Determination of Neurologic Prognosis and Clinical Decision Making in Adult Patients With Severe Traumatic Brain Injury
Bibliographic record
Abstract
OBJECTIVES: Accurate prognostic information in patients with severe traumatic brain injury remains limited, but mortality following the withdrawal of life-sustaining therapies is high and variable across centers. We designed a survey to understand attitudes of physicians caring for patients with severe traumatic brain injury toward the determination of prognosis and clinical decision making on the level of care. DESIGN, SETTING, AND PARTICIPANTS: We conducted a cross-sectional study of intensivists, neurosurgeons, and neurologists that participate in the care of patients with severe traumatic brain injury at all Canadian level 1 and level 2 trauma centers. INTERVENTION: None. MEASUREMENTS: The main outcome measure was physicians' perceptions of prognosis and recommendations on the level of care. MAIN RESULTS: Our response rate was 64% (455/712). Most respondents (65%) reported that an accurate prediction of prognosis would be most helpful during the first 7 days. Most respondents (>80%) identified bedside monitoring, clinical exam, and imaging to be useful for evaluating prognosis, whereas fewer considered electrophysiology tests (<60%) and biomarkers (<15%). In a case-based scenario, approximately one-third of respondents agreed, one-third were neutral, and one-third disagreed that the patient prognosis would be unfavorable at one year. About 10% were comfortable recommending withdrawal of life-sustaining therapies. CONCLUSIONS: A significant variation in perceptions of neurologic prognosis and in clinical decision making on the level of care was found among Canadian intensivists, neurosurgeons, and neurologists. Improved understanding of the factors that can accurately predict prognosis for patients with traumatic brain injury is urgently needed.
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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 | 0.006 |
| 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 | 0.001 |
| 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".