Admitting Hospital Influences on Withdrawal of Life-Sustaining Treatment Decision for Patients With Severe Traumatic Brain Injury
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Withdrawal of life-sustaining treatment (WLST) in severe traumatic brain injury (TBI) is complex, with a paucity of standardized guidelines. We aimed to assess the variability in WLST practices between trauma centers in North America. METHODS: This retrospective study used data from trauma centers through the American College of Surgeons Trauma Quality Improvement Program between 2017 and 2020. We included adult patients (>16 years) with severe TBI and a documented decision for WLST. We constructed a series of hierarchical logistic regression models to adjust for patient, injury, and hospital attributes influencing WLST; residual between-center variability was characterized using the median odds ratio. The impact of disparate WLST practices was further assessed by ranking centers by their conditional random intercept and assessing mortality, length of stay, and WLST between quartiles. RESULTS: We identified a total of 85 511 subjects with severe TBI treated across 510 trauma centers, of whom 20 300 (24%) had WLST. Patient-level factors associated with increased likelihood of WLST were advanced age, White race, self-pay, or Medicare insurance status (compared with private insurance). Black race was associated with reduced tendency for WLST. Treatment in nonprofit centers and higher-severity intracranial and extracranial injuries, midline shift, and pupil asymmetry also increased the likelihood for WLST. After adjustment for patient and hospital attributes, the median odds ratio was 1.45 (1.41-1.49 95% CI), suggesting residual variation in WLST between centers. When centers were grouped into quartiles by their propensity for WLST, there was increased adjusted mortality and shorter length of stay in fourth compared with first quartile centers. CONCLUSION: We highlighted the presence of contextual phenomena associated with disparate WLST practice patterns between trauma centers after adjustment for case-mix and hospital attributes. These findings highlight a need for standardized WLST guidelines to improve equity of care provision for patients with severe TBI.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 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".