Diagnostic Yield and Treatment Impact of Targeted Exome Sequencing in Early-onset Epilepsy
Bibliographic record
Abstract
Abstract Background To examine the impact on diagnosis, treatment and cost with early use of targeted whole-exome sequencing (WES) in early-onset epilepsy. Methods WES was performed on 50 patients with early-onset epilepsy (≤ 5 years) of unknown cause. Patients were classified as retrospective (epilepsy diagnosis > 6 months) or prospective (epilepsy diagnosis < 6 months). WES was performed on an Ion ProtonTM and variant reporting was restricted to the sequences of 565 known epilepsy genes. Diagnostic yield and time to diagnosis were calculated. An analysis of cost and impact on treatment was also performed. Results A likely/definite diagnosis was made in 17/50 patients (34%) with immediate treatment implications in 8/17 (47%). A possible diagnosis was identified in 9 additional patients (18%) for whom supporting evidence is pending. Time from epilepsy onset to genetic diagnosis was faster when WES was performed early in the diagnostic process (mean: 143 days prospective versus 2,172 days retrospective). Costs of prior negative tests averaged $8,344 in the retrospective group, suggesting savings of up to $5,110 per patient. Interpretation These results support the clinical utility and potential cost-effectiveness of using targeted WES early in the diagnostic workup of patients with unexplained early-onset epilepsy. The costs and clinical benefits are likely to continue to improve. Advances in precision medicine and further studies regarding impact on long-term clinical outcome will be important.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".