老年住院患者肌少症影响因素分析及风险预测模型构建和验证

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【中图分类号】R685【文献标志码】A

Influencing factors for sarcopenia in elderly hospitalized patients and construction and validation of a risk prediction model

Zhou Yilin'，Fan Qingqing'，Peng Peng'，Liu Xintong²，Jiang Hong²，He Pingfeng，Deng Dan' （1.Department of Health Statistics，College of Public Health，Chongqing Medical University; 2.Department of Geriatrics，The First Affiliated Hospital of Chongqing Medical University; 3.Department of General Practice，Chongqing University Central Hospital）

【AbstractObjective：Tinvestigatetheinfluencingfactorsforsarcopeniainospitaliedpatients，toconstructaskpredictioodel forsarcopeniainelderlyhospitalizedpatintsandtoprovideaquantitivetoolforearlysreningandinterventionofsropena basedontheintegatioofultidimensioalindicators.Methods：Aretrospectiveanalysisaspeforedfortedataofelderly patientswhowerehospitalizedinTheFstAfiliated HospitalofChongqing MedicalUniversityfrom March2O16toJuneO23.The leastabsolutesinkageandselectionoperataalysisasusdforthsreeingofarablesndtlgisticegresionalisas usedtoinvestigateteinfuencingfactorsforarcopenia.Aprdictieodelwasonstructedndintealandeteallidatioas performed.TheShapleyadditiveexplanationsmodelwasusedtoanalyzefeaturecontributions，andanomogrammodelwascostructed to visualizeand interprettheresults.Results：The1259 patientsfrom March2O16to December2O2O wererandomlydivided ntoa trainingsetwith882patintsandanitealtestsetwith377patientsataatioof7：3，andthe846patintsfromJanuarytoJune 2023 were established as the external validation set.A total of 489 cases of sarcopenia（ 55.44% ）were detected in the training set. The logisticregresioanalysisbasedonthtrainingsetsowedthatasthenia，dependenceonActivityofDailyLiving，alnutritionandincreasing age were risk factors for sarcopenia（odds ratio [OR]>1 ，P<0.05），and male sex，normal body mass index，and overweight were protective factors against sarcopenia（OR<1， P <0.05）.The model had an AUC of 0.876（95%CI=0.854-0.899） in the training set， 0.883（95%CI=0.849-0.918）in the internal test set，and 0.750 （ 95% CI=0.717-O.783）in the external validation set，suggesting that the model had good performance.The decision curve analysis showed thatthenomogrammodel had agoodclinical value.Conclusion：The predictive model for sarcopenia has good performance and holds promise for clinical application. 【Key words】sarcopenia;influencing factors;predictive model;nomogram;Shapley additive explanations

肌少症是一种以骨骼肌质量、力量和功能进行性丧失为特征的老年综合征，其发病机制可能与衰老、运动缺乏、慢性病等多种因素密切相关。（剩余16250字）