1. ZHAW digitalcollection
  2. Life Sciences und Facility Management
  3. Publikationen
  4. Publikationen Life Sciences und Facility Management
Full metadata record
DC FieldValueLanguage
dc.contributor.authorDelucchi, Matteo-
dc.contributor.authorSpinner, Georg R.-
dc.contributor.authorBijlenga, Philippe-
dc.contributor.authorMorel, Sandrine-
dc.contributor.authorHostettler, Isabel-
dc.contributor.authorWerring, David-
dc.contributor.authorWostrack, Maria-
dc.contributor.authorMeyer, Bernhard-
dc.contributor.authorBourcier, Romain-
dc.contributor.authorLindgren, Antti-
dc.contributor.authorBakker, Mark K.-
dc.contributor.authorRuigrok, Ynte M.-
dc.contributor.authorFurrer, Reinhard-
dc.contributor.authorHirsch, Sven-
dc.date.accessioned2023-12-08T15:40:01Z-
dc.date.available2023-12-08T15:40:01Z-
dc.date.issued2023-11-15-
dc.identifier.issn2514-183Xde_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/29370-
dc.description.abstractAims: Intracranial aneurysms (IAs) are present in approximately 3% of the population [Vlak et al., 2011]. Rupture of IA leads to an aneurysmal subarachnoid haemorrhage with often poor functional outcomes [Lawton and Vates, 2017]. Unruptured IA (UIA) detection rates increase with advances in imaging technologies [Bijlenga et al., 2017]. The complexity of UIA treatment decision making is compounded by the difficulty of accurately predicting the risk of rupture and the lack of understanding of how modifiable factors affect IA rupture [Lognon et al., 2022]. Here, we show an explainable model for IA rupture based on easily accessible phenotypic risk factors. Methods: This model development study was validated on IA patient‑level registry data in a multicenter (n = 7) retrospective case‑control design with 9 phenotypic risk factors. Data were analysed using discrete and additive Bayesian network (BN) models. Expert knowledge a priori restricted the model search space, leading to a sparse network representing clinical expertise [Delucchi et al., 2022]. Results: We included 8604 patients with IA (median age 54y, IQR 45−63, 67% female), of whom 4254 (49%) patients had IA at the time of diagnosis. The point prevalence of recommended follow‑up patients with UIA [Bijlenga et al., 2013] was estimated to be approximately 43%. The joint probability distribution estimates patient‑specific disease management recommendations. Preliminary results indicate, for example, that older women with an IA in a low‑risk location are unlikely to experience a rupture (OR_{rupture} = 0.05), and patients who are active smokers at the time of IA diagnosis generally have a higher likelihood to be diagnosed with a ruptured IA (OR_{rupture} = 1.46). Conclusions: This study shows that mixed‑effect additive BNs can help clinicians understand the aetiology of IA rupture and may have potential for providing personalised guidance for UIA management. Our findings anticipate the starting point for IA disease models that encompass the entire evolution of the disease and could be refined in a more extensive prospective cohort study to develop a user‑friendly bedside decision support application.de_CH
dc.language.isoende_CH
dc.publisherMDPIde_CH
dc.relation.ispartofClinical and Translational Neurosciencede_CH
dc.rightsLicence according to publishing contractde_CH
dc.subject.ddc616: Innere Medizin und Krankheitende_CH
dc.titleAn explainable multicentric analysis for understanding the aetiology of intracranial aneurysm diseasede_CH
dc.typeKonferenz: Posterde_CH
dcterms.typeTextde_CH
zhaw.departementLife Sciences und Facility Managementde_CH
zhaw.organisationalunitInstitut für Computational Life Sciences (ICLS)de_CH
dc.identifier.doi10.3390/ctn7040039de_CH
zhaw.funding.euNode_CH
zhaw.issue4de_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end47de_CH
zhaw.pages.start46de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume7de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.webfeedMedical Image Analysis & Data Modelingde_CH
zhaw.funding.zhawModellierung multizentrischer und dynamischer Schlaganfall Gesundheitsdatende_CH
zhaw.funding.zhawStroke DynamiXde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
Appears in collections:Publikationen Life Sciences und Facility Management

Files in This Item:
There are no files associated with this item.
Show simple item record
Delucchi, M., Spinner, G. R., Bijlenga, P., Morel, S., Hostettler, I., Werring, D., Wostrack, M., Meyer, B., Bourcier, R., Lindgren, A., Bakker, M. K., Ruigrok, Y. M., Furrer, R., & Hirsch, S. (2023). An explainable multicentric analysis for understanding the aetiology of intracranial aneurysm disease [Conference poster]. Clinical and Translational Neuroscience, 7(4), 46–47. https://doi.org/10.3390/ctn7040039
Delucchi, M. et al. (2023) ‘An explainable multicentric analysis for understanding the aetiology of intracranial aneurysm disease’, in Clinical and Translational Neuroscience. MDPI, pp. 46–47. Available at: https://doi.org/10.3390/ctn7040039.
M. Delucchi et al., “An explainable multicentric analysis for understanding the aetiology of intracranial aneurysm disease,” in Clinical and Translational Neuroscience, Nov. 2023, vol. 7, no. 4, pp. 46–47. doi: 10.3390/ctn7040039.
DELUCCHI, Matteo, Georg R. SPINNER, Philippe BIJLENGA, Sandrine MOREL, Isabel HOSTETTLER, David WERRING, Maria WOSTRACK, Bernhard MEYER, Romain BOURCIER, Antti LINDGREN, Mark K. BAKKER, Ynte M. RUIGROK, Reinhard FURRER und Sven HIRSCH, 2023. An explainable multicentric analysis for understanding the aetiology of intracranial aneurysm disease. In: Clinical and Translational Neuroscience. Conference poster. MDPI. 15 November 2023. S. 46–47
Delucchi, Matteo, Georg R. Spinner, Philippe Bijlenga, Sandrine Morel, Isabel Hostettler, David Werring, Maria Wostrack, et al. 2023. “An Explainable Multicentric Analysis for Understanding the Aetiology of Intracranial Aneurysm Disease.” Conference poster. In Clinical and Translational Neuroscience, 7:46–47. MDPI. https://doi.org/10.3390/ctn7040039.
Delucchi, Matteo, et al. “An Explainable Multicentric Analysis for Understanding the Aetiology of Intracranial Aneurysm Disease.” Clinical and Translational Neuroscience, vol. 7, no. 4, MDPI, 2023, pp. 46–47, https://doi.org/10.3390/ctn7040039.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.