Spiral Computed Tomography Is Comparable to Angiography for the Diagnosis of Pulmonary Embolism
Bibliographic record
Abstract
The use of spiral computed tomography (CT) for the diagnosis of pulmonary embolism has been compared to angiography, the current gold standard. However, the accuracy of pulmonary angiography has never been evaluated against an independent gold standard. The aim of this study was to compare contrast-enhanced spiral CT to pulmonary angiography for the detection of subsegmental-sized pulmonary emboli by using a methacrylate cast of porcine pulmonary vessels as an independent gold standard. We studied 16 anesthetized, juvenile pigs and injected colored methacrylate beads (3.8 mm, small; 4.2 mm, large) via the jugular vein. After embolization spiral CT (3 mm and 1 mm collimation), and pulmonary angiography were performed. Pigs were killed and the pulmonary arterial tree was cast using methacrylate. Spiral CT and angiography were interpreted independently by two radiologists. Sensitivity and 95% confidence intervals for 3 mm and 1 mm collimation CT and angiography, respectively, were: 82% (73 to 88%), 87% (79 to 93%), 87% (79 to 93%) (p = 0.42). Positive predictive values and 95% confidence intervals for 3 mm and 1 mm collimation CT and angiography, respectively, were: 94% (86 to 94%), 81% (73 to 88%), and 88% (80 to 93%). There was no difference between spiral CT and angiography for detection of subsegmental-sized pulmonary emboli. We conclude that spiral CT is comparable to angiography for detection of pulmonary emboli.
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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 | 0.008 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.001 |
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".