Diagnosis of deep vein thrombosis of the upper extremity: a systematic review and meta-analysis of test accuracy
Bibliographic record
Abstract
Abstract Upper extremity deep vein thrombosis (UEDVT) accounts for ≤10% of DVT and can be associated with morbidity and mortality. Accurate diagnosis and treatment are necessary for safe and effective patient management. We systematically reviewed the accuracy of D-dimer and duplex ultrasonography (US) for the evaluation of suspected first-episode UEDVT. We searched the Cochrane Central Register, OVID MEDLINE, EMBASE, and PubMed for eligible studies, reference lists of relevant reviews, registered trials, and relevant conference proceedings. We included prospective cross-sectional and cohort studies that evaluated test accuracy. Two investigators independently screened and collected data. The risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies 2 and certainty of evidence using the Grading of Recommendations Assessment, Development and Evaluation framework. We pooled estimates of sensitivity and specificity. The review included 9 studies. The pooled estimates for D-dimer sensitivity and specificity were 0.96 (95% confidence interval [CI], 0.87-0.99) and 0.47 (95% CI, 0.43-0.52), respectively. The pooled estimates for duplex US sensitivity and specificity were 0.87 (95% CI, 0.73-0.94) and 0.85 (95% CI, 0.72-0.93), respectively. Certainty of evidence was moderate. In this review, we summarized the test accuracy (sensitivity and specificity) of D-dimer and duplex US for this indication. The sensitivity and specificity of the tests found in the present review should be considered in the context of whether they are used alone or in combination, which is dependent on the prevalence of disease in the population, the clinical setting in which the patient is being evaluated, cost, potential harms, and patient outcomes. This study was registered at PROSPERO as Systematic Review Registration Number CRD42018098488.
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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 | 0.031 | 0.089 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.034 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".