DOI 10.1016/j.jtcvs.2016.07.076
Decision analysis to define the optimal management of athletes with anomalous aortic origin of a coronary artery.
Аннотация
OBJECTIVES
The goal of this study was to use decision analysis to evaluate the impact of varying uncertainties on the outcomes of patients with anomalous aortic origin of a coronary artery.
METHODS
Two separate decision analysis models were created: one for anomalous left coronary artery (ALCA) and one for anomalous right coronary artery (ARCA). Three strategies were compared: observation, exercise restriction, and surgery. Probabilities and health utilities were estimated on the basis of existing literature. Deterministic and probabilistic sensitivity analyses were performed.
RESULTS
Surgery was the optimal management strategy for patients <30 years of age with ALCA. As age increased, observation became an equivalent strategy and eventually surpassed surgery as the treatment of choice. The advantage on life expectancy for surgery over observation ranged from 2.6 ± 1.7 years for a 10-year-old patient to -0.03 ± 0.1 for a 65-year old patient. In patients with ARCA, observation was the optimal strategy for most patients with a life expectancy advantage over surgery of 0.1 ± 0.1 years to 0.2 ± 0.4 years, depending on age. Surgery was the preferred strategy only for patients <25 years of age when the perceived risk of sudden cardiac death was high and the perioperative mortality was low. Exercise restriction was a suboptimal strategy for both ALCA and ARCA in all scenarios.
CONCLUSIONS
The optimal management in anomalous aortic origin of a coronary artery depends on multiple factors, including individual patient characteristics. Decision analysis provides a tool to understand how these characteristics affect the outcomes with each management strategy and thus may aid in the decision making process for a particular patient.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
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