Right ventricular function assessment by transesophageal echocardiography in lung transplantation: Preoperative, intraoperative, and postoperative considerations
Bibliographic record
Abstract
Background: Right ventricular (RV) function is a key determinant of outcomes in lung transplantation, particularly in patients with pre-existing pulmonary hypertension. The RV is uniquely sensitive to perioperative hemodynamic stressors, including ischemia-reperfusion injury, abrupt afterload changes, and allograft implantation. Purpose: This review aims to summarize the perioperative echocardiographic assessment of RV function in lung transplantation, emphasizing the role of transesophageal echocardiography (TEE) in evaluating RV performance and guiding intraoperative management. Methods: A comprehensive synthesis of recent literature was performed, focusing on echocardiographic parameters relevant to RV evaluation during the preoperative, intraoperative, and postoperative phases of lung transplantation. Both conventional and advanced imaging modalities were reviewed. Discussion: TEE provides real-time insights into RV adaptation and dysfunction. Key parameters include fractional area change, tricuspid annular plane systolic excursion (TAPSE), tricuspid annular velocity (S'), and speckle-tracking-derived strain. Three-dimensional echocardiography enhances volumetric and geometric assessment, while venous congestion indices such as the Venous Excess Ultrasound (VExUS) score offer indirect hemodynamic evaluation. Intraoperatively, dynamic monitoring supports optimization of preload, afterload, and inotrope therapy. Postoperative complications-such as RV outflow tract obstruction and pulmonary vascular anastomotic dysfunction-require prompt recognition. Persistent RV dysfunction despite afterload reduction may reflect intrinsic myocardial disease. Conclusion: Comprehensive echocardiographic evaluation throughout all perioperative phases is essential for optimizing RV performance and improving outcomes in lung transplantation. Future studies should aim to standardize RV assessment protocols and validate multimodal imaging approaches for perioperative clinical decision-making.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".