Methodology for Estimation of Annual Risk of Rupture for Abdominal Aortic Aneurysm

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00159816%3A_____%2F21%3A00074712" target="_blank" >RIV/00159816:_____/21:00074712 - isvavai.cz</a>

Alternative codes found

RIV/61989100:27230/21:10247446 RIV/61989100:27240/21:10247446 RIV/00216224:14110/21:00121777

Result on the web

<a href="https://www.sciencedirect.com/science/article/abs/pii/S0169260720317491?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/abs/pii/S0169260720317491?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.cmpb.2020.105916" target="_blank" >10.1016/j.cmpb.2020.105916</a>

Result language

angličtina

Original language name

Methodology for Estimation of Annual Risk of Rupture for Abdominal Aortic Aneurysm

Original language description

Background and Objective: Estimating patient specific annual risk of rupture of abdominal aortic aneurysm (AAA) is currently based only on population. More accurate knowledge based on patient specific data would allow surgical treatment of only those AAAs with significant risk of rupture. This would be beneficial for both patients and health care system. Methods: A methodology for estimating annual risk of rupture (EARR) of abdominal aortic aneurysms (AAA) that utilizes Bayesian statistics, mechanics and patient-specific blood pressure monitoring data is proposed. EARR estimation takes into consideration, peak wall stress in AAA computed by patient-specific finite element modeling, the probability distributions of wall thickness, wall strength, systolic blood pressure and the period of time that the patient is known to have already survived with the intact AAA. Initial testing of proposed approach was performed on fifteen patients with intact AAA (mean maximal diameter 51mm +/- 8mm). They were equipped with a pressure holter and their blood pressure was recorded over 24 hours. Then, we calculated EARR values for four possible scenarios - without considering any days of survival prior identification of AAA at computed tomography scans (EARR_0), considering past survival of 30 (EARR_30), 90 (EARR_90) and 180 days (EARR_180). Finally, effect of patient-specific blood pressure variability was analyzed. Results: Consideration of past survival does indeed significantly improve predictions of future risk: EARR_30 (1.04% +/- 0.87%), EARR_90 (0.67% +/- 0.56%) and EARR_180 (0.47% +/- 0.39%) which are unrealistically high otherwise (EARR_0 5.02% +/- 5.24%). Finally, EARR values were observed to vary by an order as a consequence of blood pressure variability and by factor of two as a consequence of neglected growth. Conclusions: Methodology for computing annual risk of rupture of AAA was developed for the first time. Sensitivity analyses showed respecting patient specific blood pressure is important factor and should be included in the AAA rupture risk assessment. Obtained EARR values were generally low and in good agreement with confirmed survival time of investigated patients so proposed method should be further clinically validated. (c) 2020 Elsevier B.V. All rights reserved.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

30300 - Health sciences

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Computer Methods and Programs in Biomedicine

ISSN

0169-2607

e-ISSN

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Volume of the periodical

200

Issue of the periodical within the volume

MAR 2021

Country of publishing house

US - UNITED STATES

Number of pages

11

Pages from-to

105916

UT code for WoS article

000623113400011

EID of the result in the Scopus database

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