Prognostic value of physical function tests and muscle mass in elderly hospitalized patients. A prospective observational study

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1 bs_bs_banner Geriatr Geriatr Gerontol Gerontol Int 2018; Int : ORIGINAL ARTICLE: EPIDEMIOLOGY, CLINICAL PRACTICE AND HEALTH Prognostic value of physical function tests and muscle mass in elderly hospitalized patients. A prospective observational study Rubén Hernández-Luis, Esther Martín-Ponce, María Monereo-Muñoz, Geraldine Quintero-Platt, Silvia Odeh-Santana, Emilio González-Reimers and Francisco Santolaria 1 Internal Medicine Department, Canary Islands University Hospital, Tenerife, Spain Aim: To determine the prognostic value for mortality of physical function tests, muscle mass loss, disability and frailty in elderly hospitalized patients. Methods: We prospectively included 298 hospitalized patients aged >60 years (152 men and 146 women). We assessed comorbidity using the Charlson Comorbidity Index; nutrition by body mass index, midarm muscle area and subjective nutritional score; physical muscle function by handgrip strength, gait speed, standing balance and stand up test; disability using the Barthel test and activities of daily living; frailty by the clinical frailty scale and Fried frailty index; and cognitive impairment by the Pfeiffer test. We assessed 100-day and long-term mortality. Results: We found a high prevalence of malnutrition, comorbidity, cognitive impairment, physical function impairment, disability and frailty. Mortality at 100 days was 15.1%, with a long-term median survival of 989 days. Mortality was significantly related to age, comorbidity, nutritional status, physical function, disability and frailty. Serum vitamin D 3 levels were not related to mortality. Independent prognostic value for long-term mortality was shown by: (i) incapacity to carry out any of the walking, stand up and standing balance tests; (ii) male sex; (iii) aged >80 years; (iv) impaired handgrip strength or gait speed; (v) Charlson Comorbidity Index 1; and (6) impaired muscle mass of subjective nutritional score. Conclusions: In elderly hospitalized patients, there is an important role of muscle regarding prognosis, mainly related to physical function, but also and independently regarding muscle mass. Geriatr Gerontol Int 2017; 2018; : 18: Keywords: elderly, frailty, mortality, physical function test, sarcopenia. Introduction Life expectancy has increased in the past decades, and patients admitted to general medical wards are older and have greater comorbidity. Malnutrition with muscle loss, impaired physical function, disability and a high mortality rate are frequent among elderly patients. 1 Consequently, two concepts have emerged: sarcopenia and frailty. Sarcopenia was initially defined as the loss of muscle mass that occurs with aging, but the definition now incorporates impaired physical function, assessed by diminished handgrip strength (HGS) or slow gait speed. 2,3 Frailty is defined as vulnerability as a result of reduced homeostatic reserve in older adults, with a difficult recovery after a Accepted for publication 13 June Correspondence: Dr Francisco Santolaria MD, Servicio de Medicina Interna. Hospital Universitario de Canarias, Facultad de Medicina, Ofra sn La Laguna, Tenerife, Tfno , Spain. fsantola@gmail.com physical stress. There are two orientations for frailty assessment. One is based on physical function with five criteria: (i) weight loss; (ii) exhaustion; (iii) scarce physical activity; (iv) decreased HGS; and (v) slow gait speed. The other is related to the degree of disability, such as the clinical frailty scale of the Canadian Study of Health and Aging (CFS-CSHA). 4,5 Sarcopenia and frailty are complex terms with multiple defining criteria. Sarcopenia and the Fried frailty index are closely related by means of physical function tests. 6 The heterogeneous modalities of sarcopenia and frailty make their use difficult for clinical patient assessment. 7,8 However, physical muscle function tests are simple and easy to carry out. Furthermore, as they can assess muscle quality, their relationship with prognosis would be better than that of muscle mass. Occasionally, they have been used to assess the aging process and prognosis in older adults disregarding muscle mass Therefore, our aim was to determine the prognostic value for mortality of physical function tests (HGS, gait speed, standing balance and stand up test), muscle mass loss, disability and frailty in elderly hospitalized patients Japan Geriatrics Society doi: doi: /ggi /ggi

2 R Hernández-Luis et al. Methods We carried out a prospective and observational study including (January 2013 December 2015) 298 patients aged >60 years who were consecutively admitted to the Internal Medicine Department of the Canary Islands University Hospital, Tenerife, Spain; we studied 152 men and 146 women aged years. Patients must have been admitted for an acute illness or decompensation via the emergency room. We excluded terminal patients (with a life expectancy of <6 months) and patients with acute delirium or impaired consciousness that persisted on the second day of hospital admission. The end-point of the study was short- and long-term mortality; 45 patients died 100 days after admittance, and 109 patients died after a mean follow-up period of 739 days. Comorbidity Diseases were categorized and recorded according to diagnoses described in medical reports. Charlson s Comorbidity Index (without age) was also calculated. 12 To assess cognitive impairment, we carried out the Pfeiffer test. 13 Nutritional assessment We inquired about weight loss in the year preceding admission. Body mass index (BMI) was calculated at admission as weight / height 2. We measured midarm circumference and triceps skinfold using a Holtain lipocaliper and calculated midarm muscle area (MAMA). Anthropometric parameters were compared within sex and age categories for the adult population of the Western Canary Islands. 14 Subjective nutritional assessment included examination of the muscle mass of the upper and lower limbs and of the temporal muscle, defining two degrees of atrophy (severe, moderate), and absence of atrophy. We assigned 2, 1 and 0 points to each category. Bichat s pad and subcutaneous fat atrophy were scored in the same way. Thus, a subjective nutritional score was obtained for each patient based on the sum of the assigned points. As previously reported, a score of 0 2 was considered normal, 3 4 indicated mild malnutrition and >4 points indicated severe malnutrition. We also defined a muscular component of the subjective nutritional score considering only the 6 points of muscle assessment. 15 Samples for blood analysis were taken at hours of the second day of admission. We determined nutritional data including cholesterol, triglyceride, vitamin B 12 and folate levels, and acute phase reactants, such as serum albumin. We also determined serum vitamin D 3 and insulin-like growth factor-1. Assessment of physical performance Lower extremity function was assessed more than 2 days after admission using standing balance, gait speed and five times sit-to-stand tests. 9,11 For the standing balance test, participants were asked to attempt to maintain their feet in the side-by-side, semi-tandem (heel of one foot beside the big toe of the other foot) and tandem (heel of one foot directly in front of the other foot) positions for 10 s each. The participants were given a score of 0 if any standing was not possible, of 1 if they could hold a semi-tandem position and a score of 2 if they could hold a tandem position. A 10-m walk at the participants normal pace was timed. Speed was determined on the 6 middle meters. A score of 0 was given when it was not possible to carry out the test because of limited physical conditions; a score of 1 when velocity was <0.8 m/s; and a score of 2 when velocity was 0.8 m/s. In 90 patients, it was not possible to carry out the test because of limited physical conditions; in this case, velocity was computed as 0 m/s. Participants were asked to stand up from a sitting position once; if they successfully rose from the chair, they were asked to stand up and sit down five times. The participants were given a score of 0 when it was not possible to stand up; a score of 1 if they stood up and sat down between 1 and 4 times; and a score of 2 when they stood up and sat down five times. After adding the scores of standing balance, walking speed and ability to rise from a chair tests, we calculated a modified Short Physical Performance Battery score between 0 and 6 points. Dominant arm HGS was determined using a Collins dynamometer (Surtex-instruments, London, England, UK), selecting the best of three measurements. 16 As the reference, we took the median value of 400 healthy participants, 196 men and 204 women aged between 20 and 29 years; the median values (interquartile range) of HGS were 35 kg (25 40 kg) in men and 10 kg ( kg) in women. HGS was expressed as the percentage of reference median value according to sex. We assessed daily activity as the self-reported ability to walk a proposed distance of 3, 30, 300 or 3000 m, and to climb stairs. Sarcopenia For sarcopenia diagnosis, we required two criteria: (i) an impaired physical muscle function (HGS >20% of the standard or a gait speed >0.8 m/s); and (ii) a diminished muscle mass (MAMA <10th percentile). A second sarcopenia model was defined with the above mentioned muscle function criteria and a diminished muscle mass with a muscle component of subjective nutritional score equal 3 points Japan Geriatrics Society

3 Prognostic value of muscle function Disability We inquired into the ability to carry out the basic activities of daily living and the instrumental activities of daily living, and carried out the Barthel test. 17 We also asked about a previous history of fractures and falls in the past 2 years. Frailty Frailty was assessed using the Fried criteria: 1, involuntary weight loss >10%; 2, exhaustion (continuous tiredness); 3, weak HGS (<20% of the reference group); 4, slow walking speed, <0.8 m/s; and 5, limited activity: to walk <300 m/day. We considered patients with 0 points as not frail, those with 1 2 points as pre-frail and those with 3 5 points as frail. 4 Frailty was also assessed by the seven-point CFS-CHSA. Patients were classified in the following models: 1,very fit; 2, well (without active disease); 3, well (with treated comorbid disease, disease symptoms are well controlled); 4, apparently vulnerable (not frankly dependent, commonly complain of being slowed up or with disease symptoms); 5, mildly frail (with limited dependence for instrumental activities of daily living); 6, moderately frail (help is required with activities of daily living); and 7, severely frail (completely dependent for the activities of daily living). 5 Statistical analysis For statistical analysis, we used SPSS 20.0 software (IBM Corp., Armonk, NY, USA). As most variables were not normally distributed, we used non-parametric tests, such as the Kruskal Wallis test, Mann Whitney U-test and Spearman s correlation as necessary. All patients were followed up (after discharge) by telephone calls; Kaplan Meier curves and the log rank test were carried out to assess differences in survival after inclusion. Multivariate survival analysis: Cox regression analysis was carried out to discern which parameters yielded independent prognostic value. Results were considered significant when P < Methods were carried out according to approved guidelines. The study was approved by the Hospital Universitario de Canarias Research and Ethics Board; informed consent was obtained from all patients or their relatives in the case of confusion or dementia. Results We included 298 patients 152 men and 146 women, with a mean age of 76.6 years. There was a high prevalence of malnutrition (67% with a moderate impairment of the muscular component of subjective assessment and 37% with a MAMA <10 percentile); physical function impairment, HGS <20% in 64% and gait speed <0.8 m/s in 86%; incapacity, Barthel 40 in 19%; and frailty, Fried index >2 in60.4%. Comorbidity included: cardiovascular diseases, such as coronary disease (58; 19.5%), stroke (40; 13.4%) and peripheral arterial disease (45; 15.1%); as well as cardiovascular risk factors, such as hypertension (62; 20.8%), hyperlipidemia (168; 56.4%), obesity (BMI 30 kg/m 2 ; 81/290; 27.9%), diabetes mellitus (152; 51%) and smoking (134, 29.7%). Other diseases included: congestive heart failure (121; 40.6%), chronic obstructive pulmonary disease (56; 18.8%); cancer (52; 17.4%), alcohol abuse (45; 15.1%), liver cirrhosis (35; 11.7%), renal failure (127, 42.6%) and dementia (35; 11.7%). The most frequent infections at admission were pneumonia in 70 (23.5%) and urinary tract infection in 53 cases (17.8%); sepsis, was present in 109 cases (36.6%). The Charlson Comorbidity Index was >3 in 36%, and the Pfeiffer Index >2 in27%; As shown in Table 1, we found a close correlation between age, nutritional status (subjective assessment, BMI and MAMA), physical function tests (HGS, gait speed, balance, stand up and distance walked in a day), Pfeiffer Index, Barthel Index and frailty (Fried Index and CFS-CSHA). It is noteworthy that we found a better relationship between muscle function and the subjective nutritional assessment than between muscle function and anthropometry (BMI or MAMA). However, the Charlson Comorbidity Index did not correlate with muscle mass, physical function, disability or frailty. In the previous 2 years, 146 patients (39%) reported falls, and 41 patients (13.8%) reported diverse fractures. Falls were related to impaired muscle function tests, HGS, gait speed, standing balance and sit-to-stand tests, as well as to the reported capacity to walk and to climb stairs. Falls were also related to frailty (Fried Index and CFS-CSHA). However, falls were not related to nutritional status or to the Charlson Comorbidity Index. Of the 298 patients, 23 (7.7%) died during hospitalization and 46 (15.1%) died 100 days after admission. After long-term follow up, 109 patients died, and Kaplan Meyer curves analysis showed a median survival of 989 days. Table 2 shows how mortality at 100 days and long-term survival were closely related to age, comorbidity, nutritional status, physical function capacity, disability, sarcopenia and frailty. In Table 3, we show quantitative data with prognostic value for mortality at 100 days. We can see how serum albumin and insulin-like growth factor-1 levels are related to mortality. Again, subjective nutritional score is better related to mortality than BMI or MAMA. Although there was a high prevalence of low serum vitamin D 3 levels, 57% were 20 ng/ml, they were not related to mortality. To determine which data had independent prognostic value for long-term mortality, we carried out a survival analysis with covariates (Cox regression). The variables with independent prognostic value were: SPPB 0 (when patients did not carry out any walking test, standing up and balance tests), male sex, age >80 years, physical 2017 Japan Geriatrics Society 593

4 R Hernández-Luis et al. Table 1 Correlation (Spearman s rho) analysis between age, nutritional status, muscle physical function tests, disability and frailty SNS (M) BMI MAMA HGS Speed Balance Stand up Pfeiffer Barthel CSHA Fried Age rho P SNS (M) rho p BMI rho p MAMA rho p HGS rho p Speed rho p Balance rho p Stand up rho p Pfeiffer rho p Barthel rho P CFS-CSHA rho p The numbers in italics indicate non-significant P values. All these groups of data were significantly correlated among them. It is remarkable that the subjective nutritional score correlated better with physical function tests than anthropometric data. CFS-CSHA, clinical frailty scale of Canadian study of health and aging; HGS%, handgrip strength by dynamometry (as percentage); MAMA, midarm muscular area; SNS (M), muscle component of Subjective Nutritional Score; Speed, gait speed developed at walking test; Stand up, stand up five times Japan Geriatrics Society

5 Prognostic value of muscle function Table 2 Data with prognostic value in elderly hospitalized patients Short- and long-term mortality 100 days OR (95% CI) Median survival HR (95%CI) Age >80 years 21/90 (23.3%) 2.33 ( ) 601 days 2.02 ( ) Age 80 years 24/208 (11.5%) Pneumonia 14/ 70 (20.0%) NS 680 days 1.61 ( ) No pneumonia 31/228 (13.6%) Cancer 13/52 (25.0%) 2.23 ( ) 341 days 2.39 ( ) No cancer 32/246 (13.0%) Pfeiffer >2 21/80 (26.3%) 2.86 ( ) 566 days 1.94 ( ) Pfeiffer 2 24/217 (11.1%) Charlson >3 23/107 (21.5%) 2.09 ( ) 722 days 1.68 ( ) Charlson 3 22/190 (11.6%) SNS >2 43/213 (20.2%) 10.5 ( ) 964 days 2.25 ( ) SNS 2 2/85 (2.4%) SNS M > 2 37/193 (19.2%) 2.88 ( ) 964 days 2.01 ( ) SNS M 2 8 /105 (7.6%) MAMA <10th percentile 19/107 (17.8%) NS 998 days NS MAMA >10th percentile 25/181 (13.8%) HGS <20% 37/190 (19.5%) 2.99 ( ) 964 days 1.81 ( ) HGS 20% 8/107 (7.5%) WTunable to perform 22/90 (24.4%) 2.60 ( ) 464 days 2.58 ( ) WT performed 22/199 (11.1%) Gait speed <0.8 m/s 41/248 (16.5%) NS 964 days 3.43 ( ) Gait speed 0.8 m/s 3/40 (7.5%) Standing balance = 0 24/95 (25.3%) 2.92 ( ) 462 days 2.72 ( ) Standing balance >0 20/193 (10.4%) Stand up = 0 24/106 (22.6%) 2.43 ( ) 566 days 2.27 ( ) Stand up >0 20/186 (10.8%) Walks 300 m/day 24/106 (22.6%) 2.38 ( ) 536 days 2.22 ( ) Walks m 21/192 (10.9%) Climbs stairs 22/99 (22.2%) 2.19 ( ) 676 days 1.84 ( ) Does not climb stairs 23/199 (11.6%) HGS <20% + speed <0.8 34/174 (19.5%) 2.55 ( ) 964 days 1.81 ( ) HGS <20% or speed <0.8 9/86 (10.5%) HGS 20% + speed 0.8 1/29 (3.4%) SPPB 0 20/78 (25.6%) 2.60 ( ) 459 days 2.67 ( ) SPPB /205 (11.7%) Sarcopenia SNS-M >2 36/176 (20.5%) 3.38 ( ) 722 days 2.39 ( ) No sarcopenia SNS-M >2 8 /113 (7.1%) Sarcopenia MAMA <10 18/91 (19.8%) NS 742 days 1.55 ( ) No sarcopenia MAMA <10 25/189 (13.2) Barthel 40 16/57 (28.1%) 2.85 ( ) 462 days 2.05 ( ) Barthel >40 29/241 (12.0%) IADL 0 16/59 (27.1%) 2.74 ( ) 462 days 2.55 ( ) IADL >0 25/209 (12.0%) Frailty (Fried) /100 (28.0%) 4.14 ( ) 742 days 2.08 ( ) Frailty (Fried) /198 (8.6%) CFS-CSHA /84 (25.0%) 2.63 ( ) 566 days 2.42 ( ) CFS-CSHA /213 (11.3%) All patients 45/298 (15.1%) 989 days Odds ratio (OR) was determined by 2 2 contingency tables. Hazard ratio (HR) was determined by Cox regression analysis. Sarcopenia always includes handgrip strength (HGS) <20% or speed <0.8 and muscle component of subjective nutritional score >2 inthefirst model or midarm muscular area (MAMA) <10th percentile in a second model. 95% CI, 95% confidence interval; ADL, basic activities of daily living; CFS-CSHA, clinical frailty scale of Canadian study of health and aging; IADL, instrumental activities of daily living; NS, not significant; SNS-M, muscle component of subjective nutritional score; SPPB, short physical performance battery; WT, walking test Japan Geriatrics Society 615

6 R Hernández-Luis et al. Table 3 Quantitative data with prognostic value on 100-day mortality Alive at 100 days Dead U MW P (n) mean±sem (n) mean ± SEM z Age (years) (253) 76.2 ± 0.43 (45) 78.8 ± Charlson Comorbidity Index (252) 2.99 ± 0.15 (45) 3.93 ± Pfeiffer test (252) 1.61 ± 0.13 (45) 2.78 ± Nutrition SNS (0 10) (253) 3.79 ± 0.16 (45) 5.29 ± <0.001 SNS-MM (0 6) (253) 2.90 ± 0.11 (45) 3.62 ± BMI kg/m2 (247) 27.7 ± 0.35 (44) 26.4 ± MAMA (%) (244) 86.9 ± 1.7 (44) 83.5 ± Albumin (g/dl) (244) 3.45 ± 0.04 (41) 3.20 ± IGF-1 (ng/ml) (171) ± 6.6 (29) ± Vitamin D 3 (183) 21.4 ± 1.4 (31) 23.1 ± Physical function tests Handgrip strength (%) (252) 21.4 ± 2.0 (45) 8.29 ± Gait speed (m/s) (244) 0.43 ± 0.02 (44) 0.27 ± Standing balance (0 4) (244) 1.80 ± 0.10 (44) 1.02 ± Stand up (0 5) (248) 2.65 ± 0.13 (44) 1.77 ± SPPB (0 6) (239) 2.80 ± 0.12 (44) 1 89 ± Disability and frailty Barthel test (253) 78.9 ± 1.8 (45) 62.0 ± ADL (249) 6.41 ± 0.16 (45) 4.78 ± <0.001 CFS-CSHA index (252) 3.96 ± 0.11 (45) 4.96 ± Fried Frailty Index (253) 2.72 ± 0.08 (45) 3.36 ± ADL, basic activities of daily living; BMI, body mass index; CFS-CSHA, clinical frailty scale of Canadian Study of Health and Aging; MAMA: midarm muscle area; IGF1, insulin-like growth factor 1; SNS, subjective nutritional score; SNS-M, muscle component of subjective nutritional score; SPPB, short physical performance battery. function impairment as HGS <20% or gait speed <0.8 m/s, and the muscle component of subjective nutritional assessment >2 (Table4). Discussion The first studies on sarcopenia and frailty were carried out in the general elderly population to screen for vulnerability. A low prevalence was thus described; the initial Fried study reported a prevalence of 7%. 4 However, in hospitalized patients, the prevalence is much higher, in our study, 60.4% of patients were considered frail, whereas just 3.4% were normal according to the Fried scale. As life expectancy has increased, the number of elderly patients with a high rate of comorbidity that are admitted to general internal medicine wards has risen. The present results show how in the elderly, progressive aging is related to malnutrition, with loss of muscle mass and impaired physical function. Furthermore, we report a thick network between nutrition, daily activity, physical function, disability and frailty. Mental impairment assessed by the Pfeiffer test is also related to malnutrition, impaired physical function, disability and frailty, which has been defined as cognitive frailty Low muscle mass, decreased gait speed, and reduced HGS are the bases of sarcopenia and frailty. Gait speed and HGS are the criteria considered most useful to define frailty. 21 It has been argued that sarcopenia and frailty are two sides of the same coin, being both markedly influenced by physical muscle function. In contrast, disability is the negative expression of muscle capacity assessed by physical function tests. 6 So, we asked ourselves about the relative importance of physical function tests compared with muscle mass. In many studies, the aging process is assessed only by physical function tests disregarding muscle mass. 9 11,19,22,23 It has been repeatedly reported that physical muscle function has a better prognostic value than muscle mass In accordance with this, we found that falls were related to impaired physical function tests and frailty, but not to muscle mass impairment. It has been reported that the risk for falls is related to physical function impairment. 27 HGS and gait speed at the walking test are two very simple and inexpensive tests that assess muscle function. It has been reported that the inability to carry out the walking test is closely related to a high mortality. 1,10,27,28 Of our patients, 90 (31%) did not carry out the walking test, with a median Japan Geriatrics Society

7 Prognostic value of muscle function Table 4 Multivariate analysis of long-term survival Long-term survival (Cox regression with covariates analysis) Variables with independent predictive value Wald P HR (95% CI) SPPB (0) ( ) Male ( ) Age >80 years ( ) HGS <20% or gait speed <0.8 m/s ( ) Charlson index > ( ) SNS Muscle > ( ) Variables included in Cox analysis besides those with independent predictive value were Global Subjective Nutritional Score, Fried Frailty Index and Clinical Frailty Scale of the Canadian Study of Health and Aging. HR: hazard ratio; CI 95%: 95% confidence interval; SPPB (0): 0 points at short physical performance battery, the patient did not perform any of the tests: gait speed, stand up and balance test. HGS <20%: Hand Grip Strength lower than 20% of young (20-29 year) healthy population; SNS Muscle: muscle component of Subjective Nutritional Score. survival of just 464 days. All the tests that assessed physical function were closely related to mortality. Besides addressing the question of whether muscle mass assessment improves the prognostic value of physical function, we must consider that the muscle mass assessment might be inaccurate by anthropometry, expensive by dual energy X-ray absorptiometry and requires training by bioimpedance. In the present study, subjective assessment of muscle mass is better related to muscle function, disability and prognosis than midarm muscle area. Furthermore, subjective assessment of muscle mass is a quick and inexpensive method related to short- and long-term prognosis. We argue that if we are inclined to assess most of the elderly hospitalized patients, we need innocuous, inexpensive and quick methods. Long-term survival multivariate analyses showed that physical function tests are the main independent predictive tests. The first variable selected in the analysis was the inability to carry out any test included in the SPPB (gait speed, standing balance and standing up). The second variable selected was the failure to develop a gait speed of 0.8 m/s or a HGS of 20% of standard. Furthermore, although the muscle mass component of the subjective nutritional score is closely related to physical function tests, it has an independent predictive value. We must recall the important function of muscle mass as a protein reserve with its consequent prognostic value. Also, a relationship between low muscle mass and functional decline in older adults has been reported. 29 Finally, the Charlson Comorbidity Index has an independent predictive value on mortality, which is not related to physical function or muscle mass. It has been reported that frailty indices that include comorbidity show a better prognostic value. 30 Age and male sex are well known factors, and do not require further explanation. In conclusion, the present results show an important role of muscle regarding prognosis in elderly hospitalized patients, mainly related to physical function, but also and independently regarding muscle mass. The present results encourage clinical trials of interventions aiming to improve muscle mass and function. Disclosure statement The authors declare no conflict of interest. References 1 Martín-Ponce E, Hernández-Betancor I, González-Reimers E, Hernández-Luis R, Martínez-Riera A, Santolaria F. Prognostic value of physical function tests: Hand grip strength and six-minute walking test in elderly hospitalized patients. Sci Rep 2014; 4: srep Cruz-Jentoft AJ, Baeyens JP, Bauer JM et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European working group on sarcopenia in older people. Age Ageing 2010; 39: Bianchi L, Ferrucci L, Cherubini A et al. The predictive value of the EWGSOP definition of sarcopenia: Results from the InCHIANTI study. J Gerontol A Biol Sci Med Sci 2016; 71: Fried LP, Tangen CM, Walston J et al. Frailty in older adults: Evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001; 56: M146 M Rockwood K, Song X, MacKnight C et al. A global clinical measure of fitness and frailty in elderly people. CMAJ 2005; 173: Cesari M, Landi F, Vellas B, Bernabei R, Marzetti E. Sarcopenia and physical frailty: Two sides of the same coin. Front Aging Neurosci 2014; 6: Pagotto V, Silveira EA. Methods, diagnostic criteria, cutoff points, and prevalence of sarcopenia among older people. Scientific World Journal 2014; 2014: /2014/ Japan Geriatrics Society 637

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