Diagnostic Pathways in Acute Pulmonary Embolism: Recommendations of the PIOPED II Investigators
Bibliographic record
Abstract
Abstract Purpose To formulate comprehensive recommendations for the diagnostic approach to patients with suspected pulmonary embolism, based on randomized trials. Methods Diagnostic management recommendations were formulated based on results of the Prospective Investigation of Pulmonary Embolism Diagnosis II (PIOPED II) and outcome studies. Results The PIOPED II investigators recommend stratification of all patients with suspected pulmonary embolism according to an objective clinical probability assessment. D-dimer should be measured by the quantitative rapid enzyme-linked immunosorbent assay (ELISA), and the combination of a negative D-dimer with a low or moderate clinical probability can safely exclude pulmonary embolism in many patients. If pulmonary embolism is not excluded, contrast-enhanced computed tomographic pulmonary angiography (CT angiography) in combination with venous phase imaging (CT venography), is recommended by most PIOPED II investigators, although CT angiography plus clinical assessment is an option. In pregnant women, ventilation/perfusion scans are recommended by many as the first imaging test following D-dimer and perhaps venous ultrasound. In patients with discordant findings of clinical assessment and CT angiograms or CT angiogram/CT venogram, further evaluation may be necessary. Conclusion The sequence for diagnostic test in patients with suspected pulmonary embolism depends on the clinical circumstances.
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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 | 0.117 | 0.274 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".