New Approach to Sarcopenia Diagnosis: Physical Test for Sarcopenia Diagnosis and Its Comparison with Other Validated Tests: cross-sectional study

New Approach to Sarcopenia Diagnosis: Physical Test for Sarcopenia Diagnosis and Its Comparison with Other Validated Tests: cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article New Approach to Sarcopenia Diagnosis: Physical Test for Sarcopenia Diagnosis and Its Comparison with Other Validated Tests: cross-sectional study Blanca Pedauyé-Rueda, José Luis Maté-Muñoz, Juan Hernández-Lougedo, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6473225/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Sarcopenia is a disease characterized by the progressive loss of muscle mass and strength associated with aging. There are marked differences in sarcopenia prevalence depending on the diagnostic algorithm used. It has been demonstrated that muscle power is the most relevant predictor for determining functional limitations in older adults. The objectives of this study were to evaluate the performance of the SARC-Test for sarcopenia diagnosis and analyze its correlation with other validated tests. Methods A cross-sectional analysis was conducted on a population residing in elderly care centers. All physical tests included in the diagnostic algorithm developed by EWGSOP2 were performed. Additionally, the SARC-Test was conducted, measuring the speed at which the subject stood up from a chair. Physiological variables such as heart rate (HR), systolic blood pressure (SBP), and oxygen saturation (SpO2) were also monitored. Results The sarcopenia group showed significantly lower physical performance than the non-sarcopenia group in all tests. At a physiological level, no significant differences were found between groups in the 5-STST, Handgrip, and TUG. Additionally, the SARC-Test showed a strong correlation with Handgrip (r = 0.800), 5-STST (r=-0.719) and TUG (r=-0.523), and a moderate correlation with Gait Speed (r=-0.438) in sarcopenia group. Conclusions The SARC-Test could be a safe, accurate, and low-impact tool for sarcopenia assessment. sarcopenia diagnosis validation SARC-Test velocity chair test Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Sarcopenia is a condition characterized by the progressive loss of muscle mass and strength associated with aging [ 1 ]. However, the decline in muscle strength occurs at a faster rate than the reduction in muscle mass in older individuals [ 2 ]. In 2016, sarcopenia was officially recognized as a disease and included in the International Classification of Diseases (ICD) under the ICD-10-CM code M62.84 [ 3 ]. This condition is associated with multiple adverse health outcomes, including disability and functional decline [ 4 ], an increased risk of falls [ 5 ], and higher mortality rates [ 6 ]. These clinical consequences lead to a significant increase in healthcare costs. In 2014, individuals diagnosed with sarcopenia generated an additional annual healthcare expenditure of approximately $ 2,315.7 per person compared to those without the condition [ 7 ]. The most commonly used diagnostic algorithms for sarcopenia have been developed by the European Working Group on Sarcopenia in Older People (EWGSOP) [ 8 ], the Asian Working Group for Sarcopenia (AWGS) [ 9 ], and the Foundation for the National Institutes of Health (FNIH) [ 10 ]. Additionally, other diagnostic approaches have been proposed by the International Working Group on Sarcopenia (IWGS) [ 11 ] and the Sarcopenia Definitions and Outcomes Consortium (SDOC) [ 12 ]. Each of these algorithms incorporates different functional tests, leading to variations in diagnostic procedures, as well as the need for specific equipment and time for implementation. One of the main reasons for discrepancies in sarcopenia prevalence is the heterogeneity in diagnostic tests, established cutoff points, and the equipment used to depend on the applied algorithm [ 13 ]. In scientific literature, sarcopenia prevalence varies widely, ranging from 9.9–40.4%, with an increasing trend as age progresses [ 14 ]. These differences can be attributed to the use of different diagnostic algorithms and variability in tests assessing muscle strength, such as the 5-Sit-To-Stand Test (5-STST) and handgrip dynamometry [ 15 , 16 ]. Two studies using the EWGSOP algorithm reported different prevalence rates depending on the test used to assess muscle strength: in one study, prevalence was 3.1% when applying the 5-STST [ 17 ], whereas another study found a 3% higher prevalence when using handgrip dynamometry [ 18 ]. Muscle power has been identified as the most relevant predictor of functional limitations in older adults [ 19 ]. Various studies have employed equations incorporating variables such as leg length, chair height, and execution time to estimate muscle power. However, these methods have not been validated against reference instruments [ 20 , 21 ]. Additionally, equations have been developed to estimate power as a means of providing cost-effective and easily applicable tools for assessing sarcopenia and functional capacity in geriatric populations. Nevertheless, these equations have not yet replaced previously validated methods [ 22 ]. Other methodologies for assessing muscle strength include the One-Repetition Maximum (1RM) test, the Countermovement Jump (CMJ), and the maximum number of repetitions with a fixed load test. However, their application in older adults is limited due to their high physical demands, induced fatigue, and potential physiological alterations [ 23 ]. Consequently, these methods have primarily been restricted to sports performance assessment [ 24 ]. Given that sarcopenia is closely linked to fatigue and frailty associated with aging, it is essential to develop precise, accessible, and low-impact physiological assessment tools suitable for this population. Therefore, the objectives of this study were to evaluate the performance of a velocity-based test for sarcopenia diagnosis and to analyze its correlation with other tests used in the diagnostic algorithms proposed by leading research groups. Methods A cross-sectional analysis was conducted on older adults residing in nursing homes in the Community of Madrid between February and June 2023. This study was approved by the Ethics Committee of the Hospital Clínico San Carlos (Spain) under the code: 23/010-E_TFM. All participants provided written informed consent, and the study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for conducting observational studies in epidemiology [ 25 ]. The inclusion criteria were as follows: individuals aged 65 years or older, capable of maintaining a standing position, with an adequate understanding of Spanish, and diagnosed with sarcopenia using the EWGSOP2 algorithm. This algorithm includes the completion of the SARC-F questionnaire and the administration of the following tests: Handgrip (HG), 5-Sit-to-Stand Test (5-STST), Gait Speed (GS), and Timed Up and Go (TUG). The exclusion criteria included refusal to participate in the study, failure to sign informed consent, visual and/or auditory impairment that prevented understanding of the tests, use of psychoactive substances affecting test performance, and any orthopedic, neurological, and/or cardiorespiratory condition that hindered the participant's ability to complete the assessments included in the study. The control group, identified as non-sarcopenic using the EWGSOP2 algorithm, was recruited from the same nursing homes as the intervention group participants. They were matched by sex and age to the intervention group members. Measurements and physical tests Before starting the study, data on age and anthropometric values of the participants were collected. The order of the tests was performed according to a randomization carried out previously. The physiological variables assessed were heart rate (HR), blood pressure (BP) and oxygen saturation (SpO 2 ) before, during and after each test, allowing adequate rest periods between tests, allowing oxygen saturation and heart rate to return to baseline values with at least 30 minutes between tests (Fig. 1 ). The tests were interrupted in the following situations: a) The participant was unable to complete the test. b) Symptoms such as dizziness, dyspnea or headache appeared. c) 90% of the maximum theoretical heart rate (HRmax) reached HRmax = 210 - (0.65 × age). d) Oxygen desaturation occurred, defined as SpO2 less than 90% or a 4% decrease from baseline. e) The participant voluntarily decided to stop the test. SARC-F questionnaire After signing the informed consent form, all participants completed the SARC-F questionnaire. This questionnaire is composed of five questions with a score of 0–2 points each, where 0 = no difficulty, 1 = some difficulty and 2: great difficulty or disability. The questions provide information on strength status, need for aids for walking, getting up from a chair, climbing stairs and prevalence of falls. The maximum score is 10 points, a score that represents poorer physical fitness [ 26 ]. The EWGSOP2 uses this questionnaire for case finding and determines that it is positive when a score of 4 or more points is obtained [ 8 ]. Anthropometric and body composition values A stadiometer and a scale (Seca 711, Seca, Hamburg, Germany) were used to record the height and weight of the participants. Skeletal muscle mass was assessed with the XpertZM3 electrical impedance apparatus (Aminogram, La Ciotat - France). The measurement was quadrupole, five multi-frequencies at 200 Hz and with an accuracy of ± 1%. The body composition data were transmitted via Bluetooth to the Biody Manager application. The measurement was performed in the retromalleolar area of the right foot, prior to the measurement the area was moistened and then the bioimpedance device was placed so that the electrodes were positioned at an angle of 45º with respect to the calcaneus. 5-STST A standard height chair (46 cm) without armrests placed against a wall was used for the test, and participants were instructed that they could not use their hands or arms to push the chair seat or their body. Participants were asked to stand up on 5 occasions as quickly as possible [ 27 ]. The evaluator timed the time, which started to be measured when the verbal signal ‘go’ was given and ends when the participant sits down for the fifth time. According to the EWGSOP2, when the subject performs the test in a time longer than 15s, the subject has probable sarcopenia [ 8 ]. Handgrip The test was performed according to the recommendations of the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO) [ 28 ]. To perform the test, participants were asked to sit in a chair, with their arms resting on the armrest, take the Saehan DHD-1 digital dynamometer (Saehan Corporation,Masan Free Trade Zone - South Korea), and place the elbow in 90° flexion, the wrist in 0–30° dorsiflexion and 0–15° ulnar deviation. Participants performed three 5-second dominant hand repetitions with a 30-second rest in between [ 29 ]. The value used to evaluate the test was the mean value between the three repetitions. The cut-off points for sarcopenia according to the EWGSOP2 are < 27kg for men and < 16kg for women (9). Gait speed The recommendations of the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO) were followed for this test [ 28 ]. The start and end points of the test were marked in a corridor. The subject was instructed to walk as fast as possible from one point to the other and the time was timed from when the first foot was lifted to crossing the end mark. They were left 1m before and after the start of timing so that they had an acceleration and deceleration zone to avoid braking. The participants performed the test twice, with the necessary rest for the physiological parameters to return to baseline, the value used being the average of the two repetitions to evaluate this test. According to the EWGSOP2 there is a low walking speed of 0.8 m/s or less [ 8 ]. Time Up Go The test consisted of measuring the time it took participants to get up from a chair with a height of 46 cm, walk 3 m, turn around a cone and sit down again. The participant started with their back against the chair, arms resting on the arms of the chair and the walker within reach. The participant was instructed to stand up and walk to a line on the floor 3 metres away, turn around, return to the chair and sit down again [ 30 ]. Participants performed the test twice, with a rest period necessary for the values of the different physiological parameters to return to baseline. The value used was the mean of the two repetitions. This test was performed to assess physical performance, gait and dynamic balance [ 28 ]. The EWGSOP2 indicates that sarcopenia is severe when subjects perform it in a time equal to or greater than 20 seconds [ 8 ]. SARC-Test To carry out this test, the subject was asked to perform two lifts of a 46cm high chair without the help of the arms, performing both repetitions at maximum speed, recording the value of the fastest repetition. The speed of execution of each repetition was measured using a validated and calibrated optoelectronic encoder (Velowin v.1.7.232, Instrumentos y Tecnología Deportiva; Murcia, Spain). The software (Velowin v.1.7.232) calculated the mean propulsive velocity using algorithms [ 31 ]. As it is an optoelectrical sensor, there must be a reflective reference mark, to achieve this in a free exercise, such as the one performed in this test, we placed a reflective plate on the subject's deltoid. Sample size The statistical calculation software G*Power (latest ver. 3.1.9.7; Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany) was used and the results were checked against the guide to determine the sample size requirements for estimating the value of the intraclass correlation coefficient. Where the value of the correlation coefficient in the null hypothesis can be assumed to be zero [ 32 ]. The study aims to determine in a population of elderly people with sarcopenia the correlation between a strength test with progressive loads on lower limbs and the Five Times Sit to Stand Test, Time Up and Go Test, Gait Speed Test and Hand Grip Strength Test. The intention is to obtain a significant result (p < 0.05) with power (80%) to detect at least a correlation coefficient of 0.5 (Moderate). Therefore, the minimum required sample size for this study is 33 people with sarcopenia, given the characteristics of the study and the study population a 10% loss to follow-up is assumed, therefore, our final study sample will be at least 36 people. The formula for the calculation is based on the two-tailed test [ 33 ]. Statistical analysis SPSS version 29.0 software (IBM SPSS Statistics, Armonk, NY, USA) was used for all statistical analyses. The Shapiro-Wilk normality test was applied to the recorded data and, depending on the nature of the variables, the corresponding parametric or non-parametric test was applied for comparison of means. An analysis of variance (ANOVA) with Tukey's post-hoc test was used to compare HR, SpO2, systolic pressure and diastolic pressure. The association between variables was verified by Pearson's correlation coefficient. Data are presented as mean ± standard deviation, 95% CI, minimum and maximum. A value of p < 0.05 was considered statistically significant. Results A total of 38 older adults diagnosed with sarcopenia according to the EWGSOP2 algorithm were recruited and compared with 38 healthy subjects. The descriptive characteristics of the participants are presented in Table 1 . Regarding the physical tests included in the study and used in the EWGSOP2 sarcopenia diagnostic algorithm, as shown in Table 1 , the performance of the sarcopenic group was significantly different from that of the control group. Table 1 Descriptive statistic of the included patients. Variable Control group (n = 38) Sarcopenia group (n = 38) p Age (years) 87 (85–88) 87 (85–88) 1.000 Gender Male (n, %) Female (n, %) 18 (47%) 20 (53%) 18 (47%) 20 (53%) NA Weight (Kg) 67.7 ± 14.1 59.0 ± 12.3 0.008 Height (cm) 157.3 ± 6.9 153.0 ± 7.0 0.009 BMI (m/Kg 2 ) 27.4 (25.4–29.3) 25.2 (23.5–26.8) 0.489 TEST Control group Sarcopenia group SARC-TEST Velocity (CI 95%) 0.37 (0.33–0.41) 0.28 (0.26–0.41) < 0.001* Time Up and Go Test Time (CI 95%) 14.0 (11.5–16.5) 24.6 (15.4–33.8) 0.031 Gait Speed Test Time (CI 95%) 5.2 (4.4–5.9) 8.2 (5.5–10.8) 0.034 5-STST (CI 95%) 14.0 (12.3–15.6) 23.6 (21.7–25.6) < 0.001* Hand Grip Test Strength kg (CI 95%) 18.9 (17.1–20.8) 12.9 (11.0-14.7) 0.05) between the sarcopenia and control groups in any of the tests performed, except for baseline and final heart rate during the Gait Speed Test, which was higher in the control group in both cases (Table 2 ). Table 2 Comparison between exercise physiological response between groups. Control Group (n = 38) Sarcopenia Group (n = 38) p-value SARC-TEST SpO2 baseline (%) 95.5 ± 2.1 96.1 ± 1.7 0.102 SpO2 final (%) 95.4 ± 2.5 96.1 ± 3.8 0.164 HR baseline (bpm) 74.4 ± 13.6 71.2 ± 11.4 0.172 HR final (bpm) 81.4 ± 13.0 80.0 ± 9.6 0.301 PAS baseline (mmHg) 130.5 ± 17.0 126.4 ± 16.1 0.147 PAS final (mmHg) 131.5 ± 18.5 129.1 ± 19.7 0.300 PAD baseline (mmHg) 72.8 ± 9.8 71.6 ± 11.6 0.326 PAD final (mmHg) 73.3 ± 8.8 74.8 ± 10.0 0.258 Timed Up and Go Test SpO2 baseline (%) 95.4 ± 1.5 95.8 ± 1.3 0.100 SpO2 final(%) 95.3 ± 2.0 95.5 ± 1.7 0.289 HR baseline (bpm) 69.6 ± 10.7 67.0 ± 11.7 0.456 HR final (bpm) 74.8 ± 11.0 75.2 ± 10.9 0.425 PAS baseline (mmHg) 134.0 ± 19.7 127.6 ± 17.6 0.070 PAS final (mmHg) 134.0 ± 21.0 129.2 ± 20.1 0.156 PAD baseline (mmHg) 73.1 ± 7.2 73.7 ± 9.2 0.381 PAD final (mmHg) 71.9 ± 7.3 73.1 ± 9.2 0.269 Gait Speed Test SpO2 baseline (%) 95.5 ± 2.1 96.1 ± 1.8 0.102 SpO2 final (%) 95.4 ± 2.5 96.1 ± 2.4 0.091 HR baseline (bpm) 78.6 ± 12.4 70.3 ± 11.3 0.002* HR final (bpm) 84.6 ± 14.6 77.7 ± 14.0 0.019* PAS baseline (mmHg) 133.6 ± 18.8 128.2 ± 16.5 0.094 PAS final (mmHg) 131.9 ± 20.0 125.7 ± 20.6 0.096 PAD baseline (mmHg) 75.4 ± 14.3 77.7 ± 23.1 0.303 PAD final (mmHg) 68.6 ± 16.0 70.4 ± 17.7 0.329 5-STST SpO2 baseline (%) 96.5 ± 2.1 97.2 ± 1.9 0.120 SpO2 final (%) 97.4 ± 3.5 96.7 ± 3.9 0.144 HR baseline (bpm) 73.9 ± 11.6 73.2 ± 10.4 0.132 HR final (bpm) 80.4 ± 11.7 81.2 ± 9.2 0.351 PAS baseline (mmHg) 131.5 ± 15.0 128.3 ± 15.1 0.147 PAS final (mmHg) 132.9 ± 16.5 130.1 ± 18.7 0.358 PAD baseline (mmHg) 71.3 ± 9.8 70.9 ± 10.5 0.357 PAD final (mmHg) 73.7 ± 7.8 75.8 ± 9.0 0.278 Hand Grip Test SpO2 baseline (%) 95.5 ± 3.1 95.1 ± 1.7 0.112 SpO2 final(%) 94.4 ± 2.9 95.3 ± 1.4 0.264 HR baseline (bpm) 74.4 ± 13.6 72.3 ± 10.3 0.192 HR final (bpm) 80.4 ± 13.2 76.7 ± 13.8 0.381 PAS baseline (mmHg) 130.2 ± 16.1 127.2 ± 12.5 0.147 PAS final (mmHg) 132.5 ± 16.5 125.2 ± 19.6 0.420 PAD baseline (mmHg) 71.9 ± 8.8 76.7 ± 20.1 0.436 PAD final (mmHg) 72.3 ± 6.8 71.0 ± 16.7 0.488 SpO 2 : Oxygen saturation; HR: heart rate; PAS: pressure arterial systolic; PAD: pressure arterial diastolic; bpm: beat per minute; mmHg: millimeters of mercury; *: significant differences [Insert Table 2 ] Additionally, as observed in Table 3 , there were no significant differences (p > 0.05) in physiological responses across the different functional tests performed. Table 3 Comparison between exercise physiological response between different tests. Variable Control group (n = 38) Sarcopenia group (n = 38) SARC-Test TUG-Test GS-Test 5-STST HG-Test p-value SARC-Test TUG-Test GS-Test 5-STST HG-Test p-value SpO2 baseline (%) 95.5 ± 2.1 95.4 ± 1.5 95.5 ± 2.1 96.5 ± 2.1 96.1 ± 1.2 0.115 96.1 ± 1.7 95.8 ± 1.3 96.1 ± 1.8 97.2 ± 1.9 96.2 ± 1.3 0.841 SpO2 final (%) 95.4 ± 2.5 95.3 ± 2.0 95.4 ± 2.5 97.4 ± 3.5 96.4 ± 2.5 0.533 96.1 ± 3.8 95.5 ± 1.7 96.1 ± 2.4 96.7 ± 3.9 96.1 ± 1.6 0.343 HR baseline (bpm) 74.4 ± 13.6 69.6 ± 10.7 78.6 ± 12.4 73.9 ± 11.6 71.9 ± 10.6 0.072 71.2 ± 11.4 67.0 ± 11.7 70.3 ± 11.3 73.2 ± 10.4 71.2 ± 9.4 0.952 HR final (bpm) 81.4 ± 13.0 74.8 ± 11.0 84.6 ± 14.6 80.4 ± 11.7 78.4 ± 11.1 0.095 80.0 ± 9.6 75.2 ± 10.9 77.7 ± 14.0 81.2 ± 9.2 80.2 ± 9.7 0.216 PAS baseline (mmHg) 130.5 ± 17.0 134.0 ± 19.7 133.6 ± 18.8 131.5 ± 15.0 132.5 ± 14.0 0.390 126.4 ± 16.1 127.6 ± 17.6 128.2 ± 16.5 128.3 ± 15.1 127.3 ± 10.1 0.949 PAS final (mmHg) 131.5 ± 18.5 134.0 ± 21.0 131.9 ± 20.0 132.9 ± 16.5 131.9 ± 14.5 0.860 129.1 ± 19.7 129.2 ± 20.1 125.7 ± 20.6 130.1 ± 18.7 128.1 ± 16.7 0.176 PAD baseline (mmHg) 72.8 ± 9.8 73.1 ± 7.2 75.4 ± 14.3 71.3 ± 9.8 72.3 ± 7.8 0.385 71.6 ± 11.6 73.7 ± 9.2 77.7 ± 23.1 70.9 ± 10.5 73.9 ± 8.6 0.665 PAD final (mmHg) 73.3 ± 8.8 71.9 ± 7.3 68.6 ± 16.0 73.7 ± 7.8 71.7 ± 9.6 0.311 74.8 ± 10.0 73.1 ± 9.2 70.4 ± 17.7 75.8 ± 9.0 73.5 ± 8.1 0.541 SpO 2 : Oxygen saturation; HR: heart rate; PAS: pressure arterial systolic; PAD: pressure arterial diastolic; bpm: beat per minute; mmHg: millimeters of mercury. The tests included in the EWGSOP2 algorithm showed significant correlations (p < 0.05), with a moderate correlation in the case of the Gait Speed Test and strong correlations for the remaining tests with the SARC-Test (Fig. 2 ). Finally, in the control group, moderate correlations were found between the Gait Speed Test and the 5-STST with the SARC-Test. In the case of the Time Up Go and Handgrip tests, correlations were strong (Fig. 3 ). Discussion The aim of this study was to evaluate the performance of a movement speed-based test for diagnosing sarcopenia and assess how it correlates with other physical tests included in the diagnostic algorithms developed by various working groups. Analysis of the tests included in the diagnostic algorithms showed statistically significant differences between subjects with sarcopenia and the control group in all evaluations conducted. In particular, the application of the SARC-Test revealed a significant reduction in mean propulsive speed with body weight in individuals with sarcopenia compared to healthy controls. These results suggest that movement speed evaluation is a reliable discriminative marker for detecting sarcopenia, reinforcing its potential as a diagnostic tool in this population. Regarding the correlation of the SARC-Test with the tests employed by the EWGSOP for sarcopenia detection, results were significant in all cases. In the sarcopenic group, strong correlations were observed across all tests, except for Gait Speed, where the correlation was moderate. Similarly, in the control group, correlations ranged from moderate to strong in all cases. The 5-STST test is widely used to assess lower limb strength and predict fall risk in older adults [ 34 ]. Additionally, it has been used to estimate power generated during the maneuver of standing up from a seated position. Previous studies have established minimum power threshold values required to complete the test, showing that reduced power levels are associated with frailty in the geriatric population [ 35 , 36 ]. The methodology used in these studies is based on measuring the time required to complete the test, followed by applying an equation that integrates variables such as execution time, subject height, and chair height to calculate movement power. However, this method has methodological limitations, as variability in chair height and the imprecision of manual time measurement with a stopwatch may compromise the reliability and validity of the results. Although the 5-STST is adapted for the geriatric population, it is essential to consider that many older adults have comorbidities that may complicate, alter results, or even prevent the execution of physical tests included in the diagnostic algorithms developed by different working groups. These conditions include Parkinson's disease [ 37 ], renal failure [ 38 ], cardiovascular diseases, type II diabetes, dementia, and respiratory diseases [ 39 , 40 ], all of which can affect mobility and functional capacity, influencing the execution and accuracy of these evaluations. Additionally, in individuals with chronic heart failure, the 5-STST induced a significant increase in heart rate and perceived exertion [ 41 ]. In patients with pulmonary disease and cancer, this test also caused oxygen desaturation and increased fatigue in individuals with sarcopenia [ 42 , 43 ]. Furthermore, a strong correlation has been reported between maximum acceleration, measured via accelerometry, and performance in the 5-STST in the geriatric population [ 44 ]. It has also been shown that the speed at which an older adult rises from a chair is a more accurate parameter for assessing muscle strength than measuring the total time required to complete the 5-STST [ 22 ]. On the other hand, both the 5-STST measurements, as well as the TUG and Gait Speed, may be subject to biases derived from human error, limiting their reliability and reproducibility. In this context, the SARC-Test, by evaluating movement speed and requiring only two repetitions for execution, minimizes fatigue and provides greater accuracy due to the use of a validated instrument like the encoder. These factors suggest that the SARC-Test could be a viable alternative for evaluating sarcopenia in this population or even be integrated into the diagnostic algorithms of different working groups. Another relevant aspect is the difficulty in performing tests such as Gait Speed or TUG in subjects with gait alterations, as occurs in patients with sarcopenia and Parkinson's disease. In these cases, the presence of freezing of gait syndrome or festinating gait could compromise the execution of these tests [ 45 ].Moreover, weakness in handgrip strength, secondary to osteoarthritis and fatigue in the geriatric population, could present a barrier to the application of other tests such as Handgrip or Gait Speed [ 46 ]. Comparative analysis of baseline and final heart rate, oxygen saturation, and blood pressure between the various tests showed no statistically significant differences. In the SARC-Test, subjects with sarcopenia exhibited stable oxygen saturation levels, heart rate, and blood pressure both before and after the test. These results suggest that the SARC-Test does not induce a significant cardiopulmonary response, indicating lower sympathetic nervous system activation and confirming its safety in this population [ 47 ]. Since sarcopenia is a disease that selectively affects skeletal muscle, the progressive loss of type II fibers, responsible for high-speed movements, may explain the reduction in effort intensity in these patients [ 48 ]. Furthermore, this reduction in type II fibers forces the use of type I fibers to perform the tests, which are more resistant to fatigue, which could justify the absence of significant physiological changes during the test. The slower execution speed in the sarcopenic group implies a lower relative effort load compared to individuals without the disease, reinforcing the stability of the physiological responses observe[ 49 ]. The fact that physiological variables remain constant regardless of the test performed strengthens the suitability of the SARC-Test as a safe and effective diagnostic tool. Unlike other functional tests that may induce significant fatigue or compromise hemodynamic stability in vulnerable populations, the SARC-Test provides an objective assessment of muscle strength without inducing physiological stress. Its implementation with an encoder provides more reliable and accurate measurements compared to the simple quantification of execution time [ 31 , 50 ]. In this context, the SARC-Test emerges as a low-physiological-impact alternative for evaluating sarcopenia. Its ease of application, combined with its minimal cardiorespiratory demand, makes it an optimal tool for integration into clinical practice and research studies, enabling precise detection of sarcopenia without compromising the patient's physiological stability (Fig. 4 ). Among the main limitations of this study are the lack of categorization of subjects by age groups or the different pathologies that participants presented. The study sample was limited; a larger sample size would improve external validity and extrapolation of the findings. Moreover, due to the cross-sectional nature of the study, it is not possible to determine if the SARC-Test is useful for evaluating sarcopenia progression or the effectiveness of therapeutic interventions. On the other hand, individual factors such as patient motivation, familiarity with the test, or possible differences in execution technique may influence the results. Ensuring protocol standardization and evaluator training is crucial to improving test reproducibility. Incorporating these aspects in future research would strengthen the validity of the SARC-Test and its applicability in different clinical and population contexts. Conclusion The SARC-Test could be a safe, precise, and low-physiological-impact tool for evaluating sarcopenia, enabling discrimination between subjects without causing significant changes in cardiovascular or respiratory parameters. The lower sympathetic nervous system activation observed in subjects with sarcopenia suggests that the relative effort intensity is lower in this group, reinforcing the need for diagnostic methods adapted to their physiological characteristics. In this regard, the SARC-Test, with its ease of application, low physiological demand, and precise measurement via encoder, positions itself as a viable alternative to traditional functional tests, especially in populations with comorbidities. Given its potential to optimize sarcopenia diagnosis in clinical and research settings, future studies should validate its longitudinal utility and compare it with other reference methods to consolidate its integration into current diagnostic algorithms. Abbreviations ICD International Classification of Diseases EWGSOP European Working Group on Sarcopenia in Older People AWGS Asian Working Group for Sarcopenia 5-STST 5-sit-to-stand-test FNIH the Foundation for the National Institutes of Health IWGS International Working Group on Sarcopenia SDOC Sarcopenia Definitions and Outcomes Consortium 1RM One-Repetition Maximum CMJ Countermovement Jump STROBE Strengthening the Reporting of Observational Studies in Epidemiology HG HandGrip GS Gait Speed TUG Time Up Go HR Heart Rate BP blood pressure (BP) SpO 2 Oxygen Saturation MPV measurement physiological variables PAS pressure arterial systolic PAD pressure arterial diastolic bpm beat per minute mmHg millimeters of mercury BMI Body Mass Index CI confidence Interval Declarations Acknowledgments: EMERA Residence and Aminogram. Author’s contributions J.L M-M, J.H-L and P.G-F contributed to conception and design of the study. P. G-F performed the statistical analysis. S.C-T, M. R-B and I. R-M contributed to testing and data collection. B.P-R wrote the first draft of the manuscript. J.L M-M, J.H-L and P.G-F had a role in supervision. All authors contributed to manuscript revision, read, and approved the submitted version. Funding No funding was received for conducting this study. Data availability The datasets generated and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable request. Ethics approval and consent to participate This study was carried out in line with the ethical principles outlined in the Declaration of Helsinki. The protocol was approved by the Committee on the Ethics of Medicinal Products Research (CEIm) Hospital Clínico San Carlos (Spain) under the internal code: 23/010-E_TFM. All participants were informed about the study protocol and provided written informed consent before the assessment. Consent for publication All authors approved the final manuscript and the submission to this journal. Competing interests The authors declared no conflict of interest. Clinical trial number Not applicable. References Rosenberg IH, Sarcopenia. Origins and clinical relevance. J Nutr. 1997;127:990–1. Goodpaster BH, Park SW, Harris TB, Kritchevsky SB, Nevitt M, Schwartz AV et al. The loss of skeletal muscle strength, mass, and quality in older adults: The Health, Aging and Body Composition Study. Journals of Gerontology - Series A Biological Sciences and Medical Sciences. 2006; 61:1059–64. Anker SD, Morley JE, von Haehling S. Welcome to the ICD-10 code for sarcopenia. J Cachexia Sarcopenia Muscle. 2016;7:512–4. Janssen I, Heymsfield SB, Ross R. Low Relative Skeletal Muscle Mass (Sarcopenia) in Older Persons Is Associated with Functional Impairment and Physical Disability. 2002;889–96. Scott D, Hayes A, Sanders KM, Aitken D, Ebeling PR, Jones G. 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Differences in sarcopenia prevalence between upper-body and lower-body based EWGSOP2 muscle strength criteria: the Tromsø study 2015–2016. BMC Geriatr. 2020;20:1–11. Yee XS, Ng YS, Allen JC, Latib A, Tay EL, Abu Bakar HM, et al. Performance on sit-to-stand tests in relation to measures of functional fitness and sarcopenia diagnosis in community-dwelling older adults. Eur Rev Aging Phys Activity. 2021;18:1–11. Martinikorena I, Martínez-Ramírez A, Gómez M, Lecumberri P, Casas-Herrero A, Cadore EL et al. Gait Variability Related to Muscle Quality and Muscle Power Output in Frail Nonagenarian Older Adults. J Am Med Dir Assoc [Internet]. 2016; 17:162–7. Available from: http://dx.doi.org/10.1016/j.jamda.2015.09.015 Yanagawa N, Shimomitsu T, Kawanishi M, Fukunaga T, Kanehisa H. Sex difference in age-related changes in knee extensor strength and power production during a 10-times-repeated sit-to-stand task in Japanese elderly. J Physiol Anthropol [Internet]. 2015; 34:1–7. Available from: http://dx.doi.org/10.1186/s40101-015-0072-4 Takai Y, Ohta M, Akagi R, Kanehisa H, Kawakami Y, Fukunaga T. Sit-to-stand test to evaluate knee extensor muscle size and strength in the elderly: A novel approach. J Physiol Anthropol. 2009;28:123–8. Alcazar J, Losa-Reyna J, Rodriguez-Lopez C, Alfaro-Acha A, Rodriguez-Mañas L, Ara I et al. The sit-to-stand muscle power test: An easy, inexpensive and portable procedure to assess muscle power in older people. Exp Gerontol [Internet]. 2018; 112:38–43. Available from: https://doi.org/10.1016/j.exger.2018.08.006 Rodrigues F, Jacinto M, Antunes R, Monteiro D, Mendes D, Matos R et al. Comparing the Effects of Multicomponent and Concurrent Exercise Protocols on Muscle Strength in Older Adults. J Funct Morphol Kinesiol. 2024;9. Alcazar J, Guadalupe-Grau A, García-García FJ, Ara I, Alegre LM. Skeletal Muscle Power Measurement in Older People: A Systematic Review of Testing Protocols and Adverse Events. Journals of Gerontology - Series A Biological Sciences and Medical Sciences. 2018; 73:914–24. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol. 2008;61:344–9. Malmstrom TK, Miller DK, Simonsick EM, Ferrucci L, Morley JE. SARC-F: A symptom score to predict persons with sarcopenia at risk for poor functional outcomes. J Cachexia Sarcopenia Muscle. 2016;7:28–36. Cesari M, Kritchevsky SB, Newman AB, Eleanor M, Harris TB, Penninx BW, et al. Added Value of Physical Performance Measures in Predicting Adverse Health-Related Events: Results from the Health, Aging, and Body Composition Study Matteo. Natl Instıtutes Health. 2009;57:251–9. Beaudart C, Rolland Y, Cruz-Jentoft AJ, Bauer JM, Sieber C, Cooper C, et al. Assessment of Muscle Function and Physical Performance in Daily Clinical Practice: A position paper endorsed by the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO). Calcif Tissue Int. Springer New York LLC; 2019. Beseler MR, Rubio C, Duarte E, Hervás D, Guevara MC, Giner-Pascual M, et al. Clinical effectiveness of grip strength in predicting ambulation of elderly inpatients. Clin Interv Aging. 2014;9:1873–7. Podsiadlo D, Richardson S. The Timed Up and Go: A Test of Basic Functional Mobility for Frail Elderly Persons. J Am Geriatr Soc. 1991;39:142–8. Peña García-Orea G, Belando-Pedreño N, Merino-Barrero JA, Heredia-Elvar JR. Validation of an opto-electronic instrument for the measurement of execution velocity in squat exercise. Sports Biomech [Internet]. 2021; 20:706–19. Available from: https://doi.org/10.1080/14763141.2019.1597156 Bujang MA, Baharum N. Sample Size Guideline for Correlation Analysis. World J Social Sci Res. 2016;3:37. Guenther WC. Desk Calculation of Probabilities for the Distribution of the Sample Correlation Coefficient. Am Stat. 1977;31:45–8. Zou Z, Chen Z, Ni Z, Hou Y, Zhang Q. The effect of group-based Otago exercise program on fear of falling and physical function among older adults living in nursing homes: A pilot trial. Geriatr Nurs (Minneap) [Internet]. 2022; 43:288–92. Available from: https://doi.org/10.1016/j.gerinurse.2021.12.011 Alcazar J, Alegre LM, Suetta C, Júdice PB, Van Roie E, González-Gross M, et al. Threshold of Relative Muscle Power Required to Rise from a Chair and Mobility Limitations and Disability in Older Adults. Med Sci Sports Exerc. 2021;53:2217–24. Baltasar-Fernandez I, Alcazar J, Mañas A, Alegre LM, Alfaro-Acha A, Rodriguez-Mañas L et al. Relative sit-to-stand power cut-off points and their association with negatives outcomes in older adults. Sci Rep. 2021;11. Ponsoni A, Sardeli AV, Costa FP, Mourão LF. Prevalence of sarcopenia in Parkinson’s disease: A systematic review and meta-analysis. Geriatr Nurs (Minneap). 2023;49:44–9. Duarte MP, Almeida LS, Neri SGR, Oliveira JS, Wilkinson TJ, Ribeiro HS, et al. Prevalence of sarcopenia in patients with chronic kidney disease: a global systematic review and meta-analysis. J Cachexia Sarcopenia Muscle. 2024;15:501–12. Pacifico J, Geerlings MAJ, Reijnierse EM, Phassouliotis C, Lim WK, Maier AB. Prevalence of sarcopenia as a comorbid disease: A systematic review and meta-analysis. Exp Gerontol [Internet]. 2020; 131:110801. Available from: https://doi.org/10.1016/j.exger.2019.110801 Zhang Y, Zhang J, Ni W, Yuan X, Zhang H, Li P, et al. Sarcopenia in heart failure: a systematic review and meta-analysis. ESC Heart Fail. 2021;8:1007–17. Tanriverdi A, Kahraman BO, Ozpelit E, Savci S. Test–Retest Reliability and Validity of 1-Minute Sit-to-Stand Test in Patients With Chronic Heart Failure. Heart Lung Circ [Internet]. 2023; 32:518–24. Available from: https://doi.org/10.1016/j.hlc.2023.01.008 Tremblay Labrecque PF, Harvey J, Nadreau É, Maltais F, Dion G, Saey D. Validation and Cardiorespiratory Response of the 1-Min Sit-to-Stand Test in Interstitial Lung Disease. Med Sci Sports Exerc. 2020;52:2508–14. Martínez-Herrera BE, Trujillo-Hernández B, Sat-Muñoz D, González-Barba F, Cruz-corona E, Bayardo-López LH et al. Quality of Life and Functionality of Head and Neck Cancer Patients Are Diminished As a Function of Sarcopenia and Obesity. Ear Nose Throat J. 2022. Tateoka K, Tsuji T, Shoji T, Tokunaga S, Okura T. Relationship between Acceleration in a Sit-To-Stand Movement and Physical Function in Older Adults. Geriatr (Switzerland). 2023;8. José M, Burriel L, Pablo J, Valencia C, Jesus M, Carrasco S, et al. Congelación de la marcha y funciones ejecutivas en la enfermedad de Parkinson avanzada. Neurología Argentina. 2013;6:17–22. Vlietstra L, Stebbings S, Meredith-Jones K, Haxby Abbott J, Treharne GJ, Waters DL. Sarcopenia in osteoarthritis and rheumatoid arthritis: The association with self-reported fatigue, physical function and obesity. PLoS ONE. 2019;14:1–13. Fisher JP, Young CN, Fadel PJ. Autonomic adjustments to exercise in humans. Compr Physiol. 2015;5:475–512. Nilwik R, Snijders T, Leenders M, Groen BBL, van Kranenburg J, Verdijk LB et al. The decline in skeletal muscle mass with aging is mainly attributed to a reduction in type II muscle fiber size. Exp Gerontol [Internet]. 2013; 48:492–8. Available from: http://dx.doi.org/10.1016/j.exger.2013.02.012 Larsson L, Degens H, Li M, Salviati L, Lee Y, Il, Thompson W, et al. Sarcopenia: Aging-related loss of muscle mass and function. Physiol Rev. 2019;99:427–511. Ruiz-Alias SA, Şentürk D, Akyildiz Z, Çetin O, Kaya S, Pérez-Castilla A, et al. Validity and reliability of velocity and power measures provided by the Vitruve linear position transducer. PLoS ONE. 2024;19:e0312348. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6473225","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":452241946,"identity":"ad8f7774-6398-4e92-b365-d327274acff8","order_by":0,"name":"Blanca Pedauyé-Rueda","email":"","orcid":"","institution":"Universidad Camilo José Cela","correspondingAuthor":false,"prefix":"","firstName":"Blanca","middleName":"","lastName":"Pedauyé-Rueda","suffix":""},{"id":452241948,"identity":"4983b25e-7e47-45bf-ade5-ffe1bd1cda32","order_by":1,"name":"José Luis Maté-Muñoz","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAr0lEQVRIiWNgGAWjYBACxgYQaVAjR5IWIKo4ZkyqRWeYExuIVs887fDzBx/b2NI3HD+dwPDhDzFWzE4zbJzZJpO74UzuBsaZbURpSTBs5m1jy91wg3cDMy8xzmOcnf6x+W8bc7oBSMsf4hyWY9gM9H4CWAsDG3FaCmf2VBwznAn0y8FeYvxiODt9w4cfBjXyfMfPbnzwgxiHGTYgcQ4QoYGBQZ4oVaNgFIyCUTCyAQCoWTyy1eGdnQAAAABJRU5ErkJggg==","orcid":"","institution":"Complutense University of Madrid","correspondingAuthor":true,"prefix":"","firstName":"José","middleName":"Luis","lastName":"Maté-Muñoz","suffix":""},{"id":452241949,"identity":"f53228a1-59df-49c0-8b77-fb90000c6ec0","order_by":2,"name":"Juan Hernández-Lougedo","email":"","orcid":"","institution":"Universidad Camilo José Cela","correspondingAuthor":false,"prefix":"","firstName":"Juan","middleName":"","lastName":"Hernández-Lougedo","suffix":""},{"id":452241954,"identity":"2d15d474-14ab-4758-b4c8-db962b4e636c","order_by":3,"name":"Iñigo Aparicio-García","email":"","orcid":"","institution":"Alfonso X El Sabio University","correspondingAuthor":false,"prefix":"","firstName":"Iñigo","middleName":"","lastName":"Aparicio-García","suffix":""},{"id":452241955,"identity":"b0209543-6a5e-42bf-9bb0-e42fed151966","order_by":4,"name":"Sara Cerrolaza-Tudanca","email":"","orcid":"","institution":"Alfonso X El Sabio University","correspondingAuthor":false,"prefix":"","firstName":"Sara","middleName":"","lastName":"Cerrolaza-Tudanca","suffix":""},{"id":452241956,"identity":"67ef62ed-ac86-447f-b23e-4c9b9cb6c853","order_by":5,"name":"Manuel Rozalén-Bustín","email":"","orcid":"","institution":"Alfonso X El Sabio University","correspondingAuthor":false,"prefix":"","firstName":"Manuel","middleName":"","lastName":"Rozalén-Bustín","suffix":""},{"id":452241957,"identity":"1e8130e9-c609-45bb-b147-1b643d44001c","order_by":6,"name":"Inmaculada Rodríguez-Moreno","email":"","orcid":"","institution":"Emera Group Elderly Care Home","correspondingAuthor":false,"prefix":"","firstName":"Inmaculada","middleName":"","lastName":"Rodríguez-Moreno","suffix":""},{"id":452241958,"identity":"048956db-ed6a-4837-97c1-5f513e8c9393","order_by":7,"name":"Pablo García-Fernández","email":"","orcid":"","institution":"Complutense University of Madrid","correspondingAuthor":false,"prefix":"","firstName":"Pablo","middleName":"","lastName":"García-Fernández","suffix":""}],"badges":[],"createdAt":"2025-04-17 15:53:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6473225/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6473225/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82095285,"identity":"8c23869c-6a32-4a32-9f4e-bfce99b3c657","added_by":"auto","created_at":"2025-05-06 17:21:52","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":468072,"visible":true,"origin":"","legend":"\u003cp\u003eStudy design.\u003c/p\u003e\n\u003cp\u003eMPV: measurement physiological variables; 5-STST: 5 sit-to-stand-test; HG: Handgrip; GS: gait speed and TUG: Time Up Go.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6473225/v1/64e7c843d01be929207ba62f.jpeg"},{"id":82095284,"identity":"6c7d0e89-beff-4b65-b50f-1a176ca3f3aa","added_by":"auto","created_at":"2025-05-06 17:21:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":286741,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation graphs between the different field tests in the sarcopenia group.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6473225/v1/62f1fb4efbf06d1c07ab31dd.png"},{"id":82095900,"identity":"3b6db567-b5d6-4473-a38d-e3ce9df7a5b0","added_by":"auto","created_at":"2025-05-06 17:29:52","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":236563,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation graphs between the different field tests in the control group.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6473225/v1/1b30e70debc8d49d993ea93b.jpeg"},{"id":82095283,"identity":"72e5003f-11f2-42bd-8b39-8d9acfc99ada","added_by":"auto","created_at":"2025-05-06 17:21:52","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":359907,"visible":true,"origin":"","legend":"\u003cp\u003eNew tool for muscle strength assessment.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6473225/v1/e9ff1c72fc7c0efb1d1c39af.jpeg"},{"id":83437420,"identity":"c73fd0d3-e472-4556-a331-e9de6901664f","added_by":"auto","created_at":"2025-05-26 08:46:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2378699,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6473225/v1/aff5af33-1544-4464-b8e7-ce0fdc1bdd0c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"New Approach to Sarcopenia Diagnosis: Physical Test for Sarcopenia Diagnosis and Its Comparison with Other Validated Tests: cross-sectional study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSarcopenia is a condition characterized by the progressive loss of muscle mass and strength associated with aging [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, the decline in muscle strength occurs at a faster rate than the reduction in muscle mass in older individuals [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In 2016, sarcopenia was officially recognized as a disease and included in the International Classification of Diseases (ICD) under the ICD-10-CM code M62.84 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis condition is associated with multiple adverse health outcomes, including disability and functional decline [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], an increased risk of falls [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], and higher mortality rates [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These clinical consequences lead to a significant increase in healthcare costs. In 2014, individuals diagnosed with sarcopenia generated an additional annual healthcare expenditure of approximately \u003cspan\u003e$\u003c/span\u003e2,315.7 per person compared to those without the condition [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe most commonly used diagnostic algorithms for sarcopenia have been developed by the European Working Group on Sarcopenia in Older People (EWGSOP) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], the Asian Working Group for Sarcopenia (AWGS) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], and the Foundation for the National Institutes of Health (FNIH) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Additionally, other diagnostic approaches have been proposed by the International Working Group on Sarcopenia (IWGS) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] and the Sarcopenia Definitions and Outcomes Consortium (SDOC) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Each of these algorithms incorporates different functional tests, leading to variations in diagnostic procedures, as well as the need for specific equipment and time for implementation.\u003c/p\u003e \u003cp\u003eOne of the main reasons for discrepancies in sarcopenia prevalence is the heterogeneity in diagnostic tests, established cutoff points, and the equipment used to depend on the applied algorithm [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In scientific literature, sarcopenia prevalence varies widely, ranging from 9.9\u0026ndash;40.4%, with an increasing trend as age progresses [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These differences can be attributed to the use of different diagnostic algorithms and variability in tests assessing muscle strength, such as the 5-Sit-To-Stand Test (5-STST) and handgrip dynamometry [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Two studies using the EWGSOP algorithm reported different prevalence rates depending on the test used to assess muscle strength: in one study, prevalence was 3.1% when applying the 5-STST [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], whereas another study found a 3% higher prevalence when using handgrip dynamometry [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMuscle power has been identified as the most relevant predictor of functional limitations in older adults [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Various studies have employed equations incorporating variables such as leg length, chair height, and execution time to estimate muscle power. However, these methods have not been validated against reference instruments [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Additionally, equations have been developed to estimate power as a means of providing cost-effective and easily applicable tools for assessing sarcopenia and functional capacity in geriatric populations. Nevertheless, these equations have not yet replaced previously validated methods [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOther methodologies for assessing muscle strength include the One-Repetition Maximum (1RM) test, the Countermovement Jump (CMJ), and the maximum number of repetitions with a fixed load test. However, their application in older adults is limited due to their high physical demands, induced fatigue, and potential physiological alterations [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Consequently, these methods have primarily been restricted to sports performance assessment [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Given that sarcopenia is closely linked to fatigue and frailty associated with aging, it is essential to develop precise, accessible, and low-impact physiological assessment tools suitable for this population.\u003c/p\u003e \u003cp\u003eTherefore, the objectives of this study were to evaluate the performance of a velocity-based test for sarcopenia diagnosis and to analyze its correlation with other tests used in the diagnostic algorithms proposed by leading research groups.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eA cross-sectional analysis was conducted on older adults residing in nursing homes in the Community of Madrid between February and June 2023. This study was approved by the Ethics Committee of the Hospital Cl\u0026iacute;nico San Carlos (Spain) under the code: 23/010-E_TFM. All participants provided written informed consent, and the study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for conducting observational studies in epidemiology [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe inclusion criteria were as follows: individuals aged 65 years or older, capable of maintaining a standing position, with an adequate understanding of Spanish, and diagnosed with sarcopenia using the EWGSOP2 algorithm. This algorithm includes the completion of the SARC-F questionnaire and the administration of the following tests: Handgrip (HG), 5-Sit-to-Stand Test (5-STST), Gait Speed (GS), and Timed Up and Go (TUG).\u003c/p\u003e \u003cp\u003eThe exclusion criteria included refusal to participate in the study, failure to sign informed consent, visual and/or auditory impairment that prevented understanding of the tests, use of psychoactive substances affecting test performance, and any orthopedic, neurological, and/or cardiorespiratory condition that hindered the participant's ability to complete the assessments included in the study.\u003c/p\u003e \u003cp\u003eThe control group, identified as non-sarcopenic using the EWGSOP2 algorithm, was recruited from the same nursing homes as the intervention group participants. They were matched by sex and age to the intervention group members.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eMeasurements and physical tests\u003c/h2\u003e \u003cp\u003eBefore starting the study, data on age and anthropometric values of the participants were collected. The order of the tests was performed according to a randomization carried out previously. The physiological variables assessed were heart rate (HR), blood pressure (BP) and oxygen saturation (SpO\u003csub\u003e2\u003c/sub\u003e) before, during and after each test, allowing adequate rest periods between tests, allowing oxygen saturation and heart rate to return to baseline values with at least 30 minutes between tests (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe tests were interrupted in the following situations:\u003c/p\u003e \u003cp\u003ea) The participant was unable to complete the test.\u003c/p\u003e \u003cp\u003eb) Symptoms such as dizziness, dyspnea or headache appeared.\u003c/p\u003e \u003cp\u003ec) 90% of the maximum theoretical heart rate (HRmax) reached HRmax\u0026thinsp;=\u0026thinsp;210 - (0.65 \u0026times; age).\u003c/p\u003e\u003cp\u003ed) Oxygen desaturation occurred, defined as SpO2 less than 90% or a 4% decrease from baseline.\u003c/p\u003e \u003cp\u003ee) The participant voluntarily decided to stop the test.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSARC-F questionnaire\u003c/h3\u003e\n\u003cp\u003e After signing the informed consent form, all participants completed the SARC-F questionnaire. This questionnaire is composed of five questions with a score of 0\u0026ndash;2 points each, where 0\u0026thinsp;=\u0026thinsp;no difficulty, 1\u0026thinsp;=\u0026thinsp;some difficulty and 2: great difficulty or disability. The questions provide information on strength status, need for aids for walking, getting up from a chair, climbing stairs and prevalence of falls. The maximum score is 10 points, a score that represents poorer physical fitness [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The EWGSOP2 uses this questionnaire for case finding and determines that it is positive when a score of 4 or more points is obtained [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eAnthropometric and body composition values\u003c/h3\u003e\n\u003cp\u003eA stadiometer and a scale (Seca 711, Seca, Hamburg, Germany) were used to record the height and weight of the participants. Skeletal muscle mass was assessed with the XpertZM3 electrical impedance apparatus (Aminogram, La Ciotat - France). The measurement was quadrupole, five multi-frequencies at 200 Hz and with an accuracy of \u0026plusmn;\u0026thinsp;1%. The body composition data were transmitted via Bluetooth to the Biody Manager application. The measurement was performed in the retromalleolar area of the right foot, prior to the measurement the area was moistened and then the bioimpedance device was placed so that the electrodes were positioned at an angle of 45\u0026ordm; with respect to the calcaneus.\u003c/p\u003e\n\u003ch3\u003e5-STST\u003c/h3\u003e\n\u003cp\u003eA standard height chair (46 cm) without armrests placed against a wall was used for the test, and participants were instructed that they could not use their hands or arms to push the chair seat or their body. Participants were asked to stand up on 5 occasions as quickly as possible [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The evaluator timed the time, which started to be measured when the verbal signal \u0026lsquo;go\u0026rsquo; was given and ends when the participant sits down for the fifth time. According to the EWGSOP2, when the subject performs the test in a time longer than 15s, the subject has probable sarcopenia [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eHandgrip\u003c/h3\u003e\n\u003cp\u003eThe test was performed according to the recommendations of the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. To perform the test, participants were asked to sit in a chair, with their arms resting on the armrest, take the Saehan DHD-1 digital dynamometer (Saehan Corporation,Masan Free Trade Zone - South Korea), and place the elbow in 90\u0026deg; flexion, the wrist in 0\u0026ndash;30\u0026deg; dorsiflexion and 0\u0026ndash;15\u0026deg; ulnar deviation. Participants performed three 5-second dominant hand repetitions with a 30-second rest in between [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The value used to evaluate the test was the mean value between the three repetitions. The cut-off points for sarcopenia according to the EWGSOP2 are \u0026lt;\u0026thinsp;27kg for men and \u0026lt;\u0026thinsp;16kg for women (9).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eGait speed\u003c/h2\u003e \u003cp\u003eThe recommendations of the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO) were followed for this test [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The start and end points of the test were marked in a corridor. The subject was instructed to walk as fast as possible from one point to the other and the time was timed from when the first foot was lifted to crossing the end mark. They were left 1m before and after the start of timing so that they had an acceleration and deceleration zone to avoid braking. The participants performed the test twice, with the necessary rest for the physiological parameters to return to baseline, the value used being the average of the two repetitions to evaluate this test. According to the EWGSOP2 there is a low walking speed of 0.8 m/s or less [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTime Up Go\u003c/h3\u003e\n\u003cp\u003eThe test consisted of measuring the time it took participants to get up from a chair with a height of 46 cm, walk 3 m, turn around a cone and sit down again. The participant started with their back against the chair, arms resting on the arms of the chair and the walker within reach. The participant was instructed to stand up and walk to a line on the floor 3 metres away, turn around, return to the chair and sit down again [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Participants performed the test twice, with a rest period necessary for the values of the different physiological parameters to return to baseline. The value used was the mean of the two repetitions. This test was performed to assess physical performance, gait and dynamic balance [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The EWGSOP2 indicates that sarcopenia is severe when subjects perform it in a time equal to or greater than 20 seconds [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eSARC-Test\u003c/h3\u003e\n\u003cp\u003eTo carry out this test, the subject was asked to perform two lifts of a 46cm high chair without the help of the arms, performing both repetitions at maximum speed, recording the value of the fastest repetition. The speed of execution of each repetition was measured using a validated and calibrated optoelectronic encoder (Velowin v.1.7.232, Instrumentos y Tecnolog\u0026iacute;a Deportiva; Murcia, Spain). The software (Velowin v.1.7.232) calculated the mean propulsive velocity using algorithms [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. As it is an optoelectrical sensor, there must be a reflective reference mark, to achieve this in a free exercise, such as the one performed in this test, we placed a reflective plate on the subject's deltoid.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSample size\u003c/h2\u003e \u003cp\u003eThe statistical calculation software G*Power (latest ver. 3.1.9.7; Heinrich-Heine-Universit\u0026auml;t D\u0026uuml;sseldorf, D\u0026uuml;sseldorf, Germany) was used and the results were checked against the guide to determine the sample size requirements for estimating the value of the intraclass correlation coefficient. Where the value of the correlation coefficient in the null hypothesis can be assumed to be zero [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The study aims to determine in a population of elderly people with sarcopenia the correlation between a strength test with progressive loads on lower limbs and the Five Times Sit to Stand Test, Time Up and Go Test, Gait Speed Test and Hand Grip Strength Test. The intention is to obtain a significant result (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) with power (80%) to detect at least a correlation coefficient of 0.5 (Moderate). Therefore, the minimum required sample size for this study is 33 people with sarcopenia, given the characteristics of the study and the study population a 10% loss to follow-up is assumed, therefore, our final study sample will be at least 36 people. The formula for the calculation is based on the two-tailed test [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eSPSS version 29.0 software (IBM SPSS Statistics, Armonk, NY, USA) was used for all statistical analyses. The Shapiro-Wilk normality test was applied to the recorded data and, depending on the nature of the variables, the corresponding parametric or non-parametric test was applied for comparison of means. An analysis of variance (ANOVA) with Tukey's post-hoc test was used to compare HR, SpO2, systolic pressure and diastolic pressure. The association between variables was verified by Pearson's correlation coefficient. Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, 95% CI, minimum and maximum. A value of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 38 older adults diagnosed with sarcopenia according to the EWGSOP2 algorithm were recruited and compared with 38 healthy subjects. The descriptive characteristics of the participants are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eRegarding the physical tests included in the study and used in the EWGSOP2 sarcopenia diagnostic algorithm, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the performance of the sarcopenic group was significantly different from that of the control group.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistic of the included patients.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSarcopenia group (n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87 (85\u0026ndash;88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87 (85\u0026ndash;88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003cp\u003eMale (n, %)\u003c/p\u003e \u003cp\u003eFemale (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (47%)\u003c/p\u003e \u003cp\u003e20 (53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (47%)\u003c/p\u003e \u003cp\u003e20 (53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (Kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67.7\u0026thinsp;\u0026plusmn;\u0026thinsp;14.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.0\u0026thinsp;\u0026plusmn;\u0026thinsp;12.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e157.3\u0026thinsp;\u0026plusmn;\u0026thinsp;6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e153.0\u0026thinsp;\u0026plusmn;\u0026thinsp;7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (m/Kg\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.4 (25.4\u0026ndash;29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.2 (23.5\u0026ndash;26.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.489\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTEST\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eControl group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eSarcopenia group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSARC-TEST Velocity (CI 95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.37 (0.33\u0026ndash;0.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.28 (0.26\u0026ndash;0.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime Up and Go Test Time (CI 95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.0 (11.5\u0026ndash;16.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.6 (15.4\u0026ndash;33.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGait Speed Test Time (CI 95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.2 (4.4\u0026ndash;5.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.2 (5.5\u0026ndash;10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-STST (CI 95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.0 (12.3\u0026ndash;15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.6 (21.7\u0026ndash;25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHand Grip Test Strength kg (CI 95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.9 (17.1\u0026ndash;20.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.9 (11.0-14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBMI: Body Mass Index; CI: confidence Interval; *: significant differences\u003c/p\u003e \u003cp\u003ePhysiological variables did not show significant differences (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) between the sarcopenia and control groups in any of the tests performed, except for baseline and final heart rate during the Gait Speed Test, which was higher in the control group in both cases (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison between exercise physiological response between groups.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl Group (n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSarcopenia Group (n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eSARC-TEST\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpO2 baseline (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpO2 final (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR baseline (bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74.4\u0026thinsp;\u0026plusmn;\u0026thinsp;13.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.2\u0026thinsp;\u0026plusmn;\u0026thinsp;11.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.172\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR final (bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81.4\u0026thinsp;\u0026plusmn;\u0026thinsp;13.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80.0\u0026thinsp;\u0026plusmn;\u0026thinsp;9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.301\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAS baseline (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130.5\u0026thinsp;\u0026plusmn;\u0026thinsp;17.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e126.4\u0026thinsp;\u0026plusmn;\u0026thinsp;16.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAS final (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e131.5\u0026thinsp;\u0026plusmn;\u0026thinsp;18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e129.1\u0026thinsp;\u0026plusmn;\u0026thinsp;19.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAD baseline (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.6\u0026thinsp;\u0026plusmn;\u0026thinsp;11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.326\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAD final (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73.3\u0026thinsp;\u0026plusmn;\u0026thinsp;8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.258\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTimed Up and Go Test\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpO2 baseline (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpO2 final(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.289\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR baseline (bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.6\u0026thinsp;\u0026plusmn;\u0026thinsp;10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.0\u0026thinsp;\u0026plusmn;\u0026thinsp;11.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.456\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR final (bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74.8\u0026thinsp;\u0026plusmn;\u0026thinsp;11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.2\u0026thinsp;\u0026plusmn;\u0026thinsp;10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.425\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAS baseline (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e134.0\u0026thinsp;\u0026plusmn;\u0026thinsp;19.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127.6\u0026thinsp;\u0026plusmn;\u0026thinsp;17.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAS final (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e134.0\u0026thinsp;\u0026plusmn;\u0026thinsp;21.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e129.2\u0026thinsp;\u0026plusmn;\u0026thinsp;20.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAD baseline (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73.1\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.381\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAD final (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.9\u0026thinsp;\u0026plusmn;\u0026thinsp;7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.1\u0026thinsp;\u0026plusmn;\u0026thinsp;9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.269\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGait Speed Test\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpO2 baseline (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpO2 final (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR baseline (bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78.6\u0026thinsp;\u0026plusmn;\u0026thinsp;12.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.3\u0026thinsp;\u0026plusmn;\u0026thinsp;11.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR final (bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84.6\u0026thinsp;\u0026plusmn;\u0026thinsp;14.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.7\u0026thinsp;\u0026plusmn;\u0026thinsp;14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.019*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAS baseline (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133.6\u0026thinsp;\u0026plusmn;\u0026thinsp;18.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e128.2\u0026thinsp;\u0026plusmn;\u0026thinsp;16.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAS final (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e131.9\u0026thinsp;\u0026plusmn;\u0026thinsp;20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125.7\u0026thinsp;\u0026plusmn;\u0026thinsp;20.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAD baseline (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.4\u0026thinsp;\u0026plusmn;\u0026thinsp;14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.7\u0026thinsp;\u0026plusmn;\u0026thinsp;23.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.303\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAD final (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.6\u0026thinsp;\u0026plusmn;\u0026thinsp;16.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.4\u0026thinsp;\u0026plusmn;\u0026thinsp;17.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.329\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003e5-STST\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpO2 baseline (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpO2 final (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.144\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR baseline (bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.2\u0026thinsp;\u0026plusmn;\u0026thinsp;10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR final (bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80.4\u0026thinsp;\u0026plusmn;\u0026thinsp;11.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.351\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAS baseline (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e131.5\u0026thinsp;\u0026plusmn;\u0026thinsp;15.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e128.3\u0026thinsp;\u0026plusmn;\u0026thinsp;15.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAS final (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e132.9\u0026thinsp;\u0026plusmn;\u0026thinsp;16.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130.1\u0026thinsp;\u0026plusmn;\u0026thinsp;18.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.358\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAD baseline (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.3\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.9\u0026thinsp;\u0026plusmn;\u0026thinsp;10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.357\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAD final (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73.7\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.278\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHand Grip Test\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpO2 baseline (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpO2 final(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.264\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR baseline (bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74.4\u0026thinsp;\u0026plusmn;\u0026thinsp;13.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.192\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR final (bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80.4\u0026thinsp;\u0026plusmn;\u0026thinsp;13.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.7\u0026thinsp;\u0026plusmn;\u0026thinsp;13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.381\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAS baseline (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130.2\u0026thinsp;\u0026plusmn;\u0026thinsp;16.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127.2\u0026thinsp;\u0026plusmn;\u0026thinsp;12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAS final (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e132.5\u0026thinsp;\u0026plusmn;\u0026thinsp;16.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125.2\u0026thinsp;\u0026plusmn;\u0026thinsp;19.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.420\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAD baseline (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.9\u0026thinsp;\u0026plusmn;\u0026thinsp;8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.7\u0026thinsp;\u0026plusmn;\u0026thinsp;20.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.436\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAD final (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72.3\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.0\u0026thinsp;\u0026plusmn;\u0026thinsp;16.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.488\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eSpO\u003csub\u003e2\u003c/sub\u003e: Oxygen saturation; HR: heart rate; PAS: pressure arterial systolic; PAD: pressure arterial diastolic; bpm: beat per minute; mmHg: millimeters of mercury; *: significant differences\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[Insert Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eAdditionally, as observed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, there were no significant differences (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) in physiological responses across the different functional tests performed.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison between exercise physiological response between different tests.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eControl group (n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c13\" namest=\"c8\"\u003e \u003cp\u003eSarcopenia group (n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSARC-Test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTUG-Test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGS-Test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5-STST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHG-Test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSARC-Test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eTUG-Test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eGS-Test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5-STST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eHG-Test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSpO2 baseline (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e96.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e96.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e95.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e96.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e97.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e96.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.841\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSpO2 final (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e97.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.533\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e96.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e95.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e96.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e96.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e96.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.343\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHR baseline (bpm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74.4\u0026thinsp;\u0026plusmn;\u0026thinsp;13.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.6\u0026thinsp;\u0026plusmn;\u0026thinsp;10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78.6\u0026thinsp;\u0026plusmn;\u0026thinsp;12.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e73.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71.9\u0026thinsp;\u0026plusmn;\u0026thinsp;10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e71.2\u0026thinsp;\u0026plusmn;\u0026thinsp;11.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e67.0\u0026thinsp;\u0026plusmn;\u0026thinsp;11.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e70.3\u0026thinsp;\u0026plusmn;\u0026thinsp;11.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e73.2\u0026thinsp;\u0026plusmn;\u0026thinsp;10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e71.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.952\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHR final (bpm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81.4\u0026thinsp;\u0026plusmn;\u0026thinsp;13.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.8\u0026thinsp;\u0026plusmn;\u0026thinsp;11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84.6\u0026thinsp;\u0026plusmn;\u0026thinsp;14.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80.4\u0026thinsp;\u0026plusmn;\u0026thinsp;11.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e78.4\u0026thinsp;\u0026plusmn;\u0026thinsp;11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e80.0\u0026thinsp;\u0026plusmn;\u0026thinsp;9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e75.2\u0026thinsp;\u0026plusmn;\u0026thinsp;10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e77.7\u0026thinsp;\u0026plusmn;\u0026thinsp;14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e81.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e80.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.216\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePAS baseline (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130.5\u0026thinsp;\u0026plusmn;\u0026thinsp;17.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e134.0\u0026thinsp;\u0026plusmn;\u0026thinsp;19.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e133.6\u0026thinsp;\u0026plusmn;\u0026thinsp;18.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e131.5\u0026thinsp;\u0026plusmn;\u0026thinsp;15.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e132.5\u0026thinsp;\u0026plusmn;\u0026thinsp;14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e126.4\u0026thinsp;\u0026plusmn;\u0026thinsp;16.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e127.6\u0026thinsp;\u0026plusmn;\u0026thinsp;17.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e128.2\u0026thinsp;\u0026plusmn;\u0026thinsp;16.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e128.3\u0026thinsp;\u0026plusmn;\u0026thinsp;15.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e127.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.949\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePAS final (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e131.5\u0026thinsp;\u0026plusmn;\u0026thinsp;18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e134.0\u0026thinsp;\u0026plusmn;\u0026thinsp;21.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e131.9\u0026thinsp;\u0026plusmn;\u0026thinsp;20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e132.9\u0026thinsp;\u0026plusmn;\u0026thinsp;16.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e131.9\u0026thinsp;\u0026plusmn;\u0026thinsp;14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.860\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e129.1\u0026thinsp;\u0026plusmn;\u0026thinsp;19.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e129.2\u0026thinsp;\u0026plusmn;\u0026thinsp;20.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e125.7\u0026thinsp;\u0026plusmn;\u0026thinsp;20.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e130.1\u0026thinsp;\u0026plusmn;\u0026thinsp;18.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e128.1\u0026thinsp;\u0026plusmn;\u0026thinsp;16.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.176\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePAD baseline (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.1\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.4\u0026thinsp;\u0026plusmn;\u0026thinsp;14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71.3\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e71.6\u0026thinsp;\u0026plusmn;\u0026thinsp;11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e73.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e77.7\u0026thinsp;\u0026plusmn;\u0026thinsp;23.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e70.9\u0026thinsp;\u0026plusmn;\u0026thinsp;10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e73.9\u0026thinsp;\u0026plusmn;\u0026thinsp;8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.665\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePAD final (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73.3\u0026thinsp;\u0026plusmn;\u0026thinsp;8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.9\u0026thinsp;\u0026plusmn;\u0026thinsp;7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68.6\u0026thinsp;\u0026plusmn;\u0026thinsp;16.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e73.7\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e74.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e73.1\u0026thinsp;\u0026plusmn;\u0026thinsp;9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e70.4\u0026thinsp;\u0026plusmn;\u0026thinsp;17.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e75.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e73.5\u0026thinsp;\u0026plusmn;\u0026thinsp;8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.541\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSpO\u003csub\u003e2\u003c/sub\u003e: Oxygen saturation; HR: heart rate; PAS: pressure arterial systolic; PAD: pressure arterial diastolic; bpm: beat per minute; mmHg: millimeters of mercury.\u003c/p\u003e \u003cp\u003eThe tests included in the EWGSOP2 algorithm showed significant correlations (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with a moderate correlation in the case of the Gait Speed Test and strong correlations for the remaining tests with the SARC-Test (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFinally, in the control group, moderate correlations were found between the Gait Speed Test and the 5-STST with the SARC-Test. In the case of the Time Up Go and Handgrip tests, correlations were strong (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe aim of this study was to evaluate the performance of a movement speed-based test for diagnosing sarcopenia and assess how it correlates with other physical tests included in the diagnostic algorithms developed by various working groups.\u003c/p\u003e \u003cp\u003eAnalysis of the tests included in the diagnostic algorithms showed statistically significant differences between subjects with sarcopenia and the control group in all evaluations conducted. In particular, the application of the SARC-Test revealed a significant reduction in mean propulsive speed with body weight in individuals with sarcopenia compared to healthy controls. These results suggest that movement speed evaluation is a reliable discriminative marker for detecting sarcopenia, reinforcing its potential as a diagnostic tool in this population.\u003c/p\u003e \u003cp\u003eRegarding the correlation of the SARC-Test with the tests employed by the EWGSOP for sarcopenia detection, results were significant in all cases. In the sarcopenic group, strong correlations were observed across all tests, except for Gait Speed, where the correlation was moderate. Similarly, in the control group, correlations ranged from moderate to strong in all cases.\u003c/p\u003e \u003cp\u003eThe 5-STST test is widely used to assess lower limb strength and predict fall risk in older adults [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Additionally, it has been used to estimate power generated during the maneuver of standing up from a seated position. Previous studies have established minimum power threshold values required to complete the test, showing that reduced power levels are associated with frailty in the geriatric population [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The methodology used in these studies is based on measuring the time required to complete the test, followed by applying an equation that integrates variables such as execution time, subject height, and chair height to calculate movement power. However, this method has methodological limitations, as variability in chair height and the imprecision of manual time measurement with a stopwatch may compromise the reliability and validity of the results. Although the 5-STST is adapted for the geriatric population, it is essential to consider that many older adults have comorbidities that may complicate, alter results, or even prevent the execution of physical tests included in the diagnostic algorithms developed by different working groups. These conditions include Parkinson's disease [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], renal failure [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], cardiovascular diseases, type II diabetes, dementia, and respiratory diseases [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], all of which can affect mobility and functional capacity, influencing the execution and accuracy of these evaluations. Additionally, in individuals with chronic heart failure, the 5-STST induced a significant increase in heart rate and perceived exertion [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. In patients with pulmonary disease and cancer, this test also caused oxygen desaturation and increased fatigue in individuals with sarcopenia [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurthermore, a strong correlation has been reported between maximum acceleration, measured via accelerometry, and performance in the 5-STST in the geriatric population [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. It has also been shown that the speed at which an older adult rises from a chair is a more accurate parameter for assessing muscle strength than measuring the total time required to complete the 5-STST [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. On the other hand, both the 5-STST measurements, as well as the TUG and Gait Speed, may be subject to biases derived from human error, limiting their reliability and reproducibility. In this context, the SARC-Test, by evaluating movement speed and requiring only two repetitions for execution, minimizes fatigue and provides greater accuracy due to the use of a validated instrument like the encoder. These factors suggest that the SARC-Test could be a viable alternative for evaluating sarcopenia in this population or even be integrated into the diagnostic algorithms of different working groups.\u003c/p\u003e \u003cp\u003eAnother relevant aspect is the difficulty in performing tests such as Gait Speed or TUG in subjects with gait alterations, as occurs in patients with sarcopenia and Parkinson's disease. In these cases, the presence of freezing of gait syndrome or festinating gait could compromise the execution of these tests [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].Moreover, weakness in handgrip strength, secondary to osteoarthritis and fatigue in the geriatric population, could present a barrier to the application of other tests such as Handgrip or Gait Speed [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eComparative analysis of baseline and final heart rate, oxygen saturation, and blood pressure between the various tests showed no statistically significant differences. In the SARC-Test, subjects with sarcopenia exhibited stable oxygen saturation levels, heart rate, and blood pressure both before and after the test. These results suggest that the SARC-Test does not induce a significant cardiopulmonary response, indicating lower sympathetic nervous system activation and confirming its safety in this population [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSince sarcopenia is a disease that selectively affects skeletal muscle, the progressive loss of type II fibers, responsible for high-speed movements, may explain the reduction in effort intensity in these patients [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Furthermore, this reduction in type II fibers forces the use of type I fibers to perform the tests, which are more resistant to fatigue, which could justify the absence of significant physiological changes during the test. The slower execution speed in the sarcopenic group implies a lower relative effort load compared to individuals without the disease, reinforcing the stability of the physiological responses observe[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe fact that physiological variables remain constant regardless of the test performed strengthens the suitability of the SARC-Test as a safe and effective diagnostic tool. Unlike other functional tests that may induce significant fatigue or compromise hemodynamic stability in vulnerable populations, the SARC-Test provides an objective assessment of muscle strength without inducing physiological stress. Its implementation with an encoder provides more reliable and accurate measurements compared to the simple quantification of execution time [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this context, the SARC-Test emerges as a low-physiological-impact alternative for evaluating sarcopenia. Its ease of application, combined with its minimal cardiorespiratory demand, makes it an optimal tool for integration into clinical practice and research studies, enabling precise detection of sarcopenia without compromising the patient's physiological stability (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAmong the main limitations of this study are the lack of categorization of subjects by age groups or the different pathologies that participants presented. The study sample was limited; a larger sample size would improve external validity and extrapolation of the findings. Moreover, due to the cross-sectional nature of the study, it is not possible to determine if the SARC-Test is useful for evaluating sarcopenia progression or the effectiveness of therapeutic interventions. On the other hand, individual factors such as patient motivation, familiarity with the test, or possible differences in execution technique may influence the results. Ensuring protocol standardization and evaluator training is crucial to improving test reproducibility. Incorporating these aspects in future research would strengthen the validity of the SARC-Test and its applicability in different clinical and population contexts.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe SARC-Test could be a safe, precise, and low-physiological-impact tool for evaluating sarcopenia, enabling discrimination between subjects without causing significant changes in cardiovascular or respiratory parameters. The lower sympathetic nervous system activation observed in subjects with sarcopenia suggests that the relative effort intensity is lower in this group, reinforcing the need for diagnostic methods adapted to their physiological characteristics. In this regard, the SARC-Test, with its ease of application, low physiological demand, and precise measurement via encoder, positions itself as a viable alternative to traditional functional tests, especially in populations with comorbidities.\u003c/p\u003e \u003cp\u003eGiven its potential to optimize sarcopenia diagnosis in clinical and research settings, future studies should validate its longitudinal utility and compare it with other reference methods to consolidate its integration into current diagnostic algorithms.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eICD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternational Classification of Diseases\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eEWGSOP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEuropean Working Group on Sarcopenia in Older People\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eAWGS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAsian Working Group for Sarcopenia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003e5-STST\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e5-sit-to-stand-test\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eFNIH\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ethe Foundation for the National Institutes of Health\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eIWGS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternational Working Group on Sarcopenia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSDOC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSarcopenia Definitions and Outcomes Consortium\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003e1RM\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOne-Repetition Maximum\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCMJ\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCountermovement Jump\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSTROBE\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStrengthening the Reporting of Observational Studies in Epidemiology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHG\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHandGrip\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGait Speed\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eTUG\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTime Up Go\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHeart Rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eBP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eblood pressure (BP)\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSpO\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOxygen Saturation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMPV\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emeasurement physiological variables\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePAS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epressure arterial systolic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePAD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epressure arterial diastolic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ebpm\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebeat per minute\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003emmHg\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emillimeters of mercury\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBody Mass Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econfidence Interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e EMERA Residence and Aminogram.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ.L M-M, J.H-L and P.G-F contributed to conception and design of the study. P. G-F performed the statistical analysis. S.C-T, M. R-B and I. R-M contributed to testing and data collection. B.P-R wrote the first draft of the manuscript. J.L M-M, J.H-L and P.G-F had a role in supervision. All authors contributed to manuscript revision, read, and approved the submitted version.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received for conducting this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was carried out in line with the ethical principles outlined in the Declaration of Helsinki. The protocol was approved by the Committee on the Ethics of Medicinal Products Research (CEIm) Hospital Cl\u0026iacute;nico San Carlos (Spain) under the internal code: 23/010-E_TFM. All participants were informed about the study protocol and provided written informed consent before the assessment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors approved the final manuscript and the submission to this journal.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declared no conflict of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Not applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRosenberg IH, Sarcopenia. Origins and clinical relevance. J Nutr. 1997;127:990\u0026ndash;1.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoodpaster BH, Park SW, Harris TB, Kritchevsky SB, Nevitt M, Schwartz AV et al. The loss of skeletal muscle strength, mass, and quality in older adults: The Health, Aging and Body Composition Study. Journals of Gerontology - Series A Biological Sciences and Medical Sciences. 2006; 61:1059\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnker SD, Morley JE, von Haehling S. Welcome to the ICD-10 code for sarcopenia. J Cachexia Sarcopenia Muscle. 2016;7:512\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJanssen I, Heymsfield SB, Ross R. Low Relative Skeletal Muscle Mass (Sarcopenia) in Older Persons Is Associated with Functional Impairment and Physical Disability. 2002;889\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScott D, Hayes A, Sanders KM, Aitken D, Ebeling PR, Jones G. 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PLoS ONE. 2024;19:e0312348.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"sarcopenia, diagnosis, validation, SARC-Test, velocity, chair test","lastPublishedDoi":"10.21203/rs.3.rs-6473225/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6473225/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eSarcopenia is a disease characterized by the progressive loss of muscle mass and strength associated with aging. There are marked differences in sarcopenia prevalence depending on the diagnostic algorithm used. It has been demonstrated that muscle power is the most relevant predictor for determining functional limitations in older adults. The objectives of this study were to evaluate the performance of the SARC-Test for sarcopenia diagnosis and analyze its correlation with other validated tests.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional analysis was conducted on a population residing in elderly care centers. All physical tests included in the diagnostic algorithm developed by EWGSOP2 were performed. Additionally, the SARC-Test was conducted, measuring the speed at which the subject stood up from a chair. Physiological variables such as heart rate (HR), systolic blood pressure (SBP), and oxygen saturation (SpO2) were also monitored.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe sarcopenia group showed significantly lower physical performance than the non-sarcopenia group in all tests. At a physiological level, no significant differences were found between groups in the 5-STST, Handgrip, and TUG. Additionally, the SARC-Test showed a strong correlation with Handgrip (r\u0026thinsp;=\u0026thinsp;0.800), 5-STST (r=-0.719) and TUG (r=-0.523), and a moderate correlation with Gait Speed (r=-0.438) in sarcopenia group.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe SARC-Test could be a safe, accurate, and low-impact tool for sarcopenia assessment.\u003c/p\u003e","manuscriptTitle":"New Approach to Sarcopenia Diagnosis: Physical Test for Sarcopenia Diagnosis and Its Comparison with Other Validated Tests: cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-06 17:21:48","doi":"10.21203/rs.3.rs-6473225/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"65e61d3d-4e80-444f-8ebf-94a7a21924cc","owner":[],"postedDate":"May 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-05-26T08:38:30+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-06 17:21:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6473225","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6473225","identity":"rs-6473225","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}