Evidence for Left Atrial Volume Being an Indicator of Adverse Events in Patients With Acute Pulmonary Embolism
Bibliographic record
Abstract
PURPOSE: To assess the association between computed tomography pulmonary angiography (CTPA) atrial measurements and both 30-day pulmonary embolism (PE)-related adverse events and mortality, and non-PE-related mortality, and to identify the best predictors of these outcomes by comparing atrial measurements and widely used clinical and imaging variables. PATIENTS AND METHODS: Retrospective single-center pilot study. Acute PE patients diagnosed on CTPA who also had a transthoracic echocardiogram, electrocardiogram, and troponin T were included. CTPA left atrial (LA) and right atrial (RA) volume and short-axis diameter were measured and compared between outcome groups, along with right ventricular/left ventricular diameter ratio, interventricular septal bowing, tricuspid annular plane systolic excursion, electrocardiogram, and troponin T. RESULTS: A total of 350 patients. LA volume and diameter were associated with PE-related adverse events (P≤0.01). LA volume was the only atrial measurement associated with PE-related mortality (P=0.03), with no atrial measurements associated with non-PE-related mortality. Troponin was most associated with PE-related adverse events and mortality (both area under the curve [AUC]=0.77). On multivariate analysis, combination models did not greatly improve PE-related adverse events prediction compared with troponin alone. For PE-related mortality, the best models were the combination of troponin, age, and either LA volume (AUC=0.86) or diameter (AUC=0.87). CONCLUSION: Among patients with acute PE, CTPA LA volume is the only imaging parameter associated with PE-related mortality and is the best imaging predictor of this outcome. Reduced CTPA LA volume and diameter, along with increased RA/LA volume and diameter ratios, are significantly associated with 30-day PE-related adverse events, but not with non-PE-related mortality.
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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 | 0.002 | 0.015 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".