Effect Of Cardiometabolic Risk Factors Combined With Low Skeletal Muscle Mass On ASCVD

Objective Low skeletal muscle mass is strongly associated with quality of life and disease prognosis in older adults.Recently,the relationship between skeletal muscle mass and cardiovascular disease risk has also received attention.In this study,we propose to construct a clinical diagnostic model of low skeletal muscle mass(LSM),explore predictors of LSM occurrence,and investigate the effect of cardiometabolic risk factors combined with LSM on cardiovascular risk.MethodPart I: Retrospective study.3081 patients were collected from January 2019 to December 2022 at the Union Hospital of Tongji Medical College,Huazhong University of Science and Technology,and the study population was divided into a training cohort and a validation cohort using a random number method.The diagnostic model of LSM was constructed and the column line graphs were drawn,and the receiver operating characteristic curve(ROC),calibration curve,and Hosmer-Lemeshow test were used to evaluate the discrimination and calibration of the model.Part II: Prospective cohort study.From January 2019 to June 2019,the baseline survey of 241 patients was completed,and the follow-up was completed before December 2022.Cox proportional hazards model was used to study the relationship between Geriatric nutrition risk index(GNRI)and LSM risk.The ROC curve was drawn to determine the validity of GNRI in predicting LSM and calculate the best cut-off value.Part III: Retrospective study(same subjects as Part I).The Framingham Heart Study(FHS)10-year cardiovascular disease risk score was applied to classify the risk of atherosclerotic cardiovascular disease(ASCVD);the study population was divided according to different cardiometabolic risk factors and LSM,and the effect of cardiometabolic risk factors superimposed on LSM on the risk of ASCVD was analyzed and compared.ResultPart I: 2166 cases in the training cohort and 915 cases in the validation cohort were divided,and the variables screened using logistic regression stepwise backward regression with actual clinical significance were age,AST /ALT ratio(Aspartate aminotransferase-toalanine aminotransferase The internal and external validation of the diagnostic model showed that the model had superior diagnostic efficacy,and the area under the curve(AUC)of the ROC for the training cohort.The area under the curve(AUC)was 0.776(95% CI [0.751,0.801])for the training cohort and 0.813(95% CI [0.775,0.852])for the validation cohort,and the calibration curve and Hosmer-Lemeshow test also showed good agreement.Part II: Cox regression analysis of GNRI by quartiles found that the HR for the risk of LSM was 4.349,95% CI [0.481,39.345],2.632,95% CI [0.273,25.426],and 8.431,95% CI [1.095,64.894] for each decreasing quartile of GNRI,respectively;The best critical values of GNRI among the total population,men and women were 103.31,97.97 and 104.22,respectively,and the area under the ROC curve was 0.774,0.824 and 0.698,respectively.Part III: LSM in patients with hypertension,LSM in patients with diabetes,LSM in patients with chronic obstructive pulmonary disease,LSM in patients with chronic kidney disease,LSM in patients with overweight and obesity,LSM in patients with hypertriglyceridemia,and LSM in patients with high low-density lipoprotein cholesterol(LDL-C).LDL-C)combined with LSM and High densitylipoprotein(HDL)cholesterol,HDL-C)combined with LSM and hyperuricemia combined with LSM for high-risk ASCVD were 55.6%,60.9%,63.2%,64.8%,43.6%,50%,44.4%,53.7% and 50.8%,respectively.After adjusting for confounding factors,LSM combined with hypertension(OR=2.458,95%CI[1.585,3.812]),LSM combined with diabetes(OR=6.049,95%CI[1.585,3.812]),95%CI[3.432,10.663]),LSM combined with chronic kidney disease(OR=2.351,95%CI[1.112,4.968]),LSM combined with hypertriglyceridemia(OR=2.09,95%CI[1.112,4.968])95%CI=1.986,4.429),LSM combined with high LDL-C level(OR=2.582,95%CI[1.35,4.939]),LSM combined with low HDL-C level(OR=3.181,95%CI[1.35,4.939]),95%CI[2.004,5.051]),and LSM combined with hyperuricemia(OR=2.324,95%CI[1.441,3.748])were significantly increased in the incidence of high-risk ASCVD.ConclusionPart I: A line graph model with eight variables including age,creatinine,HDL cholesterol,NLR,AST/ALT ratio,GNRI,statin use,and H.pylori infection was developed for the diagnosis of LSM;Part II: A prospective cohort study demonstrated that the Geriatric Nutrition Risk Index(GNRI)is an independent risk factor for the development of LSM and has strong predictive validity for LSM;Part III: Hypertension,diabetes,chronic kidney disease,dyslipidemia,and hyperuricemia combined with low skeletal muscle mass significantly increased the incidence of high-risk ASCVD.