CT Venography and Compression Sonography Are Diagnostically Equivalent: Data from PIOPED II
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to compare the clinical value of CT venography (CTV) after MDCT angiography (CTA) with venous compression sonography for the diagnosis of venous thromboembolism (VTE). The Prospective Investigation of Pulmonary Embolism Diagnosis II (PIOPED II) showed that lower extremity imaging detects about 7% more patients requiring anticoagulation than CTA alone. SUBJECTS AND METHODS: PIOPED II was a prospective multicenter study investigating the accuracy of CTA alone and CTA and CTV together. A composite reference standard was used to confirm, or rule out, pulmonary embolus. Adequate quality CTV and sonographic images were obtained in 711 patients. RESULTS: There was 95.5% concordance between CTV and sonography for the diagnosis or exclusion of deep venous thrombosis (DVT); the kappa statistic was 0.809. The sensitivity and specificity of combined CTA and CTV were equivalent to those of combined CTA and sonography. Diagnostic results in subgroups, including patients with signs or symptoms of DVT, asymptomatic patients, and patients with a history of DVT, were similar whether CTV or sonography was used. Patients with signs or symptoms of DVT were eight times more likely to have DVT, and patients with a history of DVT were twice as likely to have positive findings. CONCLUSION: CTV and sonography showed similar results in diagnosing or excluding DVT. The incidence of positive studies in patients without signs, symptoms, or history of DVT is low. In terms of clinical significance, CT venography and lower extremity sonography yield equivalent diagnostic results; the incidence of positive studies in patients without signs, symptoms, or history of DVT is low; thus the choice of imaging technique can be made on the basis of safety, expense, and time constraints.
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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 | 0.004 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".