Validation of the STA-Liatest DDi assay for exclusion of proximal deep vein thrombosis according to the latest Clinical and Laboratory Standards Institute/Food and Drug Administration guideline
Bibliographic record
Abstract
: Recommended strategy for venous thromboembolism (VTE) diagnosis includes the use of sensitive D-dimer (DDi) assays along with pretest probability (PTP) assessment. The Clinical and Laboratory Standards Institute (CLSI) recently issued a guideline (US FDA endorsed) on DDi in VTE exclusion. Such guideline specifies the ideal D-dimer assay characteristics and target population. Demonstrate STA-LiatestD-Di performance combined with a PTP score for proximal deep vein thrombosis (pDVT) exclusion in a CLSI compliant study. International, multicenter, prospective nonrandomized, noninterventional clinical outcome management study conducted in a standard-of-care setting. DDi was measured in DVT-suspected consecutive low/moderate PTP outpatients, without conditions possibly impacting DDi values independently of thrombosis presence (age >80, pregnancy, postoperative, cancer) using a 0.5 μg/ml (FEU) threshold for DVT exclusion. Results were used to determine test performance. One thousand two hundred and thirty-four patients (17 centers) signed informed consent. Nine hundred and eighty (mean age: 55) with valid results (494 negative DDi) completed the study (DVT prevalence: 8.7%). STA-LiatestD-Di performance exceeded CLSI/FDA requirements: sensitivity: 100% (95% CI 95.8-100%), NPV: 100% (95% CI 99.3-100%). STA-LiatestD-Di associated with PTP score showed excellent performance for pDVT exclusion, as recently demonstrated for pulmonary embolism. The assay allows safe VTE exclusion, avoiding unnecessary imaging tests.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".