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Intraluminal thrombus effect on the progression of abdominal aortic aneurysms by using a multistate continuous-time Markov chain model

OBJECTIVE: To investigate the relationship between the characteristics of intraluminal thrombus (ILT) with abdominal aortic aneurysm (AAA) expansion. METHODS: This retrospective clinical study applied homogeneous multistate continuous-time Markov chain models to longitudinal computed tomography (CT)...

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Detalles Bibliográficos
Autores principales: Zhang, Liangliang, Zambrano, Byron A., Choi, Jongeun, Lee, Whal, Baek, Seungik, Lim, Chae Young
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7673060/
https://www.ncbi.nlm.nih.gov/pubmed/33176516
http://dx.doi.org/10.1177/0300060520968449
Descripción
Sumario:OBJECTIVE: To investigate the relationship between the characteristics of intraluminal thrombus (ILT) with abdominal aortic aneurysm (AAA) expansion. METHODS: This retrospective clinical study applied homogeneous multistate continuous-time Markov chain models to longitudinal computed tomography (CT) data from Korean patients with AAA. Four AAA states were considered (early, mild, severe, fatal) and the maximal thickness of the ILT (max(ILT)), the fraction of the wall area covered by the ILT (area(frac)) and the fraction of ILT volume (vol(frac)) were used as covariates. RESULTS: The analysis reviewed longitudinal CT images from 26 patients. Based on likelihood-ratio statistics, the area(frac) was the most significant biomarker and max(ILT) was the second most significant. In addition, within AAAs that developed an ILT layer, the analysis found that the AAA expands relatively quickly during the early stage but the rate of expansion reduces once the AAA has reached a larger size. CONCLUSION: The results recommend surgical intervention when a patient has an area(frac) more than 60%. Although this recommendation should be considered with caution given the limited sample size, physicians can use the proposed model as a tool to find such recommendations with their own data.