Head Injury in Older Adults: To Scan or Not to Scan? Ten Tips to Make the Best Decision
Bibliographic record
Abstract
Ground-level falls are a leading cause of emergency department (ED) visits by older adults. In addition to understanding the cause of the fall, the assessment of potential fall-induced injuries such as traumatic intracranial hemorrhage, can be highly challenging for emergency clinicians. Premorbid conditions, medications and concomitant injuries can all interfere with the physical examination and impact the prevalence of signs traditionally associated with traumatic brain injury (TBI). When it comes to the decision to potentially investigate for a traumatic intracranial hemorrhage with a brain imaging such as a head computed tomography (CT), many potential predictors and factors will be considered. Symptoms, history, medications, frailty, functional status, level of care, cost and access to imaging will all potentially influence that decision-making process. This brief review article will help make that decision in the interest of the patient and the health care system.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".