Comparison of the Precision of Compression Ultrasonography and Duplex Sonography in Deep Venous Thrombosis Patients
Bibliographic record
Abstract
Deep venous thrombosis is a prevalent disease and difficult being detected which can be lethal if developed. Ultrasonography and duplex ultrasonography are two of the diagnostic methods with their restrictions. The present study addresses the analysis of the succession of compression ultrasonography as a method with less restrictions in comparison with ultrasonography and duplex ultrasonography. The present study was conducted in the central urgency section of Imam Reza Hospital, Mashhad, Iran, which is a public academic institute, on 70 patients in 2014. All patients were subjected to compression ultrasonography before duplex ultrasonography and those who had previous duplex ultrasonography sessions with available results were excluded from the investigations. Finally, the results of 63 patients were analyzed, 7 being excluded due to their inaccessible data. According to the results, 52 percent of subjects were males and 48 percent were females. The result of the regular ultrasonography was positive for 37 and negative for 26 patients. Duplex ultrasonography, however, led to positive results for 35 patients (equivalent to 37 lower limb organs) and negative results for 28 subjects (equivalent to 41 lower limb organs). The sensitivity, specificity, and precision of the diagnosis via compression ultrasonography were found to be 97, 90, and 93.5 percent, respectively, and the positive and negative predictive values were calculated to be 90 and 97 percent, respectively, with a CI of 95 percent. The diagnostic accuracy of 96.8% suggests that the use of compression sonography can be a good accuracy in the diagnosis of deep vein thrombosis of the lower extremities, but it cannot replace more accurate methods that are currently used as available selected diagnostic methods.
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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 | 0.025 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 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".