[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-424146-105":3,"detail-sidebar-cat-0-en-105":81,"doc-detail-424146-en":131},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":74,"head_meta":76,"extra_data":78,"updated_unix":80},105,"en","frailty-shows-enhanced-predictive-capacity-for-1-year-unplanned-readmission-comparing-to-reason-for-admission","FRAILTY SHOWS ENHANCED PREDICTIVE CAPACITY FOR 1-YEAR UNPLANNED READMISSION - Comparing to Reason for Admission","","Frailty, a common geriatric syndrome, is linked to disability and premature mortality, while unplanned readmissions create major burdens for families and healthcare systems. This prospective cohort study assessed whether frailty predicts 1-year unplanned readmissions in patients aged 65+ and whether predictive utility varies by admission cause (acute versus chronic). Among 414 participants, frailty (FRAIL scale) was prevalent and independently increased readmission risk over one year, showing interaction with admission cause. The frailty model demonstrated improved predictive accuracy for chronic-disease admissions. Findings support systematic frailty screening at admission combined with tailored rehabilitation to reduce readmission risk.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/healthcare/","Healthcare",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/frailty-shows-enhanced-predictive-capacity-for-1-year-unplanned-readmission-comparing-to-reason-for-admission/424146/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/frailty-shows-enhanced-predictive-capacity-for-1-year-unplanned-readmission-comparing-to-reason-for-admission/424146.png","ImageObject",300,407,{"name":42,"@type":43},"Adam","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-11-02","2026-09-28",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",11,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What is the study objective regarding frailty and readmissions?","Question",{"text":63,"@type":64},"The study investigates how frailty affects 1-year unplanned readmissions in elderly inpatients and examines whether prediction differs across subgroups based on admission causes (acute vs. chronic).","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"How was frailty measured and how were participants grouped?",{"text":68,"@type":64},"Frailty was assessed using the FRAIL scale, classifying participants into non-frail and frail groups. Participants were also stratified by admission diagnosis into acute and chronic conditions.",{"name":70,"@type":61,"acceptedAnswer":71},"What were the main findings about predictive capacity and risk?",{"text":72,"@type":64},"Frailty independently predicted 1-year unplanned readmissions, and the association differed by admission cause. Subgroup analysis showed enhanced predictive accuracy for frailty in chronic-disease-related admissions.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},424146,1790764155,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,106,110,115,120,123,127],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":102,"doc_module":4,"doc_module_name":25,"category_name":103,"show_sort_weight":104,"slug":105},6,"Technology",50,"technology",{"id":107,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":108,"slug":109},7,40,"healthcare",{"id":111,"doc_module":4,"doc_module_name":25,"category_name":112,"show_sort_weight":113,"slug":114},8,"Research & Report",30,"research-report",{"id":116,"doc_module":4,"doc_module_name":25,"category_name":117,"show_sort_weight":118,"slug":119},9,"Religion & Spirituality",20,"religion-spirituality",{"id":118,"doc_module":4,"doc_module_name":25,"category_name":121,"show_sort_weight":118,"slug":122},"World Cup","world-cup",{"id":124,"doc_module":4,"doc_module_name":25,"category_name":125,"show_sort_weight":124,"slug":126},10,"Lifestyle","lifestyle",{"id":128,"doc_module":4,"doc_module_name":25,"category_name":129,"show_sort_weight":97,"slug":130},19,"General","general",{"code":4,"msg":82,"data":132},{"doc_id":79,"user_id":133,"nickname":42,"user_avatar":134,"doc_module":4,"category_id":107,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":22,"language":140,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":12,"update_tm":144,"read_time":30,"preview_page_count":4},1374404737137,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Innovation in Aging, 2025, Vol. 9, No. S2 695  \nAbstract citation ID: igaf122.2371  \nFRAILTY SHOWS ENHANCED PREDICTIVE CAPACITY FOR 1-YEAR UNPLANNED READMISSION COMPARING TO REASON FOR ADMISSION  \nJunpeng Kan, Ying Sun, Wen Tang, Yunli Xing, and Qing Ma, Beijing Friendship Hospital, Capital Medical University, Beijing, Beijing, China (People’s Republic)  \nBackground: Frailty, a prevalent geriatric syndrome, predisposes older adults to adverse outcomes including disability and premature mortality. Unplanned hospital readmissions impose substantial economic burdens on families and challenge healthcare systems. Objective: To investigate the impact of frailty on 1-year unplanned readmissions among elderly inpatients and further analyze its predictive utility across subgroups stratified by admission causes (acute vs. chronic conditions) . Methods: This prospective cohort study enrolled patients aged ≥65 years from the Geriatrics Department of Beijing Friendship Hospital, Capital Medical University. Frailty status was assessed using the FRAIL scale, categorizing participants into non-frail and frail groups. Participants were stratified by admission diagnosis (acute/chronic conditions). Baseline demographics, medical histories, and laboratory parameters were collected. Electronic medical records were reviewed to identify unplanned readmissions within 1 year. Results: A∼mong 414 enrolled patients. Median age  \nwas 82 years (IQR 72 88), 58.9%(n = 244) were frail. During the 1-year follow-up period, 173 patients (42.8%) experienced unplanned readmissions. Frailty independently predicted 1-year unplanned readmissions (OR = 1.694, 95% CI:1.013–2.830, P = 0.044), with a significant interaction between frailty and admission cause (P for interction 0.006) . Subgroup analysis revealed enhanced predictive accuracy of frailty comparing to chronic disease-related admissions. Conclusions: Frailty serves as an independent risk factor for 1-year unplanned readmissions in elderly inpatients, particularly among those hospitalized for chronic conditions. Systematic frailty screening at admission coupled with tailored physical rehabilitation programs may mitigate readmission risks.","cbCainXtf4M68jU2","https://ap.wps.com/l/cbCainXtf4M68jU2","pdf",52727,"English","# Background\n# Objective\n# Methods\n# Results\n# Conclusions","[{\"question\":\"What is the study objective regarding frailty and readmissions?\",\"answer\":\"The study investigates how frailty affects 1-year unplanned readmissions in elderly inpatients and examines whether prediction differs across subgroups based on admission causes (acute vs. chronic).\"},{\"question\":\"How was frailty measured and how were participants grouped?\",\"answer\":\"Frailty was assessed using the FRAIL scale, classifying participants into non-frail and frail groups. Participants were also stratified by admission diagnosis into acute and chronic conditions.\"},{\"question\":\"What were the main findings about predictive capacity and risk?\",\"answer\":\"Frailty independently predicted 1-year unplanned readmissions, and the association differed by admission cause. Subgroup analysis showed enhanced predictive accuracy for frailty in chronic-disease-related admissions.\"}]","FRAILTY SHOWS ENHANCED PREDICTIVE CAPACITY FOR 1-YEAR UNPLANNED READMISSION - Comparing to Reason for Admission | PDF",1790633095]