Association of Subjective Global Assessment and Adductor pollicis muscle thickness with the Sarcopenia in older patients with type 2 diabetes

Open AccessPublished:November 29, 2021DOI:https://doi.org/10.1016/j.nutos.2021.11.006

      Summary

      Background and Aim

      Sarcopenia is prevalent in older patients and increases the risk for negative outcomes during hospitalization and after hospital discharge. In patients with type 2 diabetes (T2D) this association may be even worse. Upon hospital admission, it is often difficult to identify sarcopenia, so the objective of this study was to assess whether the subjective global assessment (SGA), the European Society for Clinical Nutrition and Metabolism (ESPEN) and Global Leadership Initiative on Malnutrition (GLIM) criteria and/or usual anthropometric measures can predict sarcopenia. A secondary objective, to evaluate the accuracy of variables in the prediction of sarcopenia.

      Methodology

      Patients ≥60 years old and with T2D were included. Malnutrition was evaluated in accordance with the guidelines of ESPEN and GLIM, and SGA. Anthropometric measurements were performed by Mid-arm circumference (MAC), mid-upper arm muscle circumference (MUAMC), and adductor pollicis muscle thickness (APMT) was performed. The sarcopenia was evaluated by handgrip strength, timed Up and Go (TUG) test and muscle mass by measuring the calf circumference (CC). Logistic regression was performed to assess the association of variables with Sarcopenia.

      Results

      A total of 311 patients were included. The prevalence of malnutrition in accordance to ESPEN, GLIM and SGA was 18 (5.8%), 65 (21%) and 15 (4%), respectively. The MAC and MUAMC showed a negative relationship with sarcopenia (HR: 0.92 CI95% 0.85–0.99). However, patients with overweight had a 66% reduction in the risk of sarcopenia (HR: 0.34 CI95% 0.19–0.59). After adjustments, malnourished patients according to the SGA had a risk of HR: 5.65 (CI95% 1.64–19.38) of sarcopenia, similarly to patients with APMT <5 th HR: 2.81 (CI95% 1.53–5.13), ESPEN and GLIM criteria presented HR:3.10 (CI95%1.12–8.22) and HR:2.94 (CI95%1.64–5.27), respectively. The interaction between SGA and APMT after adjusting the model has been significant (HR: 7.23 CI95% 2.98–17.67). In the area under the curve (ROC), only SGA + APMT showed greater accuracy in the prediction of sarcopenia (AUC: 0.713 CI95% 0.650–0.803).

      Conclusion

      In our sample, it was possible to predict sarcopenia through the malnutrition criteria of ESPEN and GLIM, SGA, MAC and APMT. Measures such as APMT associated with the SGA tool seem to better predict sarcopenia in older patients with T2D.

      Keywords

      Introduction

      Older people with type 2 diabetes (T2D) are more susceptible to adverse events and complications during a hospitalization which can cause an increased length of stay, malnutrition, functional decline, unscheduled surgeries, and higher rates of mortality [
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      ]. Studies in different clinical conditions show the damage caused by the presence of sarcopenia in older patients and the sarcopenia and DM2 coexist tends to increase the chance of mortality, even after hospital discharge [
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      The body composition of patients with diabetes has particularities, such as high body fat, accelerated and early decline in muscle mass and strength [
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      Decreased muscle strength and quality in older adults with Type 2 diabetes.
      ], as well as poor muscle quality when compared to non-diabetic subjects [
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      ,
      • Kim K.S.
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      • Kim M.J.
      • Kim S.K.
      • Cho Y.W.
      • Park S.W.
      Type 2 diabetes is associated with low muscle mass in older adults.
      ]. The presence of sarcopenia in individuals with T2D increases the risk of falls and fractures [
      • Sarodnik C.
      • Bours S.P.G.
      • Schaper N.C.
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      • Van Geel T.A.C.M.
      The risks of sarcopenia, falls and fractures in patients with type 2 diabetes mellitus.
      ], thus, the nutritional assessment of these patients needs to be carried using tools that make it possible to detect body changes and identify the risk of sarcopenia.
      The Subjective Global Assessment (SGA) is a tool widely used in different locations and hospitals [1319], it presents a good prediction with a length of hospital stay [
      • Detsky A.S.
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      Use of subjective global assessment and clinical outcomes in critically ill geriatric patients receiving nutrition support.
      ], and mortality [
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      • et al.
      Nutritional screening with subjective global assessment predicts hospital stay in patients with digestive diseases.
      ,
      • da Silva Fink Jaqueline
      • Daniel de Mello Paula
      • Daniel de Mello Elza
      Subjective global assessment of nutritional status a systematic review of the literature.
      ] and is related to sarcopenia, identifying that those with sarcopenia are also malnourished [
      • Onishi Sachiyo
      • Shiraki Makoto
      • Nishimura Kayoko
      • Hanai Tatsunori
      • Moriwaki Hisataka
      • Shimizu Masahito
      Prevalence of Sarcopenia and its relationship with nutritional state and quality of life in patients with digestive diseases.
      ]. The new guidelines proposed for assessing malnutrition can also be used in individuals with sarcopenia [
      • Cederholm T.
      • Bosaeus I.
      • Barazzoni R.
      • Bauer J.
      • Van Gossum A.
      • Klek S.
      • et al.
      Diagnostic criteria for malnutrition - An ESPEN consensus statement.
      ,
      • Cederholm T.
      • Jensen G.L.
      • Correia M.I.T.D.
      • Gonzalez M.C.
      • Fukushima R.
      • Higashiguchi T.
      • et al.
      GLIM criteria for the diagnosis of malnutrition - A consensus report from the global clinical nutrition community.
      ]. The European Society for Clinical Nutrition and Metabolism (ESPEN) criteria considers sarcopenia as one of the arms of the conceptual tree of nutritional disorders [
      • Cederholm T.
      • Bosaeus I.
      • Barazzoni R.
      • Bauer J.
      • Van Gossum A.
      • Klek S.
      • et al.
      Diagnostic criteria for malnutrition - An ESPEN consensus statement.
      ]. The Global Leadership Initiative on Malnutrition (GLIM) criteria included three phenotypic criteria (weight loss, low body mass index, and reduced muscle mass) and two etiologic criteria (reduced food intake or assimilation, and inflammation or disease burden) and can be used for assessing malnutrition in adults, people with cachexia, frailty and sarcopenia [
      • Cederholm T.
      • Jensen G.L.
      • Correia M.I.T.D.
      • Gonzalez M.C.
      • Fukushima R.
      • Higashiguchi T.
      • et al.
      GLIM criteria for the diagnosis of malnutrition - A consensus report from the global clinical nutrition community.
      ].
      Anthropometric measures are used to complement the nutritional assessment of adult and older patients [
      • Frisancho R.A.
      New norms of upper limb fat and muscle areas for assessment of nutritional status.
      ], are easy-to-measure and low-cost measures. The Mid-arm circumference (MAC) and the tricipital skinfold (TS), from which we can use the MAC alone or calculate the mid-upper arm muscle circumference (MUAMC). The MUAMC has a good relationship with the muscular depletion of older patients [
      • Frisancho R.A.
      New norms of upper limb fat and muscle areas for assessment of nutritional status.
      ], a good association with sarcopenia in institutionalized patients [
      • Rodriguez-Rejon Ana Isabel
      • Artacho Reyes
      • Dolores Ruiz-Lopez María
      Anthropometric measurements and cognitive impairment rather than nutrition status are associated with sarcopenia in long-term care residents.
      ], patients with cirrhosis [
      • Santos Lívia A.A.
      • Lima Talles B.
      • do Val Ietsug Marjorie
      • de Carvalho Nunes H.R.
      • Qi X.
      • Romeiro F.G.
      • et al.
      Anthropometric measures associated with sarcopenia in outpatients with liver cirrhosis.
      ], and cancer patients in palliative care [
      • Rodrigues da Silva Jr., Jaqueline
      • Wiegert Emanuelly Varea Maria
      • Oliveira Livia
      • Calixto-Lima Larissa
      Different methods for diagnosis of sarcopenia and its association with nutritional status and survival in patients with advanced cancer in palliative care.
      ], in addition to being a predictor for mortality [
      • Landi F.
      • Russo A.
      • Liperoti R.
      • Pahor M.
      • Tosato M.
      • Capoluongo E.
      Midarm muscle circumference, physical performance and mortality: Results from the aging and longevity study in the Sirente geographic area (ilSIRENTE study).
      ]. The measurement of the adductor pollicis muscle (APMT) demonstrates a good association with sarcopenia in cancer patients, as well as a good marker for low muscle strength [
      • Rechinelli A.B.
      • Marques I.L.
      • de Morais Viana Eduarda Cristina Rodrigues
      • da Silva Oliveira Isadora
      • de Souza Vanusa Felício
      • Petarli G.B.
      • et al.
      Presence of dynapenia and association with anthropometric variables in câncer patients.
      ].
      Due to the differences in body composition of the older with T2D and the increased risk of sarcopenia in these patients, as well as the difficulty of assessing sarcopenia on hospital admission, this study aimed to assess whether SGA, ESPEN and GLIM criteria, classic anthropometric measurements such as MAC, MUAMC, APMT, predicts sarcopenia in hospitalized older patients. As a second objective, we evaluated the accuracy of the tools in prediction.

      Materials and methods

       Study population

      A prospective review was performed in a cohort of 311 patients ≥60 years old with T2D, admitted to the Southern Brazil University Hospital from July 2015 to December 2017 were considered eligible. We did not include surgical patients or with neurological sequelae, those who could not walk, and those who could not communicate. This study had its protocol approved by the ethics committee, all participants signed an informed consent term and according to the recommendations established by the Declaration of Helsinki and approved by the Ethics Committee (# 150068).
      The diagnosis of T2D was confirmed through the use of drugs to treat T2D, glycated hemoglobin >6.5% as well as confirmation by the medical team. Medications to control DM2 were consulted in medical records and confirmed with the patient or family member.
      A general questionnaire was applied to evaluate data such as socioeconomic situation, consulting the medical record for general admission data. Other covariates were collected through the Hospital information system through patient records and questionnaires. Patients were asked about the practice of physical exercise and the registration in the database was carried out as follows: practice physical activity (yes) or sedentary (not).
      Cognitive status was assessed in all patients using the Mini-Mental State Examination (MMSE), the score can vary from a minimum of 0 to a maximum total of 30 points. The cut-off point is according to schooling, being considered with less cognitive development those with less than 25 points (schooling from 1 to 4 years); 26.5 (schooling from 5 to 8 years); 28 (9–11 years), and 29 for more than 11 years [
      • Brucki S.M.D.
      • Nitrini R.
      • Caramelli P.
      • Bertolucci P.H.F.O.I.
      Sugestões para o uso do miniexame do estado mental no Brasil.
      ].
      To evaluate the independence level, the Instrumental Activities of Daily Living test (IADL) [
      • Lawton M.P.
      • Elaine M.B.
      Assessment of older people: self-maintaining and instrumental activities of daily living.
      ] was performed. The IADL is a scale that assesses eight tasks providing information about functional skills necessary to live independently in the community.
      The nutritional screening was assessed using Nutritional Risk Screening 2002 (NRS-2002): scores ≥ 3 indicate nutritional risk and <3 no risk [
      • Kondrup J.
      • Rasmussen H.H.
      • Hamberg O.L.E.
      • Stanga Z.
      • An Ad
      • Espen H.O.C.
      • et al.
      Nutritional risk screening (NRS 2002): a new method based on an analysis of controlled clinical trials.
      ].

       Nutritional assessment

      One trained nutritionist performed the anthropometric and data collection sarcopenia-related. Mid-arm circumference (MAC) and triceps skin-fold thickness (TS) were measured for calculated the mid-upper arm muscle circumference (MUAMC) [MUAMC= MAC - (3,14 ∗ PCT)] [
      • Landi F.
      • Russo A.
      • Liperoti R.
      • Pahor M.
      • Tosato M.
      • Capoluongo E.
      Midarm muscle circumference, physical performance and mortality: Results from the aging and longevity study in the Sirente geographic area (ilSIRENTE study).
      ]. The MAC was measured with an inelastic tape, positioned in the arm midpoint, between the acromion and olecranon and TS was measurement (scientific adipometer, 0.1 mm precision; Cescorf) at the location of the midpoint between the acromion and the olecranon, with the flexed arm forming an angle of 90 ° [
      • Landi F.
      • Russo A.
      • Liperoti R.
      • Pahor M.
      • Tosato M.
      • Capoluongo E.
      Midarm muscle circumference, physical performance and mortality: Results from the aging and longevity study in the Sirente geographic area (ilSIRENTE study).
      ].
      The body mass index (BMI) was calculated although the height and weight and to classify the nutritional status we use the values proposed for older people: <22kg/m2 underweight, 22–27 kg/m2: normal nutrition, and> 27 kg/m2 as overweight [
      • Lipschitz D.A.
      Screening for nutritional status in the elderly.
      ]. At the time of the interview, the patient was asked about weight loss prior to hospitalization. The usual weight was questioned and subtracted from the current weight.
      The nutritional status was evaluated in the admission through the Subjective global assessment (SGA). The patients were classified according to the cut points by SGA those who obtained SGA-A were considered with normal nutrition, SGA-B moderate malnutrition and SGA-C with severe malnutrition [
      • Detsky A.S.
      • McLaughlin J.R.
      • Baker J.P.
      • Johnston N.
      • Whittaker S.
      • Mendelson R.A.
      • et al.
      What is subjective global assessment of nutritional status?.
      ].
      In accordance with GLIM, the risk of malnutrition was confirmed with NRS-2002 and then malnutrition was diagnosed with a combination with a least one etiological and one phenotypic component. GLIM criteria [
      • Cederholm T.
      • Jensen G.L.
      • Correia M.I.T.D.
      • Gonzalez M.C.
      • Fukushima R.
      • Higashiguchi T.
      • et al.
      GLIM criteria for the diagnosis of malnutrition - A consensus report from the global clinical nutrition community.
      ] for phenotypic evaluation included: non-voluntary weight loss (>5% within past 6 months) and/or low BMI (<20 kg/m2 if <70 years, or <22 kg/m2 if 70 years) [
      • Cederholm T.
      • Jensen G.L.
      • Correia M.I.T.D.
      • Gonzalez M.C.
      • Fukushima R.
      • Higashiguchi T.
      • et al.
      GLIM criteria for the diagnosis of malnutrition - A consensus report from the global clinical nutrition community.
      ]. The etiological evaluation of GLIM involved ≤50% of energy requirements >1 week, or any reduction for >2 weeks, or chronic disease, inflammatory conditions.
      The ESPEN definition was applied using and diagnostic criteria involved: low BMI (<20 kg/m2 if less than 70 years or <22 kg/m2 if more than 70 years) and/or unintentional weight loss (>5% within the past 6 months) [
      • Cederholm T.
      • Bosaeus I.
      • Barazzoni R.
      • Bauer J.
      • Van Gossum A.
      • Klek S.
      • et al.
      Diagnostic criteria for malnutrition - An ESPEN consensus statement.
      ].

       Adductor pollicis muscle thickness

      The APMT was performed according to the proposed technique per Lameu et al. [
      • Lameu E.B.
      • Gerude M.F.
      • Lima A.
      Original research adductor policies muscle: a new anthropometric parameter.
      ]: The average of 3 measurements of the dominant hand was considered as the average adductor muscle thickness. The APMT was considered as < or equal 18 mm for men and < or equal 16 mm for women as an indicator of muscle depletion and malnutrition. These values refer to the 5th percentile, proposed in a previous study that described cutoffs, stratified by sex, for healthy adults and older people [
      • Gonzalez M.C.
      • Duarte R.R.
      • Budiziareck M.B.
      Adductor pollicis muscle: Reference values of its thickness in a healthy population.
      ]. Therefore, we have used APMT lower 5th percentile (APMT<p5) as a group of risk.

       Sarcopenia

      The presence of sarcopenia was evaluated by handgrip strength (HS), calf circumference (CC), and timed up and Go test (TUG). The TUG required patients to stand up out of the chair, walk 3 m, turn around, walk back to the chair, and sit down. Patients were given the following instructions: “stand up on the word ‘go,’ walk to the tape, turn around, walk back to the chair, and sit down.” The timing of the test began at the word “go,” and ended when the participant was seated. This course is timed and the cutoff points> 20s were used to consider the patient with low mobility [
      • Bischoff H.A.
      • Stahelin H.B.
      • Monsch A.U.
      • Iversen M.D.
      • Weyh A.
      • von Dechend M.
      • et al.
      Identifying a cut-off point for normal mobility: a comparison of the timed ‘up and go’ test in community-dwelling and institutionalised elderly women.
      ].
      HS was measured via a dynamometer (Jamar), three consecutive HS measurements were obtained using the dominant hand while in a seated position, elbow bent at a 90°angle. The average of the 3 measures was recorded and was considered with low muscle strength by the dynamometer (<17 Kgf for women and <27 Kgf for men) [
      • Benzeval M.
      • Ij D.
      • Strength G.
      • Dodds R.M.
      • Syddall H.E.
      • Cooper R.
      • et al.
      Grip Strength across the life course : normative data from twelve british studies.
      ].
      Two measurements of the CC of the right leg were performed alternately with an inextensible tape measure (Cerscorf, Brazil) by trained interviewers. The subject was instructed to stand with his legs apart and positioned approximately 20 cm apart. The measurement was taken at the point of greatest horizontal circumference [
      • Lohman T.G.
      • Roche A.F.
      • Martorell R.
      Anthropometric standardization reference manual.
      ]. The mean of the two right calf measurements was used for analytical purposes. CC of ≤34 cm (men) and ≤33 cm (women) was indicative of low muscle mass [
      • Barbosa-Silva T.G.
      • Bielemann R.M.
      • Gonzalez M.C.
      • Menezes A.M.B.
      Prevalence of sarcopenia among community-dwelling elderly of a medium-sized South American city: Results of the COMO VAI? Study.
      ].
      To assess sarcopenia, we have considered the updated consensus of the European Working Group on Sarcopenia in Older People (EWGSOP) [
      • Cruz-Jentoft Alfonso J.
      • Gülistan B.
      • Jürgen B.
      • Boyrie W.
      • Bruyère O.
      • Cederholm T.
      • et al.
      Sarcopenia: revised European consensus on definition and diagnosis.
      ]. Patients with low muscle strength by the dynamometer (<17 Kgf for women and <27 Kgf for men), calf circumference lower than (<33cm for women and <34 for men), and > the 20s in the TUG test were considered sarcopenic.

       Statistical analysis

      All variables had normality assessed by Kolmogorov-Smirnov test, the results were described as average and standard deviation or median and interquartile range (IQR). Categorical variables were reported as frequencies. Between-group comparisons of baseline and anthropometric variables and sarcopenia were performed using T-test, Fisher's exact, or Mann Whitney for non-parametric variables were performed. The association between anthropometric variables, SGA, GLIM, and ESPEN criteria with sarcopenia was analyzed by Univariate and multivariate regression models were applied to calculate the hazard ratio (HR) and 95% confidence interval (CI). The test was adjusted for the variables: Model 1: age and gender; model 2: age, gender, physical activity, mini-mental state exam and Instrumental activities of daily living.
      In the interaction analysis of the SGA and other anthropometric variables, were made the following adjustments: Model 1: age and gender; model 2: age, gender, physical activity, BMI, mini mental state exam and Instrumental activities of daily living.
      The prognostic performance of SGA, APMT, and MAC for predict sarcopenia was evaluated using the area under the receiver operating characteristic curve (AUC), considering as excellent ≥0.90; adequate: 0.70–0.89 and poor <0.70. All statistical analyzes were performed in the SPSS program version 23 (SPSS Inc. Chicago, IL, USA), and p<0.05 was considered statistically significant. The sample of patients in this study is part of a cohort of older patients with and without diabetes admitted to a university hospital [
      • Beretta M.V.
      • Filho F.F.D.
      • Eccel F.R.
      • Feldman J.V.
      • da Silva C.N.
      • et al.
      Sarcopenia and Type 2 diabetes mellitus as predictors of 2-year mortality after hospital discharge in a cohort of hospitalized older adults.
      ].

      Results

      The study population consisted of 311 T2D patients ≥60 years old (73.7 ± 6.34y) hospitalized for different reasons: cardiovascular disease [80 (25%)], neoplasia [50 (26%)], infectious diseases [98 (18.80)]. Table 1 shows the baseline characteristics for all subjects. In accordance with nutritional status by BMI, 168 (54.5%) patients were overweight at admission and well nutrition in accordance with SGA [168 (54.5%)]. The sarcopenia was identified in 96 (30.8%) and 207 (67%) show the APMT <5th.
      Table 1Baseline clinical and nutrition characteristics of older patients with T2D
      All patients (n=311)
      Age (years)73.7 ± 6.34
      Gender (Women)159 (51)
      Caucasian224 (72)
      Sedentary264 (84,9)
      HbA1C (%)7.52 ± 2.05
      Glucose (g/dl)147.99 ± 72.8
      T2D medication
       Insulin107 (34.4)
       Metformin90 (28.93)
       SGLT2i19 (6.1)
       DPP4i32 (10.28)
       Metformin + DPP4i12 (3.85)
       Diet control13 (4.18)
       None38 (12.21)
      IADL (dependent)246 (79)
      BMI (kg/m2)27.91 ± 5.71
       Normal weight108 (35.1)
       Malnutrition32 (10.4)
       Overweight168 (54.5)
      SGA
       Well nutrition192 (61.7)
       moderate malnutrition104 (33.4)
       Malnutrition15 (4)
      ESPEN (malnutrition)18 (5.8)
      GLIM (malnutrition)65 (21)
      Weight Loss (>5%)59 (19)
      Calf circumference (cm)33.51 ± 3.77
       APMT <P5 (mm)207 (67)
       Sarcopenia96 (30.8)
      Causes of hospitalization
       Cardiovascular115 (37)
       Neoplasias80 (25.7)
       Infectious diseases98 (31,5)
       Others18 (5.78)
      Student's t-test or Pearson chi-square test when appropriate. ¥ Mann-Whitney test. IADL: Instrumental Activity of Daily Living; LOS: length of stay; BMI: body mass index; SGA: subjective global assessment; MMSE: mini mental state exam; CC: calf circumference; APMT: adductor pollicis muscle tickness; DPP4: Dipeptidyl peptidase-4 inhibitor; SGLT-2: sodium-glucose cotransporter 2 inhibitor.
      In Table 2 the patients were stratified into two groups with and without sarcopenia according to the consensus (EWGSOP). The sarcopenia was identified in 96 (30.8%) patients. Older patients with T2D and sarcopenia have lower BMI (25.99 ± 4.96 vs 28.77±5.19; p<0.001), MAC (28.93 ± 3.68 vs 30.82 ± 3.96 cm; p<0.001), MUAMC (23.44 ± 3.37 vs 24.38 ± 3.40, p:0.030), CC (30.38 ± 3.86 vs 35.97 ± 3.59, p:0.004), APMT (9.38 ± 3.65 vs. 11.86 ± 4.44, p:0.003), Handgrip (15.69 ± 5.67 vs. 23.72 ± 7.10, p.001) and TUG (11.90 ±3.14 vs. 10.20 ± 2.40, p:0.003) when compared to patients without sarcopenia. In addition, 46.7% of patients with sarcopenia were moderately malnourished (vs.28%, p <0.001) in accordance with SGA.
      Table 2Clinical and nutritional characteristics on hospital admission of older patients with type 2 diabetes according to the presence of sarcopenia
      VariablesSarcopenia (n=96)Without sarcopenia (n=215)P
      Weight (Kg)65.37 ± 13.3976.52 ± 15.39<0.001
      BMI (Kg/m2)25.99 ± 4.9628.77 ± 5.19<0.001
       Normal nutrition47 (46.7%)65 (30.4%)<0.001
       malnutrition18 (19.6%)13 (6.1%)
       overweight31 (33.7%)136 (63.6%)
      MAC (cm)28.93 ± 3.6830.82 ± 3.96<0.001
      TS (mm)17.50 ± 5.8320.75 ± 7.950.001
      MUAMC (cm)23.44 ± 3.3724.38 ± 3.400.030
      CC (cm)30.38 ± 3.8635.97 ± 3.590.004
      APMT (mm)9.38 ± 3.6511.86 ± 4.440.003
      Handgrip (Kgf)15.69 ± 5.6723.72 ± 7.10<0.001
      TUG (seconds)11.90 ± 3.1410.20 ± 2.400.003
      Glucose (mg/dl)154.78 ± 89.78142.67 ± 56.420.43
      HbA1c (%)7.61 ± 2.227.43 ± 1.870.47
      SGA- A44 (45.7%)149 (69.6%)
      SGA- B45 (46.7%)60 (28%)<0.001
      SGA- C7 (6.7%)5 (2.3%)
      ESPEN (malnutrition)9 (9.8)8 (3.7)0.036
      GLIM (malnutrition)31 (33.7)33 (15.3)0.001
      MMSE (low cognition)66 (71.7%)164 (76.3%)0.24
       normal cognition26 (28.3%)51 (23.7%)
      MAC: mid-arm circumference; MUAMC: Mid-upper arm muscle circumference; TS: tricipital skinfold thickness; CC: calf circumference; APMT: adductor pollices muscle tickness; SGA: subjective global assessment (A: well nourished, B: moderately malnourished, C: malnourished); MMSE: mini mental state exam.
      The Pearson correlation analysis is described in Table 3. BMI presented a strong correlation with MAC (r2:0.769, p:0.00), MUAC (r2:0.559, p<0.001) and CC (r2:0.534, p<0.001).
      Table 3Correlation between BMI and parameters of sarcopenia
      BMIMACCCAPMTHandgripMUAC
      BMI1.00.769
      Correlation is significant at the 0.01 level (2-tailed).
      0.534
      Correlation is significant at the 0.01 level (2-tailed).
      0.090.070.559
      Correlation is significant at the 0.01 level (2-tailed).
      MAC0.769
      Correlation is significant at the 0.01 level (2-tailed).
      1.000.551
      Correlation is significant at the 0.01 level (2-tailed).
      0.070.143
      Correlation is significant at the 0.05 level (2-tailed).
      0.807
      Correlation is significant at the 0.01 level (2-tailed).
      CC0.534
      Correlation is significant at the 0.01 level (2-tailed).
      0.551
      Correlation is significant at the 0.01 level (2-tailed).
      1.000.329
      Correlation is significant at the 0.01 level (2-tailed).
      0.262
      Correlation is significant at the 0.01 level (2-tailed).
      0.364
      Correlation is significant at the 0.01 level (2-tailed).
      AMPT0.090.070.329
      Correlation is significant at the 0.01 level (2-tailed).
      1.000.306
      Correlation is significant at the 0.01 level (2-tailed).
      0.123
      Correlation is significant at the 0.05 level (2-tailed).
      Handgrip0.070.143
      Correlation is significant at the 0.05 level (2-tailed).
      0.262
      Correlation is significant at the 0.01 level (2-tailed).
      0.306
      Correlation is significant at the 0.01 level (2-tailed).
      1.000.241
      Correlation is significant at the 0.01 level (2-tailed).
      MUAC0.559
      Correlation is significant at the 0.01 level (2-tailed).
      0.807
      Correlation is significant at the 0.01 level (2-tailed).
      0.364
      Correlation is significant at the 0.01 level (2-tailed).
      0.123
      Correlation is significant at the 0.05 level (2-tailed).
      0.241
      Correlation is significant at the 0.01 level (2-tailed).
      1.00
      a Correlation is significant at the 0.01 level (2-tailed).
      b Correlation is significant at the 0.05 level (2-tailed).
      Table 4 show the univariate and multivariate logistic regression analyses that were performed to determine the association of anthropometric variables, BMI, GLIM, and ESPEN criteria with sarcopenia. The MAC and MUAMC showed a negative relationship with sarcopenia (HR: 0.86 CI95% 0.80–0.93; HR: 0.92 CI95% 0.85–0.99), respectively. However, patients identified as overweight on admission had a 66% reduction in the risk of sarcopenia (HR: 0.34 CI95% 0.19–0.59). Malnutrition in accordance with SGA, ESPEN and GLIM criteria showed a risk of sarcopenia of 4.96 (CI95% 1.51–4.27), 2.90 (CI95% 1.67–5.02) and 2.86 (CI95% 1.58–4.95) of sarcopenia, respectively and APMT <5th (HR: 2.63 CI95% 1.47–4.72). After adjust for age and sex for each variable (model 1), malnutrition according to the SGA had a risk of sarcopenia of HR: 5.65, ESPEN criteria HR: 2.93 and GLIM HR:2.8, and APMT <5th (HR: 2.78), on the other hand, BMI (HR:0.32) and MAC (0.86) showed a lower risk of sarcopenia. In model 2, the same variables remained associated with sarcopenia.
      Table 4Association between clinical and anthropometric variables with sarcopenia
      VariablesHR not adjustedCI 95%pModel 1Model 2
      HR adjustedCI 95%pHR adjustedCI 95%p
      MAC (cm)0.860.80–0.930.0010.860.80–0.92<0.0010.860.79–0.820.000
      MUAMC (cm)0.920.85–0.990.030.760.31–1.880.55------------
      SGA-C4.961.49–16.450.0095.651.66–19.240.0065.651.64–19.380.004
      SGA-B2.541.51–4.270.0012.721.59–4.650.002.681.56–4.590.000
      BMI (overweight)0.340.19–0.590.0010.320.18–0.560.0010.310.17–0.550.000
      ESPEN criteria2.901.67–5.020.0012.931.08–8.010.0343.101.12–8.220.032
      GLIM criteria2.861.58–4.950.0002.891.62–5.150.0002.941.64–5.270.001
      APMT< 5th2.631.47–4.720.0012.781.53–5.050.0012.811.53–5.130.001
      MAC: mid arm circumference; MUAMC: mid-upper arm muscle circumference; SGA: subjective global assessment; BMI: body mass index; APMT: adductor pollices muscle tickness; MMSE: mini mental state exam; IADL: Instrumental activities of daily living.
      The model was adjusted for each variable described in the table. Model 1 adjusted for age and gender and model 2: age, gender, physical activity, mini mental state exam; Instrumental activities of daily living.
      The interaction between SGA and APMT with sarcopenia are show in Table 5. In the model 1, malnourished patients with APMT <5th had a higher risk of sarcopenia when compared to patients without sarcopenia and with normal APMT (HR: 9.01 CI95 % 3.86–21.01). In model 2, the association remained significant (HR: 7.23 CI95% 2.96–17.62). On the other hand, patients with MAC normal and well-nourished have a reduced risk for sarcopenia.
      Table 5Relationship of sarcopenia with interactions between SGA and AMPT or MAC
      ParameterHRCI 95%p
      Model 1SGA-C + APMT <p59.013.05–19.950.001
      SGA-A+ APMT normal1
      Model 1SGA- C + MAC0.920.83–1.020.12
      SGA- B + MAC0.910.84–1.320.061
      SGA- A + MAC0.880.82–0.950.002
      Model 2SGA-C + APMT <p57.232.96–17.62<0.001
      SGA-A+ APMT normal1
      Model 2SGA- C + MAC0.990.89–1.100.89
      SGA- B + MAC0.960.88–1.500.38
      SGA- A + MAC0.560.26–1.240.06
      SGA: Subjective Global Assessment; APMT: adductor pollicis muscle tickness.
      Model 1: adjusted for age and gender.Model 2: age, gender, physical activity, mini mental state exam, BMI, Instrumental activities of daily living.
      SGA- A: well nourished; SGA-B: moderadly malnourished; SGA-C: Malnourished.
      The area under the curve (AUC) can be seen in Fig. 1, Fig. 2. Only SGA + APMT showed greater accuracy in the prediction of sarcopenia (AUC: 0.713 CI95% 0.650–0.803).
      Fig. 1
      Fig. 1
      Tabled 1
      AUCCI 95%p
      GLIM0.5940.522-0.6660.009
      ESPEN0.5300.458-0.6020.402
      SGA0.6250.555-0.6950.001
      APMT0.5770.510-0.6450.032
      Fig. 1. Receiver Operating Characteristic (ROC) curve for prediction of sarcopenia based on the GLIM, ESPEN, SGA and APMT. AUC: area under curve; CI: confidence interval.
      Fig. 2
      Fig. 2
      Tabled 1
      SGA + APMT
      AUCCI 95%Sig
      0.7150.65-0.803<0.001
      Fig. 2. Receiver Operating Characteristic (ROC) curve for prediction of sarcopenia based on the SGA+APMT. SGA: subjectiva Global Assessment, APMT: aductor pollicis muscle tickness; AUC: area under curve; CI: confidence interval.

      Discussion

      The objective of this study was to investigate the relationship between anthropometric variables, SGA, ESPEN, and GLIM with sarcopenia in older patients with T2D and as a secondary objective, to evaluate the accuracy of variables in the prediction of sarcopenia. Malnutrition defined according to the SGA, guideline ESPEN and GLIM, and APMT < 5th was associated with sarcopenia. Additionally, we observed that overweight patients had a lower risk for sarcopenia.
      These results demonstrate the importance of assessing older patients with T2D in the hospital environment more broadly to avoid a wrong nutritional diagnosis. In this sample, 168 (54.4%) were overweight according to the BMI and 192 (61.7%) were well nourished according to the SGA. The combination of obesity and sarcopenia - sarcopenic obesity - is a challenge that increases rapidly in times of rapid increase in older adults with overweight or even obesity [
      • Barazzoni R.
      • Bischof S.C.
      • Boirie Y.
      • Busetto L.
      • Cederholm T.
      • Dicker D.
      • et al.
      Sarcopenic obesity: time to meet the challenge.
      ]. However, these patients had APMT below the 5th percentile and 29.6% had sarcopenia on admission.
      Patients with sarcopenia had lower MAC and MUAMC, CC, and APMT. The MUAMC showed an inverse relationship with sarcopenia, however, after adjusting the model, the association was not statistically significant, perhaps due to the higher percentage of overweight patients and because we do not divide MUAMC according to the cutoff point. Other studies involving institutionalized older or with specific diseases such as cirrhosis [
      • Santos Lívia A.A.
      • Lima Talles B.
      • do Val Ietsug Marjorie
      • de Carvalho Nunes H.R.
      • Qi X.
      • Romeiro F.G.
      • et al.
      Anthropometric measures associated with sarcopenia in outpatients with liver cirrhosis.
      ], found a good relationship between MUAMC and sarcopenia, however, the older patients in these studies also had a higher percentage of malnutrition. Santos AA et al. (2019) [
      • Santos Lívia A.A.
      • Lima Talles B.
      • do Val Ietsug Marjorie
      • de Carvalho Nunes H.R.
      • Qi X.
      • Romeiro F.G.
      • et al.
      Anthropometric measures associated with sarcopenia in outpatients with liver cirrhosis.
      ], identified MUAC in cirrhotic patients as a good anthropometric measure to predict sarcopenia, however, the analysis did not present adjustments. Rodriguez-Rejon et al. (2020) [
      • Rodriguez-Rejon Ana Isabel
      • Artacho Reyes
      • Dolores Ruiz-Lopez María
      Anthropometric measurements and cognitive impairment rather than nutrition status are associated with sarcopenia in long-term care residents.
      ] assessed 249 older people from a long-term care facility and in those with MUAMC (below 19.2 cm in females and 22.1 cm in males) the risk for sarcopenia increased 4-fold (OR = 3.95; 95% CI 1.68–9.29) [
      • Rodriguez-Rejon Ana Isabel
      • Artacho Reyes
      • Dolores Ruiz-Lopez María
      Anthropometric measurements and cognitive impairment rather than nutrition status are associated with sarcopenia in long-term care residents.
      ].
      In our sample, malnutrition assessed by GLIM criteria increased the risk of sarcopenia 2.94-fold. Similarly, the study by Belanti F. et al. (2020) [
      • Bellanti F.
      • Lo Buglio A.
      • Quiete S.
      • Pellegrino G.
      • Dobrakowski M.
      • Kasperczyk A.
      • et al.
      Comparison of three nutritional screening tools with the new glim criteria for malnutrition and association with sarcopenia in hospitalized older patients.
      ], with 152 older hospitalized, those with malnutrition according to the GLIM criteria increased risk of sarcopenia 2.7-fold (95% CI 1.4–4.9, p = 0.0029). In a study the four-year follow-up, Baldart C. et al. (2019) [
      • Beaudart Charlotte
      • Sanchez-Rodriguez Dolores
      • Locquet Médéa
      • Reginster Jean-Yves
      • Lengelé Laetitia
      • Bruyère Olivier
      Malnutrition as a Strong predictor of the onset of sarcopenia.
      ] evaluated the risk of developing sarcopenia/severe sarcopenia in accordance with GLIM [sarcopenia: (HR) = 3.23 (CI) 1.73–6.05]; and ESPEN [sarcopenia: HR = 4.28 (95% CI 1.86–9.86]. The prevalence of malnutrition in accordance to ESPEN, GLIM, and SGA was 18 (5.8%), 65 (21%), and 15 (4%), respectively, similarly to the study of Beaudart C. et al. (2019) [
      • Beaudart Charlotte
      • Sanchez-Rodriguez Dolores
      • Locquet Médéa
      • Reginster Jean-Yves
      • Lengelé Laetitia
      • Bruyère Olivier
      Malnutrition as a Strong predictor of the onset of sarcopenia.
      ]; the prevalence of malnutrition by ESPEN [19 (5.65%)] and GLIM [59 (17.6%)]. The APMT showed a good association with sarcopenia, patients with APMT <5th increased risk of sarcopenia 2.63-fold. Other studies have also shown that APMT appears to be sensitive for malnutrition measures in different clinical conditions [
      • Freitas B.J.S.A.
      • Mesquita L.C.
      • Teive N.J.V.
      • Souza S.R.
      Classical anthropometry and the adductor pollicis muscle to determine the nutritional prognosis in patients with cancer.
      ,
      • Bragagnolo R.
      • Caporossi F.S.
      • Dock-Nascimento D.B.
      • eduardo de Aguilar-Nascimento J.
      Espessura do músculo adutor do polegar: um método rápido e confiável na avaliação nutricional de pacientes cirúrgicos.
      ,
      • Valente Katarina Papera
      • Lucas Almeida Betullya
      • Ricati Lazzarini Thailiny
      • de Souza V.F.
      • Chaves T.S.
      • de Moraes R.A.G.
      • et al.
      Association of adductor pollicis muscle thickness and handgrip strength with nutritional status in cancer patients.
      ,
      • Caporossi F.S.
      • Caporossi C.
      • Dock-nascimento D.B.
      Measurement of the thickness of the adductor pollicis muscle as a predictor of outcome in critically ill patients.
      ,
      • Ghorabi S.
      • Ardehali H.
      • Amiri Z.
      • Vahdat Shariatpanahi Z.
      Association of the adductor pollicis muscle thickness with clinical outcomes in intensive care unit patients.
      ], and in the healthy population [
      • Bischoff H.A.
      • Stahelin H.B.
      • Monsch A.U.
      • Iversen M.D.
      • Weyh A.
      • von Dechend M.
      • et al.
      Identifying a cut-off point for normal mobility: a comparison of the timed ‘up and go’ test in community-dwelling and institutionalised elderly women.
      ]. Richinelli et al. [
      • Rechinelli A.B.
      • Marques I.L.
      • de Morais Viana Eduarda Cristina Rodrigues
      • da Silva Oliveira Isadora
      • de Souza Vanusa Felício
      • Petarli G.B.
      • et al.
      Presence of dynapenia and association with anthropometric variables in câncer patients.
      ] identified that 158 cancer patients (mean age 54 ± 14 years) and reduced APMT had a higher risk of dynapenia (low muscle strength) (considering surgical patients <13.4 mm as the cutoff point). The APMT association has also been associated with a risk of sarcopenia through SARC-F [
      • de Souza Vanusa Felício
      • de Souza Chaves Ribeiro Thamirys
      • de Almeida Marques Rayne
      • Ribeiro T.S.C.
      • de Moraes R.A.G.
      • Pereira T.S.S.
      • et al.
      SARC-CalF-assessed risk of sarcopenia and associated factors in cancer patients.
      ]. The effectiveness of APMT as a marker of sarcopenia was assessed in a study with older patients, identifying an area under the curve of 0.70 (95% CI 0.63–0.76; P <0.001) [
      • Vaez I.A.
      • Silva H.F.
      • de Arruda W.S.C.
      • Pexe-Machado P.A.
      • Fontes A.J.F.
      • de Aguilar-Nascimento J.E.
      • et al.
      Effectiveness of adductor pollicis muscle thickness as risk marker for sarcopenia in Central-West Brazilian elderly communities.
      ].
      In this paper, the thickness of the adductor pollicis muscle was assessed using the technique proposed by Lameu et a. (2004) [
      • Gonzalez M.C.
      • Duarte R.R.
      • Budiziareck M.B.
      Adductor pollicis muscle: Reference values of its thickness in a healthy population.
      ] which was studied through images performed by tomography and magnetic resonance and on anatomical parts. This technique allows the assessment of muscle thickness using a caliper in the region in the vertex of an imaginary triangle formed by the extension of the thumb and index finger [
      • Gonzalez M.C.
      • Duarte R.R.
      • Budiziareck M.B.
      Adductor pollicis muscle: Reference values of its thickness in a healthy population.
      ]. The SARCUS project is a European initiative that harmonizes sarcopenia assessment by ultrasound (US) [
      • Perkisas S.
      • Baudry S.
      • Bauer J.
      • Beckwée D.
      • De Cock A.M.
      • Hobbelen H.
      • et al.
      The SARCUS project: evidence-based muscle assessment through ultrasound.
      ]. US assessment has been highlighted in recent studies in the assessment of sarcopenia and/or sarcopenic obesity. Deni O et al. (2020) [
      • Deniz O.
      • Cruz-Jentoft A.
      • Sengul Aycicek G.
      • Unsal P.
      • Esme M.
      • Ucar Y.
      • et al.
      Role of ultrasonography in estimating muscle mass in sarcopenic obesity.
      ] evaluated elderly patients considering the sarcopenic obese group as BMI ≥ 30 and HGS < 16 kg and <27 kg, for women and men, respectively. Anthropometric parameters that estimate muscle mass were lower in the sarcopenic group and the measures evaluated by US were more effective to assess sarcopenia than the bioimpedance method. Similarly, Sari A et al. (2020) [
      • Sari A.
      • Esme M.
      • Aycicek G.S.
      • Armagan B.
      • Kilic L.
      • Ertenli A.I.
      • et al.
      Evaluating skeletal muscle mass with ultrasound in patients with systemic sclerosis.
      ]. US measurement of the gastrocnemius or rectus abdominis thickness and calf muscle thicknesses were considered a good screening method to detect low muscle mass in patients with systemic sclerosis, high sensitivity, and negative predictive value. Esme M et al. (2021) [
      • Eşme M.
      • Karcıoğlu O.
      • Öncel A.
      • Ayçiçek G.Ş.
      • Deniz O.
      • Ulaşlı S.S.
      • et al.
      Ultrasound assessment of sarcopenia in patients with sarcoidosis.
      ] identify that the Muscle thicknesses measured by ultrasonography are helpful for the diagnosis of sarcopenia that may develop in chronic diseases.
      Several studies pointed out by the US as the reference method for evaluating an early diagnosis of sarcopenia in older patients [
      • Perkisas S.
      • Baudry S.
      • Bauer J.
      • Beckwée D.
      • De Cock A.M.
      • Hobbelen H.
      • et al.
      The SARCUS project: evidence-based muscle assessment through ultrasound.
      ,
      • Deniz O.
      • Cruz-Jentoft A.
      • Sengul Aycicek G.
      • Unsal P.
      • Esme M.
      • Ucar Y.
      • et al.
      Role of ultrasonography in estimating muscle mass in sarcopenic obesity.
      ,
      • Sari A.
      • Esme M.
      • Aycicek G.S.
      • Armagan B.
      • Kilic L.
      • Ertenli A.I.
      • et al.
      Evaluating skeletal muscle mass with ultrasound in patients with systemic sclerosis.
      ,
      • Eşme M.
      • Karcıoğlu O.
      • Öncel A.
      • Ayçiçek G.Ş.
      • Deniz O.
      • Ulaşlı S.S.
      • et al.
      Ultrasound assessment of sarcopenia in patients with sarcoidosis.
      ,
      • Ticinesi A.
      • Meschi T.
      • Maggio M.
      • Narici M.V.
      Application of ultrasound for muscle assessment in sarcopenia: the challenge of implementing protocols for clinical practice.
      ]. Due to the higher cost and lack of resources to perform this ultrasound assessment, we chose to assess using a caliper, as it is available in most hospitals in this country and its replication becomes more accessible. Unfortunately, the cohort study that originated this article was not designed to assess muscle thickness using the US method.
      Although our patients were more overweight and had good nutritional status, the presence of malnutrition or being moderately malnourished increased the risk of sarcopenia by 4.96 and 2.54 times, respectively. When adjusting the analysis for other factors, the presence of malnutrition remained significant, but with less statistical strength (HR: 1.84). However, the interaction of SGA and APMT <5th was strongly associated with sarcopenia (HR: 7.23), even after adjustments. The interaction between SGA and MUAMC was not related to the risk of sarcopenia. These data reflect the need to associate anthropometric measures and nutritional screening/assessment when evaluating older patients with T2D.
      The SGA is a tool widely used worldwide and has a good prediction for the length of hospital stay [
      • Inouye S.K.
      • Westendorp Rudi G.J.
      • Saczynski Jane S.
      Delirium in older persons.
      ] and mortality [
      • Wakahara T.
      • Shiraki M.
      • Murase K.
      • Fukushima H.
      • Matsuura K.
      • Fukao A.
      • et al.
      Nutritional screening with subjective global assessment predicts hospital stay in patients with digestive diseases.
      ,
      • da Silva Fink Jaqueline
      • Daniel de Mello Paula
      • Daniel de Mello Elza
      Subjective global assessment of nutritional status a systematic review of the literature.
      ]. Onishi et al. (2018) [
      • Onishi Sachiyo
      • Shiraki Makoto
      • Nishimura Kayoko
      • Hanai Tatsunori
      • Moriwaki Hisataka
      • Shimizu Masahito
      Prevalence of Sarcopenia and its relationship with nutritional state and quality of life in patients with digestive diseases.
      ] evaluated 303 older people with digestive diseases and those with sarcopenia had a worse nutritional status by SGA and lower MUAMC [
      • Onishi Sachiyo
      • Shiraki Makoto
      • Nishimura Kayoko
      • Hanai Tatsunori
      • Moriwaki Hisataka
      • Shimizu Masahito
      Prevalence of Sarcopenia and its relationship with nutritional state and quality of life in patients with digestive diseases.
      ]. Bellanti et al. (2020) [
      • Bellanti F.
      • Lo Buglio A.
      • Quiete S.
      • Pellegrino G.
      • Dobrakowski M.
      • Kasperczyk A.
      • et al.
      Comparison of three nutritional screening tools with the new glim criteria for malnutrition and association with sarcopenia in hospitalized older patients.
      ], compared tools such as SGA, Malnutrition Universal Screening Tool (MUST) and GLIM and verified their association with sarcopenia in 152 older and the patient high risk of malnutrition according to MUST are at high risk of presenting with sarcopenia [
      • Bellanti F.
      • Lo Buglio A.
      • Quiete S.
      • Pellegrino G.
      • Dobrakowski M.
      • Kasperczyk A.
      • et al.
      Comparison of three nutritional screening tools with the new glim criteria for malnutrition and association with sarcopenia in hospitalized older patients.
      ].
      This was the first study to evaluate the relationship between ESPEN, GLIM criteria, APMT and sarcopenia exclusively in older patients with T2D. It is known that patients with T2D have lower muscle mass when compared to patients without T2D [
      • Park S.W.
      • Goodpaster B.H.
      • Strotmeyer E.S.
      • de Rekeneire N.
      • Harris T.B.
      • Schwartz A.V.
      • et al.
      Decreased muscle strength and quality in older adults with type 2 diabetes: The health, aging, and body composition study.
      ] but most studies assess the relationship between overweight and obesity with negative outcomes without assessing muscle mass. In our data, patients with T2D were overweight, evaluated by the BMI, and also lower muscle mass.
      As for shortcomings, the APMT measurement was performed only once, 48 hours after admission, and it was not possible to assess whether the patients further reduced the thickness during hospitalization. The evaluation of muscle mass in sarcopenia was performed using CC, although, some studies have already demonstrated its effectiveness (42). As a strength of our study, we highlight the prospective design, as well as the significant number of patients evaluated.

      Conclusions

      In fact, the nutritional status during the hospitalization is important and can be a risk factor for other problems, often not related to the main reason for hospitalization. Thus, body changes in older patients with type 2 diabetes can mask muscle and functional status loss. Despite technological advances in body assessment methods, anthropometrics assessments, such as the circumference of the arm and the thickness of the adductor pollicis muscle, are still a safe, low-cost, and validated method that can be used in combination with other tools to identify body changes in older patients.

      Statement of authorship

      Beretta MV and Rodrigues TC were responsible for the study concept design, data analysis, interpretation of findings and drafted the manuscript. All authors read and approved the final manuscript.

      Funding

      Financial support was provided by Research and Events Support Fund at Hospital de Clınicas de Porto Alegre (FIPE-HCPA) and PROEX- CAPES .

      Declaration of competing interest

      The authors declare no conflict of interest.

      Acknowledgment

      We would like to thank all the hospitalized patients who agreed to participate in this study, to students of scientific initiation. To Instituto Nacional de Desenvolvimento Cientıfico e Tecnologico (CNPq).

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