Estimated Effect of an Integrated Approach to Suspected Deep Venous Thrombosis Using Limited‐compression Ultrasound
Bibliographic record
Abstract
OBJECTIVES: Deep vein thrombosis (DVT) is both common and serious, yet the desire to never miss the diagnosis, coupled with the low specificity of D-dimer testing, results in high imaging rates, return visits, and empirical anticoagulation. The objective of this study was to evaluate a new approach incorporating bedside limited-compression ultrasound (LC US) by emergency physicians (EPs) into the workup strategy for DVT. METHODS: This was a cross-sectional observational study of emergency department (ED) patients with suspected DVT. Patients on anticoagulants; those with chronic DVT, leg cast, or amputation; or when the results of comprehensive imaging were already known were excluded. All patients were treated in the usual fashion based on the protocol in use at the center, including comprehensive imaging based on the modified Wells score and serum D-dimer testing. Seventeen physicians were trained and performed LC US in all subjects. The authors identified a priori an alternate workup strategy in which DVT would be ruled out in "DVT unlikely" (Wells score < 2) patients if the LC US was negative and in "DVT likely" (Wells score ≥ 2) patients if both the LC US and the D-dimer were negative. The criterion standard was based on comprehensive imaging interpreted by radiologists blinded to LC US findings and by structured medical record review at 6 months in patients without comprehensive imaging. RESULTS: A total of 227 patients were enrolled (47% DVT likely), of whom 24 had DVT. The LC US was positive in 27 cases (21 actually DVT positive), indeterminate in 28 (one DVT positive), and negative in 172 (two DVT positive). Of 130 patients deemed DVT negative by the new strategy, one had confirmed DVT (miss rate = 0.8%; 95% confidence interval [CI] = 0.1% to 4.0%), but this patient had been misclassified by the treating physician as low risk by Wells criteria. The stand-alone sensitivity and specificity of LC US were 91% (95% CI = 70% to 98%) and 97% (95% CI = 92% to 99%), respectively. Incorporating LC US into the diagnostic approach would have reduced the rate of comprehensive imaging from 70% to 43%, D-dimer testing from 100% to 33%, and the mean time to diagnostic certainty by 5.0 hours and avoided 24 (11%) return visits for imaging and 10 (4.4%) cases of unnecessary anticoagulation. In 19% of cases, the treating and scanning physician disagreed whether the patient was DVT likely or DVT unlikely based on Wells score (κ = 0.62; 95% CI = 0.48 to 0.77). CONCLUSIONS: Limited-compression US holds promise as one component of the diagnostic approach to DVT, but should not be used as a stand-alone test due to imperfect sensitivity. Tradeoffs in diagnostic efficiency for the sake of perfect sensitivity remain a difficult issue collectively in emergency medicine (EM), but need to be scrutinized carefully in light of the costs of overinvestigation, delays in diagnosis, and risks of empirical anticoagulation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".