Conversion to sinus rhythm does not improve long-term survival after valve surgery: insights from a 20-year follow-up study☆
Bibliographic record
Abstract
OBJECTIVE: Atrial fibrillation (AF) is frequently associated with valvular heart disease and a common complication of valve surgery. Its contribution to long-term mortality and morbidity remains debated. Our objective was to determine the impact of AF on long-term mortality and embolic complications after valvular surgery and the benefit of conversion to sinus rhythm. This may provide insight to the clinical advantages of surgical anti-AF procedures. METHODS: Data concerning rhythm status, mortality and embolic complications were prospectively collected for 5466 patients with valve surgery. Patients had surgery between 1979 and 2003. Follow-up was complete and all patients had a yearly EKG. RESULTS: Patients with preoperative AF had poorer long-term survival than patients without preoperative AF (20-year survival 23.7 and 33.4%, respectively, P<0.0001). However, preoperative AF was not an independent risk factor of long-term mortality (HR=1.04, P=0.6). In patients with preoperative sinus rhythm, postoperative development of AF had an impact on long-term mortality (HR=1.46, P=0.0012). In patients with preoperative AF, postoperative rhythm did not influence mortality when adjusted for other variables (AF vs. sinus rhythm, HR=1.07, P=0.5709). Mitral valve surgery (HR=1.55, P=0.0270) but not preoperative or postoperative AF had a significant impact on the advent of embolic complications. CONCLUSIONS: The conversion to sinus rhythm did not improve long-term survival or reduce the incidence of embolic complications after valve surgery. Patients with preoperative AF had poorer survival than patients without preoperative AF. AF may be a marker of advanced disease in these patients.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".