{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Xiao H"],"funding":["key laboratory of anhui province for testing technology and energy-saving devices","National Natural Science Foundation of China","Hefei Municipal Natural Science Foundation"],"pagination":["469580231155295"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9926366"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["60"],"pubmed_abstract":["Early identification of individuals with mild cognitive impairment (MCI) is essential to combat worldwide dementia threats. Physical function indicators might be low-cost early markers for cognitive decline. To establish an early identification tool for MCI by combining physical function indicators (upper and lower limb function) via a clinical prediction modeling strategy. A total of 5393 participants aged 60 or older were included in the model. The variables selected for the model included sociodemographic characteristics, behavioral factors, mental status and chronic conditions, upper limb function (handgrip strength), and lower limb function (self-rated squat ability). Two models were developed to test the predictive value of handgrip strength (Model 1) or self-rated squat ability (Mod"],"journal":["Inquiry : a journal of medical care organization, provision and financing"],"pubmed_title":["The Value of Handgrip Strength and Self-Rated Squat Ability in Predicting Mild Cognitive Impairment: Development and Validation of a Prediction Model."],"pmcid":["PMC9926366"],"funding_grant_id":["72004003","202004b11020019","2021005"],"pubmed_authors":["Xu L","Qiong W","Yan Z","Jingya Z","Guodong S","Xiao H","Shuai Z","Fangfang H"],"additional_accession":[]},"is_claimable":false,"name":"The Value of Handgrip Strength and Self-Rated Squat Ability in Predicting Mild Cognitive Impairment: Development and Validation of a Prediction Model.","description":"Early identification of individuals with mild cognitive impairment (MCI) is essential to combat worldwide dementia threats. Physical function indicators might be low-cost early markers for cognitive decline. To establish an early identification tool for MCI by combining physical function indicators (upper and lower limb function) via a clinical prediction modeling strategy. A total of 5393 participants aged 60 or older were included in the model. The variables selected for the model included sociodemographic characteristics, behavioral factors, mental status and chronic conditions, upper limb function (handgrip strength), and lower limb function (self-rated squat ability). Two models were developed to test the predictive value of handgrip strength (Model 1) or self-rated squat ability (Mod","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Jan-Dec","modification":"2025-04-18T21:30:59.763Z","creation":"2025-04-07T09:23:17.829Z"},"accession":"S-EPMC9926366","cross_references":{"pubmed":["36760102"],"doi":["10.1177/00469580231155295"]}}