Diagnostic Accuracy of Computed Tomographic Angiography for Blunt Cerebrovascular Injury Detection in Trauma Patients
Bibliographic record
Abstract
In Brief Objective: To compare the diagnostic accuracy of computed tomographic angiography (CTA) with digital subtraction angiography (DSA) for blunt cerebrovascular injury (BCVI) detection in trauma patients. Background: Controversy exists as to whether the diagnostic performance of CTA compares favorably with the reference-standard, DSA. Methods: We searched electronic databases (1950 to May 22, 2012), article bibliographies, conference proceedings (2008–2011), and clinical trial registries for studies comparing the accuracy of CTA with DSA for BCVI detection in trauma patients. Pooled estimates of sensitivity, specificity, and positive and negative likelihood ratios were calculated using bivariate random effects models. Results: Eight studies that examined 5704 carotid or vertebral arteries in 1426 trauma patients met inclusion criteria. The pooled sensitivity and specificity for BCVI detection with CTA versus DSA was 66% (95% CI, 49%–79%; I2 = 80.4%) and 97% (95% CI, 91%–99%; I2 = 94.6%), respectively. Corresponding pooled positive and negative likelihood ratios were 20.0 (95% CI, 6.9–58.4; I2 = 87.7%) and 0.35 (95% CI, 0.22–0.56; I2 = 74.9%), respectively. Although pooled sensitivity varied with the number of available CT slices, the training of interpreting radiologists, and in a pattern suggestive of differences in diagnostic threshold for judging CTA positivity, it remained 80% or less among studies that used scanners with 16 or more slices per rotation and where the CTA was read by neuroradiologists. Conclusions: Existing evidence suggests that the diagnostic performance of CTA varies considerably across studies, likely due to an implicit variation in diagnostic threshold across trauma centers. Moreover, although CTA appears to lack sensitivity to adequately rule out BCVI, it may be useful to rule in BCVI among trauma patients with a high pretest probability of injury. This meta-analysis suggests that the diagnostic performance of computed tomographic angiography (CTA) for blunt cerebrovascular injury (BCVI) detection varies considerably between studies, likely due to a variation in diagnostic threshold across institutions. Existing evidence also suggests that CTA has excellent specificity, but limited sensitivity, for BCVI detection in trauma patients.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| 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".