Valor diagnóstico da tomografia de coluna cervical em vítimas de trauma contuso
Bibliographic record
Abstract
OBJECTIVE: to assess the value of computed tomography in the diagnosis of cervical spine and spinal cord injuries in victims of blunt trauma. METHODS: we reviewed the charts of blunt trauma victims from January 2006 to December 2008. We analyzed the following data: epidemiology, mechanism of trauma, transportation of victims to the hospital, intra-hospital care, indication criteria for CT, diagnosis, treatment and evolution of the victims. The victims were divided into two groups: Group I - without cervical spine injury, Group II - with cervical spine injury. RESULTS: we gathered medical records from 3,101 victims. Computed tomography was performed in 1572 (51%) patients, with male predominance (79%) and mean age of 38.53 years in Group I and 37.60 years in Group II. The distribution of trauma mechanisms was similar in both groups. Lesions found included: 53 fractures, eight vertebral listeses and eight spinal cord injuries. Sequelae included: paraplegia in three cases, quadriplegia in eight and brain injury in five. There were seven deaths in Group II and 240 in Group I. The average length of hospital stay was 11 days for Group I and 26.2 days for Group II. CONCLUSION. A CT scan of the cervical spine in victims of blunt trauma was effective in identifying lesions of the cervical spine and spinal cord injuries. Thus, despite the cost of neck CT and the low incidence of lesions identified by it, its indication based on the usual criteria seems justified.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".