“HERDOO2” clinical decision rule to guide duration of anticoagulation in women with unprovoked venous thromboembolism. Can I use any d-Dimer?
Bibliographic record
Abstract
BackgroundThe “HERDOO2 rule” is a prospectively validated clinical decision rule used to identify low-risk women who can safely discontinue anticoagulants after completing 5–12 months of anticoagulant treatment for unprovoked venous thromboembolism. The VIDAS® d-Dimer (DD) assay, a component of the rule, was used in the derivation and validation of the rule at half the usual diagnostic cut-point for exclusion of venous thrombosis. It is unknown if other commercial DD assays used at a corresponding cut-point will categorize patients at high concordance with the VIDAS® DD.ObjectiveTo determine if other available automated quantitative DD assays have high enough concordance with the VIDAS® DD assay to allow their use within the “HERDOO2” clinical decision rule.MethodsFrozen plasma samples from a sub-set (n = 248) of female participants in the “HERDOO2” validation study were tested using five DD assays: VIDAS®, Innovance®, HemosIL®, Tina-quant® and Liatest®, with duplicate testing for 50 samples. First, using the mean DD for 50 samples with duplicate results, we determined the optimal cut-point values for each test that corresponded with a VIDAS® DD result of 250 μg/L using linear regression analysis. Next, kappa analysis was conducted on the DD results of the remaining 198 samples to determine concordance between each tested DD at the respective optimal cut-point and the VIDAS® DD at 250 μg/L. In a separate analysis we determined the concordance at half the usual venous thrombosis exclusion cut-point.ResultsRegression analysis of the DD results in 50 samples identified the optimal cut-point for each DD assay to match a VIDAS® DD cut-point of 250 μg/L: Innovance® 177 μg/L, Liatest® 233 μg/L, Tina-quant® 48 μg/L and HemosIL® 56 μg/L. Next, in 198 different samples, the concordance of VIDAS® DD (≥250 μg/L or <250 μg/L) was explored at the optimal cut-point of the other DD assays. The concordance was poor for all DD assays: Innovance® (kappa 0.38 (95% CI, 0.26–0.51)), Liatest® (kappa 0.38 (95% CI, 0.25–0.50)), HemosIL® (kappa 0.36 (95% CI, 0.23–0.49)) and Tina-quant® (kappa 0.30 (95% CI, 0.16–0.43)). Similar poor concordance was identified using half of the diagnostic DD cut-point for each tested assay: Innovance® (kappa 0.44 (95% CI, 0.32–0.56)), Liatest® (kappa 0.38 (95% CI, 0.25–0.51)), HemosIL® (kappa 0.04 (95% CI, −0.01—0.08)) and Tina-quant® (kappa 0.04 (95% CI, −0.004–0.07)).ConclusionThe “HERDOO2 rule” is the only prospectively validated clinical decision rule that can be used to identify low-risk women with unprovoked venous thrombosis who can safely discontinue anticoagulants. An important implementation issue is whether any commercial DD assay can be used in the HERDOO2 rule, and at what cut-point. Our analysis shows that the HemosIL®, Innovance®, Liatest® and Tina-quant® DD assays should not be used in the “HERDOO2” rule due to poor concordance with the VIDAS® DD assay and unacceptable misclassification of women at high and low risk of recurrent venous thrombosis.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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".