Clinical Outcome of Patients With Severe Burns Presenting to the Emergency Department
Bibliographic record
Abstract
Background : Burns are a leading cause of morbidity and mortality worldwide. Although a local burn covering a limited surface area can heal readily, deep or extensive burns can result in systemic damage and even death. This study evaluated the clinical characteristics of the patients presenting with severe burns and investigated the factors influencing mortality. Methods: The data for 1003 patients who presented with symptoms of severe burn to a tertiary care university hospital in Turkey between 2006 and 2007 were evaluated retrospectively. Results: The overall patient mortality was 7.7% (n = 78). The effect of male gender and age on mortality was significant. The highest mortality rate was in the group aged > 40 years. A burned area larger than 21% of the body surface conferred a high risk of mortality. A hospital stay for longer than 10 days, the presence of delirium at the time of presentation, hyperuricemia, the need for debriding, grafting, or fasciotomy, sepsis, hypovolemic shock, and a positive blood culture were significant predictors of mortality. Conclusions : Severe burns have to be treated in a burn unit or burn center. As the prevention of burns is important, it is important to identify the region-specific causes of burns and the risk factors that influence mortality. doi:10.4021/jcs19e
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.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".