Sarcopenia and malnutrition in acutely ill hospitalized elderly: Prevalence and outcomes

Clinical Nutrition 34 (2015) 745e751

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Clinical Nutrition journal homepage: http://www.elsevier.com/locate/clnu

Original article

Sarcopenia and malnutrition in acutely ill hospitalized elderly: Prevalence and outcomes Anna Paola Cerri a, Giuseppe Bellelli a, b, c, *, Andrea Mazzone a, Francesca Pittella a, Francesco Landi d, Antonella Zambon e, Giorgio Annoni a, b, c a

Department of Health Sciences, University of Milano-Bicocca, Italy Geriatric Clinic, San Gerardo Hospital, Monza, Italy Milan Center for Neuroscience (Neuro-Mi), Milan, Italy d Department of Gerontology and Geriatrics, Catholic University of Sacred Heart, Roma, Italy e Department of Statistics and Quantitative Methods, Unit of Biostatistics, Epidemiology and Public Health, University of Milano-Bicocca, Milano, Italy b c

a r t i c l e i n f o

s u m m a r y

Article history: Received 29 March 2014 Accepted 29 August 2014

Background & aims: Data about the prevalence of sarcopenia among hospitalized patients is lacking and it is unclear whether the diagnostic criteria commonly used in community-dwellers is applicable in acutely ill subjects. The aims of this report are: (i) to assess the prevalence of sarcopenia among hospitalized patients; (ii) to assess whether the European Working Group on Sarcopenia in Older People (EWGSOP) criteria are applicable in an acute care setting; and (iii) to assess the mortality rate at 3 months. Methods: 103 patients admitted to the Acute Geriatric Clinic were enrolled. Inclusion criteria were: age
65 years and malnutrition or risk of malnutrition, according to the Mini Nutritional Assessment Short Form. Sarcopenia was diagnosed using the EWGSOP criteria by means of bioimpedance analysis, handgrip strength and gait speed, within 72 h of admission. Information on deaths was obtained by telephone interview at 3 months following discharge. Results: Sarcopenia was diagnosed in 22 patients (21.4%). Twenty-three patients (22.3%) were not able to perform the gait speed and/or the handgrip strength because bedridden or requiring intensive treatments. In this group, a definite diagnosis of sarcopenia was not possible, lacking at least one EWGSOP criteria. Eleven (10.7%) patients died within the 3 months post-discharge period. KaplaneMeier survival curves showed that sarcopenic patients died significantly more frequently than others (log-rank p  0.001). Conclusions: In a population of hospitalized elderly malnourished or at risk of malnutrition, sarcopenia is highly prevalent and associated with an increased risk to die in the short-term. Furthermore, the EWGSOP criteria cannot be satisfactorily applied in a relevant proportion of patients. © 2014 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Keywords: Sarcopenia Hospital EWGSOP criteria Mortality Elderly

1. Introduction Sarcopenia is a loss of muscle mass and strength and/or reduced physical performance which is associated with an increased risk of incident disability, falls, all-cause mortality and increased healthcare costs [1e4]. Estimates of the prevalence of sarcopenia in

* Corresponding author. Department of Health Sciences, University of MilanoBicocca, via Cadore 48, 20900 Monza, MB, Italy. Tel.: þ39 039 233 3475; fax: þ39 039 233 2220. E-mail address: [email protected] (G. Bellelli).

older subjects worldwide vary from 3% to 30% according to the operational definition implemented and to the settings considered in the studies [5e7]. In 2010, the European Working Group on Sarcopenia in Older People (EWGSOP) has published a consensus definition based on the measurement of lean mass, grip strength and gait speed, stating that low lean mass and either low grip strength or slow gait speed are required to make the diagnosis [1]. One year later, the International Working Group on Sarcopenia (IWGS) suggested that a diagnosis of sarcopenia could be obtained on the basis of low gait speed and an objectively measured low muscle mass [8]. In the same year, another consensus conference [9] reinforced the same

http://dx.doi.org/10.1016/j.clnu.2014.08.015 0261-5614/© 2014 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

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concept. It is therefore evident, from these definitions, that low gait speed is a key point for the diagnosis. However, gait speed can be assessed only in specific patient populations; in fact, most studies investigated the prevalence of sarcopenia and its outcomes in community-dwelling subjects [3,10] or in patients with mild physical disability, but there are few data regarding the applicability of the international criteria in populations with major disability or with acute clinical illnesses. In literature, only two studies were conducted among hospitalized patients. Gariballa et al., [11] diagnosed sarcopenia on the basis of detection of low muscle mass (measured by mid-arm muscle circumference) and low muscle strength (using a handgrip dynamometer), but no tests of physical performance (such as gait speed) were included in the assessment. Rossi et al., [12] in a study on 119 acutely ill patients admitted to a geriatric unit, assessed sarcopenia using the EWGSOP criteria but gait speed test was possible only in little more than the half population. Malnutrition is a common [13] geriatric syndrome which has been recognized as a risk factor for sarcopenia and frequently coexists with it [14]. Like sarcopenia, malnutrition is associated with substantial adverse outcomes, affecting both the patient and the healthcare system, and including increased morbidity, mortality, rehospitalization rates and healthcare costs [15,16]. Nonetheless, there is no published data assessing the prevalence and the impact of the two associated conditions in patients in an acute hospital setting. Therefore, we designed this study to investigate: a) the prevalence of sarcopenia; b) the applicability of EWGSOP criteria; and c) the impact of sarcopenia on 3-month survival in a population of elderly patients admitted to an Acute Geriatric Unit (AGU) with malnutrition or at risk of malnutrition. 2. Materials and methods 2.1. Setting This was a prospective observational study of elderly inpatients (i.e. >65 years) consecutively admitted to the AGU of the S. Gerardo University Hospital, Northern Italy, between January and June 2013. The AGU is a 38-bed unit, staffed with specially trained nurses and geriatricians, has a nurse to patient ratio of 1:5 and a physician available 24 h a day. Patients selected for the AGU are elderly patients with reacutization of chronic critical illnesses, requiring frequent monitoring of vital signs and/or intensive interventions. The majority of AGU patients are generally admitted directly from the emergency department (90%), principal diagnoses including pulmonary diseases, cardiovascular diseases, cancer, acute cerebrovascular diseases, infections of the urinary tract, diabetes and dementia [17]. The Ethics Committee of the Milano-Bicocca University approved the study. We obtained an informed consent from all patients or their next of kin when the patients were not capable of giving informed consent due to severe cognitive impairment.

neuropsychological problems such as depression or dementia, anthropometric measures (body mass index in kg/m2 or calf circumference in cm). A score ranging from 0 to 7 points means malnutrition; a score ranging from 8 to 11 points denotes risk of malnutrition, while a score ranging from 12 to 14 points denotes normal nutritional status. Exclusion criteria were: (1) being moderately to severely drowsy or delirious on admission; (2) being bedridden for three months or more, (3) having end-stage malignancies, (4) having hyperpyrexia (temperature >38  C) or hypothermia (temperature <36  C) within the first 48 h following admission; and (5) having anasarca. The flowchart of study participants is shown in Fig. 1. Of the 283 patients admitted to the AGU, 87 patients were not included because well nourished, according to MNA-SF, and 93 patients were excluded because they were delirious (n ¼ 50), bedridden for at least three months (n ¼ 14), or had end-stage malignancies (n ¼ 15) and/or hyperpyrexia (n ¼ 2); twelve patients were further excluded because of the presence of anasarca which obstructed the execution of BIA. 2.3. Comprehensive geriatric assessment In the 48 h following hospital admission, all subjects underwent a Comprehensive Geriatric Assessment (CGA), including demographic, functional, cognitive, nutritional and global health status evaluation. The functional status was assessed with the Katz's activities of daily living (ADL) [20], through patient and surrogate interview, referring to one month prior to admission and assigning a score of 1 for complete independence while 0 for dependence in each of the 6 basic ADLs (bathing, dressing, transfer from bed to chair, toileting, continence and feeding). Comorbidity was assessed with the Charlson Comorbidity Index, a score that takes into account specific chronic conditions, which significantly impact on patients' survival [21]. Nutritional status was assessed using the MNA-SF, the albumin serum levels and the body mass index (BMI). BMI was defined as weight (kilograms) divided by the square of height (meters). The modified-Richmond AgitationeSedation Scale (m-RASS) [22] was used to assess patients' drowsiness or agitation. The mRASS is a 10-point scale, which has been validated in medical units, assessing four levels of anxiety or agitation (restless, agitated, very agitated, combative), one level of normality, and five levels of sedation (drowsy, light, moderate, deep sedation, unarousable). Scores can range from þ4 (combative, violent) to 5 (unarousable); a score ¼ 0 denotes a patient alert and calm. A score of m-RASS <1 was deemed to indicate drowsiness. Delirium was diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition e Text Revised (DSM-IV-TR) [23] criteria. The DSM-IV-TR criteria are widely accepted as the gold standard method when diagnosing delirium in geriatric and medical units. 2.4. Diagnosis of sarcopenia

2.2. Selection of the sample Participants were all patients consecutively recruited from inpatients admitted to the AGU between January and June 2013. Patients were eligible for inclusion if they were aged 65 years or older and had a diagnosis of malnutrition or risk of malnutrition, obtained by using the Mini Nutritional Assessment-Short Form (MNASF) [18]. The MNA-SF is a validated tool comprising 6 items from the full Mini Nutritional Assessment [19], which assesses: appetite loss and weight loss during the last three months, mobility problems, psychological stress or acute disease in the past three months,

For this study, we followed the criteria of the European Working Group on Sarcopenia in Older People (EWGSOP) [1]. According to their recommendation, diagnosis of sarcopenia in the present study sample required the documentation of low muscle mass plus the documentation of either low muscle strength or low physical performance. Muscle mass was measured by bioelectrical impedance analysis (BIA). The BIA resistance (ohms, U) was obtained using a Quantum/ S Bioelectrical Body Composition Analyzer (Akern Srl, Florence, Italy) with an operating frequency of 50 kHz at 800 mA. Whole-

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Fig. 1. Flowchart of study participants. BIA ¼ bioelectrical impedance analysis; HG ¼ handgrip strength; GS ¼ gait speed; SMI ¼ skeletal mass index. N.a. ¼ not applicable. Of the 283 patients admitted to the AGU, 87 patients were not included because well nourished, according to MNA-SF, and 93 patients were excluded because they were delirious (n ¼ 50), bedridden for at least three months (n ¼ 14), or had end-stage malignancies (n ¼ 15) and/or hyperpyrexia (n ¼ 2); twelve patients were further excluded because of the presence of anasarca which obstructed the execution of BIA.

body bioelectrical impedance analysis measurements were taken between the right wrist and ankle with the subject in a supine position. Muscle mass (SM mass) was calculated using the bioelectrical impedance analysis equation of Janssen and colleagues [24]: SM mass (kg) ¼ [(Ht2/ Rz  0.401) þ (gender  3.825) þ (age  0.071)] þ 5.102 Ht ¼ height measured in centimeters; Rz ¼ bioelectrical impedance analysis resistance, measured in ohms; for gender man ¼ 1 and women ¼ 0; age is measured in years Absolute skeletal muscle mass was converted to skeletal muscle index (SMI) by dividing height by meters squared (kg/m2) [1]. Low muscle mass was defined as the SMI of 2 standard deviations (SDs) or more below the normal sex-specific means for young persons. Low muscle mass was classified as an SMI less than 8.87 kg/m2 in men and 6.42 kg/m2 in women, using the cutoff points indicated in the EWGSOP consensus paper. Muscle strength was assessed by handgrip strength, which was measured using a Jamar hydraulic hand dynamometer [25]. Measurement is performed with the individual seated on a chair without armrest and with feet flat on the floor, shoulder adducted, the elbow flexed at 90 , the forearm in a neutral position, and the wrist between 0 and 30 extension. Three trials for the dominant hand were performed, with a one-minute rest interval between tests, and the best result was used for the present analyses. Using the cut-off points indicated in the EWGSOP consensus, low muscle

strength was classified as handgrip less than 30 kg and 20 kg in men and women, respectively [1]. Walking speed was evaluated measuring participants usual gait speed (in m/sec) over a 4-m course. As suggested in the EWGSOP criteria, a cut-off point of <0.8 m/s identifies subjects with poor physical performance [1]. The EWGSOP criteria and the cut-off values are summarized in Table 1. The evaluations with BIA, handgrip and gait speed were conducted within 72 h of admission. 2.5. Follow-up We recorded mortality during hospital stay and at 3 months following hospital admission in all patients who participated in the

Table 1 EGWSOP criteria for diagnosing sarcopenia. Criterion

Method to assess

Cut-off values by gender

Low muscle mass

Skeletal muscle mass index (SMI) is assessed using Bioimpedance analysis (BIA)

Low muscle strength Poor physical performance

Muscle strength is assessed using Handgrip strength Physical performance is assessed measuring gait speed (4-mt course)

BIA predicted skeletal muscle mass (SM) equation (SM/height2): men: <8.87 kg/m2 women: <6.42 kg/m2 men: <30 kg women: <20 kg men: <0.8 m/s women: <0.8 m/s

Diagnosis of sarcopenia is based on the documentation of criterion1 plus (criterion 2 or criterion 3).

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Table 2 Characteristics of 103 study participants according to the presence of all, neither or only one EWGSOP criteria for diagnosing sarcopenia. Patients with sarcopenia were older and had a lower BMI in comparison to those without sarcopenia. Overall, the Charlson Comorbidity Index and the distribution of diseases were similar among the three groups, as well as the length of hospital stay. No differences were observed with regard to the other variables. Characteristics Age, years Gender, n (%) Males Females Living status before admission, n (%) Home with or without relatives Home with caregiver Nursing home or Rehabilitation Centre Katz's Activities of Daily Living (ADL) score before admission, median (IQR) Charlson Comorbidity Index, median (IQR) Myocardial infarction, n (%) Congestive heart failure, n (%) Peripheral Vascular disease, n (%) Cerebrovascular diseases, n (%) Dementia, n (%) Chronic obstructive pulmonary disease, n (%) Connective tissue diseases, n (%) Peptic ulcer disease, n (%) Mild liver disease, n (%) Diabetes, n (%) Diabetes with end-organ damage, n (%) Hemiplegia, n (%) Moderate or severe renal disease, n (%) Tumor without metastasis, n (%) Hematologic malignancy, n (%) Severe liver disease, n (%) Body Mass Index, Kg/m2 Mini nutritional assessment short form 8e11 at risk of malnutrition, n (%) <8 Malnourished, n (%) Albumin serum levels (gr/dl), median (IQR) Length of stay (days), median (IQR)

Total sample n ¼ 103

No sarcopenia n ¼ 58 b

Sarcopenia n ¼ 22 a

Uncertain diagnosis n ¼ 23

p

84.2 ± 5.9

0.05 0.79

84.2 ± 7.1

83.1 ± 7.9

42 (40.8) 61 (59.2)

22 (37.9) 36 (62.1)

10 (45.5) 12 (54.5)

10 (43.5) 13 (56.5)

78 (75.7) 20 (19.4) 5 (4.9) 4 (1e5)

47 (81) 9 (15.5) 2 (3.4) 4 (2e6)

15 (68.2) 4 (18.2) 3 (13.6) 3 (1e5)

16 (69.6) 7 (30.4) 0 3.5 (1.8e5)

2 (1e3) 15 (14.6) 13 (12.6) 16 (15.5) 26 (25.2) 29 (28.2) 15 (14.6) 4 (3.9) 5 (4.9) 3 (2.9) 21 (20.4) 5 (4.9) 11 (10.7) 9 (8.7) 9 (8.7) 3 (2.9) 1 (1.0) 22.8 ± 4.9

1.5 (1e3) 6 (10.3) 4 (6.9) 6 (10.3) 10 (17.2) 12 (20.7) 10 (17.2) 3 (5.2) 2 (3.4) 1 (1.7) 15 (25.9) 4 (6.9) 8 (13.8) 3 (5.2) 4 (6.9) 2 (3.4) 1 (1.7) 23.9 ± 5.1b

2.5 (0.8e4) 4 (18.2) 4 (18.2) 6 (27.3) 8 (36.4) 7 (31.8) 4 (18.2) 1 (4.5) 2 (9.1) 2 (9.1) 2 (9.1) 0 0 4 (18.2) 3 (13.6) 1 (4.5) 0 21.1 ± 4.2a

2 (1e3.3) 5 (21.7) 5 (21.7) 4 (17.4) 8 (34.8) 10 (43.5) 1 (4.3) 0 1 (4.3) 0 4 (17.4) 1 (4.3) 3 (13) 2 (8.7) 2 (8.7) 0 0 21.5 ± 4.5

0.49 0.36 0.13 0.17 0.10 0.11 0.28 0.54 0.57 0.14 0.23 0.43 0.19 0.18 0.63 0.62 0.67 0.03

58 (56.3) 45 (43.7) 3.4 (3.1e3.8) 10 (8e14)

35 (60.3) 23 (39.7) 3.4 (3.1e3.7) 10 (8e14)

11 (50) 11 (50) 3.5 (3.2e3.8) 9 (6e14.3)

12 (52.2) 11 (47.8) 3.4 (3.2e3.9) 11 (8e15.3)

0.63

87.4 ± 4.8

0.12 0.14

0.26 0.37

Data are shown as mean ± standard deviation unless otherwise specified. P denotes significance at the Chisquare Test (gender, living status before admission, specific diseases, nutritional status), one-way analysis of variance (age and Body mass Index) or KruskaleWallis (Katz's ADL Index, Charlson Comorbidity Index score, albumin serum levels, length of stay), respectively. Where significant group effects were detected, GameseHowell test indicated significant post hoc differences between individual groups, as follows: a, significant difference to the group without sarcopenia; b, significant difference to the group with sarcopenia.

survey. Information on deaths was obtained by telephone/structured interview.

All analyses were performed using the software PASW Statistics 19.0 Version (IBM SPSS Corp., NY, USA). For all tests the statistical significance was set at the .05 level.

2.6. Statistical analyses 3. Results Continuous variables are presented as mean ± standard deviation or median (interquartiles), where appropriate, while categorical data is presented as number and proportions. Differences in socio-demographic, functional, and clinical characteristics between patients were analyzed. Quantitative parameters with normal distribution were tested by one-way analysis of variance, after a pretest for homogeneity of variances. If abnormal distribution was present, a nonparametric test was used (KruskaleWallis rank test). Categorical variables were analyzed by the chi-square test. Where significant group effects were detected, GameseHowell test was used to assess significant post hoc differences between individual groups. We examined the mortality rate over a 3-month period following hospital admission. Time to death was calculated from the date of hospital admission to the date of death. An unadjusted survival analysis was conducted for the entire cohort and stratified according to patients groups (i.e., non sarcopenic, sarcopenic and those with reduced SMI but handgrip strength and/or gait speed not applicable) with a KaplaneMeier approach. The log-rank test was used to compare the survival functions of three samples. In order to control for the type I error, a multiple comparison adjustment was performed by a Sidak approach.

The recruited population was composed by 103 patients, with a mean age of 84.2 ± 7.1 years (range: 66e100), predominantly females (59.2%). Patients with a definite diagnosis of sarcopenia were 22 (21.4%), while 58 (56.3%) had no sarcopenia. The remaining 23 patients (22.3%) were not able to perform the gait speed test and/or the handgrip strength because of an acute disabling illness (i.e., acute respiratory failure, stroke, congestive heart failure or hip fracture), possibly requiring an intensive clinical approach. In these patients, a definite diagnosis of either sarcopenia or no-sarcopenia was not possible, lacking at least one of the EWGSOP criteria. The socio-demographic, functional, cognitive and clinical characteristics of study participants are summarized in Table 2. Patients with sarcopenia were older and had a lower BMI in comparison to those without sarcopenia. Overall, the Charlson Comorbidity Index and the distribution of diseases were similar among the three groups, as well as the length of hospital stay. No differences were observed with regard to the other variables. The patients' performances in the tests required for diagnosing sarcopenia are shown in Table 3. It should be noted that handgrip strength was obtained in 53 patients (29 in the patients with no

A.P. Cerri et al. / Clinical Nutrition 34 (2015) 745e751 Table 3 Patients' performance in the tests required for diagnosing sarcopenia. Skeletal Mass Index was measured in all patients (n ¼ 103). The handgrip strength was obtained in 53 patients (29 in the patients with no sarcopenia, 22 in the patients with sarcopenia and 2 in the patients with uncertain diagnosis), while gait speed was obtained in 23 patients (13 in the patients without sarcopenia and 10 in those with sarcopenia). Characteristics

Total sample n ¼ 103

Skeletal Mass Index (SMI), kg/m2a Males (n ¼ 57) 9 ± 1.6 Females (n ¼ 46) 6.9 ± 1.5 Handgrip strength, kgb Males (n ¼ 24) 25.1 ± 7.5 Females (n ¼ 29) 15 ± 8.5 c Gait speed, m/s Males (n ¼ 14) 0.6 ± 0.3 Females (n ¼ 9) 0.6 ± 0.2

No sarcopenia n ¼ 58

Sarcopenia n ¼ 22

Uncertain diagnosis n ¼ 23

10.3 ± 1.2 7.9 ± 1

7.7 ± 0.8 5.4 ± 0.6

7.8 ± 0.7 5.7 ± 0.7

24.1 ± 8.8 18.4 ± 8.6

26.5 ± 4.5 9.4 ± 5.6

30 20

0.7 ± 0.3 0.5 ± 0.2

0.4 ± 0.3 0.7 ± 0.2

e e

a

n ¼ 103 patients. n ¼ 53 patients (29 in patients without sarcopenia, 22 in patients with sarcopenia, 2 in patients with uncertain diagnosis). c n ¼ 23 patients (13 in patients without sarcopenia, 10 in patients with sarcopenia). b

sarcopenia, 22 in the patients with sarcopenia and 2 in the patients with uncertain diagnosis), while gait speed was obtained in 23 patients (13 in the patients without sarcopenia and 10 in those with sarcopenia). At the 3-month follow-up there were three deaths in the group of patients with no sarcopenia (5.2%), seven (31.8%) in the group with sarcopenia, and one in the group with uncertain diagnosis (4.3%). In-hospital death occurred only in patients with sarcopenia (n ¼ 4). KaplaneMeier survival curves were obtained for the 3 groups, showing that, at 3 months, sarcopenic patients

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died more frequently than others (Fig. 2). The results for the logrank statistic were highly significant (log-rank p ¼ 0.0005) and the multiple comparison adjustment by Sidak approach demonstrated that patients with sarcopenia differed from those without sarcopenia (p ¼ 0.003) and from those with uncertain condition (p ¼ 0.006). 4. Discussion This study shows that in a population of hospitalized elderly patients with malnutrition or at risk of malnutrition: (i) the prevalence of sarcopenia is high; (ii) the EWGSOP criteria cannot be satisfactorily applied in a relevant proportion of patients; (iii) at 3-month follow-up, patients with sarcopenia died significantly more commonly than patients in the other groups. Only two previous reports assessed the prevalence of sarcopenia in hospitalized elderly subjects. Gariballa et al., in a cohort of 432 acutely ill patients [11], found a prevalence of 10% while Rossi et al., [12] in a population of 119 elderly admitted to an acute care department, found a prevalence of 26%. Explanations for the differences between our and their studies include the methods to assess sarcopenia and the patients' characteristics. Gariballa and colleagues diagnosed sarcopenia using anthropometric measures (i.e., low mid-arm muscle circumference) and low muscle strength but did not include gait speed or BIA in their assessment. Rossi and colleagues assessed their patients using the same diagnostic approach that we adopted in the current study. However, while in Rossi's study all patients were able to complete the three tests recommended by the EWGSOP criteria, in our study we found that a relevant proportion of patients (more than a fifth of the whole population) were not able to perform either the gait speed or the handgrip test. This is a novel

Fig. 2. Survival curves of study participants at 3-month followeup. Gray solid line denotes non sarcopenic patients; black dotted line patients with uncertain diagnosis; black solid line denotes sarcopenic patients. The KaplaneMeier survival curves show that, at 3 months, sarcopenic patients died more frequently than others. The results for the log-rank statistic were highly significant (log-rank p ¼ 0.0005) and the multiple comparison adjustment by Sidak approach demonstrated that patients with sarcopenia differed from those without sarcopenia (p ¼ 0.003) and from those with uncertain condition (p ¼ 0.006).

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finding in the literature and deserves further comments In fact, in previous studies on community-dwellers, the EWGSOP criteria have always been applied [3,10]. The three tests recommended by the European consensus have been successfully performed also in a population of nursing home patients [26]. It could therefore be hypothesized that, in contrast to the other studies, we enrolled a population with an increased burden of frailty and disability, which hampered the completion of those tests that required an even minimal level of muscular force and intact walking abilities. This is also indicated by the median ADL scores of our patients, which denoted a considerably lower functional status than that of previous studies. A possible explanation of this finding is that we enrolled patients with malnutrition or at risk of malnutrition, two conditions which are known to be associated with disability and development of acute medical illnesses [27,28]. In fact, on admission, most of our patients were bedridden due to acute illnesses (i.e., severe congestive heart or respiratory failure, hip fractures, acute stroke) or required an intensive clinical approach, making the assessment of a reliable handgrip test and/or gait speed unsuitable. Although further research is needed, this observation suggests that current criteria for sarcopenia is flawed for hospitalized elderly populations and also that more accurate criteria are required to detect sarcopenia in patients unable to walk or to perform the handgrip test. The defect of current criteria to detect sarcopenia in many hospitalized elderly patients has already been highlighted by other authors [29]. Another interesting finding of our study is that we have demonstrated that sarcopenic patients are more likely to die at 3 months in comparison to non sarcopenic and undiagnosed sarcopenic patients. This finding is in line with previous studies among community-dwelling older people and nursing home patients [3,26]. Sarcopenia can be considered as a geriatric syndrome, which plays a crucial role in the frailty process which may lead to dramatic consequences such as falls, disability, and ultimately death [30]. A novelty of this study is the assessment of sarcopenia in acutely ill elderly patients with malnutrition or at risk of malnutrition; in fact, no previous studies have evaluated the combination of these two conditions in a similar population. We found that in many cases malnutrition assessment did not exactly match the definition of sarcopenia, suggesting that broader criteria are necessary. Alternatively, or even in addition, specific tools to identify sarcopenia in undernourished patients could be useful. A potential implication of our findings is that patients with malnutrition or at risk of malnutrition should be regarded as targets for future medication preventing the agerelated skeletal muscle decline in hospitalized patients. Furthermore, future studies should also assess whether sarcopenia related to malnutrition could have different outcomes than malnutrition unrelated to sarcopenia in hospitalized patients. The strengths of our study include an evaluation with BIA of all the subjects enrolled in the study and the patient's baseline comprehensive geriatric assessment, which was performed within 48 h after hospital admission. Another strength is the follow-up rate, which was 100% at 3 months. Limits of the study are that we did not record the causes of death and that the follow-up lasted only 3 months. Further studies with longer follow-up duration and collection of the causes of death are expected to confirm our results. In conclusion, this study shows that EWGSOP criteria to diagnose sarcopenia cannot be satisfactorily applied in a relevant proportion of acutely ill hospitalized patients and confirms that sarcopenic patients are more prone to die than non-sarcopenic in a short follow-up period.

Conflict of interest The authors have no conflict of interests to disclose, and do not receive any funding for this study.

Acknowledgments Sincere appreciations to Mrs Margaret Warren for revising the English language and to Pamina Baccella, Valentina Broggini, Lucio Carnevali, Alice Corno, Marianna Marinelli, Linda Sassi e Sara Zazzetta for their contribution in data collection.

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