{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Fan L"],"funding":["National Outstanding Youth Science Fund Project of National Natural Science Foundation of China"],"pagination":["404"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12632084"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["44(1)"],"pubmed_abstract":["<h4>Background</h4>Frailty is emerging as a determinant of adverse health outcomes in older adults; identifying high-risk groups early and taking effective interventions can improve the quality of life and prognosis for the elderly. The aim of this study was to build and test a model to predict frailty among the older Chinese person, facilitating early intervention.<h4>Methods</h4>This cross-sectional study used data from the Psychology and Behavior Investigation of Chinese Residents (PBICR), the set was split into a training set and a validation set at a 70:30 ratio. Logistic regression analyzed frailty factors, and a nomogram was developed to predict frailty, with calibration curves and decision curve analysis (DCA) assessing accuracy.<h4>Results</h4>4,367 people above 60 years of age fr"],"journal":["Journal of health, population, and nutrition"],"pubmed_title":["Development and validation of a risk prediction nomogram for frailty in older Chinese adults."],"pmcid":["PMC12632084"],"funding_grant_id":["71804125"],"pubmed_authors":["Liu Y","Fan L","Zhu H","Yu Z","Wang L"],"additional_accession":[]},"is_claimable":false,"name":"Development and validation of a risk prediction nomogram for frailty in older Chinese adults.","description":"<h4>Background</h4>Frailty is emerging as a determinant of adverse health outcomes in older adults; identifying high-risk groups early and taking effective interventions can improve the quality of life and prognosis for the elderly. The aim of this study was to build and test a model to predict frailty among the older Chinese person, facilitating early intervention.<h4>Methods</h4>This cross-sectional study used data from the Psychology and Behavior Investigation of Chinese Residents (PBICR), the set was split into a training set and a validation set at a 70:30 ratio. Logistic regression analyzed frailty factors, and a nomogram was developed to predict frailty, with calibration curves and decision curve analysis (DCA) assessing accuracy.<h4>Results</h4>4,367 people above 60 years of age fr","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Nov","modification":"2026-06-05T18:43:22.204Z","creation":"2026-05-20T03:13:57.989Z"},"accession":"S-EPMC12632084","cross_references":{"pubmed":["41267110"],"doi":["10.1186/s41043-025-01148-y"]}}