Imaging Characteristics of a Novel Technetium Tc 99m–Labeled Platelet Glycoprotein IIb/IIIa Receptor Antagonist in Patients With Acute Deep Vein Thrombosis or a History of Deep Vein Thrombosis
Bibliographic record
Abstract
BACKGROUND: The diagnosis of recurrent deep vein thrombosis (DVT) is challenging. Imaging with radiolabeled peptides offers a new approach for detecting acute DVT. Technetium Tc 99m ((99m)Tc)-apcitide binds with high affinity and specificity to the glycoprotein IIb/IIIa receptors expressed on activated platelets and, therefore, (99m)Tc-apcitide scintigraphy should be negative with residual abnormalities caused by old, inactive thrombi and positive with new, active thrombi. METHODS: In a prospective multicenter study, (99m)Tc-apcitide imaging was performed on 38 patients with a newly diagnosed first DVT (group 1) and 40 patients with previous DVT, symptoms of postthrombotic syndrome, and chronic intraluminal abnormalities on ultrasonography (group 2). Images were interpreted in a blinded fashion by 2 experts and by newly trained nuclear medicine physicians. The sensitivity and specificity of (99m)Tc-apcitide were determined by calculating the proportion of scans in group 1 patients that were read as "positive for acute DVT" and the proportion of scans in group 2 patients that were read as "negative for acute DVT," respectively. RESULTS: When read by 2 experts, ( 99m)Tc-apcitide had a sensitivity of 92% for both readers and specificities of 82% and 90%. Agreement between the experts was excellent. However, the accuracy and interreader agreement for newly trained nuclear medicine physicians were lower. CONCLUSIONS: Technetium Tc 99m-apcitide scintigraphy has potential utility in suspected recurrent DVT because it detects most acute thrombi and has few false-positive results in patients with previous DVT. However, the accuracy appears to depend on the training and experience of the interpreters.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".