Systematic review and meta-analysis of left atrial appendage closure's influence on early and long-term mortality and stroke
Bibliographic record
Abstract
Objective Left atrial appendage closure (LAAC) concomitant to heart surgery in patients with underlying atrial fibrillation (AF) has gained attention because of long-term reduction of thromboembolic complications. As of mortality benefits in the setting of non-AF, data from both observational studies and randomized controlled trials are conflicting. Methods On-line databases were screened for studies comparing LAAC versus no LAAC concomitant to other heart surgery. End points assessed were all-cause mortality and stroke at early and longest-available follow-up. Subgroup analyses stratified on preoperative AF were performed. Risk ratios (RR) with 95% CIs served as primary statistics. Results Electronic search yielded 25 studies (N = 660 [158 patients]). There was no difference between LAAC and no LAAC in terms of early mortality. In the overall population analysis, LAAC reduced long-term mortality (RR, 0.86; 95% CI, 0.74-1.00; P = .05; I 2 = 88%), reduced early stroke risk by 19% (RR, 0.81; 95% CI, 0.72-0.93; P = .002; I 2 = 57%), and reduced late stroke risk by 13% (RR, 0.87; 95% CI, 0.84-0.90; P < .001; I 2 = 58%). Subgroup analysis showed lower mortality (RR, 0.85; 95% CI, 0.72-1.01; P = .06; I 2 = 91%), short-, and long-term stroke risk reduction only in patients with preoperative AF (RR, 0.81; 95% CI, 0.71-0.93; P = .003; I 2 = 71% and RR, 0.87; 95% CI, 0.84-0.91; P < .001; I 2 = 70%, respectively). No benefit of LAAC in patients without AF was found. Conclusions Concomitant LAAC was associated with reduced stroke rates at early and long-term and possibly reduced all-cause mortality at the long-term follow-up but the benefits were limited to patients with preoperative AF. There is not enough evidence to support routine concomitant LAAC in non-AF settings.
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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 | 0.013 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.031 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".