Single whole‐leg compression ultrasound for exclusion of deep vein thrombosis in symptomatic ambulatory patients: a prospective observational cohort study
Bibliographic record
Abstract
International guidance has recently recommended serial proximal compression ultrasound (CUS) as first line imaging for suspected deep vein thrombosis (DVT). Single whole-leg CUS is a routine alternative diagnostic strategy that can reduce repeated attendances and identify alternative pathology. We conducted a prospective observational cohort study. Consecutive ambulatory, adult patients with suspected DVT and negative or inconclusive whole-leg CUS had anticoagulation withheld and were followed for 3 months. The primary outcome was a predefined clinically relevant adverse event rate. Secondary outcomes included technical failure, alternative diagnoses and all cause mortality. 212 patients agreed to participate and completed follow up. One patient was subsequently diagnosed with an isolated distal DVT. The adverse event rate was thus 1/212, 0·47% (95% confidence interval [CI] 0·08-2·62). Technical imaging failure occurred in 11·3% of cases (95% CI 7·7-16·3). Several potential predictors of an inconclusive result were identified on multivariate analysis. 150 (70·8%) patients were provided with a documented alternative diagnosis. Patients who have anticoagulation withheld following a negative or inconclusive whole-leg CUS for suspected DVT have a low rate of adverse events. Technical failure remains an issue: several factors were significantly associated with inconclusive results and may warrant an alternative diagnostic approach.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 | 0.000 |
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".