Patients with Focal Epilepsy but without Interictal Epileptiform Discharges (P4.068)
Bibliographic record
Abstract
Objectives: The interictal epileptiform discharges (IEDs) in human epilepsies are crucial for diagnosis of epilepsy and indentify different epileptic syndromes but, not all patients show IEDs on their EEGs. In this study we are evaluating patients with focal epilepsy but no IEDs during prolonged EEG-video monitoring (VEM). Methods: We did a retrospective review of VEM of all patients whom were admitted to the seizure monitoring unit (SMU) in the Calgary Epilepsy Program between Jul 2010 and Aug 2015. We included Adult patients with Focal Epilepsy base on diagnostic criteria of International League Against Epilepsy (ILAE) who had at least 3 days of VEM and had at least one epileptic seizure recorded. Result: Among a total of 706 patients admitted to SMU, 293 patients fulfilled our inclusion criteria. Fifty-five (19[percnt]) of these patients (34 males) with an average duration of 8.7.days of VEM showed no IEDs (non-spikers) and 238 (104 males) with an average duration of 10.1days of VEM had IEDs(spikers). The non-spikers had an average age and duration of epilepsy of 35 and 10 years while these were 45 and 20 years for spikers. The most frequent seizure focus was in temporal lobe (53[percnt] in non-spikers Vs. 58[percnt] in spikers). 45 ([percnt]) of non-spikers had epileptogenic lesion on their MRI while this was seen in 60([percnt]) of spikers. 9([percnt]) of non-spikers and 12.6([percnt]) of spikers had a respective epilepsy surgery. Conclusion: Almost 1 in five patients with focal epilepsy show no IEDs despite prolonged VEM. These patients, compare to the patients with IEDs, more frequently were male (62[percnt] Vs 44[percnt]) had shorter duration of epilepsy (10 Vs 20 years) but the average age, most common seizure focus, lesional Vs non-lesional, seizure intractability and seizure freedom rates were not significantly different between these two group of patients with focal epilepsy.
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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 | 0.000 |
| 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) | 0.005 | 0.001 |
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".