Timing of withdrawal of life-sustaining therapies in severe traumatic brain injury
Bibliographic record
Abstract
BACKGROUND: The care of patients with severe traumatic brain injury (TBI) is complex and confounded by uncertainty in prognoses. Studies have demonstrated significant unexplained variation in mortality between centers. Possible explanations include differences in the quality and intensity of care across centers, including the appropriateness and timing of withdrawal of life-sustaining therapies. We postulated that centers with a preponderance of early deaths might have a more pessimistic approach to the TBI patient, which would be reflected in an increased hospital TBI-related mortality. METHODS: This is a retrospective cohort study. Time to death was used as a proxy for time to withdrawal of life-sustaining therapies. Centers were classified as early or late based on when the majority (75th percentile) of their TBI-related deaths occurred. We evaluated the association between adjusted mortality and center classification using a hierarchical multivariable model. Two hundred trauma centers contributing data to the American College of Surgeons Trauma Quality Improvement Program from 2010 through 2013 were involved. The cohort included 17,505 patients with severe isolated TBI. RESULTS: One hundred eight centers were classified as early centers. The 75th percentile for time to death was 4 days among early centers versus 7 days in late centers. Mortality was 34% and 33%, respectively. After adjustment for case mix, care in an early center was not associated with increased odds of death (adjusted odds ratio, 0.95; 95% confidence interval, 0.83-1.09). Higher odds of death were independently associated with age, Glasgow Coma Scale (GCS) score, head Abbreviated Injury Scale (AIS) score, multiple comorbidities, traumatic subarachnoid hemorrhage, intracerebral mass lesions, brainstem lesions, and signs of compressed or absent basal cisterns. CONCLUSION: Centers rendering early decisions related to withdrawal of life-sustaining therapies in TBI patients, as measured by time until death, do not have worse outcomes than those making later decisions. How and when these decisions are made requires further exploration to balance an opportunity for clinical improvement with appropriate resource use. LEVEL OF EVIDENCE: Prognostic and epidemiologic study, level III.
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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 | 0.001 | 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".