Is CT pulmonary angiography overutilized in the evaluation of patients with suspected pulmonary embolism? A retrospective study
Bibliographic record
Abstract
Introduction: Despite the high mortality rate of acute untreated pulmonary embolism (PE) at 30%, diagnosing PE is challenging. While the prevalence of PE has decreased in recent years, the overuse of computed tomography pulmonary angiography (CTPA) remains a concern. The National Institute for Health and Care Excellence (NICE) provides guidelines using the Wells score for PE assessment. The Royal College of Radiologists (RCR) recommends a positive yield of 15.4% - 37% for CTPA tests. This study assesses the positive yield of CTPA for suspected PE patients and evaluates the potential reduction through Wells score/D-dimer assessment as recommended by NICE. Methods: All patients who underwent CTPA between September 1, 2019, and January 31, 2020, at Salmaniya Medical Complex were included. Data on patient demographics and pre-CTPA workup were collected from electronic patient records (EPR) and stored in MS Excel 2019 for analysis. Results: Of 188 suspected PE patients (mean age 50 ±12.3 years; 62.8% female), 12.2% were diagnosed with PE. None had documented Wells scores. A low-risk Wells score (≤4) was assigned to 68.6% of patients, with only 26.1% undergoing D-dimer testing. PE was confirmed in 4 patients with low-risk Wells scores and elevated D-dimers. All 10 patients with low-risk Wells scores and negative D-dimers were PE-negative. Conclusion: In total, 5.3% - 47.9% of the CTPAs conducted could have been avoided by following NICE guidelines. We propose integrating an algorithm-based checklist with validated tools like the Wells and Geneva scores into the ePMA system to guide appropriate CTPA referrals, promote evidence-based decision-making, reduce unnecessary imaging, and optimize patient care and resource use.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.000 |
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 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".