BackgroundThe aim of this study is to assess the prevalence of sarcopenia and investigate the associations between sarcopenia and long‐term mortality and readmission in a population of elderly inpatients in acute care wards.MethodsWe conducted a prospective observational study in the acute care wards of a teaching hospital in western China. The muscle mass was estimated according to a previously validated anthropometric equation. Handgrip strength was measured with a handheld dynamometer, and physical performance was measured via a 4 m walking test. Sarcopenia was defined according to the recommended diagnostic algorithm of the Asia Working Group for Sarcopenia. The survival status and readmission information were obtained via telephone interviews at 12, 24, and 36 months during the 3 year follow‐up period following the baseline investigation.ResultsTwo hundred and eighty‐eight participants (mean age: 81.1 ± 6.6 years) were included. Forty‐nine participants (17.0%) were identified as having sarcopenia. This condition was similar in men and women (16.9% vs. 17.5%, respectively, P = 0.915). During the 3 year follow‐up period, 49 men (22.7%) and 9 women (16.4%) died (P = 0.307). The mortality of sarcopenic participants was significantly increased compared with non‐sarcopenic participants (40.8% vs. 17.1%, respectively, P < 0.001). After adjusting for age, sex and other confounders, sarcopenia was an independent predictor of 3 year mortality (adjusted hazard ratio: 2.49; 95% confidential interval: 1.25–4.95) and readmission (adjusted hazard ratio: 1.81; 95% confidential interval: 1.17–2.80).ConclusionsSarcopenia, which is evaluated by a combination of anthropometric measures, gait speed, and handgrip strength, is valuable to predict hospital readmission and long‐term mortality in elderly patients in acute care wards.

A new term, malnutrition-sarcopenia syndrome (MSS), was recently coined to describe the clinical presentation of both malnutrition and sarcopenia. The aim of this study was to investigate the association between MSS and long-term mortality in older inpatients. We conducted a prospective study in acute geriatric wards of two local hospitals in China. Muscle mass and malnutrition were estimated by anthropometric measures and the Mini Nutritional Assessment (MNA). Of the 453 participants, 14 (3.1%) had sarcopenia with normal nutrition, 139 (30.7%) had malnutrition risk without sarcopenia, 48 (10.6%) had malnutrition risk with sarcopenia, 25 (5.5%) had malnutrition without sarcopenia, and 22 (4.9%) had MSS at baseline. Compared with non-sarcopenic subjects with normal nutrition, subjects with MSS and subjects with malnutrition risk and sarcopenia were more than four times more likely to die (hazard ratio [HR], 4.78; 95% confidence interval [CI], 2.09–10.97; and HR, 4.25; 95% CI, 2.22–8.12, respectively); non-sarcopenic subjects with malnutrition risk were more than two times more likely to die (HR, 2.41; 95% CI, 1.32–4.39). In conclusion, MSS may serve as a prognostic factor in the management of hospitalized older patients.

Both sleep disorders and sarcopenia are common among older adults. However, little is known about the relationship between these 2 conditions.This study aimed to investigate the possible association between sleep duration and sarcopenia in a population of Chinese community-dwelling older adults.Community-dwelling older adults aged 60 years or older were recruited. Self-reported sleep duration, anthropometric data, gait speed, and handgrip strength were collected by face-to-face interviews. Sarcopenia was defined according to the recommended algorithm of the Asian Working Group for Sarcopenia (AWGS).We included 607 participants aged 70.6 ± 6.6 years (range, 60–90 years) in the analyses. The prevalence of sarcopenia in the whole study population was 18.5%. In women, the prevalence of sarcopenia was significantly higher in the short sleep duration group (< 6 hours) and long sleep duration group (>8 hours) compared with women in the normal sleep duration group (6–8 hours; 27.5%, 22.2% and 13.9%, respectively; P = .014). Similar results were found in men; however, the differences between groups were not statistically significant (18.5%, 20.6%, and 13.0%, respectively; P = .356). After adjustments for the potential confounding factors, older women having short sleep duration (OR: 4.34; 95% CI: 1.74–10.85) or having long sleep duration (OR: 2.50; 95% CI: 1.05–6.99) had greater risk of sarcopenia compared with women having normal sleep duration. With comparison to men with normal sleep duration, the adjusted OR for sarcopenia was 2.12 (0.96–8.39) in the short sleep duration group and 2.25 (0.88–6.87) in the long sleep duration group, respectively.A U-shape relationship between self-reported sleep duration and sarcopenia was identified in a population of Chinese community-dwelling older adults, especially in women.

To investigate the association of the sarcopenia index (SI, serum creatinine value/cystatin C value × 100) with 3-year mortality and readmission among older inpatients, we reanalyzed a prospective study in the geriatric ward of a teaching hospital in western China. Older inpatients aged ≥ 60 years with normal kidney function were included. Survival status and readmission information were assessed annually during the 3-year follow-up. We applied Cox regression models to calculate the hazard ratio (HR) and 95% confidence intervals (CIs) of sarcopenia for predicting mortality and readmission. We included 248 participants (mean age: 81.2 ± 6.6 years). During the follow-up, 57 participants (23.9%) died, whereas 179 participants (75.2%) were readmitted at least one time. The SI was positively correlated with body mass index (BMI) (r = 0.214, p = 0.001), calf circumference (CC) (r = 0.253, p < 0.001), handgrip strength (r = 0.244, p < 0.001), and gait speed (r = 0.221, p < 0.001). A higher SI was independently associated with a lower risk of 3-year all-cause mortality after adjusting for potential confounders (HR per 1-SD = 0.80, 95% CI: 0.63-0.97). The SI was not significantly associated with readmission (HR per 1-SD = 0.97, 95% CI: 0.77-1.25). In conclusion, the SI is associated with 3-year all-cause mortality but not readmission in a study population of hospitalized older patients.

No abstract

The European Society of Clinical Nutrition and Metabolism (ESPEN) recently published new diagnostic criteria for malnutrition. The aim of this study was to evaluate whether malnutrition by the new ESPEN diagnostic criteria can predict long-term mortality in elderly inpatients. We conducted a prospective study in the acute geriatric wards. Malnutrition was defined according to the new ESPEN criteria and the Mini Nutritional Assessment (MNA), respectively. The survival status was determined by telephone interviews at 3-years. A total of 437 elderly adults were included. According to the new ESPEN criteria, 66 participants (15.1%) were malnourished. According to the MNA, 45 participants (10.3%) were identified as malnourished. The 3-year all-cause mortality was 41.7% in participants with malnutrition defined by the ESPEN criteria and 15.3% in participants without malnutrition (p < 0.001). After adjusting for relevant confounders, malnutrition defined by the ESPEN criteria was a significant predictor of 3-year all-cause mortality (hazard ratio [HR] 2.98, 95% confidence interval [CI] 1.87–4.86). However, malnutrition defined by the MNA was not a significant predictor of 3-year all-cause mortality (HR 1.67, 95% CI 0.89–2.31). In conclusion, the new ESPEN diagnostic criteria for malnutrition are reliable in predicting 3-year all-cause mortality among elderly inpatients.

Source localization by matched-field processing (MFP) can be accelerated by building a database of Green's functions which however requires a bulk-storage memory. According to the sparsity of the source locations in the search grids of MFP, compressed sensing inspires an approach to reduce the database by introducing a sensing matrix to compress the database. Compressed sensing is further used to estimate the source locations with higher resolution by solving the 𝑙1 −norm optimization problem of the compressed Green's function and the data received by a vertical/horizontal line array. The method is validated by simulation and is verified with the experimental data.

No abstract