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Growth prediction model for abdominal aortic aneurysms

Ristl, Robin (författare)
Centre for Medical Statistics, Informatics, Intelligent Systems, Medical University of Vienna, Vienna, Austria,Med Univ Vienna, Ctr Med Stat Informat & Intelligent Syst, Vienna, Austria.
Klopf, Johannes (författare)
Department 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.
Scheuba, Andreas (författare)
Department 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.
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Wolf, Florian (författare)
Department 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.
Funovics, Martin (författare)
Department 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.
Gollackner, Bernd (författare)
Department 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.
Wanhainen, Anders (författare)
Uppsala universitet,Umeå universitet,Kirurgi,Department of Surgical Sciences, Uppsala University, Uppsala, Sweden,Kärlkirurgi,Umeå Univ, Dept Surg & Perioperat Sci, Umeå, Sweden.
Neumayer, Christoph (författare)
Department 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.
Posch, Martin (författare)
Centre for Medical Statistics, Informatics, Intelligent Systems, Medical University of Vienna, Vienna, Austria,Med Univ Vienna, Ctr Med Stat Informat & Intelligent Syst, Vienna, Austria.
Brostjan, Christine (författare)
Department 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.
Eilenberg, Wolf (författare)
Department 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.
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Centre for Medical Statistics, Informatics, Intelligent Systems, Medical University of Vienna, Vienna, Austria Med Univ Vienna, Ctr Med Stat Informat & Intelligent Syst, Vienna, Austria (creator_code:org_t)
2021-11-28
2022
Engelska.
Ingår i: British Journal of Surgery. - : Oxford University Press. - 0007-1323 .- 1365-2168. ; 109:2, s. 211-219
Relaterad länk:
https://doi.org/10.1...
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https://urn.kb.se/re...
https://doi.org/10.1...
https://urn.kb.se/re...
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  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • 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.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Kirurgi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Surgery (hsv//eng)

Nyckelord

Surgery
kirurgi

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