Keywords:

Introduction: Our study aimed to determine whether malnutrition and nutrition-related conditions using the European Society for Clinical Nutrition and Metabolism (ESPEN) consensus were associated with functional status, institutionalization, readmissions, and mortality in older patients at 3month follow-up. Methods: A cohort of 102 consecutive deconditioned patients was assessed at three months postdischarge from postacute care. Inclusion criteria were age ≥70 years, scores of Mini-Mental Status Examination ≥21/30, and admission for rehabilitation after an acute non-disabling disease. Malnutrition as defined by ESPEN consensus and nutrition-related conditions (frailty, sarcopenia, overweight/obesity, nutrient deficiency, and cachexia) were assessed, and related to postdischarge clinical outcomes at 3-month follow-up. Results: Of 95 included patients (84.5±6.5 years; 63.2% women), 31 (32.6%) had unintentional weight loss and 19 (20%) fulfilled malnutrition criteria defined by the ESPEN consensus. Nutrition-related conditions were frequent: 94 (99%) patients had frailty, 44 (46.3%) sarcopenia, 58 (61.1%) overweight/obesity, and 59 (62.1%) nutrient deficiency. Sarcopenia reduced functional status at 3-month follow-up (median difference: -25.5; p=0.008). Institutionalization was related to unintentional weight loss in univariate analysis (OR= 3.9; 95%CI 1.3 to 12.4, p=0.018). Meeting the basic ESPEN definition of malnutrition was related to institutionalization in univariate (OR=3.4; 95% CI 1.0 to 11.3, p=0.042) but not multivariate analysis, and was not significantly associated with readmissions or mortality at 3-month follow-up. Conclusions: Further research is needed on the potential value of the ESPEN consensus and guidelines to identify older patients at risk of worse functional status, institutionalization, readmissions, and mortality at 3month follow-up postdischarge.

INTRODUCTION 4

Malnutrition is associated with poor functional status and increased mortality in older 5 people (1)(2) (3). The main consequences of malnutrition and its related syndromes, 6 such as frailty or sarcopenia, include increased risks of infections (4) (5), loss of 7 independence (6), worsening health-related quality of life (7), and death (8)(9) (10) (11).

8
Given the lack of consensual malnutrition guidelines, the European Society for Clinical Nutrition and Metabolism (ESPEN) recently made an effort to establish a definition of 10 malnutrition that would be applicable in all adult age-ranges and healthcare settings, 11 independent of etiology (1). The ESPEN consensus definition of malnutrition guidelines 12 on definition and diagnoses has provided clinicians and researchers a practical tool for 13 the hierarchical organization of nutrition disorders, nutrition-related conditions, and 14 nutrition-related syndromes (2). 15 The ESPEN consensus definition of malnutrition has been applied in both acute 16 (11) (12) (13) and postacute care (14) (15). In a large population of hospitalized older 17 patients with diabetes, malnutrition lengthened the hospital stay, increased the 18 probability of in-hospital death by a factor of 2.7, and decreased the probability of being 19 discharged home rather than to an institution (13). Early management of nutrition 20 disorders and nutrition-related conditions (1), once detected, could improve the life 21 course of patients (16) (17). National and international research ethics guidelines were followed [START_REF] Muller | The ethics of research publication[END_REF], including the plot showed that Barthel Index at 3 months was not normally distributed, median 109 regression was applied to check median differences (MD) with 95% confidence interval 110 (CI). The analysis of factors associated with institutionalization was performed using 111 binary logistic regression. These associations were expressed by odds ratios (OR). 3). 5). Readmissions also did not differ by malnutrition as 147 defined by the ESPEN consensus (log rank p-value= 0.685), as shown in Figure 1.

137

As shown in

148 Finally, neither malnutrition nor nutrition-related conditions were related to any 149 differences in mortality in the analysis performed (Table 6). Age and comorbidity were (15), but there were no studies on this association after 169 discharge. Data from our study showed that the association between malnutrition and 170 functional status did not persist at 3 months postdischarge, a result that was unexpected. [START_REF] Lee | Mini-Nutritional-Assessment (MNA) without body mass 353 index (BMI) predicts functional disability in elderly Taiwanese[END_REF] and frailty [START_REF] Fougère | Editorial: Weight Loss is a Major Cause of Frailty[END_REF]. Unintentional weight loss has been 187 proposed as a key indicator to assess formal nutrition because of its validity, feasibility, 188 efficiency, and availability for every population and level of healthcare assistance [START_REF] Jensen | Global Leadership Initiative on Malnutrition: Progress 358 Report From ASPEN Clinical Nutrition Week 2017[END_REF].

189

Given that unintentional weight loss is a strong predictor of negative outcomes (GLIM) (34)(40), it would be desirable that unintentional weight loss be included as a 197 part of this universal tool, suitable for older people.

198

The key point of malnutrition and malnutrition-related syndromes that has aroused great 199 interest for the scientific community is their reversibility, when properly identified and 200 managed. In the therapeutic approach to malnutrition, frailty, and sarcopenia, the most 201 effective strategies to prevent and treat malnutrition and nutrition disorders seem to be 202 an adequate nutrient intake, nutritional supplementation, and physical exercise The key point of malnutrition and malnutrition-related syndromes that has aroused great 199 interest for the scientific community is their reversibility, when properly identified and 200 managed. In the therapeutic approach to malnutrition, frailty, and sarcopenia, the most 1 and2 (c) Summarise follow-up time (eg, average and total amount) Page 3

Outcome data 15* Report numbers of outcome events or summary measures over time Page 8 and Tables 1 and2 Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence interval). Make clear which confounders were adjusted for and why they were included

9

 9

6 Portable

 6 Mental Status Questionnaire) (27), and instrumental activities of daily living 94 (Lawton index) were obtained from medical records. 95 Ethics 96

97

  Deontological Code of Ethics, Declaration of Helsinki, and Spain's confidentiality law 98 concerning personal data (Ley Orgánica 15/1999, 13 December, Protección de Datos de 99 Carácter Personal). Written informed consent to participate was signed by all 100 participants and the study was approved by the local Clinical Ethics Committee. 101 Statistical analysis 102 Descriptive analysis of the sample used percentages with frequency distributions for 103 categorical variables and means with standard deviation for quantitative continuous 104 variables. Univariate analysis was used to check clinical and functional characteristics 105 of the study participants according to the diagnosis of malnutrition as defined by 106 ESPEN consensus. Qualitative variables were compared by Chi-square or Fisher exact 107 test, as appropriate and quantitative variables by Student t test. As histograms and Q-Q 108

112Table 1 .

 1 Associations with post-discharge readmissions and mortality were evaluated by Cox 113 regression. Kaplan-Meier curves for readmissions and for mortality, by malnutrition, 114 were compared using the corresponding log-rank test at 3-month follow-up. Univariate were performed for all outcomes to examine possible 116 associations with covariables. Furthermore, the proportional hazards assumption was 117 checked for each Cox model; there was no evidence of any violation from proportional 118 hazards. P-values <0.05 were considered significant. Statistical analysis was performed 119 using R for Windows (V.3.1.3). patients discharged from the unit during the study period, 95 met 122 inclusion criteria (mean age 84.5 (SD 6.5) years, 63.2% women). Of the 31 (32.6%) 123 patients with unintentional weight loss, 19 (20%) fulfilled the criteria for a diagnosis of 124 malnutrition as defined by the ESPEN consensus. Nutrition-related conditions were 125 frequent: 94 (99%) patients met Fried criteria for frailty, 44 (46.3%) for sarcopenia, 58 126 (61.1%) for overweight/obesity, 59 (62.1%) had nutrient deficiency, and 20 (21.1%) 127 patients had cachexia. Clinical and functional characteristics of the study participants 128 during their stay in the postacute care unit and at 3-month follow-up are detailed in 129 Post-discharge clinical outcomes in patients with malnutrition and other 130 nutrition-related conditions are described in Table 2. 131 Tables 3 to 6 show univariate and multivariate analysis according to clinical outcomes 132 (Barthel index, institutionalization, readmissions, and mortality) at 3-month follow-up. 133 Sarcopenia was the only nutrition-related syndrome that affected Barthel index at 3-134 month follow-up, both in univariate analysis (median difference [MD]= -25; 95% CI: -135 43.2 to -6.8; p= 0.008) and in multivariate analysis (MD= -25.5; 95%CI: -46.6 to -4.3; 136 p= 0.019) (Table

  150 the only variables affecting mortality under multivariate analysis. The Kaplan-Meier 151 curve showed no differences in mortality by malnutrition diagnosis, as defined by the 152 ESPEN consensus (log rank p-value= 0.533) (Figure 2). assessed the association of malnutrition and nutrition-related 155 conditions with clinical outcomes in older patients at 3 months postdischarge from a 156 postacute care unit. We found that applying malnutrition criteria as defined by the 157 ESPEN consensus had no additional value in predicting poor mid-term outcomes in the 158 studied sample of geriatric patients. Instead, unintentional weight loss (i.e., one of the 159 subscores of the consensus definition) was associated with an increased likelihood of 160 postdischarge institutionalization, and sarcopenia was associated with poorer functional 161 status at 3-month follow-up. 162 The prognostic value of malnutrition as defined by the recently published ESPEN 163 consensus and guidelines has not been explored thoroughly. To the authors' knowledge, 164 the only study reporting an association between malnutrition as defined by the ESPEN 165 consensus and clinical outcomes was carried out in an acute care setting and was limited 166 to analyzing the length of hospital stay (13). Nutrition disorders diagnosed by ESPEN 167 consensus and guidelines are associated with worse functional prognosis during 168 postacute rehabilitation care

171A

  likely explanation for malnutrition's lack of predictive value for post-discharge 172 clinical outcomes is that nutritional deficiencies were correctly addressed during 173 hospitalization, and the expected poor outcomes due to the presence of malnutrition in these patients after the multidisciplinary intervention 175 performed as part of usual post-discharge therapy. 176 Unlike malnutrition as defined by the ESPEN consensus, malnutrition-related 177 syndromes such as sarcopenia or frailty seem to have a negative impact on functional 178 status and rehabilitation outcomes in various settings, including postacute care 179 (22)(29)(30)(31). This observation held true for the present sample, in which the 180 presence of sarcopenia was associated with a lower score on the Barthel index after 3 181 months (14). 182 Unintentional weight loss was related to institutionalization. In a previous study, 183 unintentional weight loss was also related to worse clinical outcomes during hospital 184 stay (poor functional rehabilitation outcomes and longer length of stay) (15). Other 185 studies have considered weight loss prior to admission the most powerful predictor of 186 poor functional outcomes

190( 1 )

 1 [START_REF] Fougère | Editorial: Weight Loss is a Major Cause of Frailty[END_REF][START_REF] Wirth | The 361 impact of weight loss and low BMI on mortality of nursing home residents -362 Results from the nutritionDay in nursing homes[END_REF][START_REF] Cheng | Weight Change and All-Cause Mortality in Older 365 Adults: A Meta-Analysis[END_REF], objective anthropometric measurements (weight and height) should be 191 registered in the medical record in order to detect eventual weight loss in patients' 192 follow-up as part of the comprehensive geriatric assessment[START_REF] Ra | Integrating Nutrition in the Comprehensive[END_REF]. This factor appears to 193 be an accessible, feasible and low-cost indicator of malnutrition itself in older adults 194 (33)(37)(38)(39). In the process of creating a consensus on malnutrition diagnostic 195 criteria, now being developed by the Global Leadership Initiative on Malnutrition196

12

 12

203( 29 )

 29 (41)[START_REF] De Van Der Schueren | A critical 382 appraisal of nutritional intervention studies in malnourished, community dwelling 383 older persons[END_REF][START_REF] Landi | Prevalence of and interventions for sarcopenia in ageing adults: a systematic 386 review. Report of the International Sarcopenia Initiative (EWGSOP and IWGS)[END_REF]. 204 Some limitations may have influenced the results of our study. The criteria for 205 admission to the postacute short-term rehabilitation program constitute an initial 206 selection bias for studies conducted in rehabilitation settings: patients with good initial 207 recovery in the acute care ward as well as those whose physical, cognitive, or functional 208 status prevents them from following a rehabilitation program are excluded. In addition, 209 patients who require a rehabilitation program longer than two weeks are usually sent to 210 other intermediate care settings (14)(22). Therefore, the population is narrowly selected, 211 by definition. It is not surprising that frailty and risk of malnutrition were present in all 212 the sample, given that functional loss resulting from an acute recent process is one of 213 the admission criteria in the postacute care unit. The MNA-SF has been validated for 214 use in Spanish translation and has been recommended as a screening tool by the Spanish 215 Geriatrics and Gerontology Society (20), but the use of the full MNA questionnaire 216 might have improved specificity. On the other hand, malnutrition as defined by the 217 ESPEN consensus is partially based on anthropometric measurements, such as height, challenging in patients who are unable to stand (12 patients, 13.6%) and 219 require the substitution of knee height; furthermore, height measurement does not take 220 into account possible kyphosis or vertebral osteoporotic degenerative changes (44). 221 These factors might interfere with the accuracy of BMI, FFMI, basic definition of 222 malnutrition, and sarcopenia or cachexia diagnosis. Finally, the relatively small sample 223 size and the overlap between malnutrition and its related conditions should also be 224 considered a potential study limitation. 225 The diagnostic criteria proposed by the Academy of Nutrition and Dietetics and 226 American Society for Parenteral and Enteral Nutrition (AND/ASPEN) have also been 227 shown to be a reliable tool in the assessment of malnutrition. Both ASPEN/AND and 228 ESPEN criteria have their pros and cons. The categories of malnutrition and the 229 approach to distinguishing the malnutrition context (acute illness or injury, chronic 230 illness, and social or environmental circumstances) are strong points of the 231 ASPEN/AND criteria; however, this is a complex tool using subjective assessment 232 skills rather than objective body composition measures (45). Conversely, the ESPEN 233 consensus definition is based on objective anthropometric measurements (BMI and 234 FFMI), but some of them have limited availability in clinical settings and are overly 235 restrictive. Further research is required in order to achieve a unified consensus suitable 236 to all populations and settings worldwide (1)(40)(46)(47).237 Conclusions 238 Malnutrition as defined by the ESPEN consensus could not predict functional status, 239 institutionalization, readmissions, and mortality at 3 months after discharge from a unit. In contrast, unintentional weight loss, i.e. one of the subscores of 241 the consensus definition, was associated with an increased likelihood of postdischarge 242 institutionalization, and sarcopenia was associated with poorer functional status at 3-243 month follow-up. Further research with larger samples, multicenter cohorts, and more 244 extended follow-up is required to clarify the clinical value of diagnosing malnutrition 245 using the ESPEN consensus and its ability to predict long-term adverse clinical 246 outcomes.

201

  effective strategies to prevent and treat malnutrition and nutrition disorders seem to be 202 an adequate nutrient intake, nutritional supplementation, and physical exercise 203[START_REF] Litchford | Counteracting the Trajectory of Frailty and Sarcopenia in Older 346 Adults[END_REF](41)[START_REF] De Van Der Schueren | A critical 382 appraisal of nutritional intervention studies in malnourished, community dwelling 383 older persons[END_REF][START_REF] Landi | Prevalence of and interventions for sarcopenia in ageing adults: a systematic 386 review. Report of the International Sarcopenia Initiative (EWGSOP and IWGS)[END_REF]. 204 Some limitations may have influenced the results of our study. The criteria for 205 admission to the postacute short-term rehabilitation program constitute an initial 206 selection bias for studies conducted in rehabilitation settings: patients with good initial 207 recovery in the acute care ward as well as those whose physical, cognitive, or functional 208 status prevents them from following a rehabilitation program are excluded. In addition, 209 patients who require a rehabilitation program longer than two weeks are usually sent to 210 other intermediate care settings (14)(22). Therefore, the population is narrowly selected, 211 by definition. It is not surprising that frailty and risk of malnutrition were present in all 212 the sample, given that functional loss resulting from an acute recent process is one of 213 the admission criteria in the postacute care unit. The MNA-SF has been validated for 214 use in Spanish translation and has been recommended as a screening tool by the Spanish 215 Geriatrics and Gerontology Society (20), but the use of the full MNA questionnaire 216 might have improved specificity. On the other hand, malnutrition as defined by the 217 ESPEN consensus is partially based on anthropometric measurements, such as height, challenging in patients who are unable to stand (12 patients, 13.6%) and 219 require the substitution of knee height; furthermore, height measurement does not take 220 into account possible kyphosis or vertebral osteoporotic degenerative changes (44). 221 These factors might interfere with the accuracy of BMI, FFMI, basic definition of 222 malnutrition, and sarcopenia or cachexia diagnosis. Finally, the relatively small sample 223 size and the overlap between malnutrition and its related conditions should also be 224 considered a potential study limitation. 225 The diagnostic criteria proposed by the Academy of Nutrition and Dietetics and 226 American Society for Parenteral and Enteral Nutrition (AND/ASPEN) have also been 227 shown to be a reliable tool in the assessment of malnutrition. Both ASPEN/AND and 228 ESPEN criteria have their pros and cons. The categories of malnutrition and the 229 approach to distinguishing the malnutrition context (acute illness or injury, chronic 230 illness, and social or environmental circumstances) are strong points of the 231 ASPEN/AND criteria; however, this is a complex tool using subjective assessment 232 skills rather than objective body composition measures (45

1 Figure 1 . 2 Figure 2 . 1 STROBE 3 (

 112213 Figure 1. Readmissions curves by malnutrition as defined by the ESPEN consensus

Page 8 - 9 , 2 Page 3 (

 8923 Statistical Methods paragraph (b) Describe any methods used to examine subgroups and interactions Pages 6-7 (c) Explain how missing data were addressed Pages 13 (patients unable to stand) (d) If applicable, explain how loss to follow-up was addressed Report numbers of individuals at each stage of study-eg numbers potentially eligible, examined for eligibility, confirmed eligible, included in the study, completing follow-up, and analysed Page 8, Table 1 and 2 (b) Give reasons for non-participation at each stage Not applicable (c) Consider use of a flow diagram Not applicable Descriptive data 14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and potential confounders Page 8 and Tables 1 and b) Indicate number of participants with missing data for each variable of interest Page 8 and Tables

Page 8 and

 8 Tables 1 to 6, includes 95% confidence interval (b) Report category boundaries when continuous variables were categorized Pages 8 (c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period Not applicable Other analyses 17 Report other analyses done-e.g. analyses of subgroups and interactions, with reference to study objectives Pages 10 (discussion of results) and 13 (Conclusion) Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision. Discuss both direction and magnitude of any potential bias Page 12 Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from similar studies, and other relevant evidence Pages 12of funding and the role of the funders for the present study and, if applicable, for the original study on which the present article is based Page 15: No internal or external funding was received to support this research.*Give information separately for exposed and unexposed groups.

F

Table 4 ,

 4 age and sex showed a significant association with At 3-month follow-up, 18 patients had been readmitted; there were no differences in

	138
	139	institutionalization in the multivariate analysis. Institutionalization was also related to
	140	unintentional weight loss in univariate analysis (OR= 3.9; 95%CI: 1.3 to 12.4; p= 0.018)
	141	and showed a strong trend in multivariate analysis (OR= 5.5; 95%CI: 0.9 to 31.6; p=
	142	0.058). Similarly, malnutrition was significantly associated with institutionalization in

144

value of the ESPEN consensus and guidelines for malnutrition: 1 Prediction of post-discharge clinical outcomes in older inpatients

  16 systematic review and meta-analysis. Ageing Research Reviews. 2013. p. 561-6. Russell MK. Functional assessment of nutrition status. Nutr Clin Pract. 2015 Apr Wijnhoven HAH, van Zon SKR, Twisk J, Visser M. Attribution of causes of 371 weight loss and weight gain to 3-year mortality in older adults: results from the Unintentional weight loss was obtained from medical records. If data for 53 the last 3 months were unavailable, weight loss was assessed by patient and caregiver 54 interview or from weight data recorded in the medical record during the last year. BMI 55 was calculated from height and weight (kg/m 2 ): height was measured in all patients able

	23 28 49 72 94 116 121	Assessment. Nutr Clin Pract. 2014 Aug 2;29(4):420-7. The objective of this longitudinal study was to determine whether the malnutrition and METHODS poses two alternative ways to diagnose malnutrition: body mass index (BMI) <18.5 of three of the following criteria: weight loss, weakness, exhaustion, slow walking Portable Mental Status Questionnaire) (27), and instrumental activities of daily living and multivariate analyses were performed for all outcomes to examine possible RESULTS
	369
	2 24 29 50 73 117 122	13;30(2):211-8. nutrition-related conditions diagnosed during hospitalization using the ESPEN Design kg/m 2 (alternative 1) or unintentional weight loss (>10% indefinite of time, or >5% over speed, and low physical activity. Overweight and obesity were considered following (Lawton index) were obtained from medical records. associations with covariables. Furthermore, the proportional hazards assumption was Of 102 eligible patients discharged from the unit during the study period, 95 met
	372 373 3 25 30 51 74 118 123	Longitudinal Aging Study Amsterdam. J Gerontol A Biol Sci Med Sci. 2014 Oct consensus definition were associated with post-discharge clinical outcomes (functional Cohort study of postacute inpatients who participated in a larger prospective study on the last 3 months) combined with age-related BMI (BMI <20 kg/m 2 in <70 years, or World Health Organization recommendations: BMI 25-30 kg/m 2 and ≥30 kg/m 2 , checked for each Cox model; there was no evidence of any violation from proportional inclusion criteria (mean age 84.5 (SD 6.5) years, 63.2% women). Of the 31 (32.6%)
	374 375 4 26 31 52 75 119 124	1;69(10):1236-43. 40. Cederholm T, Jensen GL. To create a consensus on malnutrition diagnostic INTRODUCTION status assessed by Barthel index, institutionalization, hospital readmissions, and malnutrition and sarcopenia (14). The Strengthening the Reporting of Observational <22 kg/m 2 in ≥70 years) or fat-free mass index (<17 kg/m 2 in men and 15 kg/m 2 in respectively. Nutrient deficiency was noted for total proteins, total cholesterol, hazards. P-values <0.05 were considered significant. Statistical analysis was performed patients with unintentional weight loss, 19 (20%) fulfilled the criteria for a diagnosis of
	247 248 376 377 378 379 380 381 382 402 403 5 6 7 27 32 33 76 77 78 89 90 120 125 126 127 women) (1). 67 criteria: A report from the Global Leadership Initiative on Malnutrition (GLIM) F o r P e e r R e v i e w F o r P e e r R e v i e w F o r P e e r R e v i e w F o r P e e r R e v i e w meeting at the ESPEN Congress 2016. Clin Nutr. 2017 Feb;36(1):7-10. 41. Deutz NEP, Bauer JMJM, Barazzoni R, Biolo G, Boirie Y, Bosy-Westphal A, et al. Protein intake and exercise for optimal muscle function with aging: recommendations from the ESPEN Expert Group. Clin Nutr. 2014 Dec;33(6):929-36. 42. de van der Schueren MAE, Wijnhoven HAH, Kruizenga HM, Visser M. A critical appraisal of nutritional intervention studies in malnourished, community dwelling F o r P e e r R e v i e w Malnutrition is associated with poor functional status and increased mortality in older people (1)(2)(3). The main consequences of malnutrition and its related syndromes, such as frailty or sarcopenia, include increased risks of infections (4)(5), loss of independence (6), worsening health-related quality of life (7), and death (8)(9)(10)(11). F o r P e e r R e v i e w mortality) among older patients at 3-month follow-up. F o r P e e r R e v i e w Studies in Epidemiology (STROBE) Statement (18) was followed (Additional file 1). Setting The study was conducted in a postacute geriatric rehabilitation care unit in a university F o r P e e r R e v i e w F o r P e e r R e v i e w triglycerides, homocysteine-related markers (folic acid and B12 vitamin), iron profile (serum iron, ferritin), and altered values of thyroid-stimulating hormone, ionogram (sodium, potassium), and renal profile (creatinine, urea and glomerular filtration rate the patient or caregiver. Institutionalization, readmissions, and mortality were collected F o r P e e r R e v i e w F o r P e e r R e v i e w using R for Windows (V.3.1.3). F o r P e e r R e v i e w malnutrition as defined by the ESPEN consensus. Nutrition-related conditions were frequent: 94 (99%) patients met Fried criteria for frailty, 44 (46.3%) for sarcopenia, 58 (61.1%) for overweight/obesity, 59 (62.1%) had nutrient deficiency, and 20 (21.1%) from the equation developed by the Modification of Diet in Renal Diseases Study). patients had cachexia. Clinical and functional characteristics of the study participants
	20 46 68 91	presence of low muscle function or low physical performance (24) assessed with from caregiver telephone interview and medical records at 3-month follow-up. After
	21 47 69 92	disorders and nutrition-related conditions (1), once detected, could improve the life as defined by the ESPEN consensus was then retrospectively applied in all patients bioimpedance analysis, isometric handgrip dynamometry, and gait speed in a 4-m walk follow-up was completed, survival was assessed annually for the whole cohort in the
	22 48 70 93	course of patients (16)(17). identified as at risk of malnutrition (MNA-SF scores ≤11). The ESPEN definition pro-test as previously described (14)(22). Gait speed was considered 0 m/s in bedridden same way. Data on sex, age, comorbidity (Charlson index), cognitive status (Short
	367 71	patients unable to stand. Frailty was assessed by the Frailty Phenotype (25) in presence
		15 18 2 3 4 5 6 7 8

278 8. Agarwal E, Ferguson M, Banks M, Batterham M, Bauer J, Capra S, et al. 279 Malnutrition and poor food intake are associated with prolonged hospital stay, 280 frequent readmissions, and greater in-hospital mortality: results from the 281 Nutrition Care Day Survey 2010. Clin Nutr. 2013 Oct;32(5):737-45. 17 Consensus declaration by the Spanish society of geriatrics and gerontology 323 nutrition work group. Maturitas. 2015 Jul;81(3):414-9. 324 21. Chumlea WC, Roche AF, Steinbaugh ML. Estimating stature from knee height 325 for persons 60 to 90 years of age. J Am Geriatr Soc. 1985 Feb;33(2):116-20. 326 22. Sánchez-Rodríguez D, Marco E, Miralles R, Fayos M, Mojal S, Alvarado M, et 327 al. Sarcopenia, physical rehabilitation and functional outcomes of patients in a 328 subacute geriatric care unit. Arch Gerontol Geriatr. 2014 Jan;59(1):39-43. 329 23. Schutz Y, Kyle UUG, Pichard C. Fat-free mass index and fat mass index 330 percentiles in Caucasians aged 18-98 y. Int J Obes Relat Metab Disord. 2002 331 Jul;26(7):953-60. 332 24. Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. 333 Sarcopenia: European consensus on definition and diagnosis. Age Ageing. 334 2010;39(April):412-23. 335 25. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. 336 Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 337 2001 Mar;56(3):M146-56. 338 26. Evans WJ, Morley JE, Argilés J, Bales C, Baracos V, Guttridge D, et al. 339 Cachexia: A new definition. Clin Nutr. 2008 Dec;27(6):793-9. 340 27. Pfeiffer E. A short portable mental status questionnaire for the assessment of 341 organic brain deficit in elderly patients. J Am Geriatr Soc. 1975 Oct;23(10):433-342 41. 343 28. Muller MJ, Soares M. The ethics of research publication. Eur J Clin Nutr. 2017 344 May;71(5):569. 345 29. Litchford MD. Counteracting the Trajectory of Frailty and Sarcopenia in Older 346 Adults. Nutr Clin Pract. 2014 Aug 9;29(4):428-34. 347 30. Morley JE. Nutritional supplementation and sarcopenia: the evidence grows. J 348 Am Med Dir Assoc. 2015 Sep 1;16(9):717-9. 349 31. Landi F, Bernabei R, Russo A, Zuccalà G, Onder G, Carosella L, et al. Predictors 350 of Rehabilitation Outcomes in Frail Patients Treated in a Geriatric Hospital. J Am 351 Geriatr Soc. 2002 Apr;50(4):679-84. 352 32. Lee L-C, Tsai AC. Mini-Nutritional-Assessment (MNA) without body mass 353 index (BMI) predicts functional disability in elderly Taiwanese. Arch Gerontol 354 Geriatr. 2012 May;54(3):e405-10. 355 33. Fougère B, Morley JE. Editorial: Weight Loss is a Major Cause of Frailty. J Nutr 356 Health Aging. 2017 Nov 22;21(9):933-5. 357 34. Jensen GL, Cederholm T. Global Leadership Initiative on Malnutrition: Progress 358 Report From ASPEN Clinical Nutrition Week 2017. JPEN J Parenter Enteral 359 Nutr. 2017 Apr 1;148607117707761. 360 35. Wirth R, Streicher M, Smoliner C, Kolb C, Hiesmayr M, Thiem U, et al. The 361 impact of weight loss and low BMI on mortality of nursing home residents -362 Results from the nutritionDay in nursing homes. Clin Nutr. 2016 Aug 363 19;35(4):900-6. 364 36. Cheng FW, Gao X, Jensen GL. Weight Change and All-Cause Mortality in Older 365 Adults: A Meta-Analysis. J Nutr Gerontol Geriatr. 2015 Oct 2;34(4):343-68. 366 37. DiMaria-Ghalili RA. Integrating Nutrition in the Comprehensive Geriatric 368 38. 370 39. 383 older persons. Clin Nutr. 2016 Oct;35(5):1008-14. 384 43. Cruz-Jentoft AJ, Landi F, Schneider SM, Zúñiga C, Arai H, Boirie Y, et al. 385 Prevalence of and interventions for sarcopenia in ageing adults: a systematic 386 review. Report of the International Sarcopenia Initiative (EWGSOP and IWGS). 387 Age Ageing. 2014 Nov;43(6):748-59. 388 44. Gavriilidou NN, Pihlsgård M, Elmståhl S. High degree of BMI misclassification 389 of malnutrition among Swedish elderly population: Age-adjusted height 390 estimation using knee height and demispan. Eur J Clin Nutr. 2015 391 May;69(5):565-71. 392 45. Hand RK, Murphy WJ, Field LB, Lee JA, Parrott JS, Ferguson M, et al. 393 Validation of the Academy/A.S.P.E.N. Malnutrition Clinical Characteristics. J 394 Acad Nutr Diet. 2016 May;116(5):856-64. 395 46. Cederholm T, Jensen GL. To Create a Consensus on Malnutrition Diagnostic 396 Criteria. JPEN J Parenter Enteral Nutr. 2017 Mar 17;41(3):311-4. 397 47. White J V., Guenter P, Jensen G, Malone A, Schofield M, Academy Malnutrition 398 Work Group, et al. Consensus Statement: Academy of Nutrition and Dietetics and 399 American Society for Parenteral and Enteral Nutrition: Characteristics 400 Recommended for the Identification and Documentation of Adult Malnutrition 401 (Undernutrition). J Parenter Enter Nutr. 2012 May 1;36(3):275-83. 1 Prognostic 8 Given the lack of consensual malnutrition guidelines, the European Society for Clinical 9 Nutrition and Metabolism (ESPEN) recently made an effort to establish a definition of 10 malnutrition that would be applicable in all adult age-ranges and healthcare settings, 11 independent of etiology (1). The ESPEN consensus definition of malnutrition guidelines 12 on definition and diagnoses has provided clinicians and researchers a practical tool for 13 the hierarchical organization of nutrition disorders, nutrition-related conditions, and 14 nutrition-related syndromes (2). 15 The ESPEN consensus definition of malnutrition has been applied in both acute 16 (11)(12)(13) and postacute care (14)(15). In a large population of hospitalized older 17 patients with diabetes, malnutrition lengthened the hospital stay, increased the 18 probability of in-hospital death by a factor of 2.7, and decreased the probability of being 19 discharged home rather than to an institution (13). Early management of nutrition 34 hospital. The unit focuses specifically on a 2-week period of rehabilitation and 35 functional recovery, after which patients are expected to be discharged home. 36 Participants 37 Consecutive patients aged ≥70 years hospitalized in the postacute geriatric rehabilitation 38 care unit due to functional loss resulting from a non-disabling medical disease were 39 included from January to August 2011. Patients with general and/or cognitive conditions 40 (Mini-Mental State Examination score <21/30) that prevented completion of the 41 diagnostic tests or absence of information regarding weight loss in the previous year 42 were excluded. 43 Procedure 44 All inpatients were screened for risk of malnutrition at admission by the Mini-45 Nutritional Assessment Short-Form (MNA-SF) (19)(20). The diagnosis of malnutrition 56 to stand safely, otherwise a knee height equation (21) was applied; body weight was 57 measured to the nearest 0.1 kg. Fat-free mass (FFM), expressed in kg, was measured 58 by bioimpedance (Bodystat 1500, Bodystat Ltd., Isle of Man British Isles) as previously 59 described (14)(22). The FFM values were divided by height squared to obtain the fat-60 free mass index (FFMI), expressed in kg/m 2 and compared with those of the reference 61 population (23). 62 Nutrition-related conditions (sarcopenia, frailty, overweight/obesity, and nutrient 63 deficiency) were also considered (1). The term "nutrition-related syndrome" was used to 64 refer to a condition included in the definition, such as sarcopenia and frailty that is also 65 identified as a geriatric syndrome. Sarcopenia was assessed following The European 66 Working Group on Sarcopenia in Older People (EWGSOP) criteria: low muscle mass in 79 Diagnostic criteria for cachexia (wasting disease) in adults were applied. These 80 included weight loss of at least 5% in previous 12 months or less, in the presence of 81 underlying illness and three of the following criteria: decreased muscle strength, fatigue 82 (defined as physical and/or mental weariness resulting from exertion), anorexia (total 83 caloric intake <20 kcal/kg body weight/day or <70% of usual food intake), low FFMI, 84 or abnormal biochemistry (hemoglobin <12 g/dl or low serum albumin <3.2 g/dl) (26). 85 Outcome variables 86 Main outcome variables were functional status assessed by Barthel index, 87 institutionalization, readmissions, and mortality. Functional status was recorded after 88 discharge by an investigator blinded to the study, obtained by telephone interview with 128 during their stay in the postacute care unit and at 3-month follow-up are detailed in 129

Table 1 .

 1 Post-discharge clinical outcomes in patients with malnutrition and other

	139
	140	unintentional weight loss in univariate analysis (OR= 3.9; 95%CI: 1.3 to 12.4; p= 0.018)
	141	and showed a strong trend in multivariate analysis (OR= 5.5; 95%CI: 0.9 to 31.6; p=
	142	0.058). Similarly, malnutrition was significantly associated with institutionalization in

130

nutrition-related conditions are described in Table

2

.

131 Tables 3 to

6

show univariate and multivariate analysis according to clinical outcomes 132 (Barthel index, institutionalization, readmissions, and mortality) at 3-month follow-up. 133 Sarcopenia was the only nutrition-related syndrome that affected Barthel index at 3-134 month follow-up, both in univariate analysis (median difference [MD]= -25; 95% CI: -135 43.2 to -6.8; p= 0.008) and in multivariate analysis (MD= -25.5; 95%CI: -46.6 to -4.3; 136 p= 0.019) (Table

3

).

137

As shown in Table

4

, age and sex showed a significant association with 138 institutionalization in the multivariate analysis. Institutionalization was also related to 149 differences in mortality in the analysis performed (Table

6

). Age and comorbidity were 150 the only variables affecting mortality under multivariate analysis. The Kaplan-Meier 151 curve showed no differences in mortality by malnutrition diagnosis, as defined by the 152 ESPEN consensus (log rank p-value= 0.533) (Figure 2). 162 The prognostic value of malnutrition as defined by the recently published ESPEN 163 consensus and guidelines has not been explored thoroughly. To the authors' knowledge, 164 the only study reporting an association between malnutrition as defined by the ESPEN 165 consensus and clinical outcomes was carried out in an acute care setting and was limited 166 to analyzing the length of hospital stay (13). Nutrition disorders diagnosed by ESPEN 167 consensus and guidelines are associated with worse functional prognosis during 168 postacute rehabilitation care (

15

), but there were no studies on this association after 169 discharge. Data from our study showed that the association between malnutrition and 170 functional status did not persist at 3 months postdischarge, a result that was unexpected. 171 A likely explanation for malnutrition's lack of predictive value for post-discharge 182 Unintentional weight loss was related to institutionalization. In a previous study, 183 unintentional weight loss was also related to worse clinical outcomes during hospital 184 stay (poor functional rehabilitation outcomes and longer length of stay) (15). Other 185 studies have considered weight loss prior to admission the most powerful predictor of 186 poor functional outcomes

[START_REF] Lee | Mini-Nutritional-Assessment (MNA) without body mass 353 index (BMI) predicts functional disability in elderly Taiwanese[END_REF]

and frailty

[START_REF] Fougère | Editorial: Weight Loss is a Major Cause of Frailty[END_REF]

. Unintentional weight loss has been 187 proposed as a key indicator to assess formal nutrition because of its validity, feasibility, 188 efficiency, and availability for every population and level of healthcare assistance

[START_REF] Jensen | Global Leadership Initiative on Malnutrition: Progress 358 Report From ASPEN Clinical Nutrition Week 2017[END_REF]

.

189

Given that unintentional weight loss is a strong predictor of negative outcomes 190 (1)(33)(35)(36), objective anthropometric measurements (weight and height) should be 191 registered in the medical record in order to detect eventual weight loss in patients' 192 follow-up as part of the comprehensive geriatric assessment (37). This factor appears to 197 part of this universal tool, suitable for older people.

198

Table 1 .

 1 In contrast, unintentional weight loss, i.e. one of the subscores of 241 the consensus definition, was associated with an increased likelihood of postdischarge 242 institutionalization, and sarcopenia was associated with poorer functional status at 3-Russell MK. Functional assessment of nutrition status. Nutr Clin Pract. 2015 Apr Wijnhoven HAH, van Zon SKR, Twisk J, Visser M. Attribution of causes of 371 weight loss and weight gain to 3-year mortality in older adults: results from the Clinical and functional characteristics of the study participants according to malnutrition as defined by the ESPEN consensus (n= 95).

	237
	238	Conclusions
	239	Malnutrition as defined by the ESPEN consensus could not predict functional status,
	240	institutionalization, readmissions, and mortality at 3 months after discharge from a

). Conversely, the ESPEN 233 consensus definition is based on objective anthropometric measurements (BMI and 234 FFMI), but some of them have limited availability in clinical settings and are overly 235 restrictive. Further research is required in order to achieve a unified consensus suitable 236 to all populations and settings worldwide (1)(40)(46)(47). 368 38. 370 39.

Postdischarge variables at 3-month follow-up

	F o r
	P e
		e r
		R e
		v
		i e
	Barthel index Institutionalization	48.3 (30.6) 15 (15.8%)	36.5 (27.7) 6 (47.4%) w	51.4 (30.7) 9 (11.8%)	0.055 0.035
	Readmissions	19 (20%)	3 (15.8%)	16 (21.1%)	0.608
	Mortality postdischarge	13 (13.7%)	3 (15.8%)	10 (13.2%)	0.765
	(*) Data are expressed as numbers and percentages for categorical variables, and as mean and standard
	deviation (SD) for continuous variables.
		2

Table 2 .

 2 Post-discharge clinical outcomesaccording to malnutrition and malnutritionrelated syndromes at 3-month follow-up (n= 95).

		Malnutrition	Sarcopenia	Frailty	Cachexia	Total
		(ESPEN)	(EWGSOP)	(Fried)	(Evans)	sample
		(n= 19)	(n= 44)	(n= 94)	(n= 20)	(n= 95)
	Barthel index	36.5 (27.7)	38.8 (28.2)	48 (30.6)	42.4 (29.0)	48.3 (30.6)
	Institutionalization	6 (31.6%)	7 (15.9%)	15 (16.0%)	4 (20%)	15 (15.8%)
	Readmissions	3 (15.8%)	8 (18.2%)	19 (20.2%)	3 (15%)	19 (20%)
	Mortality	3 (15.8%)	5 (11.4%)	12 (12.8%)	2 (10%)	12 (12.6%)
	(*) Data are expressed as numbers and percentages for categorical variables, and as mean and standard
	deviation (SD) for continuous variables. List of abbreviations. ESPEN: European Society of Clinical
	Nutrition and Metabolism; EWGSOP: European Working Group on Sarcopenia in Older People; BMI:
	Body mass index; SD: Standard deviation.

Table 3 .

 3 Factors affecting Barthel index at 3-month follow-up, according to clinical characteristics, components of malnutrition as defined by the ESPEN consensus and nutrition-related conditions.

		Barthel indexat 3-month follow-up
		Univariate analysis	Multivariate analysis
		Median difference	p	Median difference	p
		(95%CI)		(95%CI)
	Clinical characteristics
	Age	-2 (-3.50 to -0.50)	0.009	-2.19 (-7.28 to 2.89)	0.393
	Sex	15 (-8.47 to 38.47)	0.208	18.05 (-0.41 to 36.51)	0.055
	Comorbidity (Charlson >2)	0 (-6.21 to 6.21)	1.00	-2.19 (-7.28 to 2.89)	0.393
	Unintentional weight loss	-12 (-34.91 to -10.91)	0.301	-5.29 (-29.28 to 18.69)	0.662
	Malnutrition and nutrition-related
	conditions
	Malnutrition	-20 (-46.65 to 6.65)	0.139	-14.10 (-46.06 to 17.87)	0.383
	Sarcopenia	-25 (-43.22 to -6.78)	0.008	-25.49 (-46.66 to -4.32)	0.019
	Overweight-obesity	15 (-8.86 to 38.86)	0.215	0.24 (-20.58 to 21.07)	0.981
	Nutrient deficiency	0 (-22.18 to 22.18)	1.000	12.93 (-5.31 to 31.17)	0.162
	Cachexia	-15 (-41.65 to 11.65)	0.266	11.83 (-18.60 to 42.25)	0.441

Table 4 .

 4 Factors affecting institutionalization at 3-month follow-up, according to clinical characteristics, components of malnutrition as defined by the ESPEN consensus and nutrition-related conditions.

	Institutionalizationat 3-month follow-up
		Univariate analysis	Multivariate analysis
		Odds ratio (95%CI)	p	Odds ratio (95%CI)	p
	Clinical characteristics
	Age	1.08 (0.99 to 1.19)	0.083	1.14 (1.01 to 1.28)	0.033
	Sex	0.32 (0.10 to 1.0)	0.005	0.18 (0.04 to 0.72)	0.016
	Comorbidity (Charlson>2)	0.88 (0.63 to 1.22)	0.443	0.85 (0.58 to 1.25)	0.420
	Unintentional weight loss	3.95 (1.26 to 12.41)	0.018	5.46 (0.94 to 31.62)	0.058
	Malnutrition and nutrition-related
	conditions
	Malnutrition	3.44 (1.04 to 11.31)	0.042	3.69 (0.34 to 40.27)	0.285
	Sarcopenia	1.02 (0.34 to 3.07)	0.976	1.51 (0.28 to 8.17)	0.629
	Overweight-obesity	1.33 (0.42 to 4.27)	0.628	2.53 (0.49 to 13.15)	0.268
	Nutrient deficiency	0.9 (0.29 to 2.78)	0.855	0.63 (0.16 to 2.50)	0.511
	Cachexia	1.45 (0.41 to 5.17)	0.563	0.58 (0.05 to 6.30)	0.657

Table 5 .

 5 Factors affecting readmissions at 3-month follow-up, according to clinical characteristics, components of malnutrition as defined by ESPEN consensusand nutrition-related conditions.

	Readmissions at 3-month follow-up
		Univariate analysis	Multivariate analysis
		Odds ratio	p	Odds ratio (95%CI)	p
		(95%CI)
	Clinical characteristics
	Age	0.93 (0.91 to 1.56)	0.074	0.93 (0.85 to 1.01)	0.095
	Sex	1 (0.35 to 2.83)	1	1.09 (0.35 to 3.37)	0.879
	Comorbidity (Charlson >2)	1.19 (0.91 to 1.56)	0.211	1.18 (0.88 to 1.59)	0.269
	Unintentional weight loss	0.94 (0.32 to 2.77)	0.913	0.82 (0.19 to 3.47)	0.784
	Malnutrition and nutrition-related
	conditions
	Malnutrition	0.70 (0.18 to 2.71)	0.609	0.91 (0.13 to 6.44)	0.929
	Sarcopenia	0.81 (0.29 to 2.23)	0.681	1.03 (0.27 to 3.88)	0.964
	Overweight-obesity	0.85 (0.30 to 2.36)	0.752	0.59 (0.17 to 2.07)	0.408
	Nutrient deficiency	1.41 (0.48 to 4.12)	0.527	1.33 (0.42 to 4.17)	0.623
	Cachexia	0.66 ( 0.17 to 2.50)	0.532	0.52 (0.08 to 3.58)	0.506

Table 6 .

 6 Factors affecting postdischarge mortality, according to clinical characteristics, components of malnutrition as defined by the ESPEN consensus and nutrition-related conditions.

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		Postdischarge mortality
		Univariate analysis	Multivariate analysis
		Odds ratio (95%CI)	p	Odds ratio (95%CI)	p
	Clinical characteristics
	Age	1.05 (1.01 to 1.09)	0.005	1.08 (1.03 to 1.13)	0.001
	Sex	1.01 (0.61 to 1.69)	0.964	1.10 (0.65 to 1.87)	0.718
	Comorbidity (Charlson>2)	1.11 (0.98 to 1.27)	0.105	1.15 (1.0 to 1.33)	0.053
	Unintentional weight loss	1.10 (0.616 to 1.85)	0.711	1.20 (0.56 to 2.55)	0.641
	Malnutrition and nutrition-related
	conditions
	Malnutrition	1.21 (0.67 to 2.18)	0.534	1.28 (0.52 to 3.11)	0.589
	Sarcopenia	1.03 (0.63 to 1.69)	0.896	0.85 (0.44 to 1.63)	0.625
	Overweight-obesity	1.04 (0.62 to 1.72)	0.889	1.09 (0.57 to 2.10)	0.788
	Nutrient deficiency	1.07 (0.64 to 1.76)	0.800	1.13 (0.66 to 1.94)	0.654
	Cachexia	0.98 (0.53 to 1.80)	0.940	0.88 (0.39 to 2.01)	0.772

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  For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe comparability of assessment methods if there is more than one group Pages 5-6: calculation and cut-off points of outcomes measures; data source for all Describe all statistical methods, including those used to control for confounding

	Data sources/	8*
	measurement
			variables
	Bias	9	Describe any efforts to address potential sources of bias
			Page 12, efforts to minimize errors and bias
	Study size	10	Explain how the study size was arrived at
			Prospective cohort study of all inpatients admitted in postacute care during study
			period
	Quantitative variables	11	Explain how quantitative variables were handled in the analyses. If applicable,
			describe which groupings were chosen and why
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			matched studies, give matching criteria and number of exposed and
			unexposed
			Not applicable: this was not a matched study
	Variables	7	Clearly define all outcomes, exposures, predictors, potential confounders, and effect
			modifiers. Give diagnostic criteria, if applicable
			Pages 3-4: procedure and data collection
			Pages 4-6: variables and diagnostic criteria
			Page 4-6: outcome variables
			Exposures, predictors, potential confounders, and effect modifiers are not applicable
			to our study.
			2

  An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at http://www.strobe-statement.org.

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Acknowledgements Acknowledgements

No internal or external funding was received to support this research. gratefully acknowledge Elaine Lilly, PhD, for unfailing support, language No internal or external funding was received to support this research.

Ethics

96

National and international research ethics guidelines were followed [START_REF] Muller | The ethics of research publication[END_REF], including the