Abstract 4346986: Comparable Efficacy of Intracardiac and Transesophageal Echocardiography in Left Atrial Appendage Closure: Findings from an Umbrella Review
Bibliographic record
Abstract
Background: As left atrial appendage closure (LAAC) becomes more widely adopted for stroke prevention in patients with atrial fibrillation, optimizing peri-procedural imaging has gained increasing clinical relevance. While transesophageal echocardiography (TEE) remains the standard imaging modality, intracardiac echocardiography (ICE) has emerged as a viable alternative. This umbrella review evaluated whether ICE provides comparable procedural outcomes to TEE and examined differences in safety and post-procedural complications based on the current evidence. Methods: To identify relevant studies for inclusion in this umbrella review, a comprehensive search was conducted across databases, including PubMed, Cochrane Library, and Google Scholar. The GRADE (Grading of Recommendations, Assessment, Development and Evaluations) method, a widely accepted tool for assessing the quality of evidence and strength of recommendations in systematic reviews, was utilized to assess the overall certainty of the evidence comprehensively. Furthermore, the quality of the included reviews underwent evaluation by applying the AMSTAR 2 and the New Castle Ottawa scale. Results: This review incorporates findings from seven systematic reviews and meta-analyses. In terms of procedural success, the analysis showed no significant difference between intracardiac echocardiography (ICE) and transesophageal echocardiography (TEE) (RR [95% CI]: 1.01 [1.00, 1.02], I2: 0%, p-value: 0.21). Regarding peri-procedural complications, the analysis indicated that ICE was associated with a significantly lower risk compared to TEE (RR [95% CI]: 0.79 [0.67, 0.94], I2: 0%, p-value: 0.008). Regarding the residual interatrial septal defects (IASDs), the analysis revealed that ICE was linked to a significantly higher risk of residual IASDs compared to TEE (RR [95% CI]: 1.97 [1.45, 2.68], I2: 0%, p-value: <0.0001). Conclusion: In conclusion, ICE is a potentially beneficial substitute for TEE in the context of LAAC, as it decreases overall complications. However, whereas literature provides evidence for the advantages of ICE, comparative studies demonstrate that ICE and TEE have equal efficacy and safety profiles. This highlights the need for additional future evidence-based trials to evaluate each strategy comparative advantages in LAAC procedures thoroughly.
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 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 | 0.021 | 0.087 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.014 |
| Bibliometrics | 0.015 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".