Introduction: Per- and polyfluoroalkyl substances (PFAS) have infiltrated countless everyday products, raising concerns about potential effects on human health, specifically on the cardiovascular system and the development of abdominal aortic calcification (AAC). However, our understanding of this relationship is still limited.
Objectives: This study aims to investigate the effects of PFAS on AAC using machine learning algorithms.
Methods: Leveraging the power of machine learning technique, extreme gradient boosting (XGBoost), we assessed the relationship between PFAS exposure and AAC risk. We focused on three PFAS compounds, perfluorodecanoic acid (PFDeA), perfluorohexane sulfonic acid (PFHxS), and perfluorononanoic acid (PFNA) through multiple logistic regression, restricted cubic spline (RCS), and quantile g-computation (QGC) models. To get more insight into the underlying mechanisms, mediation analyses are used to investigate the potential mediating role of fatty acids and blood cell fractions in AAC.
Results: Our findings indicate that elevated serum levels of PFHxS and PFDeA are associated with the increased risk of AAC. The QGC analyses underscore the overall positive association between the PFAS mixture and AAC risk, with PFHxS carrying the greatest weight, followed by PFDeA. The RCS analyses reveal a dose-dependent increase between serum PFHxS concentration and AAC risk in an inverted V-shape way. Moreover, age and PFHxS exposure are identified as the primary factors contributing to abdominal aortic calcification risk in SHapley Additive exPlanation (SHAP) summary plot combined with XGBoost technique. Although PFAS significantly change the profile of fatty acids, we do not find any mediating roles of them in AAC. Despite strong associations between PFAS exposure and hematological indicators, our analysis does not find evidence that these indicators mediate the development of AAC.
Conclusions: In summary, our study highlights the detrimental impact of PFAS on abdominal aortic health and emphasizes the need for further research to understand the underlying mechanisms involved.
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http://dx.doi.org/10.1016/j.jare.2024.04.022 | DOI Listing |
Abdom Radiol (NY)
January 2025
Kerman University of Medical Sciences, Kerman, Islamic Republic of Iran.
Background And Aim: Prior investigations of the natural history of abdominal aortic aneurysms (AAAs) have been constrained by small sample sizes or uneven assessments of aggregated data. Natural language processing (NLP) can significantly enhance the investigation and treatment of patients with AAAs by swiftly and effectively collecting imaging data from health records. This meta-analysis aimed to evaluate the efficacy of NLP techniques in reliably identifying the existence or absence of AAAs and measuring the maximal abdominal aortic diameter in extensive datasets of radiology study reports.
View Article and Find Full Text PDFEur Heart J Cardiovasc Imaging
January 2025
PULS/e group, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
Aims: Image-based, patient-specific rupture risk analysis of AAAs is promising but it is limited by invasive and costly imaging modalities. Ultrasound (US) offers a safe, more affordable alternative, allowing multiple assessments during follow-up and enabling longitudinal studies on AAA rupture risk.
Methods And Results: This study used time-resolved three-dimensional US to assess AAA rupture risk parameters over time, based on vessel and intraluminal thrombus (ILT) geometry.
J Endovasc Ther
January 2025
Department of Vascular Surgery, Rijnstate, Arnhem, The Netherlands.
Purpose: The goal of the study described in this protocol is to build a multimodal artificial intelligence (AI) model to predict abdominal aortic aneurysm (AAA) shrinkage 1 year after endovascular aneurysm repair (EVAR).
Methods: In this retrospective observational multicenter study, approximately 1000 patients will be enrolled from hospital records of 5 experienced vascular centers. Patients will be included if they underwent elective EVAR for infrarenal AAA with initial assisted technical success and had imaging available of the same modality preoperatively and at 1-year follow-up (CTA-CTA or US-US).
Cureus
December 2024
Department of Cardiovascular Surgery, Shizuoka General Hospital, Shizuoka, JPN.
Thoracoabdominal aortic aneurysm (TAAA) repair remains one of the most challenging procedures and is associated with high mortality and complication rates. Careful consideration of the surgical strategy is essential, particularly in cases involving extensive replacement and high-risk patients. A 61-year-old man with a 55-mm TAAA was referred for surgical treatment.
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