摘要
BACKGROUND The association of different body components,including lean mass and body fat,with the risk of death in acute coronary syndrome(ACS)patients are unclear.METHODS We enrolled adults diagnosed with ACS at our center between January 2011 and December 2012 and obtained fol-low-up outcomes via telephone questionnaires.We used restricted cubic splines(RCS)with the Cox proportional hazards model to analyze the associations between body mass index(BMI),predicted lean mass index(LMI),predicted body fat percentage(BF),and the value of LMI/BF with 10-year mortality.We also examined the secondary outcome of death during hospitalization.RESULTS During the maximum 10-year follow-up of 1398 patients,331 deaths(23.6%)occurred,and a U-shaped relationship was found between BMI and death risk(P_(nonlinearity)=0.03).After adjusting for age and history of diabetes,the overweight group(24≤BMI<28 kg/m^(2))had the lowest mortality(HR=0.53,95%CI:0.29-0.99).Predicted LMI and LMI/BF had an inverse linear relationship with a 10-year death risk(P_(nonlinearity)=0.24 and P_(nonlinearity)=0.38,respectively),while an increase in BF was associ-ated with increased mortality(P_(nonlinearity)=0.64).During hospitalization,31 deaths(2.2%)were recorded,and the associations of the indicators with in-hospital mortality were consistent with the long-term outcome analyses.CONCLUSION Our study provides new insight into the“obesity paradox”in ACS patients,highlighting the importance of considering body composition heterogeneity.Predicted LMI and BF may serve as useful tools for assessing nutritional status and predicting the prognosis of ACS,based on their linear associations with all-cause mortality.
基金
This study was supported by Sichuan Science and Technology Program(Grant numbers:2022ZDZX0030,2021YFS0330,Sichuan,China)
Sichuan Provincial Cadre Health Research Project,China(Sichuan Ganyan ZH2021-101)
1·3·5 project for disciplines of excellence-Clinical Research Incubation Project,West China Hospital,Sichuan University(Grant number:2021HXFH061,Sichuan,China).
