Systematic review and meta-analysis of standard vs selective temporal lobe epilepsy surgery
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
OBJECTIVE: To compare standard anterior temporal lobectomy (ATL) with selective amygdalohippocampectomy (SAH) for postoperative seizure control in temporal lobe epilepsy (TLE). METHODS: We searched MEDLINE and Embase using Medical Subject Headings and keywords related to ATL and SAH. We included original research that directly compared seizure outcomes in patients undergoing SAH or ATL for TLE. A fixed-effect model was used to derive a pooled risk ratio (RR) for either an Engel Class I (free of disabling seizures) or a composite of an Engel Class I and II (rare disabling seizures) outcome. RESULTS: Of 4,675 abstracts initially identified by the search, 65 were reviewed as full text. Thirteen studies containing data from 8 countries (5 continents) met our inclusion criteria. Eleven studies comprising 1,203 patients demonstrated that participants were statistically more likely to achieve an Engel Class I outcome after ATL compared with SAH (risk ratio 1.32, 95% confidence interval [CI] 1.12-1.57; p < 0.01). The summary risk difference of 8% (95% CI 3%-14%) translates to a number needed to treat of 13 (95% CI 7-33) for 1 additional patient to achieve an Engel Class I outcome after ATL. The result remained significant when 2 studies that contained fewer than 15 participants in at least 1 arm were excluded and in analyses restricted to hippocampal sclerosis. CONCLUSIONS: Standard ATL confers an improved chance of achieving freedom from disabling seizures in patients with TLE. Improved seizure freedom must be balanced against the neuropsychological impact of each procedure. A randomized controlled trial is justified.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.022 | 0.004 |
| 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 it