Spiral computed tomographic pulmonary angiography for investigating suspected pulmonary embolism: clinical outcomes.
Bibliographic record
Abstract
PURPOSE: To assess the clinical outcomes of patients who were suspected of having acute pulmonary embolism and underwent spiral computed tomographic pulmonary angiography (CTPA) for diagnosis. METHODS: We evaluated the clinical outcomes of 62 patients with suspected pulmonary embolism; 82 CTPA scans were performed in a 15-month period. Clinical outcomes were recorded for all patients for a minimum of 3 months. RESULTS: Acute pulmonary embolism was diagnosed and treated in 11 (18%) of the 62 patients evaluated via CTPA. Scans of the other 51 (82%) patients were negative for pulmonary embolism. Seven (14%) of these patients died during the 3-month follow-up period; pulmonary embolism was considered to be a contributing factor in 1 of these deaths. Seven (14%) of the 51 patients were lost to follow-up, and 37 (74%) showed no evidence of disease at least 3 months after a negative CTPA study. Despite the presence or absence of an acute pulmonary embolism, an alternate or additional diagnosis was made on 32 (52%) CTPA scans. CONCLUSION: Spiral CTPA can be effectively used to rule out clinically significant pulmonary emboli and also serves to provide alternate diagnoses in patients who do not have a 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".