Assessment of Deep Vein Thrombosis or Pulmonary Embolism by the Combined Use of Clinical Model and Noninvasive Diagnostic Tests
Bibliographic record
Abstract
Deep vein thrombosis (DVT) and pulmonary embolism (PE) are relatively common diseases and are amenable to therapy but with a potentially fatal outcome if untreated. The diagnosis can be made in most patients with use of the noninvasive imaging tests, but limitations exist. The standard first choice of investigation in patients with suspected DVT is compression ultrasonography (CUS). As with all tests, there is a potential for false-positive and false-negative results. The latter are especially an issue for calf vein thrombi, and this in part has led to the concept of serial CUS testing of the proximal venous system and not imaging of the calf. The premise of the repeat (serial) CUS test is that only thrombi that extend to the proximal system are clinically relevant, and these thrombi will be detected during subsequent testing. However, despite the safety of the serial CUS testing concept, it is inconvenient and expensive. The standard first choice of investigation in patients with suspected PE, the ventilation-perfusion (V/Q) lung scan is nondiagnostic in most cases. In the past few years, the diagnostic process has improved because of the validation of clinical models that accurately categorize patients as having low (5%), moderate (20% to 30%), or high probability (>60%) for venous thromboembolic disease. Among the improvements this provides is the elimination of serial CUS testing if the ultrasound results are normal and the clinical probability is low in patients with suspected DVT. In patients with suspected PE in whom further testing is necessary, determination of clinical probability allows selection of invasive (angiography) or noninvasive testing (serial ultrasound) in patients with non-high-probability V/Q scans. The fibrin degradation product D-dimer has had a high negative predictive value; negative results with enzyme-linked immunosorbent assay (ELISA) tests effectively rule out DVT or PE. In addition, a negative result with less-sentive D-dimer testing and a low clinical probability excludes DVT or PE.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".