Intraoperative transesophageal echocardiography following mitral valve repair: a systematic review
Bibliographic record
Abstract
OBJECTIVE: We aimed to examine the recent evidence and search for novel assessments on intraoperative TEE following mitral valve repair that can impact short and long-term outcomes. METHODS: The Ovid MEDLINE, PubMed, and EMBASE databases were searched from January 1, 2008, until January 27, 2021, for studies on patients with severe Mitral Valve Regurgitation (MR) undergoing Mitral Valve (MV) repair surgery with intraoperative Transesophageal Echocardiography (TEE) performed after the repair. Additional searches were conducted using Google search engine, Web of Science, and Cochrane Library. RESULTS: After reviewing 302 records, 8 retrospective and 22 prospective studies were included (n = 30). Due to clinical and methodological diversity, these studies are noncomparable and data were not amenable to quantitative synthesis. CONCLUSION: Although technological advances allowed the objective assessment of geometric and dynamic alterations of the MV, the impact of the use of these technologies on short- or long-term outcomes was not studied. There is uncertainty and conflicting evidence on the ideal method and metrics to evaluate MV patency post-repair. Few isolated studies validated methods to assess coaptation surface and LV function post-repair.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.065 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 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".