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 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 | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".