Ventricular-arterial decoupling is associated with in-hospital adverse events in normotensive pulmonary embolism
Bibliographic record
Abstract
Abstract Purpose During acute pulmonary embolism (PE) a compensatory increase in right ventricular (RV) contractility is required to match increased afterload to maintain right ventricular-pulmonary arterial (RV-PA) coupling. The aim of this study was to assess the prognostic utility of RV-PA decoupling in acute PE. Methods We assessed the association between measures of transthoracic echocardiography (TTE)-derived RV-PA coupling including tricuspid annular plane systolic excursion (TAPSE)/pulmonary artery systolic pressure (PASP) and right ventricular fractional area change (FAC)/PASP as well as stroke volume index (SVI)/PASP (a measure of pulmonary artery capacitance) with adverse PE-related events (in-hospital PE-related mortality or cardiopulmonary decompensation) using logistic regression analysis. Results In 820 normotensive patients TTE-derived markers of RV-PA coupling were associated with PE-related adverse events. For each 0.1mm/mmHg decrease in TAPSE/PASP the odds of an adverse event increased by 2.5-fold (adjusted OR (aOR) 2.49, 95% confidence interval (CI) 1.46–4.24, p = 0.001), for every 0.1%/mmHg decrease in FAC/PASP the odds of an adverse event increased by 1.4-fold (aOR 1.42, CI 1.09–1.86, p = 0.010), and for every 0.1mL/mmHg•m2 decrease in SVI/PASP the odds of an event increased by 2.75-fold (aOR 2.78, CI 1.72–4.50, p < 0.001). In multivariate analysis, TAPSE/PASP and SVI/PASP were independent of other risk stratification methods including computed tomography-derived RVD, the Bova score, and subjective assessment of TTE-derived RVD. Conclusion In patients with normotensive acute PE, TTE-derived measures of RV-PA coupling are strongly associated with adverse in-hospital PE-related events and provide incremental value in the risk assessment beyond computed tomography-derived RVD, the Bova score, or subjective TTE-derived RVD.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".