Using an age-dependent D-dimer cut-off value increases the number of older patients in whom deep vein thrombosis can be safely excluded
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Bibliographic record
Abstract
BACKGROUND: D-dimer testing to rule out deep vein thrombosis is less useful in older patients because of a lower specificity. An age-adjusted D-dimer cut-off value increased the proportion of older patients (>50 years) in whom pulmonary embolism could be excluded. We retrospectively validated the efficacy of this cut-off combined with clinical probability for the exclusion of deep vein thrombosis. DESIGN AND METHODS: Five management study cohorts of 2818 consecutive outpatients with suspected deep vein thrombosis were used. Patients with non-high or unlikely probability of deep vein thrombosis were included in the analysis; four different D-dimer tests were used. The proportion of patients with a normal D-dimer test and the failure rates were calculated using the conventional (500 μg/L) and the age-adjusted D-dimer cut-off (patient's age x 10 μg/L in patients >50 years). RESULTS: In 1672 patients with non-high probability, deep vein thrombosis could be excluded in 850 (51%) patients with the age-adjusted cut-off value versus 707 (42%) patients with the conventional cut-off value. The failure rates were 7 (0.8; 95% confidence interval 0.3-1.7%) for the age-adjusted cut-off value and 5 (0.7%, 0.2-1.6%) for the conventional cut-off value. The absolute increase in patients in whom deep vein thrombosis could be ruled out using the age-adjusted cut-off value was largest in patients >70 years: 19% among patients with non-high probability. CONCLUSIONS: The age-adjusted cut-off of the D-dimer combined with clinical probability greatly increases the proportion of older patients in whom deep vein thrombosis can be safely excluded.
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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) | 0.001 | 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) | 0.001 | 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 it