Long‐term outcomes of stereotactic radiofrequency ablation in hypothalamic hamartomas: A single‐center experience
Bibliographic record
Abstract
OBJECTIVE: Hypothalamic hamartomas (HHs) lead to refractory epilepsy, and minimally invasive surgical approaches are standard of care for affected patients. Stereotactic radiofrequency thermocoagulation (SRT) is one of the treatment methods recognized to achieve seizure freedom. This study reports surgical outcome from a single center reporting an ablation technique using fewer trajectories than previously reported and assesses the effect of coagulated volume on long-term seizure freedom. METHODS: Retrospective analysis was made of all patients who underwent SRT at the University of Freiburg between 2016 and 2024 with a follow-up of ≥12 months. Statistical analysis was made of outcome dependent on type of hamartoma, seizure type, coagulation volume (based on magnetic resonance imaging evaluation), and epilepsy duration. RESULTS: Forty-three patients received SRT; 35 (22 children) had >12 months of follow-up, with a median of 38 months. Nine patients had two SRTs, and two patients had three SRTs. Twelve months after their last SRT, 60% of patients were seizure-free, 88.6% were free of bilateral tonic-clonic seizures, and 77.1% were free of gelastic seizures (last follow-up: 54.3% seizure-free, 88.6% free of bilateral tonic-clonic seizures, 74.3% free of gelastic seizures). There was a significant reduction of antiseizure medication (ASM) postsurgically, with an average number of ASMs of two prior to surgery and one after surgery. After 12 months, 14.3% of patients experienced ongoing but mostly mild surgical complications, with hypothalamic dysfunction being the most common. Coagulation volumes were higher in larger HHs, but no correlation was observed between coagulated volume and seizure freedom or complication rates. SIGNIFICANCE: SRT is a minimally invasive method to successfully treat refractory seizures in patients with HH. Disconnection seems to be more important for successful treatment than volume reduction. Even large HHs can be successfully treated with small coagulation volumes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".