Utility of multidetector computed tomography quantitative measurements in identifying sarcopenia: a propensity score matched study.

OBJECTIVE: To evaluate the utility of multidetector computed tomography MDCT quantitative measurements in identifying sarcopenia. MATERIALS AND METHODS: The clinical data and MDCT images of 64 patients of sarcopenia and 184 non-sarcopenic participants between October 2020 and January 2021were retrospectively analyzed. Propensity score matching was used to match the sarcopenic patients with the non-sarcopenic participants. Two radiologists independently measured the cross-sectional area (CSA) of skeletal muscle and intramuscular fat tissue and CT density of skeletal muscle at the middle L3 vertebral level on CT images of all participants. Intra-observer agreement was evaluated via intraclass correlation coefficients (ICC). A receiver operating characteristic (ROC) curve was built for each variable. Correlations between CT parameters and clinical data were assessed via Pearson or Spearman correlation coefficient. RESULTS: A total of 74 participants (mean age 72 ± 4 years, range 66-85 years; 38 men and 36 women) were included, comprising 37 sarcopenic patients and 37 non-sarcopenic participants. There were no significant intergroup differences regarding age, sex ratio, and body mass index (BMI) (P < 0.05). The CSA and density of skeletal muscle measured by two radiologists were reliable (ICC ≥ 0.75, P < 0.001). Compared with the sarcopenic group, the non-sarcopenic group had a significantly greater CSA and CT density of the total skeletal muscle (TSM) and paraspinal skeletal muscle (PSM) and skeletal muscle index at L3 level (L3 SMI) (P < 0.05). The fat infiltration ratio (FIR) of TSM, PSM, and psoas muscle was significantly higher in the sarcopenic group than that in non-sarcopenic participants (P < 0.05). ROC curve analysis showed the PSM FIR + PSM CT density (PSM D) had the best predictive value for sarcopenia (AUC = 0.836). The PSM FIR and age were moderately positively correlated (r = 0.410, P < 0.001). CONCLUSION: Fat infiltration of skeletal muscle had better predictive value than L3 SMI in the diagnosis of sarcopenic. The PSM FIR + PSMD had the best predictive value for sarcopenia, which was moderately positively correlated with age.

Association Between the Cardiometabolic Index and Hyperuricemia in an Asymptomatic Population with Normal Body Mass Index.

BACKGROUND AND PURPOSE: The association between the cardiometabolic index (CMI) and hyperuricemia was investigated to provide theoretical support for the management of hyperuricemia in an asymptomatic population with normal body mass index (BMI). METHODS: A cross-sectional study was carried out among 374 asymptomatic adults with normal BMI. Traditional anthropometric indices and CMI were calculated. Anthropometric indices were divided into four quartiles and multivariate logistic analysis was used to analyze the association between these indices and hyperuricemia. Receiver operating characteristic (ROC) curves and area under the curve (AUC) were used to evaluate the power of the indices to predict hyperuricemia values. The DeLong test was used to compare the AUC of different anthropometric indices. RESULTS: After adjusting for confounding variables, the CMI exhibited a stronger association with hyperuricemia than other anthropometric indices. The odds ratio (OR) for hyperuricemia in the highest quartile of the CMI was 16.674 (confidence interval [CI]=4.424-62.846). The AUC of the CMI was 0.777 (95% CI=0.719-0.835, p<0.001), which was higher than the values for other anthropometric indices. The differences in AUC between the CMI and other indices were statistically significant; the optimal cutoff value of the CMI was 0.655, with sensitivity of 57.1% and specificity of 84.2%. CONCLUSION: The CMI, which combines waist circumference, height and blood lipid parameters, was more strongly associated with hyperuricemia than other anthropometric indices in asymptomatic population with normal BMI. The CMI may serve as a potential monitoring indicator for hyperuricemia management in asymptomatic populations with normal BMI.

[Effects of land use change on soil organic carbon and total nitrogen storage in Karst immigration regions of Guangxi Province, China.] / å¹¿è¥¿å–€æ–¯ç‰¹ç§»æ°‘è¿å ¥åŒºåœŸåœ°åˆ©ç”¨å˜åŒ–å¯¹åœŸå£¤æœ‰æœºç¢³å’Œå ¨æ°®å‚¨é‡çš„å½±å“.

Land use change is an important factor affecting soil carbon and nitrogen cycle, and this is a hot spot in the study of global climate change. Based on the fixed depth method (FD) and the equivalent mass method (ESM), we explored the effects of land use change on soil organic carbon (SOC) and total nitrogen (TN) storage from the perspectives of forest reclamation and farmland vegetation restoration in Karst area. The storage of SOC and TN significantly decreased after the fore-sts were converted to grassland, eucalyptus and farmland. On average, the SOC and TN losses calculated by the FD method were 47.4% and 41.6%, respectively, the losses of SOC and TN calculated by ESM method were 54.8% and 49.7%. The SOC and TN storage increased significantly after abandonment of farmland to grassland or planting eucalyptus. On average, the SOC and TN stocks calculated based on the FD method increased by 60.5% and 49.7%, while the SOC and TN calculated by the ESM method increased by 85.5% and 70.8% respectively. The difference between FD method and ESM method was analyzed, it was concluded that FD method ignored the difference of soil bulk density after land use change. Soil bulk density was significantly increased after forest destruction. The loss of SOC and TN storage was overestimated by the FD method. Soil bulk density decreased after vegetation restoration, FD method will underestimate the enhancement of SOC and TN storage. It is suggested that the ESM method should be used to estimate the impacts of land use change on SOC and TN storage.