Subsegmental Pulmonary Embolism Diagnosed by Computed Tomography: Incidence and Clinical Implications. A Systematic Review and Meta-Analysis of the Management Outcome Studies.
Bibliographic record
Abstract
Abstract Abstract 4002 Poster Board III-938 Background Multiple-detectors CTPA appears to have a higher sensitivity for PE as compared to single-detector CTPA. In particular, multiple-detectors CTPA allows better visualization of segmental and subsegmental pulmonary arteries, hence the proportion of patients with suspected PE in whom isolated subsegmental thrombus are reported might be higher using multiple-detectors CTPA. The clinical significance of subsegmental PE is unknown. In the PIOPED study, PE limited to subsegmental pulmonary arteries were most prevalent among patients with low-probability ventilation/perfusion (V/Q) scans. Patients with non diagnostic (low or intermediate probability) V/Q scans can be safely managed without anticoagulation. Nonetheless, patients with isolated subsegmental PE detected on CTPA are more commonly receiving anticoagulation than not. Purpose To determine whether multiple-detectors CTPA increases the proportion of PE diagnosis limited to subsegmental arteries and to assess the safety of diagnostic strategies based on CTPA. Data Source: A systematic literature search strategy was conducted using MEDLINE, EMBASE, the Cochrane Register of Controlled Trials and all EBM Reviews. Study Selection Twenty four articles met all the inclusions criteria (21 prospective cohort studies; 3 randomized controlled trials). Data extraction Two reviewers independently extracted data onto standardized forms. Data Synthesis A total of 2674 patients with suspected PE were included in the analyses. Of these, 1140 and 1534 patients underwent a single and multiple-detectors CTPA respectively. Conclusion The use of multiple-detectors CTPA in diagnostic strategies for PE appears to increase the proportion of patients diagnosed with subsegmental PE with comparable outcomes in patients with negative tests. This suggests that patients with subsegmental PE appear to not require anticoagulation. Disclosures: Rodger: Biomerieux: Research Funding; Boehringer Ingelheim: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Pfizer: Research Funding; Leo Pharma: Research Funding; Bayer: Research Funding; GTC Therapeutics: Research Funding.
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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 | 0.015 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.026 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".