The role of clinical frailty in predicting mortality following surgery for infective endocarditis
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Published on: July 24, 2013
Özer Kandemir1, Murat Koç1, Kaan Kaya1
1Department of Cardiovascular Surgery, University of Health Sciences Türkiye, Ankara Etlik City Hospital, Ankara, Türkiye.
Background:
Infective endocarditis continues to pose a significant challenge in cardiovascular surgery, with high morbidity and mortality rates despite advancements in diagnosis and treatment. This study aimed to identify predictors of in-hospital mortality among patients undergoing surgical intervention for active infective endocarditis, with a particular focus on frailty.
Methods:
A retrospective analysis was conducted on fifty-five consecutive patients who underwent surgery for active infective endocarditis between October 2022 and April 2025. Clinical variables, operative data, and outcomes were also collected. Frailty was assessed using the clinical frailty scale. Univariate and multivariate logistic regression analyses were performed.
Results:
The in-hospital mortality rate was 25.5%. Patients who did not survive were significantly older (median age 65.7 vs. 56.2 years) and had higher clinical frailty scale scores (mean 7.1 vs. 5.4) than those who survived. Frailty emerged as the sole independent predictor of mortality (odds ratio =3.41; 95% confidence interval: 1.20-9.65; p=0.021).
Conclusion:
Frailty is a key predictor of early mortality in patients with surgical infective endocarditis. Preoperative frailty assessment and targeted interventions may enhance outcomes in this high-risk population.
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Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

