Assessment of Right Ventricle Function in Patients with Mitral Repair: Case Series
Bibliographic record
Abstract
OBJECTIVES: We aim to assess right ventricular function in patients undergoing mitral valve repair using trans-esophageal echocardiography, focusing on the predictive value of right ventricular longitudinal strain compared to other echocardiographic measures. DESIGN: Retrospective analysis. SETTING: Toronto General Hospital. PARTICIPANTS: Thirty elective patients undergoing mitral valve repair. INTERVENTIONS: Quantitative assessment of right ventricular function using transesophageal echocardiography images pre- and post-mitral valve repair, including right ventricular longitudinal strain, fractional area change, tricuspid annular plane systolic excursion, and systolic peak velocity (S'). MEASUREMENTS AND MAIN RESULTS: 3 patterns of RV strain were identified with right ventricular longitudinal strain emerging as the most significant discriminator among right ventricular functional subgroups, with 43% of cases showing worsening, 20% showing no change, and 37% showing improvement. No correlation was found between right ventricular performance parameters and the need for vasopressors post-cardiopulmonary bypass. There was also no association between initial right ventricular longitudinal strain and difficulty in weaning off bypass or increased demand for pressors. Changes in tricuspid annular plane systolic excursion across all cases warrant further investigation with a larger cohort. CONCLUSIONS: Right ventricular longitudinal strain is a valuable tool for assessing right ventricular function post-mitral valve repair, offering insights into immediate postoperative outcomes and long-term right ventricular remodeling. Despite limitations like single-surgeon experience and institution-specific choice of pressors, our study provides useful insights into right ventricular function post-mitral repair surgery, paving the way for future research in larger patient populations.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".