 patients (41%), respectively. Seizure freedom was achieved in 32 patients (78.1%) after a mean follow-up of 4.3 years. CONCLUSIONS: Seizure outcomes after resective surgery or MRgLITT in children with BOSD were generally favorable. The authors found that the neurophysiological abnormality and pathology often extended beyond the MRI-visible BOSD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".