External validation and comparison of recently described prediction rules for suspected pulmonary embolism
Bibliographic record
Abstract
PURPOSE OF REVIEW: The assessment of pretest probability, allowing the categorization of patients clinically suspected of having pulmonary embolism in low, intermediate, and high clinical probability, is an essential step in contemporary diagnostic strategies because it permits limiting the number of additional diagnostic tests, especially invasive tests. Clinical probability can be evaluated implicitly or by prediction rules. Two prediction rules for pulmonary embolism have been described: the Canadian prediction rule (the Wells score) and the Geneva prediction rule. Their original descriptions were published in 2000 and 2001, respectively. These prediction rules need to be externally validated, and, ideally, outcome studies should demonstrate that patients may be safely treated on the basis of the assessment of the clinical probability they provide. Therefore, the purpose of this review is to discuss the external validation of these rules, because this particular point has been only recently achieved. RECENT FINDINGS: Application of both rules in an external setting and in a prospective study have confirmed their validity. A recent study suggests that the best evaluation is probably based on a prediction rule associated with possible clinical override. SUMMARY: Studies comparing an empiric assessment with explicit assessment, such as the Wells simplified score or the Geneva score, have shown that the three tools show similar accuracy. External validation and use of both rules in prospective management studies have only recently been performed and have confirmed their validity. Some reports suggest that empiric assessment may be influenced by level of training. Objective prediction rules seems to be less influenced by experience and should be preferred by more junior doctors. The tool used for clinical probability assessment is probably less important than the principle of a careful clinical probability assessment in each patient with suspected pulmonary embolism.
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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 | 0.023 | 0.140 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".