{"id":4698,"date":"2021-01-22T21:20:38","date_gmt":"2021-01-23T02:20:38","guid":{"rendered":"https:\/\/ccna-ccnv.ca\/ccna_publication\/portals-to-frailty-data-driven-analyses-detect-early-frailty-profiles-2\/"},"modified":"2024-12-03T14:57:25","modified_gmt":"2024-12-03T19:57:25","slug":"portals-to-frailty-data-driven-analyses-detect-early-frailty-profiles-2","status":"publish","type":"ccna_publication","link":"https:\/\/ccna-ccnv.ca\/fr\/ccna_publication\/portals-to-frailty-data-driven-analyses-detect-early-frailty-profiles-2\/","title":{"rendered":"Portals to frailty? Data-driven analyses detect early frailty profiles"},"content":{"rendered":"<h2 class=\"title\">Abstract<\/h2>\n<div id=\"enc-abstract\" class=\"abstract-content selected\">\n<p><strong class=\"sub-title\">Background:\u00a0<\/strong>Frailty is an aging condition that reflects multisystem decline and an increased risk for adverse outcomes, including differential cognitive decline and impairment. Two prominent approaches for measuring frailty are the frailty phenotype and the frailty index. We explored a complementary data-driven approach for frailty assessment that could detect early frailty profiles (or subtypes) in relatively healthy older adults. Specifically, we tested whether (1) modalities of early frailty profiles could be empirically determined, (2) the extracted profiles were differentially related to longitudinal cognitive decline, and (3) the profile and prediction patterns were robust for males and females.<\/p>\n<p><strong class=\"sub-title\">Methods:\u00a0<\/strong>Participants (n = 649; M age = 70.61, range 53-95) were community-dwelling older adults from the Victoria Longitudinal Study who contributed data for baseline multi-morbidity assessment and longitudinal cognitive trajectory analyses. An exploratory factor analysis on 50 multi-morbidity items produced 7 separable health domains. The proportion of deficits in each domain was calculated and used as continuous indicators in a data-driven latent profile analysis (LPA). We subsequently examined how frailty profiles related to the level and rate of change in a latent neurocognitive speed variable.<\/p>\n<p><strong class=\"sub-title\">Results:\u00a0<\/strong>LPA results distinguished three profiles: not-clinically-frail (NCF; characterized by limited impairment across indicators; 84%), mobility-type frailty (MTF; characterized by impaired mobility function; 9%), and respiratory-type frailty (RTF; characterized by impaired respiratory function; 7%). These profiles showed differential neurocognitive slowing, such that MTF was associated with the steepest decline, followed by RTF, and then NCF. The baseline frailty index scores were the highest for MTF and RTF and increased over time. All observations were robust across sex.<\/p>\n<p><strong class=\"sub-title\">Conclusions:\u00a0<\/strong>A data-driven approach to early frailty assessment detected differentiable profiles that may be characterized as morbidity-intensive portals into broader and chronic frailty. Early inventions targeting mobility or respiratory deficits may have positive downstream effects on frailty progression and cognitive decline.<\/p>\n<\/div>\n","protected":false},"author":19,"featured_media":0,"template":"","meta":{"_acf_changed":false},"studies-relation":[],"class_list":["post-4698","ccna_publication","type-ccna_publication","status-publish","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.8 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Portals to frailty? Data-driven analyses detect early frailty profiles - CCNA - CCNV<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/ccna-ccnv.ca\/fr\/ccna_publication\/portals-to-frailty-data-driven-analyses-detect-early-frailty-profiles-2\/\" \/>\n<meta property=\"og:locale\" content=\"fr_CA\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Portals to frailty? Data-driven analyses detect early frailty profiles - CCNA - CCNV\" \/>\n<meta property=\"og:description\" content=\"Abstract Background:\u00a0Frailty is an aging condition that reflects multisystem decline ...\" \/>\n<meta property=\"og:url\" content=\"https:\/\/ccna-ccnv.ca\/fr\/ccna_publication\/portals-to-frailty-data-driven-analyses-detect-early-frailty-profiles-2\/\" \/>\n<meta property=\"og:site_name\" content=\"CCNA - CCNV\" \/>\n<meta property=\"article:modified_time\" content=\"2024-12-03T19:57:25+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/ccna-ccnv.ca\/wp-content\/uploads\/2025\/01\/CCNA.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1200\" \/>\n\t<meta property=\"og:image:height\" content=\"675\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Estimation du temps de lecture\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/ccna-ccnv.ca\/fr\/ccna_publication\/portals-to-frailty-data-driven-analyses-detect-early-frailty-profiles-2\/\",\"url\":\"https:\/\/ccna-ccnv.ca\/fr\/ccna_publication\/portals-to-frailty-data-driven-analyses-detect-early-frailty-profiles-2\/\",\"name\":\"Portals to frailty? 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Data-driven analyses detect early frailty profiles - CCNA - CCNV","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/ccna-ccnv.ca\/fr\/ccna_publication\/portals-to-frailty-data-driven-analyses-detect-early-frailty-profiles-2\/","og_locale":"fr_CA","og_type":"article","og_title":"Portals to frailty? 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