Multidetector computed tomography for the diagnosis of acute pulmonary embolism
Bibliographic record
Abstract
PURPOSE OF REVIEW: This review describes the accuracy of multidetector contrast-enhanced computed tomography (CT) for the diagnosis of acute pulmonary embolism, the role of clinical assessment and of venous phase imaging in combination with it, and the approach to the diagnosis. RECENT FINDINGS: The sensitivity of CT angiography was 83%, specificity 96% and positive predictive value 86%. Positive predictive values were 97% for pulmonary embolism in a main or lobar artery, 68% for a segmental vessel, and 25% for a subsegmental branch. A CT angiogram with concordant clinical probability assessment resulted in high predictive values, but with a discordant clinical probability, predictive value was low. The sensitivity for pulmonary embolism increased to 90% by using CT venography in combination with CT angiography.A negative D-dimer by the rapid enzyme-linked immunosorbent assay method with a low or moderate probability clinical assessment can safely exclude pulmonary embolism. Clinical probability assessment and D-dimer are recommended. In general, CT angiography in combination with CT venography is recommended, but the choice of diagnostic tests depends on the clinical situation. SUMMARY: The reliability of multislice CT angiography is enhanced by clinical assessment and CT venography used with it. Clinical assessment and D-dimer are recommended before imaging.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".