Predicting Prognosis in Thermal Burns With Associated Inhalational Injury: A Systematic Review of Prognostic Factors in Adult Burn Victims
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Burn injuries are a significant problem with high associated morbidity and mortality. Those associated with inhalational trauma (IHT) may be associated with higher mortality, but studies on prognosis are small and underpowered. This study was designed to identify prognostic factors that increase the risk of death, to quantify this risk, and to identify existing prognostic models. An electronic search of English-language publications that identify prognostic risk factors in thermal burns including IHT was carried out. Each article was reviewed systematically, and data extraction, quality assessment, and summarization of the articles were performed. Thirteen articles that met the inclusion/exclusion criteria of this study were reviewed. Overall, the mortality rate among burn patients in this review was 13.9% (4-28.3%), with the mortality rate among those with IHT being 27.6% (7.8-28.3%). Those studies with multivariate analyses identified increasing %TBSA, presence of IHT, and increasing age as the strongest predictors for mortality in this patient population. It seems that %TBSA, presence of IHT, and age are the best predictors of mortality among the current published literature on burn prognosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.005 |
| 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