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Background: Thoracic endovascular aortic repair (TEVAR) has expanded access to descending thoracic aortic aneurysm (DTAA) repair particularly for elderly and frail patients. This high-risk population has limited long-term overall survival, such that appropriate patient selection is required to optimize patient benefit and resource utilization. Our objective is to develop and validate a frailty-based, procedure-specific risk score for patients undergoing elective TEVAR for DTAA.
Methods: Patients undergoing nonemergent TEVAR for DTAA during 2005-2016 were identified in the National Surgical Quality Improvement Program database. Those with concurrent cardiac or open aortic surgery, abdominal visceral intervention, or Zone 0 deployment were excluded. Patients were randomly divided between derivation and validation samples. The primary outcome was 30-day major adverse events (MAE), including mortality and major systemic complications. Using the derivation cohort, variables associated with MAE were identified by univariable analyses. Those with P < 0.05 were included in multivariable logistic regression analysis. Independent procedure-specific and frailty-related risk factors for MAE were used to develop a pragmatic score to assess risk for TEVAR.
Results: Overall, 1,784 patients were included. 14% of the derivation patients had MAE (14% major complications, 4% mortality). Independent risk factors for MAE were primarily associated with markers of frailty and TEVAR extent and complexity and included functional dependence (OR 2.9, 95% CI 1.6-5.4), pulmonary disease (1.6, 1.1-2.4), thoracoabdominal extent (2.2 (1.4-3.4), need for iliac access (2.1, 1.1-3.8), and Zone I or II deployment (OR 1.7, 1.1-2.5). According to their respective beta coefficients, each variable was assigned a single point. Based on total points, patients were stratified as low- (0 points), intermediate- (1 point), or high-risk (≥2 points), with stepwise increases in mortality (0%, 4%, and 9%) and major complications (7%, 11%, and 23%) between strata. Validation patients had similar characteristics, risk strata distribution, and outcomes as the derivation patients, and the risk model had similar performance in both groups.
Conclusions: Markers of frailty and procedure complexity strongly predict MAE after TEVAR for DTAA and can improve patient selection by enabling patient and procedure-specific risk stratification. While TEVAR is safe in low-risk patients, intermediate-risk patients warrant careful discussion of the risks and benefits of aortic intervention; under certain circumstances, high-risk patients may not benefit. Further study is required to define the association between frailty and long-term outcomes.
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http://dx.doi.org/10.1016/j.avsg.2019.10.090 | DOI Listing |
Arterioscler Thromb Vasc Biol
September 2025
Institute of Cardiovascular Diseases and Department of Cardiology, Ultrasound in Cardiac Electrophysiology and Biomechanics Key Laboratory of Sichuan Province, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu (K.L., H.M., W.J
Background: The estimated glucose disposal rate (eGDR) is a validated surrogate marker of insulin resistance. However, its association with stroke and dementia in nondiabetic populations remains insufficiently investigated.
Methods: This prospective cohort study included nondiabetic participants from the UK Biobank.
Stroke
September 2025
Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York. (F.C.P., M.R., M.S., A.K., S.G., S.A., S.P., J.C., D.J.R.).
Background: Major ABO-incompatible platelet transfusions are associated with poor intracerebral hemorrhage (ICH) outcomes, yet drivers for this relationship remain unclear. Brain magnetic resonance imaging (MRI) ischemic lesions after ICH are neuroimaging biomarkers of secondary brain injury and are associated with poor outcomes. Given that ABO-incompatible platelet transfusions can induce immune complex formation, thrombo-inflammation, and endothelial barrier disruption, factors that could exacerbate cerebral ischemia, we explored whether major ABO-incompatible platelet transfusions are risk factors for ischemic lesions on brain MRI after ICH.
View Article and Find Full Text PDFEmerg Med Australas
October 2025
Australian Centre for Health Services Innovation, School of Public Health & Social Work, Queensland University of Technology, Brisbane, Queensland, Australia.
Reliably defining the risk of adverse in-flight events in aeromedical trauma patients could enable more informed pre-departure treatment and guide central asset allocation to achieve better system-level outcomes. Unfortunately, the current literature base specifically examining the in-flight period is sparse. Flight duration is often considered a proxy for the risk of in-flight deterioration; however, there is limited data to support this commonly held assumption.
View Article and Find Full Text PDFCirc Genom Precis Med
September 2025
Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China (J.Z., S.R., L.C., M.C., F.T., B.A., Y.Y., H.L.).
Background: Previous studies have suggested that the associations between ambient air pollution and atherosclerotic cardiovascular diseases (ASCVD) differ by genotype. A genome-wide approach provides a more comprehensive understanding of this relationship on a genomic scale.
Methods: Using data from ≈300 000 UK Biobank participants, we conducted a genome-wide interaction analysis on 10 745 802 variants.
Circ Genom Precis Med
September 2025
Division of Cardiology, Emory University School of Medicine, Atlanta, GA. (A.K.Y., A.C.R., L.S.S., A.A.Q., Y.V.S.).
Background: Cardio-kidney-metabolic (CKM) disease represents a significant public health challenge. While proteomics-based risk scores (ProtRS) enhance cardiovascular risk prediction, their utility in improving risk prediction for a composite CKM outcome beyond traditional risk factors remains unknown.
Methods: We analyzed 23 815 UK Biobank participants without baseline CKM disease, defined by -Tenth Revision codes as cardiovascular disease (coronary artery disease, heart failure, stroke, peripheral arterial disease, atrial fibrillation/flutter), kidney disease (chronic kidney disease or end-stage renal disease), or metabolic disease (type 2 diabetes or obesity).