ArticleJournal of cardiothoracic surgery2026
Neurological dysfunction after transcatheter aortic valve replacement risk factor analysis and prediction.
Article in Journal of cardiothoracic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveTo explore the risk factors associated with neurological dysfunction (ND) after transcatheter aortic valve replacement (TAVR) and to construct a risk prediction model to assess the occurrence of neurological dysfunction.
methodsClinical data of patients with aortic stenosis (AS) or aortic regurgitation (AR) who underwent TAVR between June 2022 and June 2024 at the First Affiliated Hospital of Nanchang University were collected and retrospectively analyzed. The patients were divided into ND and non-ND groups based on whether they developed ND after surgery, and the baseline characteristics and procedural indices of the two groups were compared. The data were statistically analyzed using SPSS software. Independent risk factors for ND after TAVR were identified by univariate and multivariable logistic regression analyses. Furthermore, receiver operating characteristic (ROC) curve analysis was applied selectively to continuous independent variables to determine their optimal clinical cutoff values.
resultsA total of 127 patients were included in the study, of which 79 were in the non-ND group and 48 were in the ND group, and the incidence of post-TAVR ND reached 37.8%. Multifactorial regression analysis showed that preoperative D-dimer level exceeding 0.64 mg/L, atrial fibrillation, calcification of the aortic arch, intraoperative contrast time longer than 25.5 min, and postoperative hypotension were independent risk factors for ND after TAVR.
conclusionsPreoperative D-dimer level higher than 0.64 mg/L, atrial fibrillation, aortic arch calcification, intraoperative contrast time greater than 25.5 min, and postoperative hypotension were independent risk factors for ND after TAVR. The prediction model based on these risk factors has good predictive effect and can help to identify high-risk patients at an early stage.
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