Sepsis in burn care: incidence and outcomes
Bibliographic record
Abstract
Abstract Background Although sepsis is known to be the leading cause of morbidity and mortality in adult burn patients, its epidemiology and impact are poorly understood. This study aims to address these gaps by further characterizing predictors of sepsis and comparing outcomes between septic and non-septic burn patients in different age groups. Methods We included patients (≥ 18 years) with thermal burn injuries ≥ 5% total body surface area (TBSA) admitted to two burn centers between 1 January 2006 and 30 June 2021, and 1 January 2023 and 6 April 2025. Patients were stratified by age into adults (18–59 years) and older adults (≥ 60 years), and by diagnosis of sepsis during hospitalization (sepsis vs. control). Demographics, injury characteristics, mortality, and in-hospital complications were assessed. Multivariate logistic regression models were used to identify predictors of sepsis and mortality among septic patients. Results This study included a total of 1465 patients, including 1094 adults and 371 older adults. Sepsis was diagnosed in 20.1% of adult burn patients, with a median onset at 10 d following injury. Increasing age, greater TBSA, and inhalation injury were identified as significant risk factors for sepsis. Among patients who developed sepsis, earlier onset and female sex were associated with an elevated risk of mortality. In older adults, the incidence of sepsis was 22.9%, with a median onset at 11 d post-burn. The odds of sepsis diagnosis increased with higher TBSA and the presence of inhalation injury. Earlier sepsis onset was associated with increased mortality in older adults. Conclusions Sepsis represents a significant clinical challenge in burn patients, with age, TBSA, inhalation injury, and comorbidities significantly influencing its incidence and outcomes. Notably, early sepsis onset and female sex are associated with increased mortality, highlighting the need for advanced monitoring, prompt interventions, and the exploration of innovative sex-specific strategies to optimize outcomes in this high-risk population.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.106 | 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 teacher head, 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".