Impact of clinical symptoms on CT ordering policy in minor head injuries.
Bibliographic record
Abstract
INTRODUCTION: The aim of our study was to determine the impact of clinical signs and symptoms on CT ordering policy in minor head injuries. PATIENTS AND METHODS: The study encompassed 1830 patients that have sustained minor or mild head injury, as assessed by clinical criteria. Basic clinical variables were recorded and a subset of patients meeting either Canadian or New Orleans criteria were subjected to CT. Outcome in terms of "positive" CT scans and number of patients requiring surgery was recorded. RESULTS: The mean age was 30.4 years (ranging from 10 days to 80 years). 176 patients were subjected to CT scan (based on clinical criteria). CT scan revealed intracranial pathology in 29 patients (16.5% of patients subjected to CT scan) and 19 patients were subsequently subjected to surgery (accounting for 10.8% of patients subjected to CT scan and 1.0% of all patients with mild or minor head injuries). Brain contusions were detected in 10 (5.7%) patients, followed by epidural hematomas (10 patients or 5.7% were found to harbor an epidural hematoma) and subdural hematomas, that were found in 7 patients or 4.0% of patients subjected to CT scan. DISCUSSION: Despite numerous studies that have analyzed the importance of clinical signs and CT in the diagnosis and treatment of minor head injuries, there is still much controversy about the mode of treatment of these patients. Canadian protocol really reduces the need for CT of the brain in relation to the New Orleans protocol, which suggests more observation in hospital patients with minor or mild head injury. CONCLUSION: The authors conclude that minor or mild head injuries should prompt a CT as recommended by Canadian or New Orleans guidelines and that the strongest scientific evidence available at this time would suggest that a CT strategy is a safe way to triage patients for admission.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".