Implementation of the YEARS algorithm to optimise pulmonary embolism diagnostic workup in the emergency department
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Excessive use of CT pulmonary angiography (CTPA) to investigate pulmonary embolism (PE) in the emergency department (ED) contributes to adverse patient outcomes. Non-invasive D-dimer testing, in the context of a clinical algorithm, may help decrease unnecessary imaging but this has not been widely implemented in Canadian EDs. AIM: To improve the diagnostic yield of CTPA for PE by 5% (absolute) within 12 months of implementing the YEARS algorithm. MEASURES AND DESIGN: Single centre study of all ED patients >18 years investigated for PE with D-dimer and/or CTPA between February 2021 and January 2022. Primary and secondary outcomes were the diagnostic yield of CTPA and frequency of CTPA ordered compared with baseline. Process measures included the percentage of D-dimer tests ordered with CTPA and CTPAs ordered with D-dimers <500 µg/L Fibrinogen Equivalent Units (FEU). The balancing measure was the number of PEs identified on CTPA within 30 days of index visit. Multidisciplinary stakeholders developed plan- do-study-act cycles based on the YEARS algorithm. RESULTS: Over 12 months, 2695 patients were investigated for PE, of which 942 had a CTPA. Compared with baseline, the CTPA yield increased by 2.9% (12.6% vs 15.5%, 95% CI -0.06% to 5.9%) and the proportion of patients that underwent CTPA decreased by 11.4% (46.4% vs 35%, 95% CI -14.1% to -8.8%). The percentage of CTPAs ordered with a D-dimer increased by 26.3% (30.7% vs 57%, 95% CI 22.2% 30.3%) and there were two missed PE (2/2695, 0.07%). IMPACT: Implementing the YEARS criteria may safely improve the diagnostic yield of CTPAs and reduce the number of CTPAs completed without an associated increase in missed clinically significant PEs. This project provides a model for optimising the use of CTPA in the ED.
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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 | Other design | low |
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it