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Growth prediction m...
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Ristl, RobinCentre for Medical Statistics, Informatics, Intelligent Systems, Medical University of Vienna, Vienna, Austria,Med Univ Vienna, Ctr Med Stat Informat & Intelligent Syst, Vienna, Austria.
(författare)
Growth prediction model for abdominal aortic aneurysms
- Artikel/kapitelEngelska2022
Förlag, utgivningsår, omfång ...
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2021-11-28
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Oxford University Press,2022
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electronicrdacarrier
Nummerbeteckningar
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LIBRIS-ID:oai:DiVA.org:umu-192374
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https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-192374URI
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https://doi.org/10.1093/bjs/znab407DOI
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https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-471011URI
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Språk:engelska
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Sammanfattning på:engelska
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Ämneskategori:ref swepub-contenttype
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Ämneskategori:art swepub-publicationtype
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BACKGROUND: The most relevant determinant in scheduling monitoring intervals for abdominal aortic aneurysms (AAAs) is maximum diameter. The aim of the study was to develop a statistical model that takes into account specific characteristics of AAA growth distributions such as between-patient variability as well as within-patient variability across time, and allows probabilistic statements to be made regarding expected AAA growth.METHODS: CT angiography (CTA) data from patients monitored at 6-month intervals with maximum AAA diameters at baseline between 30 and 66 mm were used to develop the model. By extending the model of geometric Brownian motion with a log-normal random effect, a stochastic growth model was developed. An additional set of ultrasound-based growth data was used for external validation.RESULTS: The study data included 363 CTAs from 87 patients, and the external validation set comprised 390 patients. Internal and external cross-validation showed that the stochastic growth model allowed accurate description of the distribution of aneurysm growth. Median relative growth within 1 year was 4.1 (5-95 per cent quantile 0.5-13.3) per cent. Model calculations further resulted in relative 1-year growth of 7.0 (1.0-16.4) per cent for patients with previously observed rapid 1-year growth of 10 per cent, and 2.6 (0.3-8.3) per cent for those with previously observed slow growth of 1 per cent. The probability of exceeding a threshold of 55 mm was calculated to be 1.78 per cent at most when adhering to the current RESCAN guidelines for rescreening intervals. An online calculator based on the fitted model was made available.CONCLUSION: The stochastic growth model was found to provide a reliable tool for predicting AAA growth.
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Klopf, JohannesDepartment of General Surgery, Division of Vascular Surgery, Medical University of Vienna, Vienna, Austria,Med Univ Vienna, Dept Gen Surg, Div Vasc Surg, Waehringer Guertel 18-20, A-1090 Vienna, Austria.
(författare)
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Scheuba, AndreasDepartment of General Surgery, Division of Vascular Surgery, Medical University of Vienna, Vienna, Austria,Med Univ Vienna, Dept Gen Surg, Div Vasc Surg, Waehringer Guertel 18-20, A-1090 Vienna, Austria.
(författare)
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Wolf, FlorianDepartment of Biomedical Imaging and Image Guided Therapy, Division of Cardiovascular and Interventional Radiology, Medical University of Vienna, Vienna, Austria,Med Univ Vienna, Div Cardiovasc & Intervent Radiol, Dept Biomed Imaging & Image Guided Therapy, Vienna, Austria.
(författare)
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Funovics, MartinDepartment of Biomedical Imaging and Image Guided Therapy, Division of Cardiovascular and Interventional Radiology, Medical University of Vienna, Vienna, Austria,Med Univ Vienna, Div Cardiovasc & Intervent Radiol, Dept Biomed Imaging & Image Guided Therapy, Vienna, Austria.
(författare)
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Gollackner, BerndDepartment of General Surgery, Division of Vascular Surgery, Medical University of Vienna, Vienna, Austria,Med Univ Vienna, Dept Gen Surg, Div Vasc Surg, Waehringer Guertel 18-20, A-1090 Vienna, Austria.
(författare)
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Wanhainen, AndersUppsala universitet,Umeå universitet,Kirurgi,Department of Surgical Sciences, Uppsala University, Uppsala, Sweden,Kärlkirurgi,Umeå Univ, Dept Surg & Perioperat Sci, Umeå, Sweden.(Swepub:uu)anwan103
(författare)
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Neumayer, ChristophDepartment of General Surgery, Division of Vascular Surgery, Medical University of Vienna, Vienna, Austria,Med Univ Vienna, Dept Gen Surg, Div Vasc Surg, Waehringer Guertel 18-20, A-1090 Vienna, Austria.
(författare)
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Posch, MartinCentre for Medical Statistics, Informatics, Intelligent Systems, Medical University of Vienna, Vienna, Austria,Med Univ Vienna, Ctr Med Stat Informat & Intelligent Syst, Vienna, Austria.
(författare)
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Brostjan, ChristineDepartment of General Surgery, Division of Vascular Surgery, Medical University of Vienna, Vienna, Austria,Med Univ Vienna, Dept Gen Surg, Div Vasc Surg, Waehringer Guertel 18-20, A-1090 Vienna, Austria.
(författare)
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Eilenberg, WolfDepartment of General Surgery, Division of Vascular Surgery, Medical University of Vienna, Vienna, Austria,Med Univ Vienna, Dept Gen Surg, Div Vasc Surg, Waehringer Guertel 18-20, A-1090 Vienna, Austria.
(författare)
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Centre for Medical Statistics, Informatics, Intelligent Systems, Medical University of Vienna, Vienna, AustriaMed Univ Vienna, Ctr Med Stat Informat & Intelligent Syst, Vienna, Austria.
(creator_code:org_t)
Sammanhörande titlar
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Ingår i:British Journal of Surgery: Oxford University Press109:2, s. 211-2190007-13231365-2168
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Ristl, Robin
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Klopf, Johannes
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Scheuba, Andreas
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Wolf, Florian
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Funovics, Martin
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Gollackner, Bern ...
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Wanhainen, Ander ...
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Neumayer, Christ ...
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Posch, Martin
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Brostjan, Christ ...
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Eilenberg, Wolf
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