Interest of chest X-ray in tailoring the diagnostic strategy in patients with suspected pulmonary embolism
Bibliographic record
Abstract
Current diagnostic strategies for pulmonary embolism rely on the sequential use of noninvasive diagnostic tests including ventilation-perfusion (V/Q) scan and computed tomography pulmonary angiography (CTPA). V/Q scan remains criticized because of a high proportion of nondiagnostic test results, especially when the chest X-ray (CXR) is abnormal. The present study assesses whether CXR results have an impact on the conclusiveness of a noninvasive diagnostic strategy of pulmonary embolism based on the combination of pretest probability, compression ultrasonography, V/Q scan, and CTPA. Patients suspected of having pulmonary embolism were managed according to a validated diagnostic strategy. All patients underwent a CXR within 24 h of the suspicion of pulmonary embolism. CXR results were correlated to strategy conclusiveness, as assessed by the rate of required CTPA as per the diagnostic algorithm. Two hundred and twenty-three patients were retrospectively analyzed. CXRs were considered as normal in 108 (48%) patients and abnormal in 115 (52%) patients. According to the diagnostic algorithm, a CTPA was required to reach a diagnostic conclusion in 11 (10%) patients of the normal CXR group, and in 14 (12%) patients of the abnormal CXR group (P > 0.05). In this study, the presence of CXR abnormalities did not have an impact on the conclusiveness of a diagnostic strategy of pulmonary embolism based on V/Q scan. CXR abnormalities should likely not be regarded as a contraindication to the use of V/Q scan in patients with suspected pulmonary embolism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".