Year: 2024
Type: article
Study design: Observational Study
Abstract: Background: Precise preoperative risk assessment is essential in cardiac surgery to enhance patient outcomes. Myocardial perfusion imaging (MPI) plays a critical role in assessing myocardial ischemia and guiding surgical decisions, but its specific impact on surgical outcomes requires further investigation. Methods: This retrospective study included 780 patients who underwent cardiac surgery at the Interventional Centers in Xining, Qinghai, China, between March 2020 and September 2023. MPI findings were analyzed to assess their association with intraoperative and postoperative complications. Positron emission tomography (PET) imaging was evaluated for its sensitivity and specificity in detecting ischemia. Results: The cohort had a mean age of 65 years, with 66.5% being male, and a high prevalence of hypertension (69.6%) and diabetes mellitus (41.3%). The MPI results indicated that 33.2% of patients had normal perfusion, while 22.3, 16.8 and 14.9% of patients had mild, moderate and severe ischemia, respectively. Patients with severe ischemia experienced significantly higher rates of intraoperative complications (16.4%), postoperative myocardial infarction (10.3%), arrhythmias (14.7%) and mortality (5.2%) compared to patients with normal perfusion (1.9, 0.8, 3.1 and 0.4%, respectively). PET imaging demonstrated superior diagnostic performance, with the highest specificity (88.3%) and sensitivity (92.6%) for detecting ischemia and guiding surgical decisions. Conclusions: The severity of ischemia, as assessed by MPI, is a significant predictor of clinical outcomes in cardiac surgery. These findings underscored the importance of using MPI not only for preoperative risk stratification but also for guiding personalized treatment based on ischemia severity. PET imaging's diagnostic accuracy further highlights its role as a preferred modality in this context.
Source: The Heart Surgery Forum
DOI: 10.59958/hsf.7991
Authors: Wenxing Zhao, Jiandong Cao
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4405823424