SCORTEN Accurately Predicts Mortality Among Toxic Epidermal Necrolysis Patients Treated in a Burn Center
Why this work is in the frame
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Bibliographic record
Abstract
SCORTEN is a scoring system used to predict mortality in toxic epidermal necrolysis (TEN) patients. The accuracy of SCORTEN among TEN patients treated in burn centers has not been established. The purpose of this study was to assess the discriminative power and calibration of SCORTEN among TEN patients treated at an adult regional burn center. Retrospective analysis of a consecutive series of TEN patients was used to compare actual mortality with that predicted by SCORTEN. A standardized mortality ratio was obtained to compare the actual number of deaths to the predicted number based on SCORTEN. Discrimination was measured using the area under the receiver operator characteristic curve, and model fit (calibration) was measured using the Hosmer-Lemeshow goodness-of-fit statistic. A total of 61 adult patients were analyzed. The actual overall mortality rate of 29.5% was not significantly different than the mortality rate of 25.2% predicted by SCORTEN (standardized mortality ratio, 1.17; 95% confidence intervals, 0.695-1.853; P = .08). The area under the receiver operator characteristic curve was 0.82 and the Hosmer-Lemeshow statistic was 1.381 (P = .710). SCORTEN is an accurate scoring system for estimation of mortality among TEN patients treated in a burn center setting.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it