Usefulness of an early sarcopenia screening in predicting short-term mortality in older patients discharged for acute heart failure .

Usefulness of an early sarcopenia screening in predicting short-term mortality in older patients discharged for acute heart failure . | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Usefulness of an early sarcopenia screening in predicting short-term mortality in older patients discharged for acute heart failure . Chukwuma Okoye, Virginia Morelli, Riccardo Franchi, Tessa Mazzarone, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4223789/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Purpose Sarcopenia is a potentially reversible syndrome is associated with an increased risk of cardiogenic cachexia and adverse outcomes in older patients with HF. Despite its significance, sarcopenia is often underdiagnosed due to the complexity of a thorough assessment in patients with acute heart failure. The purpose of this study was to evaluate whether early sarcopenia screening can predict the short-term prognostic risk in very old patients recently discharge for Acutely Decompensated Heart Failure (ADHF). Methods We consecutively enrolled patients aged 75 years or older hospitalized with acutely DHF in the Geriatrics Unit of a tertiary care hospital. All patients underwent physical examination, complete blood tests, point-of-care ultrasound, and a comprehensive geriatric assessment, including physical performance through SARC-F and Hand Grip Strength test (HGS). The thirty-day post-discharge mortality rate was assessed by phone interview. Results Out of 184 patients hospitalized with ADHF enrolled in the study (mean [SD], 86.8 [5.9] years, 60.3% female), 47 died within 30 days after discharge. By multivariate logistic analysis, HGS (β = -0.73 ± 0.03, p = 0.008) and SARC-F [adjusted OR = 1.18 (CI95% 1.03–1.33), p = 0.003] resulted independently associated with mortality. Furthermore, two SARC-F sub-items, namely, limitation in rising from a chair and history of falls [aOR: 3.26 (CI95% 1.27–8.34), p = 0.008; aOR: 3.30 (CI95% 1.28–8.49), p = 0.01; respectively] emerged as determinants of 30-days mortality. Conclusion An early sarcopenia assessment comprising SARC-F and HGS test independently predicts 30-day post-discharge mortality in oldest-old patients hospitalized for acute HF. Heart Failure older adults sarcopenia handgrip outcomes Figures Figure 1 Figure 2 Key summary points Aim: To determine the usefulness of the Hand grip strength test (HGS) and SARC-F in predicting short-term mortality among hospitalized older patients with acute heart failure Findings: HGS test and SARC-F questionnaire predict short-term mortality in older patients with acute HF Message: Early sarcopenia screening can reliably predict the short-term mortality in older HF patients. Introduction Heart failure (HF) is one of the major causes of mortality and hospitalization worldwide, and 4 out of 5 patients with HF are older than 65 years [ 1 ]. Despite medical improvement, the five-year survival rates for HF remain poorer than most cancers [ 2 ]. In particular, the risk of re-hospitalization or death is highest in the 30-days following discharge for acute decompensated heart failure (ADHF)[ 3 ]. Moving the aim away from the treatment of a single disease and toward a more holistic approach, the latest guidelines advocate for a comprehensive multidisciplinary assessment of HF patients[ 1 ]. In this regard, recent investigations reported that 20–30% of patients with HF may have a diagnosis of sarcopenia, a potentially reversible geriatric syndrome characterized by a progressive loss of skeletal muscle and strength resulting in impaired physical performance that can gradually lead to disability, reduced quality of life and even death [ 4 , 5 ]. Compared to non-HF patients, those with HF have a significantly higher prevalence of sarcopenia [ 6 ] thus suggesting the existence of a strong interconnection between the pathophysiological pathways involved in HF, age-related changes in body composition, and sarcopenia [ 7 ]. Patients with HF and sarcopenia are more prone to develop physical frailty and related negative health outcomes, with a higher risk of HF progression with the need for hospitalization [ 5 ] and an increased mortality rate [ 8 , 9 ]. Notwithstanding, very few studies have attempted to evaluate the short-term prognostic significance of sarcopenia in older individuals with HF [ 10 – 13 ]. According to the European Working Group on Sarcopenia in Older People 2 (EWGSOP2) guidelines [ 6 ], all patients with suspected sarcopenia should undergo the SARC-F, a 5-item questionnaire that is self-reported by patients based on their perception of limitations in strength, walking ability, rising from a chair, stair climbing, and experiences with falls. Subsequently, several diagnostic evaluation should be made to correctly diagnose sarcopenia, namely: i) evaluation of muscle strength using a calibrated handheld dynamometer or chair stand test, ii) assessment of muscle quantity through magnetic resonance imaging (MRI), computer tomography (CT) or Dual-energy X-ray absorptiometry (DEXA), iii) recognition of low physical performance that can be measured by gait speed, Short Physical Performance Battery (SPPB)[ 14 ] and the Timed-Up and Go test (TUG). Nevertheless, SARC-F is an inexpensive and convenient method for sarcopenia risk screening [ 15 ] and has been proved valid and accurate for identifying people at risk of sarcopenia associated adverse outcomes[ 16 ]. Given these premises, early sarcopenia screening could be helpful in predicting the outcomes of older patients with ADHF. This study aimed to determine the short-term prognostic role of sarcopenia assessed by the SARC-F questionnaire in hospitalized older patients with ADHF. Secondary endpoint was to evaluate the relationship between in-hospital Hand Grip Strength test (HGS) values, SARC-F sub-items, and short-term prognosis. Methods We prospectively enrolled all patients aged 75 years or older hospitalized with ADHF in our tertiary care hospital between January 1, 2022, and February 1, 2023. The exclusion criteria were: (1) inability to communicate with researchers or obtain informed consent; (2) critical illness requiring invasive ventilation at admission (3) acute coronary syndrome; (4) inability to perform a HGS test. A panel of clinicians adjudicated the diagnosis of congestive heart failure based on clinical symptoms, signs, chest x-ray film results, echocardiographic findings and therapy at admission in line with recent international guidelines[ 1 ]. All patients underwent a focused cardiac ultrasound (FOCUS), performed by an expert clinician. FOCUS follows the principle formulated in the focused assessed transthoracic echocardiography (FATE) protocol [ 17 ]. Furthermore, as patients underwent a diagnostic examination with bedside Point of care ultrasound (POCUS) including lung ultrasound, focused cardiac ultrasound, pleural effusion score (PEFS)[ 18 ], and inferior vena cava (IVC) assessment. All the patients underwent physical examination, complete blood tests, and a comprehensive geriatric assessment (CGA)[ 19 ] including cognitive evaluation using the Short Portable Mental Status Questionnaire (SPMSQ)[ 20 ], level of autonomy in terms of independence in the performance of basic (ADL)[ 21 ], and instrumental (IADL)[ 22 ], activities of daily living. Systolic Arterial Pressure (SAP) and Heart Rate (HR) were also collected at hospital discharge. The risk of malnutrition was assessed through the Mini Nutritional Assessment-Short Form (MNA-SF)[ 23 ] and Body Mass Index (BMI). Functional capabilities and physical performance were evaluated through a pre-morbid SARC-F and HGS. SARC-F includes 5 items: strength, assistance in walking, rising from a chair, climbing stairs, and history of falls. Each component is scored on a 0–2 scale and summed for an overall range of 0–10. A total score of SARC-F ≥ 4 indicates high risk of sarcopenia [ 24 ]. Given that the onset of acute HF could influence the physical performance, patients or caregivers were asked to answer to SARC-F questions regarding the physical status and habits approximately thirty days prior to hospital admission for heart failure (pre-morbid status). The HGS test was performed using a hand dynamometer with the dominant hand. HGS is a simple measure of strength and may be utilized as a marker of mobility. The cut-off level of < 16 kg in women and < 27 kg in men have been identified to detect patients at risk for sarcopenia. Participants were seated with shoulder adducted, elbow flexed to 90 degrees, and forearm and wrist neutral. The highest score of three consecutive measurements was recorded. The 30 post-discharge mortality rate was assessed by phone interview. The study complied with the Declaration of Helsinki and was approved by the local Ethics Committee (Tuscany Regional Ethics Committee for the Clinical Experimentation: FUN-sc 23956). Each patient provided written informed consent to participate in the study. Statistical Analysis Statistical analysis was performed with IBM SPSS Statistic (IBM SPSS Statistic version 27.0 lnk IBM Corporation and its licensor 1989–2020) and RStudio (RStudio Team: Integrated Development for R. RStudio, PBC, Boston, MA). Continuous variables were presented as mean and standard deviation, ordinal variables as median and interquartile range (IQR), and categorical variables as percentage. Mann-Whitney and chi-square tests were used for multiple comparisons. A multivariable logistic regression was performed to evaluate the association between SARC-F, HGS test and 30-days-mortality using a priori selected model covariates on the basis of clinical considerations. As a secondary analysis a logistic multivariable analysis was performed among SARC-F sub-items with a resulted statistically significant at the univariate analysis. Covariates included in the multivariable model were age, sex, number of comorbidities, NT-pro-BNP, and SAP at discharge. Estimate odds ratios (ORs) with 95% confidence intervals (CIs) were obtained. The sample size was calculated on the basis of previous research and required at least 155 patients, to detect a 10% difference in odds ratio for 1-point increase of SARC-F (as ordinal predictor), with a power of 80% and a 0.05 α risk. Tests were performed considering a level of significance of 5%. Results As shown in Supplementary Fig. 1, 229 patients hospitalized with acutely DHF were assessed for eligibility. Thirty-two patients were not included in the study due to in-hospital deaths (10), inability to participate (19), or refusal (3). Thus, 191 patients were finally enrolled, of whom 7 were lost to follow-up. The remaining 184 patients (mean [SD], 86.8 [5.9] years) were ultimately included in the statistical analysis; among them 47 (25.5%) died within 30 days following hospital discharge. No differences were found between deceased and survived patients in terms of gender prevalence, mean age, body weight, or the number and type of comorbidities (see Table 1 ). Deceased patients had a higher median SARC-F [8 (IQR = 3.5) vs 5 (IQR = 6); respectively, p = 0.005] and mean Hand Grip Strength [11.1 (SD = 7.4) Kg vs 15.8 (SD = 7.7) Kg, respectively; p = 0.006], compared to their counterparts. Regarding pulmonary and systemic congestion, no differences were detected in terms of B lines number, pleural effusion score (PEFS) and characteristics of inferior vena cava. Table 1 Comparison between deceased patients and controls. All patients N = 184 Death at 30 days N = 47 Controls N = 137 P-value Demographics Female (%) 111 (60.3) 28 (59.6) 83 (60.6) 0.90 Age mean, years (SD) 86.8 (5.9) 87.6 (6) 86.6 (6) 0.30 BMI mean, kg/m 2 (SD) 24.6 (4.5) 24.1 (4.5) 24.8 (4.6) 0.49 HGS mean, kg (SD) 14.8 (7.8) 11.1 (7.4) 15.8 (7.7) 0.006 CFS median (IQR) 6 (3) 7 (1) 5 (3) < 0.001 SARC-F median (IQR) 5 (5) 8 (3.5) 5 (6) 0.005 SARC-F ≥ 4 (%) 122 (66.1) 37 (79) 85 (62) 0.04 In-Hospital events Length of stay median, days (IQR) 7 (3) 8 (4) 7 (4) 0.06 Upgrade diuretic therapy (%) 75 (41) 15 (32.5) 60 (43.8) 0.20 Pulmonary edema (%) 26 (14.1) 7 (15) 19 (13.8) 0.85 Adverse events (%) 53 (28.9) 16 (35) 37 (27.1) 0.34 Post-discharge events 30 days readmission (%) 25 (13.9) 5 (11.4) 20 (14.8) 0.62 Comorbidities N° of comorbidities median (IQR) 4 (2.5) 4 (2.5) 4 (2) 0.29 COPD (%) 47 (25.9) 12 (26.1) 35 (25.9) 0.98 Hypertension (%) 120 (65.5) 25 (54) 95 (69) 0.06 Heart Failure (%) 116 (63) 34 (74) 82 (60) 0.08 Diabetes (%) 52 (28.8) 12 (26.1) 40 (29.8) 0.63 Stroke (%) 32 (17.5) 12 (26.1) 20 (14.5) 0.17 Chronic renal failure (%) 60 (32.8) 20 (43.5) 40 (29) 0.07 Ischemic heart disease (%) 65 (35.6) 19 (41.3) 46 (33.6) 0.35 Atrial fibrillation (%) 116 (63.3) 32 (67.4) 84 (61.8) 0.50 Cancer (%) 39 (21.5) 11 (23.9) 28 (20.6) 0.64 Examination and laboratory values B-lines number median (IQR) 12 (12) 12 (11.5) 12 (13) 0.77 PEFS cumulative median (IQR) 2 (5) 4 (4.5) 2 (5) 0.13 IVC max mean, mm (SD) 17.3 (5.6) 17.9 (6) 17.1 (5.5) 0.49 IVC min mean, mm (SD) 10.6 (6.9) 11.6 (7.7) 10.3 (6.7) 0.35 LVEF < 40% (%) 58 (31.7) 15 (31.4) 43 (31.8) 0.97 NT-proBNP admission median, pg/ml (IQR) 7837 (12075.5) 13558 (26195.25) 7463 (8830) 0.002 NT-proBNP discharge median, pg/ml (IQR) 3843 (6897.5) 6443 (11455) 3505 (5615.5) 0.03 Mean SAP (SD) 123(21) 116 (20) 126 (21) 0.044 Mean PAD (SD) 71 (12) 68 (14) 72 (11) 0.096 Mean HR (SD) 80(13) 83(14) 79(12) 0.156 Mean Creatinine (SD) 1.39 (0.71) 1.49(0.84) 1.36(0.65) 0.395 Albumin mean, g/dl (SD) 3.03 (0.53) 2.9 (0.55) 3.1 (0.51) 0.19 Mean Hemoglobin g/L (SD) 10.7(1.8) 10.4(1.9) 10.8(1.7) 0.318 P/F admission mean (SD) 311.3 (93.7) 308.3 (100.5) 312.3 (91.6) 0.80 Medications Beta-blockers at discharge (%) 151 (82.2) 40 (84.2) 111 (81.3) 0.78 ACE-I at discharge (%) 71 (38.7) 23 (47.3) 48 (34.8) 0.35 ARB at discharge (%) 18 (9.6) 5 (10.5) 13 (9.3) 0.88 MRA at discharge (%) 32 (17.7) 4 (10.5) 28 (21) 0.32 Furosemide at discharge (%) 151 (82.2) 42 (89.4) 109 (79) 0.32 Digoxin at discharge (%) 15 (8) 0 (0) 15 (11.6) 0.12 SGLT2-i at discharge (%) 9 (4.8) 0 (0) 9 (6.9) 0.23 Continuous variables are expressed as mean SD or median with IQR properly. Abbreviations: BMI indicates Body Mass Index; HGS, Hand Grip Strength; CFS, Clinical Frailty Scale; SARC-F, Strength- Assistance with walking- Rising from a chair- Climbing stairs and Falls questionnaire; COPD, Chronic Obstructive Pulmonary Disease; PEFS, Pleural EFfusion Score; IVC, Inferior Vena Cava; LVEF, Left Ventricular Ejection Fraction; NT-proBNP, N-Terminal pro-B-type Natriuretic Peptide; SAP, Systolic Arterial Pressure; HR, Heart Rate; P/F, PaO2/FiO2 ratio; ACE-i, Angiotensin-Converting Enzyme inhibitors; ARB, Angiotensin Receptor Blocker; MRA, Mineralocorticoid Receptor Antagonist; SGLT2-i, Sodium-GLucose coTransporter-2 inhibitors. As shown in Table 2 , 122 patients (66.3%) were found to be at high risk of sarcopenia (SARC-F ≥ 4), showing a 1.9 times higher 30-day mortality than controls (30% vs. 16%, p = 0.04). Patients with SARC-F ≥ 4 were older [mean age: 87.8 years (SD = 5.5) vs 84.5 (SD = 6.2); respectively, p < 0.001] and more frequently women (65% vs. 48.3%, p = 0.03), and lower HGS score [mean HGS test: 12.9 (SD = 6.8) vs 18.9 (SD = 8.3) respectively; p < 0.001], compared to their peers. By Point-of-care Ultrasound (POCUS) assessment, we observed that patients at high risk of sarcopenia had higher Pleural Effusion Score [3 (IQR = 5) vs 1 (IQR = 4); respectively, p = 0.009] compared to counterparts. Concerning comorbidities, we found a higher prevalence of chronic heart failure (68.4% vs. 50.8%, p = 0.02) in patients at high risk of sarcopenia compared to those at low risk. Table 2 Comparison between patients with positive screening for sarcopenia (SARC-F ≥ 4) and controls. All patients N = 184 SARC-F ≥ 4 N = 122 SARC-F < 4 N = 62 P Demographics Female (%) 111 (60.3) 81 (65) 30 (48.3) 0.03 Age mean, years (SD) 86.8 (5.9) 87.8 (5.5) 84.5 (6.2) < 0.001 BMI mean, kg/m 2 (SD) 24.6 (4.5) 24.1 (4.6) 25.6 (4.3) 0.07 HGS mean, kg (SD) 14.8 (7.8) 12.9 (6.8) 18.9 (8.3) < 0.001 CFS median (IQR) 6 (3) 7 (2) 4 (2) < 0.001 In-Hospital events Hospital stay median, days (IQR) 7 (3) 7 (3) 7 (3.25) 0.60 Upgrade diuretic therapy (%) 75 (41) 49 (39.6) 26 (42.1) 0.75 Pulmonary edema (%) 26 (14.1) 17 (14.4) 9 (14) 0.95 Adverse events (%) 53 (28.9) 38 (31) 15 (24.6) 0.40 Post-discharge events 30 days readmission (%) 25 (13.9) 16 (13.4) 9 (15.2) 0.77 30 days mortality (%) 47 (25.5) 37 (30) 10 (16) 0.04 Comorbidities N° of comorbidities median (IQR) 4 (2.5) 4 (3) 4 (2.25) 0.49 COPD (%) 47 (25.9) 30 (25.4) 17 (28.8) 0.63 Hypertension (%) 120 (65.5) 82 (67.5) 38 (62.7) 0.52 Heart Failure (%) 116 (63) 84 (68.4) 32 (50.8) 0.02 Diabetes (%) 52 (28.8) 34 (27.2) 18 (28.9) 0.82 Stroke (%) 32 (17.5) 25 (21) 7 (11.9) 0.13 Chronic renal failure (%) 60 (32.8) 43 (35) 17 (27.1) 0.29 Ischemic heart disease (%) 65 (35.6) 44 (35.9) 21 (32.2) 0.62 Atrial fibrillation (%) 116 (63.3) 80 (65.8) 36 (57.7) 0.30 Cancer (%) 39 (21.5) 24 (20.2) 15 (25.4) 0.42 Examination and laboratory values B-lines number median (IQR) 12 (12) 11.5 (12) 9.5 (13.75) 0.75 PEFS cumulative median (IQR) 2 (5) 3 (5) 1 (4) 0.009 IVC max mean, mm (SD) 17.3 (5.6) 16.9 (6) 18.2 (5) 0.17 IVC min mean, mm (SD) 10.6 (6.9) 10.6 (7.1) 10.7 (6.9) 0.95 LVEF < 40% (%) 58 (31.7) 25 (28) 15 (35) 0.36 NT-proBNP max median, pg/ml (IQR) 7837 (12075.5) 9804.5 (14690.5) 6264 (6942) 0.09 NT-proBNP min median, pg/ml (IQR) 3843 (6897.5) 4257(6553.22) 2112 (4630.5) 0.20 Mean PAS (SD) 123 (21) 123 (22) 123 (19) 0.88 Mean PAD (SD) 71 (12) 71 (13) 71 (11) 0.82 Mean HR (SD) 80 (13) 79 (13) 81 (12) 0.48 Mean Creatinine (SD) 1.39 (0.71) 1.45 (0.75) 1,26 (0.59) 0.21 Mean Hemoglobin g/L (SD) 10.7 (1.8) 10.5 (1.8) 11.3 (1.7) 0.05 P/F admission mean (SD) 311.3 (93.7) 316.3 (90.3) 298.9 (101.4) 0.26 HCO3- admission mean, mmol/L (SD) 25.4 (4.4) 25.7 (4.7) 25.1 (3.7) 0.43 HCO3- dimission mean, mmol/L (SD) 29.3 (5.7) 29.5 (6.2) 28.8 (4.4) 0.45 Medications Beta-blockers at discharge (%) 151 (82.2) 108 (88.3) 43 (68.4) 0.06 ACE-i at discharge (%) 71 (38.7) 42 (34.8) 29 (47.3) 0.35 ARB at discharge (%) 18 (9.6) 8 (6.9) 10 (15.7) 0.27 MRA at discharge (%) 32 (17.7) 26 (21) 6 (10.5) 0.32 Furosemide at discharge (%) 151 (82.2) 102 (83.7) 49 (79) 0.65 Digoxin at discharge (%) 15 (8) 8 (7) 7 (10.5) 0.63 SGLT2-i at discharge (%) 9 (4.8) 3 (2.3) 6 (10.5) 0.16 Abbreviations : BMI indicates Body Mass Index; HGS, Hand Grip Strength; CFS, Clinical Frailty Scale; SARC-F, Strength- Assistance with walking- Rising from a chair- Climbing stairs and Falls questionnaire; COPD, Chronic Obstructive Pulmonary Disease; PEFS, Pleural EFfusion Score; IVC, Inferior Vena Cava; LVEF, Left Ventricular Ejection Fraction; NT-proBNP, N-Terminal pro-B-type Natriuretic Peptide; SAP, Systolic Arterial Pressure; HR, Heart Rate; P/F, PaO2/FiO2 ratio; ACE-i, Angiotensin-Converting Enzyme inhibitors; ARB, Angiotensin Receptor Blocker; MRA, Mineralocorticoid Receptor Antagonist; SGLT2-i, Sodium-GLucose coTransporter-2 inhibitors. Regarding SARC-F items, as shown in Table 3 , we observed higher proportion of inability to rise from a chair in deceased patients compared to those survived (53.5% vs 29.2%, respectively, p = 0.01), and an increased number of falls in the last year prior hospitalization (1–3 falls in 30.2% vs 14.5%, respectively; 4 or more falls in 25.6% vs 14.5%, respectively, p = 0.01 for both); no other relevant differences were found across other items. Table 3 SARC-F items and their relationship with 30-day post-discharge mortality. Sarc-F Items All patients n = 184 Death 30 days n = 47 Controls n = 137 P-value Limitation in lifting 10 kg (%) -None (0 pt) -Some (1 pt) -Unable (2 pt) 34 (18.2) 41 (22.2) 109 (59.6) 8 (16.3) 8 (16.3) 31 (67.4) 26 (18.8) 33 (24.1) 78 (57.1) 0.45 Limitation in walking across a room (%) None (0 pt) Some (1 pt) Unable (2 pt) 65 (35.6) 49 (26.5) 70 (37.9) 11 (23.3) 13 (27.9) 23 (48.8) 54 (39.5) 36 (26.1) 47 (34.4) 0.11 Limitation in rising from a chair (%) -None (0 pt) -Some (1 pt) -Unable (2 pt) 62 (33.9) 57 (31.1) 65 (35) 10 (20.9) 12 (25.6) 25 (53.5) 52 (38) 45 (32.8) 40 (29.2) 0.01 Limitation in climbing 10 stairs (%) -None (0 pt) -Some (1 pt) -Unable (2 pt) 33 (18.1) 56 (30.5) 95 (51.4) 6 (13.9) 10 (20.9) 31 (65.2) 27 (19.4) 46 (33.6) 64 (47) 0.11 N° of falls in last year (%) -None (0 pt) -1-3 falls (1 pt) -4 or more (2 pt) 118 (64.7) 34 (18.4) 32 (16.9) 21 (44.2) 14 (30.2) 12 (25.6) 97 (71) 20 (14.5) 20 (14.5) 0.01 Using a univariate logistic regression model, SARC-F and systolic arterial pressure (SAP) were found to be the only statistically significant variables in terms of 30-days post-discharge mortality (see Supplemental Table 1). By multivariate logistic analysis, SARC-F resulted independently associated with mortality after adjustment for age, sex, number of comorbidities, NT-pro-BNP and SAP at discharge [adjusted OR: 1.13 (CI95% 1.03–1.33), p = 0.03], (Fig. 1 and Supplementary Table 2). Furthermore, HGS score resulted independently associated with mortality after extensive adjustment for potential confounders [(adjusted standardized β = -0.73 ± 0.03, p = 0.008), Fig. 2 ]. As secondary analysis, we performed multivariate logistic regression with the SARC-F sub-items. Inability in rising from a chair resulted independently associated with mortality [adjusted OR: 3.26 (CI95% 1.27–8.34), p = 0.014] as well as the number of falls in the last year. More in-depth, both Score 1 (ie, a number of falls between one and three in the last year) and Score 2 (greater than or equal to four falls) resulted independently associated with 30-days mortality [adjusted OR: 3.47 (CI95% 1.28–8.70), p = 0.008; adjusted OR: 3.30 (CI95% 1.28–8.49), p = 0.01; respectively (See Supplementary Tables 3 and 4]. Discussion In our study, we established the efficacy of early sarcopenia screening, employing the SARC-F questionnaire and handgrip strength test, in predicting 30-day post-discharge mortality among patients aged 75 years and older hospitalized for acute decompensated heart failure. For every 1-unit increase in the SARC-F questionnaire, the odds of 30-day mortality rose independently by 18%, a relationship robust to multiple adjustments for confounding variables. This research represents a pioneering attempt to validate a brief sarcopenia risk assessment as a prognostic indicator in the very old patient admitted for acute decompensated heart failure. In the present study more than 66% of older patients with DHF were found to be at high risk for sarcopenia, in agreement with a previous study by Zhao et al. [ 16 ]. As expected, patients with SARC-F ≥ 4 were older and frailer, showing a 18% higher prevalence of chronic HF as compared to those with SARC-F < 4. This result is consistent with a recent meta-analysis highlighting how patients with heart failure are typically prone to experience sarcopenia [ 25 ]. As a fact, sarcopenia and chronic HF seem to strictly be linked one another. In patients with HF, elevated oxidative processes, higher apoptotic activity and the decreased synthesis of striated muscle growth factors contribute to muscle wasting by catabolic shift in the muscle homeostasis [ 4 ]. Significantly, patients with a SARC-F score of ≥ 4 exhibited heightened pulmonary congestion, indicating severe cardiac failure, regardless of hypoalbuminemia status upon hospital admission. Notably, within the SARC-F sub-items, experiencing one or more falls in the preceding year and complete inability to rise from a chair emerged as robust independent predictors of 30-day mortality, reaffirming the adverse prognostic implications of accidental falls and physical frailty in the oldest-old patient demographic.[ 26 , 27 ]. Based on our data analysis, we found a direct correlation between lower handgrip strength (HGS) and increased mortality rates, highlighting HGS as an independent predictor of short-term adverse outcomes, consistent with findings from a recent study by Dai et al.[ 28 ]. This finding is significant, as it might be reasonable to assume that during the acute phase of hospitalization for HF, HGS may not necessarily reflect muscle weakness. However, these data suggest that incorporating the HGS test during hospitalization and assessing the SARC-F questionnaire could have notable implications in clinical practice. Not only can it aid in evaluating sarcopenia risk, but it can also contribute to the management and risk stratification of older patients recently discharged for acute HF. Noteworthy, Konishi et al. observed in their multicentre prospective cohort study, that in older patients with heart failure, sarcopenia and low hand grip values significantly affect mortality equally in HFpEF and HFrEF.[ 13 ] However, bioelectrical impedance analysis (BIA) or dual-energy X-ray absorptiometry (DEXA) may not always be economically feasible for developing countries or secondary care hospitals. In contrast, the SARC-F questionnaire and HGS test are simple, rapid, and cost-effective tools. Moreover, our study underscores the potential significance of preventive interventions for patients with DHF who exhibit an inability to rise from a chair and/or have a history of falls. These individuals may derive substantial benefits from early implementation of functional rehabilitation programs, nutritional reassessment, and evaluation in specialized heart failure outpatient clinics. Significantly, our findings underscore the significance of sarcopenia screening, as identified through these interventions, highlighting its potential reversibility. The Nutritional Intervention Program in Malnourished Patients Admitted for Heart Failure (PICNIC) has demonstrated that personalized nutritional interventions during and after hospitalization for acute HF may confer prognostic benefits [ 29 ]. Moreover, a multimodal, multidisciplinary assessment, based on physical activity and dietary recommendation has been proven to be effective in reducing poor outcomes in vulnerable older people [ 30 ], with women experiencing greater benefits than men [ 31 , 32 ]. However, at least two limitations of the study need to be acknowledged. Firstly, as a single-centre investigation, further multicentre studies are warranted to validate the prognostic significance of SARC-F in older patients with acutely DHF; yet the clinical uniformity of the cohort and the clear protocol represent strengths of our investigation. Secondly, the current study has only examined patients at risk for sarcopenia while, a definitive sarcopenia diagnosis was not ascertained due to the lack of a validated diagnostic muscle mass assessment; however, muscle mass, strength, and function have been recognized to be strongly influenced by demographic and anthropometric features and standard, uniformed threshold values have not been established [ 4 ]. Additionally, the current research was not specifically designed to evaluate sarcopenic patients but to test the prognostic usefulness of early sarcopenia assessment. In conclusion, in the present study increasing SARC-F total score, inability in rising from a chair, history of falls and low HGS score were independently associated with higher short-term mortality risk, thus defining older patients with acutely DHF at high risk of poor outcome following hospitalization. Nevertheless, further studies are needed to determine whether sarcopenia can be a potential target to improve outcomes in older patients with DHF. Abbreviations BMI indicates Body Mass Index HGS Hand Grip Strength CFS Clinical Frailty Scale SARC-F Strength- Assistance with walking- Rising from a chair- Climbing stairs and Falls questionnaire COPD Chronic Obstructive Pulmonary Disease PEFS Pleural EFfusion Score IVC Inferior Vena Cava LVEF Left Ventricular Ejection Fraction NT-proBNP N-Terminal pro-B-type Natriuretic Peptide SAP Systolic Arterial Pressure HR Heart Rate P/F PaO2/FiO2 ratio ACE-i Angiotensin-Converting Enzyme inhibitors ARB Angiotensin Receptor Blocker MRA Mineralocorticoid Receptor Antagonist SGLT2-i Sodium-GLucose coTransporter-2 inhibitors. Statements and Declarations Declaration of interest: the authors declare they have no conflict of interest Competing interests : On behalf of all authors, the corresponding author states that there is no conflict of interest Acknowledgments: The authors thank Dr. Maria Giovanna Bianco, Dr. Andrea Giusti, Dr. Bianca Lemmi, Dr. Igino Maria Pompilii, Dr. Cinzia Guerrini and all the members of the Cardio-geriatrics Interest Group of the Geriatrics Unit of Pisa University Hospital for the help given throughout the project. Funding : This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors contributions: Conceptualization: Chukwuma Okoye, Virginia Morelli, Riccardo Franchi. Methodology: Chukwuma Okoye, Agostino Virdis, Tessa Mazzarone; Formal analysis and investigation: Riccardo Franchi, Virginia Morelli, Lorenzo Maccioni, Chukwuma Okoye, Cristina Cargiolli; Writing - original draft preparation: Chukwuma Okoye, Virginia Morelli; Writing - review and editing: Agostino Virdis, Daniela Guarino, Filippo Niccolai, Valeria Calsolaro; Supervision: Agostino Virdis, Daniela Guarino. References McDonagh TA, Metra M, Adamo M, Gardner RS, Baumbach A, Böhm M, et al. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure. Eur Heart J. 2021 Sep;42(36):3599–726. Braunwald E. The war against heart failure: the Lancet lecture. Lancet (London, England). 2015 Feb;385(9970):812–24. Lloyd-Jones D, Adams RJ, Brown TM, Carnethon M, Dai S, De Simone G, et al. Heart disease and stroke statistics--2010 update: a report from the American Heart Association. Circulation. 2010 Feb;121(7):e46–215. Lena A, Anker MS, Springer J. Muscle Wasting and Sarcopenia in Heart Failure-The Current State of Science. Int J Mol Sci. 2020 Sep;21(18). Curcio F, Testa G, Liguori I, Papillo M, Flocco V, Panicara V, et al. Sarcopenia and Heart Failure. Nutrients. 2020 Jan;12(1). Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing [Internet]. 2019 Jan 1;48(1):16–31. Available from: https://pubmed.ncbi.nlm.nih.gov/30312372 Springer J, Springer J-I, Anker SD. Muscle wasting and sarcopenia in heart failure and beyond: update 2017. ESC Hear Fail. 2017 Nov;4(4):492–8. Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JGF, Coats AJS, et al. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution. Eur J Heart Fail. 2016 Aug;18(8):891–975. Loncar G, Springer J, Anker M, Doehner W, Lainscak M. Cardiac cachexia: hic et nunc. J Cachexia Sarcopenia Muscle. 2016 Jun;7(3):246–60. Honda S, Uemura Y, Shibata R, Sekino T, Takemoto K, Ishikawa S, et al. Clinical implications of severe sarcopenia in Japanese patients with acute heart failure. Geriatr Gerontol Int. 2022 Jun;22(6):477–82. Xu J, Reijnierse EM, Pacifico J, Wan CS, Maier AB. Sarcopenia is associated with 3-month and 1-year mortality in geriatric rehabilitation inpatients: RESORT. Age Ageing. 2021 Nov;50(6):2147–56. Maeda D, Matsue Y, Kagiyama N, Jujo K, Saito K, Kamiya K, et al. Sex differences in the prevalence and prognostic impact of physical frailty and sarcopenia among older patients with heart failure. Nutr Metab Cardiovasc Dis. 2022 Feb;32(2):365–72. Konishi M, Kagiyama N, Kamiya K, Saito H, Saito K, Ogasahara Y, et al. Impact of sarcopenia on prognosis in patients with heart failure with reduced and preserved ejection fraction. Eur J Prev Cardiol. 2021 Aug;28(9):1022–9. Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG, et al. A Short Physical Performance Battery Assessing Lower Extremity Function: Association With Self-Reported Disability and Prediction of Mortality and Nursing Home Admission. J Gerontol [Internet]. 1994 Mar 1;49(2):M85–94. Available from: https://doi.org/10.1093/geronj/49.2.M85 Tanaka S, Kamiya K, Hamazaki N, Matsuzawa R, Nozaki K, Maekawa E, et al. Utility of SARC-F for Assessing Physical Function in Elderly Patients With Cardiovascular Disease. J Am Med Dir Assoc. 2017 Feb;18(2):176–81. Zhao W, Lu M, Wang X, Guo Y. The role of sarcopenia questionnaires in hospitalized patients with chronic heart failure. Aging Clin Exp Res. 2021 Feb;33(2):339–44. Nagre A. Focus-assessed transthoracic echocardiography: Implications in perioperative and intensive care. Vol. 22, Annals of Cardiac Anaesthesia. Wolters Kluwer Medknow Publications; 2019. p. 302–8. Lindner M, Thomas R, Claggett B, Lewis EF, Groarke J, Merz AA, et al. Quantification of pleural effusions on thoracic ultrasound in acute heart failure. Eur Hear journal Acute Cardiovasc care. 2020 Aug;9(5):513–21. Stuck AE, Siu AL, Wieland GD, Adams J, Rubenstein LZ. Comprehensive geriatric assessment: a meta-analysis of controlled trials. Lancet (London, England). 1993 Oct;342(8878):1032–6. Pfeiffer E. A short portable mental status questionnaire for the assessment of organic brain deficit in elderly patients. J Am Geriatr Soc. 1975 Oct;23(10):433–41. Katz S, Ford Ab, Moskowitz Rw, Jackson Ba, Jaffe Mw. Studies Of Illness In The Aged. The Index Of ADL: A Standardized Measure Of Biological And Psychosocial Function. Jama. 1963 Sep;185:914–9. Lawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist. 1969;9(3):179–86. Guigoz Y, Lauque S, Vellas BJ. Identifying the elderly at risk for malnutrition. The Mini Nutritional Assessment. Clin Geriatr Med. 2002 Nov;18(4):737–57. Barbosa-Silva TG, Menezes AMB, Bielemann RM, Malmstrom TK, Gonzalez MC. Enhancing SARC-F: Improving Sarcopenia Screening in the Clinical Practice. J Am Med Dir Assoc. 2016 Dec;17(12):1136–41. Zhang Y, Zhang J, Ni W, Yuan X, Zhang H, Li P, et al. Sarcopenia in heart failure: a systematic review and meta-analysis. ESC Hear Fail. 2021 Apr;8(2):1007–17. Hartholt KA, van Beeck EF, van der Cammen TJM. Mortality From Falls in Dutch Adults 80 Years and Older, 2000-2016. JAMA. 2018 Apr;319(13):1380–2. Florence CS, Bergen G, Atherly A, Burns E, Stevens J, Drake C. Medical Costs of Fatal and Nonfatal Falls in Older Adults. J Am Geriatr Soc. 2018 Apr;66(4):693–8. Dai KZ, Laber EB, Chen H, Mentz RJ, Malhotra C. Hand Grip Strength Predicts Mortality and Quality of Life in Heart Failure: Insights From the Singapore Cohort of Patients With Advanced Heart Failure. J Card Fail. 2022 Dec; Toth MJ, Gottlieb SS, Goran MI, Fisher ML, Poehlman ET. Daily energy expenditure in free-living heart failure patients. Am J Physiol Metab [Internet]. 1997 Mar 1;272(3):E469–75. Available from: https://doi.org/10.1152/ajpendo.1997.272.3.E469 Bernabei R, Landi F, Calvani R, Cesari M, Del Signore S, Anker SD, et al. Multicomponent intervention to prevent mobility disability in frail older adults: randomised controlled trial (SPRINTT project). BMJ. 2022 May;377:e068788. Zhang Y, Zou L, Chen S-T, Bae JH, Kim DY, Liu X, et al. Effects and Moderators of Exercise on Sarcopenic Components in Sarcopenic Elderly: A Systematic Review and Meta-Analysis. Vol. 8, Frontiers in medicine. 2021. p. 649748. Chen N, He X, Feng Y, Ainsworth BE, Liu Y. Effects of resistance training in healthy older people with sarcopenia: a systematic review and meta-analysis of randomized controlled trials. Eur Rev aging Phys Act Off J Eur Gr Res into Elder Phys Act. 2021 Nov;18(1):23. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4223789","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":289560477,"identity":"5312af74-a3ff-41f7-a71f-6f2b933f0bd5","order_by":0,"name":"Chukwuma Okoye","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABC0lEQVRIiWNgGAWjYDACCQZmKIsNRNgwGDAkAGkDBh64BAEtachacOhB03IYqgUMsGvhn91jbMzbtk2egb0t8TFPxfk8c/YENumCgjsyDOz8B7BacueMcTJv223DBp5jh415ztwutux5wCY9w+AZTocZSOQYH85tu83YIJHeJg3Um7jhBtAWHoPDBLXYQ7T8O0eclmSglsQGibRj0rwNBwhrkbiRVmz859zt5DaeY8mGc44lFxucedhszQP0CxszswHWEJuRvFlyRtlt2372NsMHb2rs8gyOJx+8zfPnjj0//8EHWK2BAVCsMPEwgCKFsQHIPgCJJ0KA8QcDPB4PEKNhFIyCUTAKRgYAAOAsWMzSzZLfAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-2969-7393","institution":"University of Milano-Bicocca","correspondingAuthor":true,"prefix":"","firstName":"Chukwuma","middleName":"","lastName":"Okoye","suffix":""},{"id":289560478,"identity":"dba4fb6e-d479-4b80-bb10-46df6b649652","order_by":1,"name":"Virginia Morelli","email":"","orcid":"","institution":"Pisana University Hospital: Azienda Ospedaliero Universitaria Pisana","correspondingAuthor":false,"prefix":"","firstName":"Virginia","middleName":"","lastName":"Morelli","suffix":""},{"id":289560479,"identity":"d246080b-cf94-43a8-a6ab-44fa69115604","order_by":2,"name":"Riccardo Franchi","email":"","orcid":"","institution":"Azienda USL Toscana nord ovest","correspondingAuthor":false,"prefix":"","firstName":"Riccardo","middleName":"","lastName":"Franchi","suffix":""},{"id":289560480,"identity":"1e002390-188a-4120-81d7-a64aec1f3dba","order_by":3,"name":"Tessa Mazzarone","email":"","orcid":"","institution":"Pisana University Hospital: Azienda Ospedaliero Universitaria Pisana","correspondingAuthor":false,"prefix":"","firstName":"Tessa","middleName":"","lastName":"Mazzarone","suffix":""},{"id":289560481,"identity":"d0b50d9f-f9ff-4b1a-8b08-b8ea66df32d7","order_by":4,"name":"Daniela Guarino","email":"","orcid":"","institution":"Pisana University Hospital: Azienda Ospedaliero Universitaria Pisana","correspondingAuthor":false,"prefix":"","firstName":"Daniela","middleName":"","lastName":"Guarino","suffix":""},{"id":289560482,"identity":"14573302-6ef2-428a-ad0f-0d1c1aa6e7d7","order_by":5,"name":"Lorenzo Maccioni","email":"","orcid":"","institution":"Pisana University Hospital: Azienda Ospedaliero Universitaria Pisana","correspondingAuthor":false,"prefix":"","firstName":"Lorenzo","middleName":"","lastName":"Maccioni","suffix":""},{"id":289560483,"identity":"0d40cd34-efbb-4441-a2af-befe018e3670","order_by":6,"name":"Cristina Cargiolli","email":"","orcid":"","institution":"Pisana University Hospital: Azienda Ospedaliero Universitaria Pisana","correspondingAuthor":false,"prefix":"","firstName":"Cristina","middleName":"","lastName":"Cargiolli","suffix":""},{"id":289560484,"identity":"6d471fa4-a7f5-4aa7-b33c-2f37a146615c","order_by":7,"name":"Valeria Calsolaro","email":"","orcid":"","institution":"AOU Pisana: Azienda Ospedaliero Universitaria Pisana","correspondingAuthor":false,"prefix":"","firstName":"Valeria","middleName":"","lastName":"Calsolaro","suffix":""},{"id":289560485,"identity":"a8aaa490-baff-4d6d-b2c4-c66d34158950","order_by":8,"name":"Filippo Niccolai","email":"","orcid":"","institution":"AOU Pisana: Azienda Ospedaliero Universitaria Pisana","correspondingAuthor":false,"prefix":"","firstName":"Filippo","middleName":"","lastName":"Niccolai","suffix":""},{"id":289560486,"identity":"1a9ce137-9906-4706-b17a-79abc8342b5c","order_by":9,"name":"Agostino Virdis","email":"","orcid":"","institution":"Pisana University Hospital: Azienda Ospedaliero Universitaria Pisana","correspondingAuthor":false,"prefix":"","firstName":"Agostino","middleName":"","lastName":"Virdis","suffix":""}],"badges":[],"createdAt":"2024-04-05 15:14:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4223789/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4223789/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54928522,"identity":"0365c4f2-1d69-4146-96c5-74a0d8022559","added_by":"auto","created_at":"2024-04-18 17:39:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":100332,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between SARC-F and predicted 30-day-mortality. Multivariable analysis, inferential plot.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4223789/v1/197432da2d6aa9b43ba1abf4.png"},{"id":54928523,"identity":"cabaf8b9-ce8b-4adf-8a12-577ef610c618","added_by":"auto","created_at":"2024-04-18 17:39:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":84316,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between Hand grip strength test and predicted 30-day-mortality. Multivariable analysis, inferential plot.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4223789/v1/bdcdf74f8e0b15b562f5de7b.png"},{"id":54929267,"identity":"ec9b56e4-9101-4944-a28f-8a507dd547dd","added_by":"auto","created_at":"2024-04-18 17:47:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":500750,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4223789/v1/38d79362-364b-4a9c-983e-77720f221540.pdf"},{"id":54928524,"identity":"166f2cc7-af99-4546-98e8-309a10de88e4","added_by":"auto","created_at":"2024-04-18 17:39:11","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":98773,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTablessarcf.docx","url":"https://assets-eu.researchsquare.com/files/rs-4223789/v1/908e8969375339cea5c23b75.docx"}],"financialInterests":"","formattedTitle":"Usefulness of an early sarcopenia screening in predicting short-term mortality in older patients discharged for acute heart failure .","fulltext":[{"header":"Key summary points","content":"\u003cp\u003e\u003cstrong\u003eAim:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo determine the usefulness of the Hand grip strength test (HGS) and SARC-F in predicting short-term mortality among hospitalized older patients with acute heart failure\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFindings:\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eHGS test and SARC-F questionnaire predict short-term mortality in older patients with acute HF\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eMessage:\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eEarly sarcopenia screening can reliably predict the short-term mortality in older HF patients.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Introduction","content":"\u003cp\u003eHeart failure (HF) is one of the major causes of mortality and hospitalization worldwide, and 4 out of 5 patients with HF are older than 65 years [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Despite medical improvement, the five-year survival rates for HF remain poorer than most cancers [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In particular, the risk of re-hospitalization or death is highest in the 30-days following discharge for acute decompensated heart failure (ADHF)[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Moving the aim away from the treatment of a single disease and toward a more holistic approach, the latest guidelines advocate for a comprehensive multidisciplinary assessment of HF patients[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In this regard, recent investigations reported that 20\u0026ndash;30% of patients with HF may have a diagnosis of sarcopenia, a potentially reversible geriatric syndrome characterized by a progressive loss of skeletal muscle and strength resulting in impaired physical performance that can gradually lead to disability, reduced quality of life and even death [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Compared to non-HF patients, those with HF have a significantly higher prevalence of sarcopenia [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] thus suggesting the existence of a strong interconnection between the pathophysiological pathways involved in HF, age-related changes in body composition, and sarcopenia [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Patients with HF and sarcopenia are more prone to develop physical frailty and related negative health outcomes, with a higher risk of HF progression with the need for hospitalization [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] and an increased mortality rate [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Notwithstanding, very few studies have attempted to evaluate the short-term prognostic significance of sarcopenia in older individuals with HF [\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. According to the European Working Group on Sarcopenia in Older People 2 (EWGSOP2) guidelines [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], all patients with suspected sarcopenia should undergo the SARC-F, a 5-item questionnaire that is self-reported by patients based on their perception of limitations in strength, walking ability, rising from a chair, stair climbing, and experiences with falls. Subsequently, several diagnostic evaluation should be made to correctly diagnose sarcopenia, namely: i) evaluation of muscle strength using a calibrated handheld dynamometer or chair stand test, ii) assessment of muscle quantity through magnetic resonance imaging (MRI), computer tomography (CT) or Dual-energy X-ray absorptiometry (DEXA), iii) recognition of low physical performance that can be measured by gait speed, Short Physical Performance Battery (SPPB)[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and the Timed-Up and Go test (TUG). Nevertheless, SARC-F is an inexpensive and convenient method for sarcopenia risk screening [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and has been proved valid and accurate for identifying people at risk of sarcopenia associated adverse outcomes[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Given these premises, early sarcopenia screening could be helpful in predicting the outcomes of older patients with ADHF. This study aimed to determine the short-term prognostic role of sarcopenia assessed by the SARC-F questionnaire in hospitalized older patients with ADHF. Secondary endpoint was to evaluate the relationship between in-hospital Hand Grip Strength test (HGS) values, SARC-F sub-items, and short-term prognosis.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eWe prospectively enrolled all patients aged 75 years or older hospitalized with ADHF in our tertiary care hospital between January 1, 2022, and February 1, 2023. The exclusion criteria were: (1) inability to communicate with researchers or obtain informed consent; (2) critical illness requiring invasive ventilation at admission (3) acute coronary syndrome; (4) inability to perform a HGS test.\u003c/p\u003e \u003cp\u003eA panel of clinicians adjudicated the diagnosis of congestive heart failure based on clinical symptoms, signs, chest x-ray film results, echocardiographic findings and therapy at admission in line with recent international guidelines[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. All patients underwent a focused cardiac ultrasound (FOCUS), performed by an expert clinician. FOCUS follows the principle formulated in the focused assessed transthoracic echocardiography (FATE) protocol [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Furthermore, as patients underwent a diagnostic examination with bedside Point of care ultrasound (POCUS) including lung ultrasound, focused cardiac ultrasound, pleural effusion score (PEFS)[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], and inferior vena cava (IVC) assessment. All the patients underwent physical examination, complete blood tests, and a comprehensive geriatric assessment (CGA)[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] including cognitive evaluation using the Short Portable Mental Status Questionnaire (SPMSQ)[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], level of autonomy in terms of independence in the performance of basic (ADL)[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], and instrumental (IADL)[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], activities of daily living. Systolic Arterial Pressure (SAP) and Heart Rate (HR) were also collected at hospital discharge. The risk of malnutrition was assessed through the Mini Nutritional Assessment-Short Form (MNA-SF)[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and Body Mass Index (BMI). Functional capabilities and physical performance were evaluated through a pre-morbid SARC-F and HGS. SARC-F includes 5 items: strength, assistance in walking, rising from a chair, climbing stairs, and history of falls. Each component is scored on a 0\u0026ndash;2 scale and summed for an overall range of 0\u0026ndash;10. A total score of SARC-F\u0026thinsp;\u0026ge;\u0026thinsp;4 indicates high risk of sarcopenia [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Given that the onset of acute HF could influence the physical performance, patients or caregivers were asked to answer to SARC-F questions regarding the physical status and habits approximately thirty days prior to hospital admission for heart failure (pre-morbid status). The HGS test was performed using a hand dynamometer with the dominant hand. HGS is a simple measure of strength and may be utilized as a marker of mobility. The cut-off level of \u0026lt;\u0026thinsp;16 kg in women and \u0026lt;\u0026thinsp;27 kg in men have been identified to detect patients at risk for sarcopenia. Participants were seated with shoulder adducted, elbow flexed to 90 degrees, and forearm and wrist neutral. The highest score of three consecutive measurements was recorded. The 30 post-discharge mortality rate was assessed by phone interview. The study complied with the Declaration of Helsinki and was approved by the local Ethics Committee (Tuscany Regional Ethics Committee for the Clinical Experimentation: FUN-sc 23956). Each patient provided written informed consent to participate in the study.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was performed with IBM SPSS Statistic (IBM SPSS Statistic version 27.0 lnk IBM Corporation and its licensor 1989\u0026ndash;2020) and RStudio (RStudio Team: Integrated Development for R. RStudio, PBC, Boston, MA). Continuous variables were presented as mean and standard deviation, ordinal variables as median and interquartile range (IQR), and categorical variables as percentage. Mann-Whitney and chi-square tests were used for multiple comparisons.\u003c/p\u003e \u003cp\u003eA multivariable logistic regression was performed to evaluate the association between SARC-F, HGS test and 30-days-mortality using a priori selected model covariates on the basis of clinical considerations. As a secondary analysis a logistic multivariable analysis was performed among SARC-F sub-items with a resulted statistically significant at the univariate analysis. Covariates included in the multivariable model were age, sex, number of comorbidities, NT-pro-BNP, and SAP at discharge. Estimate odds ratios (ORs) with 95% confidence intervals (CIs) were obtained. The sample size was calculated on the basis of previous research and required at least 155 patients, to detect a 10% difference in odds ratio for 1-point increase of SARC-F (as ordinal predictor), with a power of 80% and a 0.05 α risk. Tests were performed considering a level of significance of 5%.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eAs shown in Supplementary Fig. 1, 229 patients hospitalized with acutely DHF were assessed for eligibility. Thirty-two patients were not included in the study due to in-hospital deaths (10), inability to participate (19), or refusal (3). Thus, 191 patients were finally enrolled, of whom 7 were lost to follow-up. The remaining 184 patients (mean [SD], 86.8 [5.9] years) were ultimately included in the statistical analysis; among them 47 (25.5%) died within 30 days following hospital discharge. No differences were found between deceased and survived patients in terms of gender prevalence, mean age, body weight, or the number and type of comorbidities (see Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Deceased patients had a higher median SARC-F [8 (IQR\u0026thinsp;=\u0026thinsp;3.5) vs 5 (IQR\u0026thinsp;=\u0026thinsp;6); respectively, p\u0026thinsp;=\u0026thinsp;0.005] and mean Hand Grip Strength [11.1 (SD\u0026thinsp;=\u0026thinsp;7.4) Kg vs 15.8 (SD\u0026thinsp;=\u0026thinsp;7.7) Kg, respectively; p\u0026thinsp;=\u0026thinsp;0.006], compared to their counterparts. Regarding pulmonary and systemic congestion, no differences were detected in terms of B lines number, pleural effusion score (PEFS) and characteristics of inferior vena cava.\u0026nbsp;\u003c/p\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison between deceased patients and controls.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAll patients\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;184\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDeath at 30 days\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;47\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControls\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;137\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eDemographics\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e111 (60.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (59.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83 (60.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge mean, years (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86.8 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e87.6 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86.6 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI mean, kg/m\u003csup\u003e2\u003c/sup\u003e (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.6 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.1 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.8 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHGS mean, kg (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.8 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.1 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.8 (7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCFS median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSARC-F median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSARC-F\u0026thinsp;\u0026ge;\u0026thinsp;4 (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122 (66.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37 (79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85 (62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.04\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eIn-Hospital events\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLength of stay median, days (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUpgrade diuretic therapy (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75 (41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (32.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60 (43.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePulmonary edema (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 (14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdverse events (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53 (28.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37 (27.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003ePost-discharge events\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 days readmission (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (13.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eComorbidities\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u0026deg; of comorbidities median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCOPD (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 (25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (26.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypertension (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e120 (65.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95 (69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeart Failure (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e116 (63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 (74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82 (60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiabetes (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52 (28.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (26.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (29.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStroke (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (17.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (26.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChronic renal failure (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60 (32.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (43.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIschemic heart disease (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65 (35.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (41.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46 (33.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAtrial fibrillation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e116 (63.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (67.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84 (61.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCancer (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39 (21.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (23.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (20.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eExamination and laboratory values\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eB-lines number median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (11.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePEFS cumulative median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIVC max mean, mm (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.3 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.9 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.1 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIVC min mean, mm (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.6 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.6 (7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.3 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLVEF\u0026thinsp;\u0026lt;\u0026thinsp;40% (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58 (31.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (31.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (31.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNT-proBNP admission median, pg/ml (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7837 (12075.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13558 (26195.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7463 (8830)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNT-proBNP discharge median, pg/ml (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3843 (6897.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6443 (11455)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3505 (5615.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean SAP (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e123(21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e116 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e126 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.044\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean PAD (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68 (14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean HR (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80(13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83(14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79(12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.156\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean Creatinine (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.39 (0.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.49(0.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.36(0.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.395\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlbumin mean, g/dl (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.03 (0.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.9 (0.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.1 (0.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean Hemoglobin g/L (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.7(1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.4(1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.8(1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.318\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP/F admission mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e311.3 (93.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e308.3 (100.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e312.3 (91.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eMedications\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBeta-blockers at discharge (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e151 (82.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (84.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e111 (81.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACE-I at discharge (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71 (38.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (47.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48 (34.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eARB at discharge (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMRA at discharge (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (17.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFurosemide at discharge (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e151 (82.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42 (89.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e109 (79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDigoxin at discharge (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSGLT2-i at discharge (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eContinuous variables are expressed as mean SD or median with IQR properly.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations:\u0026nbsp;\u003c/em\u003eBMI indicates Body Mass Index; HGS, Hand Grip Strength; CFS, Clinical Frailty Scale; SARC-F, Strength- Assistance with walking- Rising from a chair- Climbing stairs and Falls questionnaire; COPD, Chronic Obstructive Pulmonary Disease; PEFS, Pleural EFfusion Score; IVC, Inferior Vena Cava; LVEF, Left Ventricular Ejection Fraction; NT-proBNP, N-Terminal pro-B-type Natriuretic Peptide; SAP, Systolic Arterial Pressure; HR, Heart Rate; P/F, PaO2/FiO2 ratio; ACE-i, Angiotensin-Converting Enzyme inhibitors; ARB, Angiotensin Receptor Blocker; MRA, Mineralocorticoid Receptor Antagonist; SGLT2-i, \u0026nbsp;Sodium-GLucose coTransporter-2 inhibitors.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;As shown in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, 122 patients (66.3%) were found to be at high risk of sarcopenia (SARC-F\u0026thinsp;\u0026ge;\u0026thinsp;4), showing a 1.9 times higher 30-day mortality than controls (30% vs. 16%, p\u0026thinsp;=\u0026thinsp;0.04). Patients with SARC-F\u0026thinsp;\u0026ge;\u0026thinsp;4 were older [mean age: 87.8 years (SD\u0026thinsp;=\u0026thinsp;5.5) vs 84.5 (SD\u0026thinsp;=\u0026thinsp;6.2); respectively, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001] and more frequently women (65% vs. 48.3%, p\u0026thinsp;=\u0026thinsp;0.03), and lower HGS score [mean HGS test: 12.9 (SD\u0026thinsp;=\u0026thinsp;6.8) vs 18.9 (SD\u0026thinsp;=\u0026thinsp;8.3) respectively; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001], compared to their peers. By Point-of-care Ultrasound (POCUS) assessment, we observed that patients at high risk of sarcopenia had higher Pleural Effusion Score [3 (IQR\u0026thinsp;=\u0026thinsp;5) vs 1 (IQR\u0026thinsp;=\u0026thinsp;4); respectively, p\u0026thinsp;=\u0026thinsp;0.009] compared to counterparts. Concerning comorbidities, we found a higher prevalence of chronic heart failure (68.4% vs. 50.8%, p\u0026thinsp;=\u0026thinsp;0.02) in patients at high risk of sarcopenia compared to those at low risk.\u0026nbsp;\u003c/p\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison between patients with positive screening for sarcopenia (SARC-F\u0026thinsp;\u0026ge;\u0026thinsp;4) and controls.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAll patients\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;184\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSARC-F\u0026thinsp;\u0026ge;\u0026thinsp;4\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;122\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSARC-F\u0026thinsp;\u0026lt;\u0026thinsp;4\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;62\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eDemographics\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e111 (60.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e81 (65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (48.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge mean, years (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86.8 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e87.8 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84.5 (6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI mean, kg/m\u003csup\u003e2\u003c/sup\u003e (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.6 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.1 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.6 (4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHGS mean, kg (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.8 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.9 (6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.9 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCFS median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eIn-Hospital events\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHospital stay median, days (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (3.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUpgrade diuretic therapy (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75 (41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 (39.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 (42.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePulmonary edema (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 (14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (14.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdverse events (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53 (28.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38 (31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (24.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003ePost-discharge events\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 days readmission (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (13.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (13.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 days mortality (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 (25.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37 (30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.04\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eComorbidities\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u0026deg; of comorbidities median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (2.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCOPD (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 (25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (25.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (28.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypertension (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e120 (65.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82 (67.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38 (62.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeart Failure (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e116 (63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84 (68.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (50.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiabetes (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52 (28.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 (27.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (28.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStroke (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (17.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChronic renal failure (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60 (32.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (27.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIschemic heart disease (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65 (35.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44 (35.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (32.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAtrial fibrillation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e116 (63.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 (65.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36 (57.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCancer (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39 (21.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (20.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (25.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eExamination and laboratory values\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eB-lines number median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.5 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.5 (13.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePEFS cumulative median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIVC max mean, mm (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.3 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.9 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.2 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIVC min mean, mm (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.6 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.6 (7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.7 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLVEF\u0026thinsp;\u0026lt;\u0026thinsp;40% (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58 (31.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNT-proBNP max median, pg/ml (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7837 (12075.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9804.5 (14690.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6264 (6942)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNT-proBNP min median, pg/ml (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3843 (6897.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4257(6553.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2112 (4630.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean PAS (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e123 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e123 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e123 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean PAD (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean HR (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e81 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean Creatinine (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.39 (0.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.45 (0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,26 (0.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean Hemoglobin g/L (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.7 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.5 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.3 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP/F admission mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e311.3 (93.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e316.3 (90.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e298.9 (101.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHCO3- admission mean, mmol/L (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.4 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.7 (4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.1 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHCO3- dimission mean, mmol/L (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.3 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.5 (6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.8 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eMedications\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBeta-blockers at discharge (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e151 (82.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e108 (88.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (68.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACE-i at discharge (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71 (38.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42 (34.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (47.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eARB at discharge (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMRA at discharge (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (17.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFurosemide at discharge (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e151 (82.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e102 (83.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 (79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDigoxin at discharge (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSGLT2-i at discharge (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations\u003c/em\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eBMI indicates Body Mass Index; HGS, Hand Grip Strength; CFS, Clinical Frailty Scale; SARC-F, Strength- Assistance with walking- Rising from a chair- Climbing stairs and Falls questionnaire; COPD, Chronic Obstructive Pulmonary Disease; PEFS, Pleural EFfusion Score; IVC, Inferior Vena Cava; LVEF, Left Ventricular Ejection Fraction; NT-proBNP, N-Terminal pro-B-type Natriuretic Peptide; SAP, Systolic Arterial Pressure; HR, Heart Rate; P/F, PaO2/FiO2 ratio; ACE-i, Angiotensin-Converting Enzyme inhibitors; ARB, Angiotensin Receptor Blocker; MRA, Mineralocorticoid Receptor Antagonist; SGLT2-i, \u0026nbsp;Sodium-GLucose coTransporter-2 inhibitors.\u003c/p\u003e\n\u003cp\u003eRegarding SARC-F items, as shown in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, we observed higher proportion of inability to rise from a chair in deceased patients compared to those survived (53.5% vs 29.2%, respectively, p\u0026thinsp;=\u0026thinsp;0.01), and an increased number of falls in the last year prior hospitalization (1\u0026ndash;3 falls in 30.2% vs 14.5%, respectively; 4 or more falls in 25.6% vs 14.5%, respectively, p\u0026thinsp;=\u0026thinsp;0.01 for both); no other relevant differences were found across other items.\u0026nbsp;\u003c/p\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSARC-F items and their relationship with 30-day post-discharge mortality.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSarc-F Items\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAll patients\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;184\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDeath 30 days\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;47\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControls\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;137\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLimitation in lifting 10 kg (%)\u003c/p\u003e\n \u003cp\u003e-None (0 pt)\u003c/p\u003e\n \u003cp\u003e-Some (1 pt)\u003c/p\u003e\n \u003cp\u003e-Unable (2 pt)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 (18.2)\u003c/p\u003e\n \u003cp\u003e41 (22.2)\u003c/p\u003e\n \u003cp\u003e109 (59.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (16.3)\u003c/p\u003e\n \u003cp\u003e8 (16.3)\u003c/p\u003e\n \u003cp\u003e31 (67.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 (18.8)\u003c/p\u003e\n \u003cp\u003e33 (24.1)\u003c/p\u003e\n \u003cp\u003e78 (57.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLimitation in walking across a room (%)\u003c/p\u003e\n \u003cp\u003eNone (0 pt)\u003c/p\u003e\n \u003cp\u003eSome (1 pt)\u003c/p\u003e\n \u003cp\u003eUnable (2 pt)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65 (35.6)\u003c/p\u003e\n \u003cp\u003e49 (26.5)\u003c/p\u003e\n \u003cp\u003e70 (37.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (23.3)\u003c/p\u003e\n \u003cp\u003e13 (27.9)\u003c/p\u003e\n \u003cp\u003e23 (48.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54 (39.5)\u003c/p\u003e\n \u003cp\u003e36 (26.1)\u003c/p\u003e\n \u003cp\u003e47 (34.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLimitation in rising from a chair (%)\u003c/p\u003e\n \u003cp\u003e-None (0 pt)\u003c/p\u003e\n \u003cp\u003e-Some (1 pt)\u003c/p\u003e\n \u003cp\u003e-Unable (2 pt)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62 (33.9)\u003c/p\u003e\n \u003cp\u003e57 (31.1)\u003c/p\u003e\n \u003cp\u003e65 (35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (20.9)\u003c/p\u003e\n \u003cp\u003e12 (25.6)\u003c/p\u003e\n \u003cp\u003e25 (53.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52 (38)\u003c/p\u003e\n \u003cp\u003e45 (32.8)\u003c/p\u003e\n \u003cp\u003e40 (29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLimitation in climbing 10 stairs (%)\u003c/p\u003e\n \u003cp\u003e-None (0 pt)\u003c/p\u003e\n \u003cp\u003e-Some (1 pt)\u003c/p\u003e\n \u003cp\u003e-Unable (2 pt)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33 (18.1)\u003c/p\u003e\n \u003cp\u003e56 (30.5)\u003c/p\u003e\n \u003cp\u003e95 (51.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (13.9)\u003c/p\u003e\n \u003cp\u003e10 (20.9)\u003c/p\u003e\n \u003cp\u003e31 (65.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27 (19.4)\u003c/p\u003e\n \u003cp\u003e46 (33.6)\u003c/p\u003e\n \u003cp\u003e64 (47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u0026deg; of falls in last year (%)\u003c/p\u003e\n \u003cp\u003e-None (0 pt)\u003c/p\u003e\n \u003cp\u003e-1-3 falls (1 pt)\u003c/p\u003e\n \u003cp\u003e-4 or more (2 pt)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e118 (64.7)\u003c/p\u003e\n \u003cp\u003e34 (18.4)\u003c/p\u003e\n \u003cp\u003e32 (16.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (44.2)\u003c/p\u003e\n \u003cp\u003e14 (30.2)\u003c/p\u003e\n \u003cp\u003e12 (25.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e97 (71)\u003c/p\u003e\n \u003cp\u003e20 (14.5)\u003c/p\u003e\n \u003cp\u003e20 (14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003eUsing a univariate logistic regression model, SARC-F and systolic arterial pressure (SAP) were found to be the only statistically significant variables in terms of 30-days post-discharge mortality (see Supplemental Table 1). By multivariate logistic analysis, SARC-F resulted independently associated with mortality after adjustment for age, sex, number of comorbidities, NT-pro-BNP and SAP at discharge [adjusted OR: 1.13 (CI95% 1.03\u0026ndash;1.33), p\u0026thinsp;=\u0026thinsp;0.03], (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and Supplementary Table 2).\u003c/p\u003e\n\u003cp\u003eFurthermore, HGS score resulted independently associated with mortality after extensive adjustment for potential confounders [(adjusted standardized \u0026beta; = -0.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03, p\u0026thinsp;=\u0026thinsp;0.008), Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e]. As secondary analysis, we performed multivariate logistic regression with the SARC-F sub-items. Inability in rising from a chair resulted independently associated with mortality [adjusted OR: 3.26 (CI95% 1.27\u0026ndash;8.34), p\u0026thinsp;=\u0026thinsp;0.014] as well as the number of falls in the last year. More in-depth, both Score 1 (ie, a number of falls between one and three in the last year) and Score 2 (greater than or equal to four falls) resulted independently associated with 30-days mortality [adjusted OR: 3.47 (CI95% 1.28\u0026ndash;8.70), p\u0026thinsp;=\u0026thinsp;0.008; adjusted OR: 3.30 (CI95% 1.28\u0026ndash;8.49), p\u0026thinsp;=\u0026thinsp;0.01; respectively (See Supplementary Tables 3 and 4].\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn our study, we established the efficacy of early sarcopenia screening, employing the SARC-F questionnaire and handgrip strength test, in predicting 30-day post-discharge mortality among patients aged 75 years and older hospitalized for acute decompensated heart failure. For every 1-unit increase in the SARC-F questionnaire, the odds of 30-day mortality rose independently by 18%, a relationship robust to multiple adjustments for confounding variables. This research represents a pioneering attempt to validate a brief sarcopenia risk assessment as a prognostic indicator in the very old patient admitted for acute decompensated heart failure.\u003c/p\u003e \u003cp\u003eIn the present study more than 66% of older patients with DHF were found to be at high risk for sarcopenia, in agreement with a previous study by Zhao et al. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. As expected, patients with SARC-F\u0026thinsp;\u0026ge;\u0026thinsp;4 were older and frailer, showing a 18% higher prevalence of chronic HF as compared to those with SARC-F\u0026thinsp;\u0026lt;\u0026thinsp;4. This result is consistent with a recent meta-analysis highlighting how patients with heart failure are typically prone to experience sarcopenia [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. As a fact, sarcopenia and chronic HF seem to strictly be linked one another. In patients with HF, elevated oxidative processes, higher apoptotic activity and the decreased synthesis of striated muscle growth factors contribute to muscle wasting by catabolic shift in the muscle homeostasis [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Significantly, patients with a SARC-F score of \u0026ge;\u0026thinsp;4 exhibited heightened pulmonary congestion, indicating severe cardiac failure, regardless of hypoalbuminemia status upon hospital admission. Notably, within the SARC-F sub-items, experiencing one or more falls in the preceding year and complete inability to rise from a chair emerged as robust independent predictors of 30-day mortality, reaffirming the adverse prognostic implications of accidental falls and physical frailty in the oldest-old patient demographic.[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBased on our data analysis, we found a direct correlation between lower handgrip strength (HGS) and increased mortality rates, highlighting HGS as an independent predictor of short-term adverse outcomes, consistent with findings from a recent study by Dai et al.[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. This finding is significant, as it might be reasonable to assume that during the acute phase of hospitalization for HF, HGS may not necessarily reflect muscle weakness. However, these data suggest that incorporating the HGS test during hospitalization and assessing the SARC-F questionnaire could have notable implications in clinical practice. Not only can it aid in evaluating sarcopenia risk, but it can also contribute to the management and risk stratification of older patients recently discharged for acute HF. Noteworthy, Konishi et al. observed in their multicentre prospective cohort study, that in older patients with heart failure, sarcopenia and low hand grip values significantly affect mortality equally in HFpEF and HFrEF.[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] However, bioelectrical impedance analysis (BIA) or dual-energy X-ray absorptiometry (DEXA) may not always be economically feasible for developing countries or secondary care hospitals. In contrast, the SARC-F questionnaire and HGS test are simple, rapid, and cost-effective tools.\u003c/p\u003e \u003cp\u003eMoreover, our study underscores the potential significance of preventive interventions for patients with DHF who exhibit an inability to rise from a chair and/or have a history of falls. These individuals may derive substantial benefits from early implementation of functional rehabilitation programs, nutritional reassessment, and evaluation in specialized heart failure outpatient clinics. Significantly, our findings underscore the significance of sarcopenia screening, as identified through these interventions, highlighting its potential reversibility. The Nutritional Intervention Program in Malnourished Patients Admitted for Heart Failure (PICNIC) has demonstrated that personalized nutritional interventions during and after hospitalization for acute HF may confer prognostic benefits [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Moreover, a multimodal, multidisciplinary assessment, based on physical activity and dietary recommendation has been proven to be effective in reducing poor outcomes in vulnerable older people [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], with women experiencing greater benefits than men [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, at least two limitations of the study need to be acknowledged. Firstly, as a single-centre investigation, further multicentre studies are warranted to validate the prognostic significance of SARC-F in older patients with acutely DHF; yet the clinical uniformity of the cohort and the clear protocol represent strengths of our investigation. Secondly, the current study has only examined patients at risk for sarcopenia while, a definitive sarcopenia diagnosis was not ascertained due to the lack of a validated diagnostic muscle mass assessment; however, muscle mass, strength, and function have been recognized to be strongly influenced by demographic and anthropometric features and standard, uniformed threshold values have not been established [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Additionally, the current research was not specifically designed to evaluate sarcopenic patients but to test the prognostic usefulness of early sarcopenia assessment.\u003c/p\u003e \u003cp\u003eIn conclusion, in the present study increasing SARC-F total score, inability in rising from a chair, history of falls and low HGS score were independently associated with higher short-term mortality risk, thus defining older patients with acutely DHF at high risk of poor outcome following hospitalization. Nevertheless, further studies are needed to determine whether sarcopenia can be a potential target to improve outcomes in older patients with DHF.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMI indicates Body Mass Index\u003c/div\u003e \u003cdiv class=\"Description\"\u003e\u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHGS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHand Grip Strength\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCFS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eClinical Frailty Scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSARC-F\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStrength- Assistance with walking- Rising from a chair- Climbing stairs and Falls questionnaire\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOPD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChronic Obstructive Pulmonary Disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePEFS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePleural EFfusion Score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIVC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInferior Vena Cava\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLVEF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLeft Ventricular Ejection Fraction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNT-proBNP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eN-Terminal pro-B-type Natriuretic Peptide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSAP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSystolic Arterial Pressure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHeart Rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eP/F\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePaO2/FiO2 ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eACE-i\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAngiotensin-Converting Enzyme inhibitors\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eARB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAngiotensin Receptor Blocker\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMRA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMineralocorticoid Receptor Antagonist\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSGLT2-i\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSodium-GLucose coTransporter-2 inhibitors.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Statements and Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eDeclaration of interest:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003ethe authors declare they have no conflict of interest\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003cem\u003e:\u003c/em\u003e On behalf of all authors, the corresponding author states that there is no conflict of interest\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments: \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank Dr. Maria Giovanna Bianco, Dr. Andrea Giusti, Dr. Bianca Lemmi, Dr. Igino Maria Pompilii, Dr. Cinzia Guerrini and all the members of the Cardio-geriatrics Interest Group of the Geriatrics Unit of Pisa University Hospital for the help given throughout the project.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: Chukwuma Okoye, Virginia Morelli, Riccardo Franchi. Methodology: Chukwuma Okoye, Agostino Virdis, Tessa Mazzarone; Formal analysis and investigation: Riccardo Franchi, Virginia Morelli, Lorenzo Maccioni, Chukwuma Okoye, Cristina Cargiolli; Writing - original draft preparation: Chukwuma Okoye, Virginia Morelli; Writing - review and editing: Agostino Virdis, Daniela Guarino, Filippo Niccolai, Valeria Calsolaro; Supervision: Agostino Virdis, Daniela Guarino.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eMcDonagh TA, Metra M, Adamo M, Gardner RS, Baumbach A, B\u0026ouml;hm M, et al. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure. Eur Heart J. 2021 Sep;42(36):3599\u0026ndash;726.\u003c/li\u003e\n \u003cli\u003eBraunwald E. The war against heart failure: the Lancet lecture. Lancet (London, England). 2015 Feb;385(9970):812\u0026ndash;24.\u003c/li\u003e\n \u003cli\u003eLloyd-Jones D, Adams RJ, Brown TM, Carnethon M, Dai S, De Simone G, et al. 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ESC Hear Fail. 2017 Nov;4(4):492\u0026ndash;8.\u003c/li\u003e\n \u003cli\u003ePonikowski P, Voors AA, Anker SD, Bueno H, Cleland JGF, Coats AJS, et al. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution. Eur J Heart Fail. 2016 Aug;18(8):891\u0026ndash;975.\u003c/li\u003e\n \u003cli\u003eLoncar G, Springer J, Anker M, Doehner W, Lainscak M. Cardiac cachexia: hic et nunc. J Cachexia Sarcopenia Muscle. 2016 Jun;7(3):246\u0026ndash;60.\u003c/li\u003e\n \u003cli\u003eHonda S, Uemura Y, Shibata R, Sekino T, Takemoto K, Ishikawa S, et al. Clinical implications of severe sarcopenia in Japanese patients with acute heart failure. Geriatr Gerontol Int. 2022 Jun;22(6):477\u0026ndash;82.\u003c/li\u003e\n \u003cli\u003eXu J, Reijnierse EM, Pacifico J, Wan CS, Maier AB. Sarcopenia is associated with 3-month and 1-year mortality in geriatric rehabilitation inpatients: RESORT. Age Ageing. 2021 Nov;50(6):2147\u0026ndash;56.\u003c/li\u003e\n \u003cli\u003eMaeda D, Matsue Y, Kagiyama N, Jujo K, Saito K, Kamiya K, et al. Sex differences in the prevalence and prognostic impact of physical frailty and sarcopenia among older patients with heart failure. Nutr Metab Cardiovasc Dis. 2022 Feb;32(2):365\u0026ndash;72.\u003c/li\u003e\n \u003cli\u003eKonishi M, Kagiyama N, Kamiya K, Saito H, Saito K, Ogasahara Y, et al. Impact of sarcopenia on prognosis in patients with heart failure with reduced and preserved ejection fraction. Eur J Prev Cardiol. 2021 Aug;28(9):1022\u0026ndash;9.\u003c/li\u003e\n \u003cli\u003eGuralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG, et al. A Short Physical Performance Battery Assessing Lower Extremity Function: Association With Self-Reported Disability and Prediction of Mortality and Nursing Home Admission. J Gerontol [Internet]. 1994 Mar 1;49(2):M85\u0026ndash;94. Available from: https://doi.org/10.1093/geronj/49.2.M85\u003c/li\u003e\n \u003cli\u003eTanaka S, Kamiya K, Hamazaki N, Matsuzawa R, Nozaki K, Maekawa E, et al. Utility of SARC-F for Assessing Physical Function in Elderly Patients With Cardiovascular Disease. J Am Med Dir Assoc. 2017 Feb;18(2):176\u0026ndash;81.\u003c/li\u003e\n \u003cli\u003eZhao W, Lu M, Wang X, Guo Y. The role of sarcopenia questionnaires in hospitalized patients with chronic heart failure. Aging Clin Exp Res. 2021 Feb;33(2):339\u0026ndash;44.\u003c/li\u003e\n \u003cli\u003eNagre A. Focus-assessed transthoracic echocardiography: Implications in perioperative and intensive care. Vol. 22, Annals of Cardiac Anaesthesia. Wolters Kluwer Medknow Publications; 2019. p. 302\u0026ndash;8.\u003c/li\u003e\n \u003cli\u003eLindner M, Thomas R, Claggett B, Lewis EF, Groarke J, Merz AA, et al. Quantification of pleural effusions on thoracic ultrasound in acute heart failure. Eur Hear journal Acute Cardiovasc care. 2020 Aug;9(5):513\u0026ndash;21.\u003c/li\u003e\n \u003cli\u003eStuck AE, Siu AL, Wieland GD, Adams J, Rubenstein LZ. Comprehensive geriatric assessment: a meta-analysis of controlled trials. Lancet (London, England). 1993 Oct;342(8878):1032\u0026ndash;6.\u003c/li\u003e\n \u003cli\u003ePfeiffer E. A short portable mental status questionnaire for the assessment of organic brain deficit in elderly patients. J Am Geriatr Soc. 1975 Oct;23(10):433\u0026ndash;41.\u003c/li\u003e\n \u003cli\u003eKatz S, Ford Ab, Moskowitz Rw, Jackson Ba, Jaffe Mw. Studies Of Illness In The Aged. The Index Of ADL: A Standardized Measure Of Biological And Psychosocial Function. Jama. 1963 Sep;185:914\u0026ndash;9.\u003c/li\u003e\n \u003cli\u003eLawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist. 1969;9(3):179\u0026ndash;86.\u003c/li\u003e\n \u003cli\u003eGuigoz Y, Lauque S, Vellas BJ. Identifying the elderly at risk for malnutrition. The Mini Nutritional Assessment. Clin Geriatr Med. 2002 Nov;18(4):737\u0026ndash;57.\u003c/li\u003e\n \u003cli\u003eBarbosa-Silva TG, Menezes AMB, Bielemann RM, Malmstrom TK, Gonzalez MC. Enhancing SARC-F: Improving Sarcopenia Screening in the Clinical Practice. J Am Med Dir Assoc. 2016 Dec;17(12):1136\u0026ndash;41.\u003c/li\u003e\n \u003cli\u003eZhang Y, Zhang J, Ni W, Yuan X, Zhang H, Li P, et al. Sarcopenia in heart failure: a systematic review and meta-analysis. ESC Hear Fail. 2021 Apr;8(2):1007\u0026ndash;17.\u003c/li\u003e\n \u003cli\u003eHartholt KA, van Beeck EF, van der Cammen TJM. Mortality From Falls in Dutch Adults 80 Years and Older, 2000-2016. JAMA. 2018 Apr;319(13):1380\u0026ndash;2.\u003c/li\u003e\n \u003cli\u003eFlorence CS, Bergen G, Atherly A, Burns E, Stevens J, Drake C. Medical Costs of Fatal and Nonfatal Falls in Older Adults. J Am Geriatr Soc. 2018 Apr;66(4):693\u0026ndash;8.\u003c/li\u003e\n \u003cli\u003eDai KZ, Laber EB, Chen H, Mentz RJ, Malhotra C. Hand Grip Strength Predicts Mortality and Quality of Life in Heart Failure: Insights From the Singapore Cohort of Patients With Advanced Heart Failure. J Card Fail. 2022 Dec;\u003c/li\u003e\n \u003cli\u003eToth MJ, Gottlieb SS, Goran MI, Fisher ML, Poehlman ET. Daily energy expenditure in free-living heart failure patients. Am J Physiol Metab [Internet]. 1997 Mar 1;272(3):E469\u0026ndash;75. Available from: https://doi.org/10.1152/ajpendo.1997.272.3.E469\u003c/li\u003e\n \u003cli\u003eBernabei R, Landi F, Calvani R, Cesari M, Del Signore S, Anker SD, et al. Multicomponent intervention to prevent mobility disability in frail older adults: randomised controlled trial (SPRINTT project). BMJ. 2022 May;377:e068788.\u003c/li\u003e\n \u003cli\u003eZhang Y, Zou L, Chen S-T, Bae JH, Kim DY, Liu X, et al. Effects and Moderators of Exercise on Sarcopenic Components in Sarcopenic Elderly: A Systematic Review and Meta-Analysis. Vol. 8, Frontiers in medicine. 2021. p. 649748.\u003c/li\u003e\n \u003cli\u003eChen N, He X, Feng Y, Ainsworth BE, Liu Y. Effects of resistance training in healthy older people with sarcopenia: a systematic review and meta-analysis of randomized controlled trials. Eur Rev aging Phys Act Off J Eur Gr Res into Elder Phys Act. 2021 Nov;18(1):23.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-geriatric-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"EGEM","sideBox":"Learn more about [European Geriatric Medicine](https://www.springer.com/journal/41999)","snPcode":"41999","submissionUrl":"https://www.editorialmanager.com/egem/default2.aspx","title":"European Geriatric Medicine","twitterHandle":"","acdcEnabled":false,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Heart Failure, older adults, sarcopenia, handgrip, outcomes","lastPublishedDoi":"10.21203/rs.3.rs-4223789/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4223789/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003ePurpose\u003c/b\u003e\u003c/p\u003e \u003cp\u003eSarcopenia is a potentially reversible syndrome is associated with an increased risk of cardiogenic cachexia and adverse outcomes in older patients with HF. Despite its significance, sarcopenia is often underdiagnosed due to the complexity of a thorough assessment in patients with acute heart failure. The purpose of this study was to evaluate whether early sarcopenia screening can predict the short-term prognostic risk in very old patients recently discharge for Acutely Decompensated Heart Failure (ADHF).\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe consecutively enrolled patients aged 75 years or older hospitalized with acutely DHF in the Geriatrics Unit of a tertiary care hospital. All patients underwent physical examination, complete blood tests, point-of-care ultrasound, and a comprehensive geriatric assessment, including physical performance through SARC-F and Hand Grip Strength test (HGS). The thirty-day post-discharge mortality rate was assessed by phone interview.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOut of 184 patients hospitalized with ADHF enrolled in the study (mean [SD], 86.8 [5.9] years, 60.3% female), 47 died within 30 days after discharge. By multivariate logistic analysis, HGS (β = -0.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03, p\u0026thinsp;=\u0026thinsp;0.008) and SARC-F [adjusted OR\u0026thinsp;=\u0026thinsp;1.18 (CI95% 1.03\u0026ndash;1.33), p\u0026thinsp;=\u0026thinsp;0.003] resulted independently associated with mortality. Furthermore, two SARC-F sub-items, namely, limitation in rising from a chair and history of falls [aOR: 3.26 (CI95% 1.27\u0026ndash;8.34), p\u0026thinsp;=\u0026thinsp;0.008; aOR: 3.30 (CI95% 1.28\u0026ndash;8.49), p\u0026thinsp;=\u0026thinsp;0.01; respectively] emerged as determinants of 30-days mortality.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAn early sarcopenia assessment comprising SARC-F and HGS test independently predicts 30-day post-discharge mortality in oldest-old patients hospitalized for acute HF.\u003c/p\u003e","manuscriptTitle":"Usefulness of an early sarcopenia screening in predicting short-term mortality in older patients discharged for acute heart failure .","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-18 17:39:06","doi":"10.21203/rs.3.rs-4223789/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revisions","date":"2024-06-12T05:34:09+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-05-08T17:12:17+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-10T06:59:39+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-09T07:05:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Geriatric Medicine","date":"2024-04-08T02:27:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-geriatric-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"EGEM","sideBox":"Learn more about [European Geriatric Medicine](https://www.springer.com/journal/41999)","snPcode":"41999","submissionUrl":"https://www.editorialmanager.com/egem/default2.aspx","title":"European Geriatric Medicine","twitterHandle":"","acdcEnabled":false,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"c9c86b82-7740-4451-ba91-31d8408d00aa","owner":[],"postedDate":"April 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-08-29T08:38:22+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-18 17:39:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4223789","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4223789","identity":"rs-4223789","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}