Patterns of Clinical Use of Stereotactic Laser Ablation: Analysis of a Multicenter Prospective Registry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Stereotactic laser ablation (SLA), also termed laser interstitial thermal therapy, is a minimally invasive procedure that is increasingly used in neurosurgery. We wished to examine how and whether SLA is changing the landscape of treatment options for neurosurgical patients. METHODS: Patients undergoing stereotactic laser ablation were prospectively enrolled in the Laser Ablation of Abnormal Neurological Tissue (LAANTERN) registry. Data from the first 100 enrolled patients are presented here. RESULTS: Clinical indications for SLA include treatment of primary intracranial tumors (48%; 81% being high-grade gliomas [HGGs]), brain metastases (BMs, 34%), epilepsy (16%), and other (2%). For HGGs, SLA was equally likely used for newly diagnosed (45%) or previously treated/recurrent lesions (55%, P = 0.54). By contrast, SLA was predominantly used as treatment for BMs in which radiation therapy/radiosurgery had failed (91%), with only 9% of SLAs performed as initial treatment for newly diagnosed lesions (P < 0.001). Of all SLAs performed, 45% of the procedures were in lieu of surgical resection, with 43% performed because the lesion was not accessible by conventional neurosurgical techniques. CONCLUSION: HGGs and BMs are the leading indications for SLA in the LAANTERN study. For HGGs, SLA is equally used in the presenting or previously treated/recurrent setting. For BMs, SLA is typically used in the recurrent setting. SLAs are equally likely to be performed for difficult-to-access lesions or in lieu of conventional open surgery.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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 it