Background: Sarcopenic obesity (SO) is the coexistence of sarcopenia and obesity in an individual. The present study is designed to define the usefulness of skeletal muscle ultrasonography (US) in the definition of SO. Methods: Eighty-nine participants aged ≥65 whose body mass index (BMI, kg/m 2) was ≥30 were consecutively enrolled in an outpatient clinic of geriatric medicine. All underwent comprehensive geriatric assessment. US measurements were obtained in 6 different muscles consisting of core and limb muscles. We defined SO as the presence of low muscle function (defined by a handgrip strength < 27 kg in males and <16 kg in females) and high BMI (≥30). Results: The median age of the participants was 72 (65-85) years; 81% were female, and 35% (n = 31) had SO. Anthropometric parameters that estimate muscle mass were lower in the sarcopenic group, but estimations of muscle mass with bioelectrical impedance analysis (BIA) did not differ between groups. All US estimations of muscle mass were lower in sarcopenic obese participants, albeit not all significantly. RF muscle cross-sectional area (RF CSA) and abdominal subcutaneous fat thickness were most strongly correlated with grip strength (r = 0.477 and r = −508, respectively). Receiver operating characteristic analysis suggested that the optimum cutoff point of RF CSA for SO was ≤5.22 cm 2 , with 95.8% sensitivity and 46.7% specificity (area under the curve: 0.686). Conclusions: US evaluation of muscle mass may be more accurate than BIA-derived skeletal muscle index assessment for the diagnosis of SO.
See the Reply by https://doi.org/10.1111/jgs.15805.
BackgroundsAlzheimer's disease is frequently encountered with nutrition‐related conditions such as malnutrition, sarcopenia, frailty, overnutrition, and micronutrient abnormalities in older patients. In this study, we aimed to evaluate the prevalence of nutrition disorders and nutrition‐related conditions in the same patient group.MethodsA total of 253 older patients with Alzheimer's disease underwent comprehensive geriatric assessment, which included nutrition‐related disorders, malnutrition via the Mini Nutritional Assessment‐Short Form (MNA‐SF), frailty via the Clinical Frailty Scale (CFS), and sarcopenia was diagnosed according to European Working Group on Sarcopenia in Older People‐2 criteria.ResultsThe patients' mean age was 79.8 ± 6.5 years, and 58.1% were women. In our patients, 64.8% had malnutrition or were at risk of malnutrition; 38.3% had sarcopenia; 19.8% were prefrail; and 80.2% were frail. Malnutrition, frailty, and sarcopenia prevalence increased as the Alzheimer's disease stage progressed. Malnutrition was found to be significantly related with frailty scores via CFS (odds ratio [OR], 1.397; P = 0.0049) and muscle mass via fat‐free mass index (FFMI) (OR, 0.793; P = 0.001). In logistic regression analysis, age, MNA‐SF, and CFS were included in the model to detect the independent correlates of probable and confirmed sarcopenia. CFS was independently associated with probable and confirmed sarcopenia (OR, 1.822; P = 0.013; OR, 2.671; P = 0.001, respectively). Frailty was similarly related with FFMI (OR, 0.836; P = 0.031). Obesity was independently related with FFMI (OR, 0.688; P < 0.001).ConclusionIn conclusion, nutrition disorders and nutrition‐related conditions can present concurrently in patients with all stages of Alzheimer's disease; therefore, these frequent problems should be screened and diagnosed accordingly.
Background:The aim of this study is to identify cutoff values for muscle ultrasound (US) to be used in Global Leadership Initiative on Malnutrition (GLIM) criteria, and to define the effect of reduced muscle mass assessment on malnutrition prevalence at hospital admission.Methods: A total of 118 inpatients were enrolled in this cross-sectional study. Six different muscles were evaluated by US. Following defining thresholds for muscle US to predict low muscle mass measured by bioelectrical impedance analysis, malnutrition was diagnosed by GLIM criteria with seven approaches, including calf circumference, mid-upper arm circumference (MAC), handgrip strength (HGS), skeletal muscle index (SMI), rectus femoris (RF) muscle thickness, and cross-sectional area (CSA) in addition to without using the reduced muscle mass criterion. Results:The median age of patients was 64 (18-93) years, 55.9% were female. RF muscle thickness had moderate positive correlations with both HGS (r = 0.572) and SMI (r = 0.405). RF CSA had moderate correlation with HGS (r = 0.567) and low correlation with SMI (r = 0.389). The cutoff thresholds were 11.3 mm (area under the curve [AUC] = 0.835) and 17 mm (AUC = 0.737) for RF muscle thickness and 4 cmš (AUC = 0.937) and 7.2 cmš (AUC = 0.755) for RF CSA in females and males, respectively. Without using the reduced muscle mass criterion, malnutrition prevalence was 46.6%; otherwise, it ranged from 47.5% (using MAC) to 65.2% (using HGS). Conclusions:Muscle US may be used in GLIM criteria. However, muscle US needs a standard measurement technique and specific cutoff values in future studies.
Background Insomnia increases the incidence of falls and impairs executive function. Moreover, falls are associated with executive function impairment. The relationship between falls and executive function in patients with insomnia is not clear. The aim of this study was to evaluate relationship between falls and executive function in individuals with insomnia and a control group. Methods This study involved 122 patients (47 insomnia, 75 controls). The Mini‐Mental State Examination, Quick Mild Cognitive Impairment Screen, Trail Making Test A, clock‐drawing test, and digit span test were used to measure executive function. Semantic and working memory dual task was also performed. Fall history was recorded and the Falls Efficacy Scale – International administered. Results The median age of the patients was 71 years (range: 65–89 years), and 60.7% were women. The insomnia group scored lower on the three‐word recall than the control group (P = 0.005), but there was no difference between the groups on cognitive tests. Fall history and fear of falling were more frequent in the insomnia group (P = 0.003, P < 0.001). Semantic and working memory dual tasks were correlated with clock‐drawing test only in the insomnia group (r = −0.316, P = 0.031; r = −0.319, P = 0.029). Depression (odds ratio (OR) = 9.65, P = 0.001) and Trail Making Test A (OR = 1.025, P = 0.07) were independently associated with insomnia. Four‐metre walking speed (OR = 2.342, P = 0.025), insomnia (OR = 3.453; P = 0.028), and the semantic memory dual task (OR = 1.589; P = 0.025) were also independently associated with falls. Conclusion Our study showed that dual tasking and executive function are related to falls in patients with insomnia. Managing insomnia and assessment of executive dysfunction may have beneficial effects on preventing falls.
Objective: The Observation and Interview Based Diurnal Sleepiness Inventory (ODSI) is a valid 3-item tool used for assessment of excessive daytime sleepiness (EDS). The aim of this study was to investigate the reliability and validity of the ODSI in the Turkish language.Methods: Linguistic validation of the ODSI was performed by forward-backward translation. The Turkish version of the ODSI and the Epworth Sleepiness Scale (ESS) were administered in EDS and control groups.Results: The ODSI was tested in 106 older patients. The median age of the patients was 73 (65–89) years and 55.7% were female. The EDS group was older and more dependent on instrumental activities of daily living than the control group. The inter-rater reliability of the ODSI was high (interclass correlation coefficient [ICC]: 0.851, 95% confidence interval [CI]: 0.540–0.958, p<0.001). Test-retest reliability was also high for the total sample (ICC: 0.871, 95% CI: 0.632–0.959, p<0.001). Positive strong correlations were found with the ESS (Speraman’s rho=0.876, 95% bootstrap CI [0.813–0.918], p<0.001). ROC curve analysis showed an area under the curve of 0.968 (95% CI: 0.937–0.998), a cutoff score of ≥6, a sensitivity of 94.1%, a specificity of 87.6%, a positive predictive value of 76.55%, and a negative predictive value of 97.2%.Conclusion: Our data validate the ODSI for application in Turkish-speaking populations. The simplicity, reliability, and the apparent lack of relevant influences of cultural background on performance of the 3-item ODSI make it a valuable tool for clinical management and research.
Aim: Malnutrition is a significant issue in the geriatric population. The frequency of infections, morbidity, and mortality rates are higher in malnourished patients. The purpose of this research is to evaluate scientific articles on geriatric malnutrition using statistical methods and to evaluate the topic from a novel viewpoint. Material and Method: Statistical and bibliometric techniques were used to examine articles on geriatric malnutrition published between 1980 and 2022 in the Web of Science database. For correlation analyses, the Spearman correlation coefficient was used. To predict the number of publications in the subsequent years, a nonlinear (exponential growth model) regression analysis was performed. Trending subjects and connections were identified using keyword network visualization maps. Results: Within the search criteria, 595 publications on geriatric malnutrition were identified between 1980 and 2022. 427 of those (articles and reviews) were included in the analysis. Since 2005, the quantity of published materials on the issue has expanded dramatically and continues to rise. The most active countries were USA and Spain, the most active author was Volkert, D., and the most active journal on the subject was Clinical Nutrition. Conclusion: This research on geriatric malnutrition explores 427 publications, their origin countries, authors, and most used keywords. Geriatric malnutrition is one of the current trending research topics and seems more relevant every year in the aging world. This article may help physicians’ and scientists’ understanding of worldwide efforts on geriatric malnutrition.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.