GR.3 Mortality in tuberous sclerosis complex: current understandings
Bibliographic record
Abstract
Background: Tuberous Sclerosis Complex (TSC) is a multisystemic neurocutaneous disorder in which hamartomas confer significant medical risks, including mortality, by disruption of local tissues. However, only recently have multiple studies assessed specific aetiologies of mortality in TSC. Methods: A literature review of all available studies examining mortality in TSC was conducted until December 15, 2024. Results: We identified 13 studies reporting 411 deaths from 6735 individuals with TSC. Crude mortality per 100 individuals ranged from 1.4-13.8 over average intervals of 11-45 years. Mortality risk ranged from 3.0-4.9 (mean 4.3) versus the general population. Mean life expectancy was 66.2 years compared to 81.8 in the general population. In seven studies that reported specific aetiologies of mortality, 6/7 (85%) had renal (commonly renal failure or angiomyolipoma hemorrhage) or brain disease (most frequently sudden unexpected death in epilepsy or brain tumours) as the most common cause of mortality. Intellectual delay conferred increased mortality risk. Lymphangioleiomyomatosis conferred significant risk of mortality in adult women and cardiac rhabdomyomas were the dominant cause of neonatal mortality. Conclusions: Mortality in TSC is elevated compared to the general population, with brain and renal disease most frequently culpable. Future studies should assess the impact of disease modifying therapies on mortality in TSC.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".