Child Neurology (General Pediatric Neurology)
Bibliographic record
Abstract
Background: Tuberous sclerosis complex (TSC) is a neurocutaneous syndrome that can present with many disabling neurological symptoms, the most common being seizures. Although it is a chronic systemic syndrome, healthcare utilization and long-term outcome of subjects with TSC are not well defined. The goal of this study was to evaluate the direct cost and long-term outcome of TSC compared to other forms of epilepsy and healthy controls. Methods: Our provincial health care database was interrogated to determine use of medical services by patients with TSC, epilepsy and healthy controls from 1996-2011. Data on demographics, outcomes and health care utilization were analyzed. Results: 1004 TSC, 41,934 with epilepsy and 41,934 controls were identified. The prevalence of TSC was 1/7,872 compared to 1/189 for epilepsy. TSC experienced more hospitalizations, medical visits and prescription drug use, resulting in higher total health care costs. Their most common admission diagnosis was seizures and age at death was significantly lower: 61,3 years old for TSC vs 69,6 and 76,6 years old for epilepsy and controls, (p<0,001). Conclusions: TSC subjects have a significantly higher burden of disease than other subjects with epilepsy. These results stress the need for specialized services in this population through the lifespan.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.057 | 0.007 |
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".