Nutrition in Toxic Epidermal Necrolysis
Bibliographic record
Abstract
BACKGROUND: Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are severe exfoliative diseases treated in burn centers due to large skin losses. Literature on SJS/TEN refers to parenteral nutrition (PN) as the preferred route of nutrition support. This study describes nutrition support interventions in SJS/TEN patients admitted to burn centers. MATERIALS AND METHODS: Seven burn centers participated in this Institutional Review Board-exempted retrospective chart review of adults with SJS/TEN admitted from 2000-2012. RESULTS: This analysis included 171 patients with SJS/TEN. Median total body surface area involvement was 35% (n = 145; interquartile range [IQR], 16%-62%). The majority required mechanical ventilation (n = 105). Based on indirect calorimetry, measured energy needs were 24.2 kcal/kg of admit weight (n = 58; IQR, 19.4-29.9). Thirty-one patients did not require enteral nutrition (EN) and started oral intake on hospital day 1 (IQR, 1-2), and 81% required EN support due to inadequate oral intake and remained on EN until day 16 (median hospital day, 16; IQR, 9-25). High-protein enteral formulas predominated. PN was rarely used (n = 12, 7%). Most patients were discharged home (57%), with 14% still requiring EN. CONCLUSIONS: Nutrition support should be considered in patients with SJS/TEN due to increased metabolic needs and an inability to meet these needs orally. Most SJS/TEN patients continued on EN and did not require escalation to PN.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".