The Effect of Facial Burns on Long-Term Outcomes in Young Adults: A 5-Year Study
Bibliographic record
Abstract
Long-term functional outcomes in young adults with facial burns remain poorly studied. This 5-year (2003-2008) prospective multicenter study includes burn survivors (age 19-30 years) who completed the Young Adult Burn Outcome Questionnaire (YABOQ) from 0 to 36 months after baseline survey administration. A composite canonical score was developed from 15 YABOQ domains using discriminant analysis, maximizing the difference at the baseline between burn-injured patients with face involved and not involved. A generalized linear model with the generalized estimation equation technique was used to track the changing pattern of the composite score over time. Individual domain scores with high correlation to the canonical score were used to evaluate recovery patterns in facial burns. A total of 153 burned (31% with face burns) and 112 nonburned subjects completed 620 questionnaires. Canonical analysis showed that early postburn, facial burns were associated with a difference in outcome, but this overall difference diminished over time. Regression analysis showed that for survivors with facial injury, Emotion and Sexual Function scores were persistently lower (worse), while Religion scores were persistently higher. Satisfaction with Role was initially better than the nonface burned group, but over time got worse, while Perceived Appearance was initially worse in the face burned group but this difference diminished over time. Social Function Limited by Appearance was initially similar between the groups, but over time the group with face burns scored lower. The overall difference in recovery between survivors with and without facial burns diminished over time while the individual domains had various patterns of recovery.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".