Predictors of Prolonged Length of Stay (LOS) in Adult and Elderly Burn Patients: A Retrospective Review of 2325 Patients
Bibliographic record
Abstract
Increased length of stay (LOS) in patients with burn injuries is associated with increased adverse and poorer outcomes. Despite the awareness of the profound risks associated with increased LOS, large studies examining associated variables are lacking. This study aimed to identify pre-existing conditions, injury characteristics, and intrahospital events that influence whether patients meet or exceed the expected LOS based on the LOS:TBSA ratio, 1.5 days for adults aged 18-59 years and 2.0 days for older adults aged ≥ 60 years. A retrospective review of an adult cohort study admitted to a tertiary burn center was conducted. We included all surviving patients with burn injuries admitted from January 2006 to June 2021. Primary outcome was whether patients met or exceeded the expected LOS:TBSA ratio. Median (IQR) age was 45 (31-58) years, 1635 (70%) were male, and median (IQR) %TBSA was 7 (3-14). Median (IQR) LOS was 13 (6-20) days, and LOS:TBSA median (IQR) was 1.65 (0.98-2.95). We found inhalation injury to be a predictor of prolonged LOS in both adults and older adults, while female sex and greater age only contributed to increased LOS in the adult group. In-hospital complications are modifiable factors of prolonged LOS in both adults and older adult patients. We identified that greater age, female sex, inhalation injury along with in-hospital complications affected LOS in adults. Greater age and sex did not affect LOS in older adult patients. Identified risk factors should be adjusted for in future prospective studies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".