Abstract: Outcomes of Mechanical vs. Biological Aortic Valve Replacement in Patients Aged Over 60

Background
Aortic valve replacement (AVR) is essential for treating severe aortic stenosis or regurgitation. In patients over 60, the choice between mechanical and biological valves is critical due to differences in durability, anticoagulation needs, and complications. Mechanical valves offer long-term durability but require lifelong anticoagulation, increasing bleeding and thromboembolic risks. Biological valves avoid these complications but are less durable. This study compares outcomes of mechanical and biological AVR in patients over 60.

Methods
This retrospective cohort study analyzed 144 patients aged over 60 who underwent AVR at Sheba Medical Center from 2001 to October 2024. Patients were stratified into two equal groups of 72, matched using propensity score analysis for age, gender, and ejection fraction. Outcomes compared included hospital mortality, survival at 1 and 3 years, and short- and long-term complications.

Results
The mean age of the cohort was 66 years. One-year survival rates were 94.4% in the mechanical group and 97.2% in the biological group (p = 0.086), while 3-year survival rates were 91.6% and 93%, respectively (p = 1.0). Rates of bleeding and thromboembolic events were slightly higher in the mechanical group and rate of reoperation was lower, but not statistically significant. No differences in valve dysfunction or endocarditis were observed.

Conclusions
Both mechanical and biological valves are viable options for AVR in patients over 60, with distinct benefits and risks:

Mechanical valves: Durable but require lifelong anticoagulation, increasing bleeding and thromboembolic risks.
Biological valves: Lower anticoagulation-related risks but higher degeneration and reoperation rates over time.
The choice of valve should be individualized, considering comorbidities, life expectancy, bleeding risk, and anticoagulation preferences. Larger studies with extended follow-up are needed to further define the optimal choice for this population.