P254“HERDOO2” clinical decision rule to guide duration of anticoagulation in women with unprovoked venous thromboembolism: D-Dimer inter-assay concordance
Bibliographic record
Abstract
Background: The “HERDOO2” rule is a prospectively validated clinical decision rule used to identify low-risk women who can safely discontinue anticoagulants after 5–12 months of treatment for unprovoked venous thromboembolism (VTE). The VIDAS® D-Dimer (DD) assay, a component of the rule, was used in the derivation (Rodger, CMAJ, 2008) and validation (Rodger, BMJ, 2016) of the rule at half the usual diagnostic cut-point for exclusion of VTE. It is unknown if other commercial DD assays used at a corresponding cut-point will categorize patients at high concordance with the VIDAS® DD (the clinical gold standard for this indication). Purpose: To determine if other available DD assays have high enough concordance with the VIDAS DD assay to allow their use with “HERDOO2” rule. Methods: Frozen plasma samples from a sub-set (n=250) of female participants (“HERDOO2” is only applied in women) in the “HERDOO2” validation study were tested using the VIDAS®, Innovance, HemosIL®, Tina-quant and Liatest® DD assays. First, we determined the optimal cut-point values for each test that corresponded with a VIDAS® DD result of 250μg/L using linear regression analysis in 50 samples with duplicate testing for each tested DD (mean results used in regression analysis). Next, kappa analysis was conducted on the DD results of the remaining 200 samples to determine concordance between each tested DD at the respective optimal cut-points and the VIDAS® DD at 250μg/L. In a separate analysis we determined the concordance at half the usual VTE exclusion cut-point.
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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 | 0.010 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".