Posterior Cingulate Epilepsy: A Systematic Review
Bibliographic record
Abstract
SUMMARY: In this review, authors discuss epilepsy originating from posterior cingulate regions, a challenging entity to diagnose and most likely underrecognized. A systematic review of posterior middle and posterior cingulate epilepsy cases was conducted to present a summary of current knowledge about this localization-based type of epilepsy. The literature search identified 32 articles, for a total of 69 patients (34 with posterior middle cingulate epilepsy [pMCE] and 35 with posterior cingulate epilepsy [PCE]). Most patients were children and young adults with drug-resistant lesional epilepsy with high seizure burden. In both groups, most patients reported auras, mainly sensory, but various types were reported, including autonomic, behavioral, and cognitive manifestations. Most pMCE and PCE showed motor manifestations (mainly respectively asymmetric tonic posturing and automotor features). Impaired awareness during seizures was more frequently reported in PCE than in pMCE. As for ictal scalp EEG, epileptogenic abnormalities were poorly lateralized and did not localize the seizure onset zone. An ictal temporal involvement was only observed in PCE. Interictal EEG findings were nonspecific. As for other presurgical noninvasive investigations, data are limited, and no studies have adequately assessed their value. Partly explained by our inclusion criteria, most patients underwent a surgical procedure (either lesionectomy or resection of epileptogenic zone as defined by intracranial EEG study results), which overall yielded good outcomes.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".