Consequences of applying the different criteria of the EWGSOP2 guideline for sarcopenia case-finding in Spanish community-dwelling older adults

Proteomic profiling of human plasma extracellular vesicles identifies PF4 and C1R as novel biomarker in sarcopenia

BACKGROUND

Sarcopenia, the gradual and generalized loss of muscle mass and function with ageing, is one of the major health problems in older adults, given its high prevalence and substantial socioeconomic implications. Despite the extensive efforts to reach consensus on definition and diagnostic tests and cut-offs for sarcopenia, there is an urgent and unmet need for non-invasive, specific and sensitive biomarkers for the disease. Extracellular vesicles (EVs) are present in different biofluids including plasma, whose cargo reflects cellular physiology. This work analysed EV proteome in sarcopenia and robust patients in the search for differentially contained proteins that can be used to diagnose the disease.

METHODS

Plasma small EVs (sEVs) from a total of 29 robust controls (aged 73.4 ± 5.6 years; 11 men and 18 women) and 49 sarcopenic patients (aged 82.3 ± 5.4 years; 15 men and 34 women) aged 65 years and older were isolated and their cargo was analysed by proteomics. Proteins whose concentration in sEVs was different between sarcopenic and robust patients were further validated using ELISA. The concentration of these candidates was correlated to the EWGSOP2 sarcopenia tests for low muscle strength and low physical performance, and receiver operating characteristic (ROC) curve analyses were carried out to evaluate their diagnostic power, sensitivity and specificity.

RESULTS

Proteomic analysis identified 157 sEVs proteins in both sarcopenic and robust samples. Among them, 48 proteins had never been reported in the ExoCarta nor Vesiclepedia databases. Statistical analysis revealed eight proteins whose concentration was significantly different between groups: PF4 (log2 FC = 4.806), OIT3 (log2 FC = -1.161), MMRN1 (log2 FC = -1.982), MASP1 (log2 FC = -0.627), C1R (log2 FC = 1.830), SVEP1 (log2 FC = 1.295), VCAN (FC = 0.937) and SPTB (log2 FC = 1.243). Among them, platelet factor 4 (PF4) showed the lowest concentration while Complement C1r subcomponent (C1R) increased the most in sarcopenic patients, being these results confirmed by ELISA (P = 1.07E-09 and P = 0.001287, respectively). The concentrations of candidate proteins significantly correlated with EWGSOP2 tests currently used. ROC curve analysis showed an area under the curve of 0.8921 and 0.7476 for PF4 and C1R, respectively. Choosing the optimal for PF4, 80% sensitivity and 85.71% specificity was reached while the optimal cut-off value of C1R would allow sarcopenia diagnosis with 75% sensitivity and 66.67% specificity.

CONCLUSIONS

Our results support the determination of EV PF4 and C1R as plasma diagnostic biomarkers in sarcopenia and open the door to investigate the role of the content of these vesicles in the pathogeny of the disease.

Comparing Sarcopenia Definitions and Muscle Power Reduction: Associations with Health Outcomes in Spanish Community-Dwelling Older Adults

Objectives: To analyze the associations between the different operational definitions of sarcopenia published in the last decade and reduced muscle power with a set of adverse health-related outcomes, such as comorbidities, depression, polypharmacy, self-perceived health, educational attainment, socioeconomic status, falls, and hospitalizations in Spanish community-dwelling older adults. Methods: A total of 686 community-dwelling older adults (median age: 72; women: 59.2%; physically active: 84%) were included in this cross-sectional analysis (ClinicalTrials.gov: NCT05148351). Sarcopenia was assessed using the FNIH, EWGSOP2, AWGS, and SDOC algorithms. Reduced muscle power was defined as the lowest sex-specific tertile and measured during the rising phase of the sit-to-stand test using a validated mobile application. Unadjusted and adjusted logistic regressions by potential confounders were performed to identify the association between sarcopenia and reduced muscle power with health-related outcomes. Results: Sarcopenia prevalence was 3.4%, 3.8%, 12.4%, and 21.3% according to the SDOC, FNIH, EWGSOP2, and AWGS, respectively. Among these definitions, moderate and large associations with health-related outcomes were observed for EWGSOP2 and SDOC, respectively, but few associations were found for FNIH and AWGS criteria. Reduced muscle power was associated more frequently and moderately with health-related outcomes compared to sarcopenia definitions. These associations remained constant after adjusting for confounders. Conclusions: The prevalence and impact of sarcopenia varied depending on the definitions used. Among the sarcopenia definitions, the SDOC exhibited the strongest associations, while reduced muscle power was the variable most frequently associated with health-related outcomes compared to any of the four sarcopenia definitions in well-functioning and physically active community-dwelling older adults.

Risk of secondary sarcopenia in Europeans with fibromyalgia according to the EWGSOP2 guidelines: systematic review and meta-analysis

INTRODUCTION

Fibromyalgia is characterized by chronic widespread pain accompanied by reduced levels of physical activity and associated comorbidities such as overweight and obesity which have been associated to sarcopenia development. The aim of this systematic review is to ascertain whether Europeans with fibromyalgia show a reduction in sarcopenia determinants compared to apparently-healthy controls and to determine the risk of sarcopenia and its possible risk factors (PROSPERO: CRD42023439839).

EVIDENCE ACQUISITION

Systematic searches were conducted on six databases (Academic-Search-Ultimate, CENTRAL, PubMed, SciELO, WOS-Core Collection, and ClinicalTrials.gov last-search February-2024) looking for original studies developed in European countries which assessed any of the sarcopenia determinants proposed by the EWGSOP2-guidelines (handgrip strength, five sit-to-stand, appendicular skeletal mass [ASM], skeletal muscle index [SMI]) and included fibromyalgia and healthy-control individuals. Studies mixing fibromyalgia with other diagnoses were excluded. Random-effects meta-analyses and meta-regressions were used to analyze possible differences and associated risk factors. The risk of bias was assessed using the Cochrane-Rob tool and the Quality Assessment Tool for Observational Studies, and the certainty of the evidence using GRADE-approach.

EVIDENCE SYNTHESIS

A total of 25 studies (6393 individuals; 97% women; 20-65 years) were included. Fibromyalgia individuals showed reduced muscle strength ([handgrip] SMD: -1.16 [-1.29, -1.03]; high-certainty; [five sit-to-stand] not-assessed) and muscle quantity ([ASM] mean-difference: -0.83 kg [-1.41, -0.37]; [SMI] mean-difference: -0.26 kg/m2 [-0.41, -0.10]; both low-certainty) compared to healthy-controls. Fibromyalgia individuals had nine-times greater risk for probable sarcopenia (OR: 9.23 [6.85, 12.45]; high-certainty), but not for confirmed sarcopenia ([ASM] OR: 0.91 [0.49, 1.67]; [SMI] OR: 0.67 [0.19, 2.33]; both low-certainty) according to the EWGSOP2 cut-off points. Reduced muscle strength was strongly associated to fibromyalgia-severity (β=-0.953 [-0.069, -0.038]). Studies were rated as high-risk of bias overall because did not account for some potential confounders (physical activity, sedentary time, Body Mass Index) which could influence the estimated effect.

CONCLUSIONS

Europeans with fibromyalgia have a large reduction in muscle strength and may have a reduction in muscle quantity. The risk of probable sarcopenia according to the EWGSOP2 cut-off points was nine-times higher, but may have no difference in risk of reduced muscle quantity relative to healthy-controls. Muscle strength was strongly associated to disease severity.

Validity of a video-analysis-based app to detect prefrailty or frailty plus sarcopenia syndromes in community-dwelling older adults: Diagnostic accuracy study

Objectives

Sarcopenia and frailty have been associated with an increased risk of suffering health-related adverse events but the combination of both conditions results in worse health-related outcomes than either condition alone. Since both syndromes are reversible states, their early detection is fundamental. This study aims to validate a video analysis-based App to detect the presence of frailty or prefrailty plus sarcopenia syndromes and to analyze its construct validity with health-related risk factors.

Methods

A total of 686 community-dwelling older adults (median-age: 72, 59% female) were enrolled. Muscle power generated during a sit-to-stand test using the App and calf circumference were considered the index test. The reference standards were the EWGSOP2 criteria (five-chair stand test plus appendicular skeletal mass or skeletal muscle index) and Fried's frailty phenotype. Area under the curve (AUC), sensitivity, specificity, positive and negative predictive values (PPV and NPV) were calculated.

Results

The prevalence of both syndromes varied from 2.9% to 7.2% depending on the diagnostic criteria used for sarcopenia assessment. Excellent-to-outstanding AUC values were observed (range 0.80-0.92). Sensitivity and specificity ranged from 75% to 100% and 81.7% to 87.2%, respectively. PPV and NPV ranged from 12.1% to 37.5% and 97.9% to 100%, respectively. Individuals diagnosed by the App showed an increased risk of polypharmacy, depression, comorbidities, falls, hospitalization, low socioeconomical and educational levels, and smoking and poor self-perceived health compared to their healthy counterparts.

Conclusions

This App seems to be reliable to detect the simultaneous presence of both syndromes in community-dwelling older adults. Individuals diagnosed by the App showed more odds to have health-related risk factors.

Sit-to-Stand Video Analysis-Based App for Diagnosing Sarcopenia and Its Relationship With Health-Related Risk Factors and Frailty in Community-Dwelling Older Adults: Diagnostic Accuracy Study

BACKGROUND

Probable sarcopenia is determined by a reduction in muscle strength assessed with the handgrip strength test or 5 times sit-to-stand test, and it is confirmed with a reduction in muscle quantity determined by dual-energy X-ray absorptiometry or bioelectrical impedance analysis. However, these parameters are not implemented in clinical practice mainly due to a lack of equipment and time constraints. Nowadays, the technical innovations incorporated in most smartphone devices, such as high-speed video cameras, provide the opportunity to develop specific smartphone apps for measuring kinematic parameters related with sarcopenia during a simple sit-to-stand transition.

OBJECTIVE

We aimed to create and validate a sit-to-stand video analysis-based app for diagnosing sarcopenia in community-dwelling older adults and to analyze its construct validity with health-related risk factors and frailty.

METHODS

A total of 686 community-dwelling older adults (median age: 72 years; 59.2% [406/686] female) were recruited from elderly social centers. The index test was a sit-to-stand video analysis-based app using muscle power and calf circumference as proxies of muscle strength and muscle quantity, respectively. The reference standard was obtained by different combinations of muscle strength (handgrip strength or 5 times sit-to-stand test result) and muscle quantity (appendicular skeletal mass or skeletal muscle index) as recommended by the European Working Group on Sarcopenia in Older People-2 (EWGSOP2). Sensitivity, specificity, positive and negative predictive values, and area under the curve (AUC) of the receiver operating characteristic curve were calculated to determine the diagnostic accuracy of the app. Construct validity was evaluated using logistic regression to identify the risks associated with health-related outcomes and frailty (Fried phenotype) among those individuals who were classified as having sarcopenia by the index test.

RESULTS

Sarcopenia prevalence varied from 2% to 11% according to the different combinations proposed by the EWGSOP2 guideline. Sensitivity, specificity, and AUC were 70%-83.3%, 77%-94.9%, and 80.5%-87.1%, respectively, depending on the diagnostic criteria used. Likewise, positive and negative predictive values were 10.6%-43.6% and 92.2%-99.4%, respectively. These results proved that the app was reliable to rule out the disease. Moreover, those individuals who were diagnosed with sarcopenia according to the index test showed more odds of having health-related adverse outcomes and frailty compared to their respective counterparts, regardless of the definition proposed by the EWGSOP2.

CONCLUSIONS

The app showed good diagnostic performance for detecting sarcopenia in well-functioning Spanish community-dwelling older adults. Individuals with sarcopenia diagnosed by the app showed more odds of having health-related risk factors and frailty compared to their respective counterparts. These results highlight the potential use of this app in clinical settings.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05148351; https://clinicaltrials.gov/study/NCT05148351.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.3390/s22166010.

Machine Learning Applications in Sarcopenia Detection and Management: A Comprehensive Survey

This extensive review examines sarcopenia, a condition characterized by a loss of muscle mass, stamina, and physical performance, with a particular emphasis on its detection and management using contemporary technologies. It highlights the lack of global agreement or standardization regarding the definition of sarcopenia and the various techniques used to measure muscle mass, stamina, and physical performance. The distinctive criteria employed by the European Working Group on Sarcopenia in Older People (EWGSOP) and the Asian Working Group for Sarcopenia (AWGSOP) for diagnosing sarcopenia are examined, emphasizing potential obstacles in comparing research results across studies. The paper delves into the use of machine learning techniques in sarcopenia detection and diagnosis, noting challenges such as data accessibility, data imbalance, and feature selection. It suggests that wearable devices, like activity trackers and smartwatches, could offer valuable insights into sarcopenia progression and aid individuals in monitoring and managing their condition. Additionally, the paper investigates the potential of blockchain technology and edge computing in healthcare data storage, discussing models and systems that leverage these technologies to secure patient data privacy and enhance personal health information management. However, it acknowledges the limitations of these models and systems, including inefficiencies in handling large volumes of medical data and the lack of dynamic selection capability. In conclusion, the paper provides a comprehensive summary of current sarcopenia research, emphasizing the potential of modern technologies in enhancing the detection and management of the condition while also highlighting the need for further research to address challenges in standardization, data management, and effective technology use.

Concurrent and discriminant validity and reliability of an Android App to assess time, velocity and power during sit-to-stand test in community-dwelling older adults

INTRODUCTION

Nowadays, smartphones are equipped with the most sophisticated hardware which provides the opportunity to develop specific smartphone apps to analyze kinetic and kinematic parameters during sit-to-stand test in a clinical setting. The aims were to ascertain whether a new Android video-analysis based-App is comparable to the previously validated Apple-App for measuring time, velocity and power during sit-to-stand test, to determine its reliability and discriminant validity.

METHODS

One-hundred sixty-one older adults (61-86 years) were recruited from an elderly social center. Sit-to-stand variables were simultaneously recorded through the Android and Apple-App. Their validity and inter-rater, intra-rater, and test-retest reliability was tested using an intraclass correlation coefficient (ICC_2-1). Low gait speed (< 1.0 m/s), low physical performance (Short Physical Performance Battery < 10 points), and sarcopenia (EWGSOP2 guideline) were used to determine discriminant validity which was reported as the area under the curves (AUC) and their effect sizes (Hedges' g) for independent sample t-test.

RESULTS

Excellent reproducibility (ICC_2-1 > 0.85) and strong agreement (ICC_2-1 > 0.90) between operating systems for sit-to-stand variables derived from the App was found. Older adults classified as sarcopenic (11.2%), low physical performance (15.5%), or reduced gait speed (14.3%) showed worse sit-to-stand time, velocity and power with large effect sizes (Hedges' g: > 0.8) compared to their respective counterpart. These variables showed the acceptable-to-excellent ability to identify low gait speed, low physical performance, and sarcopenic older adults (AUC-range: 0.73-0.82).

CONCLUSION

The new Sit-to-Stand App running on the Android operating system is comparable to the previously validated Apple App. Excellent reproducibility and acceptable-to-excellent discriminant validity were found.