BACKGROUND:Sarcopenia is an age-related systemic skeletal muscle disease,which is associated with a variety of adverse outcomes such as falls,functional decline,frailty,and death.Postmenopausal women are one of the high-risk groups for sarcopenia.OBJECTIVE:To develop a predictive model for assessing the risk of sarcopenia in Chinese postmenopausal women based on high-quality database.METHODS:Data for this study were derived from 2 370 postmenopausal women from the China Health and Retirement Longitudinal Study(CHARLS),and sarcopenia was assessed using the Asian Working Group on Sarcopenia 2019(AWGS2019)recommended metrics.The study cohort was randomized into a training set(70％)and a validation set(30％).Risk factors for sarcopenia in postmenopausal women were screened using the least absolute shrinkage and selection operator,ten-fold cross-validation,and logistic regression.Nomogram predicting the risk of sarcopenia in postmenopausal women was constructed based on the risk factors,and the model efficacy was evaluated by the receiver operating characteristic curve and area under the curve(AUC),calibration curve,and decision curve analysis.RESULTS AND CONCLUSION:The prevalence of sarcopenia in this study was 23.50％and age,place of residence,sleep quality,cognitive function,depression,and the number of chronic diseases were selected as predictors of sarcopenia in postmenopausal women.The nomogram model showed good discrimination between the training and validation sets,with an AUC value of 0.751(95％confidence interval=0.724-0.778,P＜0.001),a specificity of 72.2％,and a sensitivity of 63.2％in the training set,and an AUC value of 0.763(95％confidence interval=0.721-0.805,P＜0.001),with a specificity of 69.6％and a sensitivity of 70.8％.The calibration curve showed a relatively significant agreement between the nomogram model and the actual observations,and the decision curve analysis demonstrated broad and good clinical utility.To conclude,the nomogram to assess the risk of sarcopenia constructed based on age,place of residence,sleep quality,cognitive function,depression,and number of chronic diseases,provides an effective tool for identifying and eliminating risk factors for sarcopenia in Chinese postmenopausal women,and helps to reduce the incidence of sarcopenia.

BACKGROUND:Sarcopenia is an age-related systemic skeletal muscle disease,which is associated with a variety of adverse outcomes such as falls,functional decline,frailty,and death.Postmenopausal women are one of the high-risk groups for sarcopenia.OBJECTIVE:To develop a predictive model for assessing the risk of sarcopenia in Chinese postmenopausal women based on high-quality database.METHODS:Data for this study were derived from 2 370 postmenopausal women from the China Health and Retirement Longitudinal Study(CHARLS),and sarcopenia was assessed using the Asian Working Group on Sarcopenia 2019(AWGS2019)recommended metrics.The study cohort was randomized into a training set(70％)and a validation set(30％).Risk factors for sarcopenia in postmenopausal women were screened using the least absolute shrinkage and selection operator,ten-fold cross-validation,and logistic regression.Nomogram predicting the risk of sarcopenia in postmenopausal women was constructed based on the risk factors,and the model efficacy was evaluated by the receiver operating characteristic curve and area under the curve(AUC),calibration curve,and decision curve analysis.RESULTS AND CONCLUSION:The prevalence of sarcopenia in this study was 23.50％and age,place of residence,sleep quality,cognitive function,depression,and the number of chronic diseases were selected as predictors of sarcopenia in postmenopausal women.The nomogram model showed good discrimination between the training and validation sets,with an AUC value of 0.751(95％confidence interval=0.724-0.778,P＜0.001),a specificity of 72.2％,and a sensitivity of 63.2％in the training set,and an AUC value of 0.763(95％confidence interval=0.721-0.805,P＜0.001),with a specificity of 69.6％and a sensitivity of 70.8％.The calibration curve showed a relatively significant agreement between the nomogram model and the actual observations,and the decision curve analysis demonstrated broad and good clinical utility.To conclude,the nomogram to assess the risk of sarcopenia constructed based on age,place of residence,sleep quality,cognitive function,depression,and number of chronic diseases,provides an effective tool for identifying and eliminating risk factors for sarcopenia in Chinese postmenopausal women,and helps to reduce the incidence of sarcopenia.

Objective:To assess the characteristics and correlation of motor development in preterm infants of different gestational weeks by using the Test of Infant Motor Performance (TIMP) method, and to develop better individualized early interventions based on TIMP test results.Methods:A prospective study involving 43 full-term healthy infants and 77 preterm followed up in 3201 Hospital from June 2019 to July 2021 was conducted.Preterm infants were divided into the early preterm group (39 cases) and late preterm group (38 cases) according to their gestational age at birth.TIMP assessment was performed at the gestational age of 40 weeks and the corrected age of 16 weeks after birth.Similarly, the full-term healthy infants were assessed by TIMP at the postnatal age of 16 weeks.The differences between groups were investigated using ANOVA or Mann- Whitney rank sum test.Correlations were analyzed by the Pearson correlation method. Results:There were no significant difference in TIMP scores between early and late preterm infants at the gestational age of 40 weeks [(65.74±6.52) scores vs.(66.96±8.51) scores] and the corrected age of 16 weeks [(101±10) scores vs.(104±8) scores] (all P>0.05). TIMP scores in the full-term healthy group at the corrected age of 16 weeks [(108±10) scores] differed significantly from those of early and late preterm infants ( P<0.05). Compared with full-term infants, early and late preterm infants had lower TIMP scores in observation, supine position, and supine turning (all P<0.05), but a higher TIMP score in standing position ( P<0.05). For both early and late preterm infants, TIMP scores at the gestational age of 40 weeks were significantly positively correlated with those at the corrected age of 16 weeks ( r=0.565, 0.302, all P<0.01). Conclusions:There were significant differences in motor development between preterm infants of different gestational ages and term infants, which had guiding significance for early intervention.English version TIMP could play a positive role in promoting individualized follow-up and early intervention of preterm infants in China.