Background: Though hypertension is a commonly studied risk factor for white matter lesions (WMLs), measures of blood pressure may fluctuate depending on external conditions resulting in measurement error. Indicators of arterial stiffening and reduced elasticity may be more sensitive indicators of risk for WMLs in aging; however the interdependent nature of vascular indicators creates statistical complications.
Objective: The purpose of the study was to determine whether a factor score comprised of multiple vascular indicators would be a stronger predictor of WMLs than traditional measures of blood pressure.
Methods: In a sample of well-characterized nondemented older adults, we used a factor analytic approach to account for variance common across multiple vascular measures while reducing measurement error. The result was a single factor score reflecting arterial stiffness and reduced elasticity. We used this factor score to predict white matter lesion volumes acquired via fluid attenuated inversion recovery (FLAIR) magnetic resonance imaging.
Results: The combined vascular factor score was a stronger predictor of deep WML (β = 0.42, p < 0.001) and periventricular WML volumes (β = 0.49, p < 0.001). After accounting for the vascular factor, systolic and diastolic blood pressure measurements were not significant predictors.
Conclusions: This suggests that a combined measure of arterial elasticity and stiffening may be a stronger predictor of WMLs than systolic and diastolic blood pressure accounting for the multicollinearity associated with a variety of interrelated vascular measures.
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http://dx.doi.org/10.3233/JAD-142085 | DOI Listing |
Sci Rep
December 2024
Trauma Nursing Research Center, Kashan University of Medical Sciences, Kashan, Iran.
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December 2024
School of Psychology, Inner Mongolia Normal University, Hohhot, China.
The purpose of this study was to evaluate the psychometric properties of the Chinese version of the Revised Indebtedness Scale (IS-R-C) in mainland China. A total of 1057 university students participated in this study using a two-wave whole-group sampling method. Sample 1, consisting of 537 participants, was used for item analysis and exploratory factor analysis (EFA) of the Revised Indebtedness Scale (IS-R).
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December 2024
Nehme and Therese Tohme Multiple Sclerosis Center, American University of Beirut Medical Center, Riad El-Solh, PO Box 11-0236, 1107 2020, Beirut, Lebanon.
Fatigue is one of the most prevalent and disabling symptoms among patients with MS, but there is limited research investigating the longitudinal determinants of fatigue progression. This study aims to identify the sociodemographic, behavioral and clinical characteristics, and therapeutic regimens that are correlated with worsening fatigue over time in patients diagnosed with MS. This is a retrospective chart review of 483 patients.
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December 2024
Department of Medical and Surgical Sciences, Institute of Cardiology, University of Bologna, Policlinico S.Orsola-Malpighi, via Massarenti 9, Bologna, 40138, Italy.
Cardiac implantable electronic devices infections (CIEDI) are associated with poor survival despite the improvement in transvenous lead extraction (TLE). Aetiology and systemic involvement are driving factors of clinical outcomes. The aim of this study was to explore their contribute on overall mortality.
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December 2024
School of Civil & Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Per- and polyfluoroalkyl substances (PFASs) have recently garnered considerable concerns regarding their impacts on human and ecological health. Despite the important roles of polyamide membranes in remediating PFASs-contaminated water, the governing factors influencing PFAS transport across these membranes remain elusive. In this study, we investigate PFAS rejection by polyamide membranes using two machine learning (ML) models, namely XGBoost and multimodal transformer models.
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