Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/126230
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dc.contributor.authorTully, P.-
dc.contributor.authorQchiqach, S.-
dc.contributor.authorPereira, E.-
dc.contributor.authorDebette, S.-
dc.contributor.authorMazoyer, B.-
dc.contributor.authorTzourio, C.-
dc.date.issued2017-
dc.identifier.citationBMJ Open, 2017; 7(12):e018328-1-e018328-9-
dc.identifier.issn2044-6055-
dc.identifier.issn2044-6055-
dc.identifier.urihttp://hdl.handle.net/2440/126230-
dc.descriptionFirst published December 29, 2017.-
dc.description.abstractObjectives: The objective was to develop and validate a risk model for the likelihood of extensive white matter lesions (extWML) to inform clinicians on whether to proceed with or forgo diagnostic MRI. Design: Population-based cohort study and multivariable prediction model. Setting: Two representative samples from France. Participants: Persons aged 60–80 years without dementia or stroke. Derivation sample n=1714; validation sample n=789. Primary and secondary outcome measures: Volume of extWML (log cm3) was obtained from T2-weighted images in a 1.5 T scanner. 20 candidate risk factors for extWML were evaluated with the C-statistic. Secondary outcomes in validation included incident stroke over 12 years follow-up. Results: The multivariable prediction model included six clinical risk factors (C-statistic=0.61). A cut-off of 7 points on the multivariable prediction model yielded the optimum balance in sensitivity 63.7% and specificity 54.0% and the negative predictive value was high (81.8%), but the positive predictive value was low (31.5%). In further validation, incident stroke risk was associated with continuous scores on the multivariable prediction model (HR 1.02; 95% CI 1.01 to 1.04, P=0.02) and dichotomised scores from the multivariable prediction model (HR 1.28; 95% CI 1.02 to 1.60, P=0.03). Conclusions: A simple clinical risk equation for WML constituted by six variables can inform decisions whether to proceed with or forgo brain MRI. The high-negative predictive value demonstrates potential to reduce unnecessary MRI in the population aged 60–80 years.-
dc.description.statementofresponsibilityPhillip J Tully, Sarah Qchiqach, Edwige Pereira, Stephanie Debette, Bernard Mazoyer, Christophe Tzourio-
dc.language.isoen-
dc.publisherBMJ Journals-
dc.rights© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted. This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http:// creativecommons. org/ licenses/ by- nc/ 4. 0/-
dc.subjectleukoaraiosis-
dc.titleDevelopment and validation of a priori risk model for extensive white matter lesions in people age 65 years or older: the Dijon MRI study-
dc.typeJournal article-
dc.identifier.doi10.1136/bmjopen-2017-018328-
pubs.publication-statusPublished-
dc.identifier.orcidTully, P. [0000-0003-2807-1313]-
Appears in Collections:Aurora harvest 8
Psychology publications

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