Pulmonary embolism: update on management and controversies
Bibliographic record
Abstract
Pulmonary embolism is a common and potentially fatal cardiovascular disorder that must be promptly diagnosed and treated. The diagnosis, risk assessment, and management of pulmonary embolism have evolved with a better understanding of efficient use of diagnostic and therapeutic options. The use of either clinical probability adjusted or age adjusted D-dimer interpretation has led to a reduction in diagnostic imaging to exclude pulmonary embolism. Direct oral anticoagulation therapies are safe, effective, and convenient treatments for most patients with acute venous thromboembolism, with a lower risk of bleeding than vitamin K antagonists. These oral therapeutic options have opened up opportunities for safe outpatient management of pulmonary embolism in selected patients. Recent clinical trials exploring the use of systemic thrombolysis in intermediate to high risk pulmonary embolism suggest that this therapy should be reserved for patients with evidence of hemodynamic compromise. The role of low dose systemic or catheter directed thrombolysis in other patient subgroups is uncertain. After a diagnosis of pulmonary embolism, all patients should be assessed for risk of recurrent venous thromboembolism to guide duration of anticoagulation. Patients with a venous thromboembolism associated with a strong, transient, provoking risk factor can safely discontinue anticoagulation after three months of treatment. Patients with an ongoing strong risk factor, such as cancer, or unprovoked events are at increased risk of recurrent events and should be considered for extended treatment. The use of a risk prediction score can help to identify patients with unprovoked venous thromboembolism who can benefit from extended duration therapy. Despite major advances in the management of pulmonary embolism, up to half of patients report chronic functional limitations. Such patients should be screened for chronic thromboembolic pulmonary hypertension, but only a small proportion will have this as the explanation of their symptoms. In the remaining patients, future studies are needed to understand the pathophysiology and explore interventions to improve quality of life.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.000 | 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, 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".