Should we be looking for and treating isolated calf vein thrombosis?
Bibliographic record
Abstract
Management of isolated calf deep vein thrombosis is an area of significant international debate and variable clinical practice. Both therapeutic anticoagulation and conservative management carry risk. As clinical care of suspected and confirmed venous thromboembolic disease increasingly becomes the remit of emergency medicine, complex decisions are left to practising clinicians at the front door. We aim to provide a contemporary overview of recent evidence on this topic and associated challenges facing clinicians. Given the lack of high-level evidence, we present this work as a narrative review, based on structured literature review and expert opinion. A decision to manage calf thrombosis is principally dependent on the risk of complications without treatment balanced against the risks of therapeutic anticoagulation. Estimates of the former risks taken from systematic review, meta-analysis, observational cohort and recent pilot trial evidence include proximal propagation 7%-10%, pulmonary embolism 2%-3% and death <1%. Fatal bleeding with therapeutic anticoagulation stands at <0.5%, and major bleeding at approximately 2%. Estimates of haemorrhagic risk are based on robust data from large prospective management studies of venous thromboembolic disease; the risks of untreated calf deep vein thrombosis are based on small cohorts and therefore less exact. Pending further trial evidence, these risks should be discussed with patients openly, in the context of personal preference and shared decision-making. Anticoagulation may maximally benefit those patients with extensive and/or symptomatic disease or those with higher risk for complication (unprovoked, cancer-associated or pregnancy).
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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 | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".