Bioelectrical impedance vector analysis as an auxiliary method in diagnosing of sarcopenia among hospitalized older patients – a preliminary report

Accuracy and prognostic ability of the SARC-F questionnaire and Ishii's score in the screening of sarcopenia in geriatric inpatients

Sarcopenia remains poorly managed in clinical practice due to the lack of simple and accurate screening tools. This study aimed to identify the cutoff values of the SARC-F questionnaire and Ishii's score using the variables age, grip strength, and calf circumference in older inpatients in China to compare the accuracy of the two methods and to explore their predictive ability for adverse outcomes (rehospitalization, falls, fracture, and death). Hospitalized patients (n=138) aged ≥60 years were included. The accuracy of the two tools was evaluated using the reference diagnosis recommended by the Asian Working Group on Sarcopenia (assessing patients with measurements of muscle mass, handgrip strength, and usual gait speed). Follow-up data were obtained by telephone and clinical visits combined with the inpatient medical record system after discharge for at least one year. The results showed that the SARC-F score reached the highest Youden's index when a score of 3 was set as the cutoff value. Ishii's score presented a higher accuracy than SARC-F (area under the receiver operating curve: 0.78 vs 0.64, P=0.01). The Kaplan-Meier survival analysis demonstrated a higher cumulative incidence of rehospitalization in sarcopenic individuals compared to non-sarcopenic individuals according to SARC-F (log-rank test, P<0.001). Cox analysis revealed that SARC-F was an independent risk factor for rehospitalization (adjusted hazard ratio: 4.23, 95%CI: 2.12-9.79, P<0.001). The SARC-F and Ishii's scores might facilitate the early detection of sarcopenia and help identify older adults at risk for adverse outcomes in clinical practice.

Body composition, nutritional status, and endothelial function in physically active men without metabolic syndrome--a 25 year cohort study

BACKGROUND

The purpose of this analysis was to investigate the relationship between body composition, metabolic parameters and endothelial function among physically active healthy middle-aged and older men.

METHODS

Out of 101 asymptomatic men prospectively tracked for traditional cardiovascular risk factors (mean observation period 25.1 years), 55 metabolically healthy individuals who maintained stable leisure time physical activity (LTPA) level throughout the observation and agreed to participate in the body composition assessment were recruited (mean age 60.3 ± 9.9 years). Body composition and raw bioelectrical parameters were measured with bioelectrical impedance analysis (BIA). Microvascular endothelial function was evaluated by means of the reactive hyperemia index (RHI) using Endo-PAT2000 system.

RESULTS

Strong correlations were observed between lifetime physical activity (PA), aerobic fitness and most of analyzed body composition parameters. The strongest inverse correlation was found for fat mass (p < 0.01) while positive relationship for fat-free mass (p < 0.01), total body water (p < 0.05 for current aerobic capacity and p < 0.01 for historical PA), body cell mass (p < 0.001), muscle mass (p < 0.001), calcium and potassium (p < 0.01 and p < 0.001 for current aerobic capacity and p < 0.001 and p < 0.01 for historical PA, respectively) and glycogen mass (p < 0.001). Among metabolic parameters, HDL cholesterol (HDL-C) and uric acid were significantly associated with most body composition indicators. Regarding endothelial function, a negative correlation was found for RHI and body mass (p < 0.05) while positive relationship for RHI and body cell mass (p < 0.05), calcium (p < 0.05) and potassium mass (p < 0.05). Impaired endothelial function was observed among 8 subjects. Among bioelectrical parameters, impedance (Z) and resistance (R) normalized for subjects' height were negatively related with body mass, body mass index (BMI) and waist circumference (p < 0.001); while reactance (Xc) normalized for patients' height was negatively related with body mass (p < 0.05). The mean phase angle value was relatively high (8.83 ± 1.22) what reflects a good level of cellularity and cell function. Phase angle was positively related with body mass and BMI (p < 0.05).

CONCLUSIONS

Both fat mass and muscle mass components are important predictors of metabolic profile. Maintaining regular high PA level and metabolically healthy status through young and middle adulthood may have beneficial influence on body composition parameters and may prevent age-related decrease of fat-free mass and endothelial dysfunction.