Safety of a D-dimer based strategy and repeated ultrasonography did not differ in DVT and normal proximal vein ultrasonography
Bibliographic record
Abstract
Kearon C, Ginsberg JS, Douketis J, et al. A randomized trial of diagnostic strategies after normal proximal vein ultrasonography for suspected deep venous thrombosis: D-dimer testing compared with repeated ultrasonography. Ann Intern Med 2005;142:490–6. [OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] Q In patients with suspected deep venous thrombosis (DVT) and negative results on proximal vein ultrasonography, how does a D-dimer–based management strategy that minimises additional assessments compare with routine repeated ultrasonography? Clinical impact ratings IM/Ambulatory care ★★★★★★☆ Emergency medicine ★★★★★☆☆ Haematology ★★★★★★☆ ### ![Graphic][5] Design: randomised controlled trial. ### ![Graphic][6] Allocation: concealed.* ### ![Graphic][7] Blinding: blinded (outcome assessors).* ### ![Graphic][8] Follow up period: 6 months. ### ![Graphic][9] Setting: thrombosis services of 4 university hospitals in Hamilton, Ontario, Canada. ### ![Graphic][10] Patients: 810 patients (mean age 59.5 y, 62% women) with a suspected first episode of DVT and negative results on proximal vein ultrasonography who were referred by primary care and hospital-based physicians to a thrombosis outpatient service. Exclusion criteria included life expectancy <6 months, contraindication to venography, use of full dose heparin for >48 hours, use of long term warfarin therapy, symptoms of pulmonary embolism, and … [1]: {openurl}?query=rft.jtitle%253DAnnals%2Bof%2BInternal%2BMedicine%26rft.stitle%253DANN%2BINTERN%2BMED%26rft.issn%253D0003-4819%26rft.aulast%253DKearon%26rft.auinit1%253DC.%26rft.volume%253D142%26rft.issue%253D7%26rft.spage%253D490%26rft.epage%253D496%26rft.atitle%253DA%2BRandomized%2BTrial%2Bof%2BDiagnostic%2BStrategies%2Bafter%2BNormal%2BProximal%2BVein%2BUltrasonography%2Bfor%2BSuspected%2BDeep%2BVenous%2BThrombosis%253A%2BD-Dimer%2BTesting%2BCompared%2Bwith%2BRepeated%2BUltrasonography%26rft_id%253Dinfo%253Adoi%252F10.7326%252F0003-4819-142-7-200504050-00007%26rft_id%253Dinfo%253Apmid%252F15809460%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.7326/0003-4819-142-7-200504050-00007&link_type=DOI [3]: /lookup/external-ref?access_num=15809460&link_type=MED&atom=%2Febmed%2F10%2F6%2F179.atom [4]: /lookup/external-ref?access_num=000228167800002&link_type=ISI [5]: /embed/inline-graphic-1.gif [6]: /embed/inline-graphic-2.gif [7]: /embed/inline-graphic-3.gif [8]: /embed/inline-graphic-4.gif [9]: /embed/inline-graphic-5.gif [10]: /embed/inline-graphic-6.gif
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".