Optimal approach to performing and reporting computed tomography angiography for suspected acute pulmonary embolism: a clinical consensus statement of the ESC Working Group on Pulmonary Circulation & Right Ventricular Function, the Fleischner Society, the Association for Acute CardioVascular Care (ACVC) and the European Association of Cardiovascular Imaging (EACVI) of the ESC, endorsed by European Respiratory Society (ERS), Asian Society of Thoracic Radiology (ASTR), European Society of Thoracic Imaging (ESTI), and Society of Thoracic Radiology (STR)
Bibliographic record
Abstract
Computed tomography angiography (CTA) is the modality used most frequently for diagnosing acute pulmonary embolism (PE). Given the vast amount of information that can be extracted from CTA, the CTA report should be written in a way that conveys all relevant findings using standardized nomenclature and definitions. Broad consensus on a core set of CTA findings that are relevant for all PE patients is not currently available. This clinical consensus statement written by the European Society of Cardiology (ESC) Working Group on Pulmonary Circulation and Right Ventricular Function, the Fleischner Society and the Association for Acute Cardiovascular Care and the European Association of Cardiovascular Imaging of the ESC provides a current update of CTA techniques, a definition of often used nomenclature and recommendations on the proposed content of CTA reports along with a detailed image atlas with instructions on how to assess all relevant CTA findings and a lay language guidance on the meaning of these findings. Ultimately, upon implementation, this document is expected to standardize CTA radiology reports with respect to diagnostic and prognostic CT imaging findings to guide and harmonize management decisions, ultimately improving outcomes of care for PE patients.
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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 | 0.101 | 0.134 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.011 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.012 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 0.007 |
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".