Sarcopenia is the degenerative loss of skeletal muscle mass (0.5–1% loss per year after the age of 50), quality, and strength associated with aging.
Sarcopenia is a component of the frailty syndrome. It is often a component of cachexia. It can also exist independently of cachexia; whereas cachexia includes malaise and is secondary to an underlying pathosis (such as cancer), sarcopenia may occur in healthy people and does not necessarily include malaise. The term is from the Greek σάρξ sarx, “flesh” and πενία penia, “poverty”.
Computed tomography (CT) scan is frequently used to assess skeletal muscle mass and further calculate skeletal muscle index (SMI) at the third lumbar vertebra level (L3), which is used to define sarcopenia 1).
No association could be demonstrated between temporal muscle thickness and temporal muscle area and overall survival of glioblastoma patients. In addition, the median disease-free survival was found to be longer in patients with low temporal muscle area. There is an unmet need to determine the optimal method of sarcopenia in glioblastoma patients 2).
Katsuki et al. assumed that elderly patients with SAH who do not suffer from sarcopenia tend to have good outcomes. Temporal muscle thickness (TMT) and area (TMA) are useful indicators of sarcopenia. We investigated the clinical characteristics, including temporal muscle, in SAH patients over 75 years old.
They retrospectively analyzed 49 SAH patients over 75 years old from 2014 to 2018, who accounted for 37% of the patients in all age group. The correlations between the clinical variables and the modified Rankin Scale (mRS) at discharge were analyzed.
Of the all 49 SAH patients over 75 years old, premorbid mRS, WFNS grade, lymphocyte, aneurysm size, TMT, TMA, showed significant correlations with mRS at discharge. Men and the absence of hydrocephalus were correlated with favorable outcomes. Thirteen of the 24 patients over 75 years old whose WFNS grade were I to III but also who underwent aneurysm treatment had favorable outcomes (mRS 0-2), and their standardized TMT divided by height, by weight, and TMA divided by weight were significantly larger than that with poor outcomes.
Aneurysm intervention should be considered when patients over 75 years old do not suffer from sarcopenia. Temporal muscle would indicate premorbid mRS and be potentially useful to decide surgical indication and to predict outcome after aneurysm treatment in the elderly 3).
Data from the 2015 China Health and Retirement Longitudinal Study (CHARLS), a high-quality micro-level data representative of households and individuals aged 45 years and older adults in China. The study analyzed 65 indicators, including sociodemographic indicators, health-related indicators, and biochemical indicators.
3454 older adults enrolled in the CHARLS database in 2015 were included in the final analysis. A total of 997 (28.8%) had phenotypes of sarcopenia. Multivariate logistic regression analysis showed that sex, Body Mass Index (BMI), Mean Systolic Blood Pressure (MSBP), Mean Diastolic Blood Pressure (MDBP) and pain were predictive factors for sarcopenia in older adults. These factors were used to construct a nomogram model, which showed good consistency and accuracy. The AUC value of the prediction model in the training set was 0.77 (95% CI = 0.75-0.79); the AUC value in the validation set was 0.76 (95% CI = 0.73-0.79). Hosmer-Lemeshow test values were P = 0.5041 and P = 0.2668 (both P > 0.05). Calibration curves showed significant agreement between the nomogram model and actual observations. ROC and DCA showed that the nomograms had good predictive properties.
The constructed sarcopenia risk prediction model, incorporating factors such as sex, BMI, MSBP, MDBP, and pain, demonstrates promising predictive capabilities. This model offers valuable insights for clinical practitioners, aiding in early screening and targeted interventions for sarcopenia in Chinese older adults 4).
Data from the 2015 China Health and Retirement Longitudinal Study (CHARLS), a high-quality micro-level data representative of households and individuals aged 45 years and older adults in China. The study analyzed 65 indicators, including sociodemographic indicators, health-related indicators, and biochemical indicators.
3454 older adults enrolled in the CHARLS database in 2015 were included in the final analysis. A total of 997 (28.8%) had phenotypes of sarcopenia. Multivariate logistic regression analysis showed that sex, Body Mass Index (BMI), Mean Systolic Blood Pressure (MSBP), Mean Diastolic Blood Pressure (MDBP) and pain were predictive factors for sarcopenia in older adults. These factors were used to construct a nomogram model, which showed good consistency and accuracy. The AUC value of the prediction model in the training set was 0.77 (95% CI = 0.75-0.79); the AUC value in the validation set was 0.76 (95% CI = 0.73-0.79). Hosmer-Lemeshow test values were P = 0.5041 and P = 0.2668 (both P > 0.05). Calibration curves showed significant agreement between the nomogram model and actual observations. ROC and DCA showed that the nomograms had good predictive properties.
The constructed sarcopenia risk prediction model, incorporating factors such as sex, BMI, MSBP, MDBP, and pain, demonstrates promising predictive capabilities. This model offers valuable insights for clinical practitioners, aiding in early screening and targeted interventions for sarcopenia in Chinese older adults 5).