Background: Carotid intima-media thickness (cIMT) provides an index of arterial injury. Frailty is an indicator of vulnerability to adverse health outcomes. It is unclear whether cIMT is associated with the multi-dimensional frailty index and/or if this relationship is age- or sex-specific. The aim was to determine the impact of age and sex on the relationship between cIMT and frailty level in middle-aged and older adults.
Methods: Frailty and cIMT data were extracted from the Canadian Longitudinal Study of Aging baseline comprehensive cohort of middle-aged (45-64 years) and older adults (>65 years) (n = 10,209). cIMT was assessed via high-resolution ultrasound. Frailty was determined using a 52-item index. Covariate-adjusted ordinary least squares regressions were conducted separately for middle-aged males (n = 3178), middle-aged females (n = 3125), older males (n = 2031), and older females (n = 1875).
Results: Average cIMTs were larger in older versus middle-aged adults and in males versus females (all, p < 0.001). Average cIMT was positively associated with frailty level in adjusted linear regression models in middle-aged males [adj. R = 0.09; β = 0.015 (95 % CI: 0.005-0.026), p = 0.004], middle-aged females [adj. R = 0.11; β = 0.040 (95 % CI: 0.025-0.054), p < 0.001], older males [adj. R = 0.12; β = 0.019 (95 % CI: 0.004-0.034), p = 0.01], and older females [adj. R = 0.11; β = 0.020 (95 % CI: 0.002-0.039), p = 0.03].
Conclusion: cIMT was an independent contributor to frailty level regardless of age group (middle-aged/older adults) or sex, with the strongest effect observed in middle-aged females. Our cross-sectional study documents the independent relationship between a marker of cardiovascular function and an increased vulnerability to adverse health outcomes in middle-aged and older males and females.
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http://dx.doi.org/10.1016/j.jjcc.2023.01.004 | DOI Listing |
Diabetes Obes Metab
January 2025
Endocrinologie, Diabétologie Et Gynécologie Pédiatrique, Hopital Necker-Enfants Malades, Université Paris Cité, AP-HP centre, Paris, France.
Background: Transition from paediatric to adult healthcare is a turning point for patients with Type 1 diabetes (T1D). A gradual coordinated process connecting paediatric and adult healthcare providers may improve adherence to adult follow-up.
Aims: To describe a transition process developed jointly by paediatric and adult diabetology units and compare patients progressing or not to follow-up in adult care setting.
Otolaryngol Head Neck Surg
January 2025
Department of Otolaryngology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
Objective: To evaluate factors impacting access to and timing of surgery in patients with submucous cleft palate (SMCP) and velopharyngeal dysfunction (VPD).
Study Design: Retrospective cohort study.
Setting: Single academic medical center.
Wound Repair Regen
January 2025
Research Unit for Plastic Surgery, University of Southern Denmark, Odense, Denmark.
The WOUND-Q is a patient-reported outcome measure for individuals with any type of chronic wound. This study aimed to identify patient and wound factors associated with the four WOUND-Q health-related quality of life (HRQL) scales: Life impact, Psychological, Sleep, and Social. Adults with a chronic wound were recruited internationally through clinical settings between August 2018 and May 2020, and through an online platform (i.
View Article and Find Full Text PDFEClinicalMedicine
December 2024
Nottingham Digestive Diseases Centre (NDDC), Translational Medical Sciences, School of Medicine, University of Nottingham, NG7 2UH, UK.
Background: Despite the availability of various pharmacological and behavioural interventions, alcohol-related mortality is rising. This systematic review aimed to critically evaluate the existing literature on the association between glucagon-like peptide-1 receptor agonists use (GLP-1 RAs) and alcohol consumption.
Methods: Electronic searches were conducted on Ovid Medline, EMBASE, PsycINFO, clintrials.
World J Clin Cases
January 2025
Department of Gastroenterology, Laiko General Hospital, National and Kapodistrian University of Athens, Athens 11527, Greece.
Machine learning (ML) is a type of artificial intelligence that assists computers in the acquisition of knowledge through data analysis, thus creating machines that can complete tasks otherwise requiring human intelligence. Among its various applications, it has proven groundbreaking in healthcare as well, both in clinical practice and research. In this editorial, we succinctly introduce ML applications and present a study, featured in the latest issue of the .
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