Development of a Pediatric Epilepsy Program: Analysis of Early Multidimensional Outcomes
Bibliographic record
Abstract
Abstract Background A Pediatric Epilepsy Program was instituted in Manitoba in 2016. This report seeks to describe changes in the management of pediatric epilepsy patients in Manitoba since the inception of this Program, to provide an early analysis of local outcomes, and to present a framework for further program development. Methods Data was collected for patients treated both before and after inception of the Program. Caregivers completed questionnaires on quality of life and program satisfaction. An online database was created to capture demographic information, seizure and quality of life outcomes, and caregiver satisfaction ratings. Descriptive statistics were used to summarize the results. Results Prior to commencement of the Program, 16 patients underwent vagal nerve stimulator (VNS) insertion. At last follow-up, 6.25% of patients achieved Engel class I outcome, 75% achieved class III outcome, and 18.75% were classified as class IV. Following inception of the Program, 11 patients underwent resective procedures and 3 underwent VNS insertions. At last follow-up, 78.6% of patients achieved Engel class I outcome, 14.3% achieved class III outcome, and 7.1% were classified as class IV. Since inception of the Program, the average Quality of Life in Childhood Epilepsy Questionnaire-55 score measuring patient quality of life was (59.7 ± 23.2)/100. The average Care-Related Quality of Life-7D score measuring caregiver quality of life was (78.3 ± 18.6)/100. Caregiver satisfaction had an average rating of (9.4 ± 0.8)/10. Conclusion Access to epilepsy surgery has significantly improved for children in Manitoba and has led to favorable, early multidimensional outcomes. Structural organization, funding, and multidisciplinary engagement are necessary for program sustainability and growth.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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 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".