Dataset Information

Cut-offs for calf circumference as a screening tool for low muscle mass: WASEDA'S Health Study.

ABSTRACT:

Aim

To re-evaluate the suitability of calf circumference as a surrogate marker of low muscle mass measured by both bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA). We also examined the effects of obesity and age on low muscle mass screening using calf circumference.

Methods

In total, 1239 adults participated in this cross-sectional study. We measured the maximum calf circumference in a standing position and appendicular skeletal muscle mass (ASM) using BIA and DXA. We defined low muscle mass based on the Asian Working Group for Sarcopenia 2019 consensus.

Results

Calf circumference was positively correlated with BIA-measured ASM/height² (men: r = 0.81, women: r = 0.73) and DXA-measured ASM/height² (men: r = 0.78, women: r = 0.76). In the subgroup analyses by obesity and age, calf circumference was also positively correlated with ASM/height² . The optimal calf circumference cut-offs for low muscle mass screening measured by BIA and DXA were 35 cm (sensitivity 91%, specificity 84%) and 36 cm (sensitivity 82%, specificity 80%) for men, and 33 cm (sensitivity 82%, specificity 84%) and 34 cm (sensitivity 85%, specificity 72%) for women, respectively.

Conclusions

Calf circumference is positively correlated with BIA- and DXA-measured muscle mass regardless of obesity and age and is a simple and accurate surrogate marker of muscle mass for diagnosing sarcopenia. Geriatr Gerontol Int 2020; 20: 943-950.

SUBMITTER: Kawakami R

PROVIDER: S-EPMC7590124 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Publications

Cut-offs for calf circumference as a screening tool for low muscle mass: WASEDA'S Health Study.

Kawakami Ryoko R Miyachi Motohiko M Sawada Susumu S SS Torii Suguru S Midorikawa Taishi T Tanisawa Kumpei K Ito Tomoko T Usui Chiyoko C Ishii Kaori K Suzuki Katsuhiko K Sakamoto Shizuo S Higuchi Mitsuru M Muraoka Isao I Oka Koichiro K

Geriatrics & gerontology international 20200904 10

<h4>Aim</h4>To re-evaluate the suitability of calf circumference as a surrogate marker of low muscle mass measured by both bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA). We also examined the effects of obesity and age on low muscle mass screening using calf circumference.<h4>Methods</h4>In total, 1239 adults participated in this cross-sectional study. We measured the maximum calf circumference in a standing position and appendicular skeletal muscle mass (ASM) ...[more]

PMID: 32886830

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Project description:BackgroundThe correlation between calf circumference（CC）and sarcopenia has been demonstrated, but the correlation between calf maximum muscle circumference (CMMC) measured by ultrasound and sarcopenia has not been reported. We aims to construct a predictive model for sarcopenia based on CMMC in hospitalized older patients.MethodsThis was a retrospective controlled study of patients > 60 years of age hospitalized in the geriatric department of Hunan Provincial People's Hospital. The patients were thoroughly evaluated by questionnaires, laboratory, and ultrasound examinations, including measuring muscle thickness and calf muscle maximum circumference using ultrasound. Patients were categorized into sarcopenia and non-sarcopenia groups according to the consensus for diagnosis of sarcopenia recommended by the Asian Working Group on Sarcopenia 2019 (AWGS2). Independent predictors of sarcopenia were identified by univariate and multivariate logistic regression analyses, and a predictive model was developed and simplified. The prediction performance of the models was assessed using sensitivity, specificity, and area under the curve (AUC) and compared with independent predictors.ResultsWe found that patient age, albumin level (ALB), brachioradialis muscle thickness (BRMT), gastrocnemius lateral head muscle thickness (Glh MT), and calf maximum muscle circumference (CMMC) were independent predictors of sarcopenia in hospitalized older patients. The prediction model was established and simplified to Logistic P = -4.5 + 1.4 × age + 1.3 × ALB + 1.6 × BR MT + 3.7 × CMMC + 1.8 × Glh MT, and the best cut-off value of the model was 0.485. The sensitivity, specificity, and AUC of the model were 0.884 (0.807-0.962), 0.837 (0.762-0.911), and 0.927 (0.890-0.963), respectively. The kappa coefficient between this model and the diagnostic criteria recommended by AWGS2 was 0.709.ConclusionWe constructed a sarcopenia prediction model with five variables: age, ALB level, BR MT, Glh MT, and CMMC. The model could quickly predict sarcopenia in older hospitalized patients.

Project description:BackgroundPatients with epilepsy (PwE) have an increased risk of active and lifetime depression. Two in 10 patients experience depression. Lack of trained psychiatric staff in low- and middle-income countries (LMIC) creates a need for screening tools that enable detection of depression in PwE. We describe the translation, validity and reliability assessment of the Patient Health Questionnaire-9 (PHQ-9) as a screening tool for depression among PwE in Rwanda.MethodPHQ-9 was translated to Kinyarwanda using translation-back translation and validated by a discussion group. For validation, PwE of ≥15 years of age were administered the PHQ-9 and Hamilton Depression Rating Scale (HDRS) by trained psychiatry staff at Visit 1. A random sample of 20% repeated PHQ-9 and HDRS after 14 days to assess temporal stability and intra-rater reliability. Internal structure, reliability and external validity were assessed using confirmatory factor analysis, reliability coefficients and HDRS-correlation, respectively. Maximal Youden's index was considered for cut-offs.ResultsFour hundred and thirty-four PwE, mean age 30.5 years (SD ±13.3), were included of whom 33.6%, 37.9%, 13.4%, and 15.1% had no, mild, moderate and severe depression, respectively. PHQ-9 performed well on a one-factor model (unidimensional model), with factor loadings of 0.63-0.86. Reliability coefficients above 0.80 indicated strong internal consistency. Good temporal stability was observed (0.79 [95% CI: 0.68-0.87]). A strong correlation (R = 0.66, p = 0.01) between PHQ-9 and HDRS summed scores demonstrated robust external validity. The optimal cut-off for the PHQ-9 was similar (≥5) for mild and moderate depression and ≥7 for severe depression.ConclusionPHQ-9 validation in Kinyarwanda creates the capacity to screen PwE in Rwanda at scores of ≥5 for mild or moderate and ≥7 for severe depression. The availability of validated tools for screening and diagnosis for depression is a forward step for holistic care in a resource-limited environment.

Project description:BackgroundStudies have reported an increase in the prevalence of depression during the COVID-19 pandemic. The accuracy of screening tools may change with the prevalence and distribution of a disease in a population or sample: the "Spectrum Effect".MethodsFirst, we selected commonly used screening tools and developed search strategies for the inclusion of original studies during the pandemic. Second, we searched PsycINFO, EMBASE, and MEDLINE from March 2020 to September 2022 to obtain original studies that investigated the accuracy of depression screening tools during the pandemic. We then searched these databases to identify meta-analyses summarizing the accuracy of these tools conducted before the pandemic and compared the optimal cut-offs for depression screening tools during the pandemic with those before.ResultFour original studies evaluating the optimal cut-offs for four screening tools (Beck Depression Inventory [BDI-II], Hospital Anxiety and Depression Scale-Depression [HADS-D], Patient Health Questionnaire-9 [PHQ-9], and Geriatric Depression Scale-4 [GDS-4]) were published during the pandemic. Four meta-analyses summarizing these tools before the pandemic. We found that the optimal cut-off of BDI-II was 14 during the pandemic (23.8% depression prevalence, screening patients with Type 2 diabetes) and 14.5 before the pandemic (17.6% depression prevalence, screening psychiatric, primary care, and healthy populations); HADS-D was 10 during the pandemic (23.8% depression prevalence, screening patients with type 2 diabetes) and 7 before the pandemic (15.0% depression prevalence, screening medically ill patients); PHQ-9 was 11 during the pandemic (14.5% depression prevalence, screening university students) and 8 before the pandemic (10.9% depression prevalence, screening the unrestricted population), and GDS-4 was 1.8 during the pandemic (29.0% depression prevalence, screening adults seen in a memory clinic setting) and 3 before the pandemic (18.5% depression prevalence, screening older adults).ConclusionThe optimal cut-off for different screening tools may be sensitive to changes in study populations and reference standards. And potential spectrum effects that should be considered in post-COVID time which aiming to improve diagnostic accuracy.

Dataset Information

Cut-offs for calf circumference as a screening tool for low muscle mass: WASEDA'S Health Study.

Aim

Methods

Results

Conclusions

Publications

Cut-offs for calf circumference as a screening tool for low muscle mass: WASEDA'S Health Study.

Similar Datasets

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