Defining malnutrition in persons with spinal cord injury – does the Global Criteria for Malnutrition work?

Hanne Bjørg Slettahjell; Maria Bastakis; Fin Biering-Sørensen; Vegard Strøm; Christine Henriksen

doi:10.29219/fnr.v68.9989

Hanne Bjørg Slettahjell Sunnaas Rehabilitation Hospital, Bjørnemyr, Norway; Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Norway
Maria Bastakis Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Norway
Fin Biering-Sørensen Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark; Department for Brain- and Spinal Cord Injuries, Bodil Eskesen Center, Glostrup, Denmark https://orcid.org/0000-0002-2186-0144
Vegard Strøm Sunnaas Rehabilitation Hospital, Bjørnemyr, Norway https://orcid.org/0000-0002-1990-0071
Christine Henriksen Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Norway https://orcid.org/0000-0002-8079-8467

DOI: https://doi.org/10.29219/fnr.v68.9989

Keywords: spinal cord, rehabilitation, malnutrition, fat-free mass

Abstract

Background and aims: Physiologic and metabolic changes following spinal cord injury (SCI) lead to an increased risk of malnutrition. The Global Leadership Initiative on Malnutrition (GLIM) is a three-step approach to diagnose malnutrition: 1) screening; 2) phenotypic and etiological criteria; and 3) malnutrition severity. The main aim of this study was to assess malnutrition in patients with SCI, according to the GLIM criteria.

Methods: Patients with SCI (≥ 18 years) admitted to rehabilitation were included. Anthropometrics, food intake, and inflammation were assessed on admission. Fat-free mass index (FFMI) was estimated from bioimpedance analysis. Malnutrition was diagnosed by the GLIM criteria, using the Malnutrition Universal Screening Tool (MUST) as the first step screening tool. Sensitivity and specificity analyses were performed.

Results: In total, 66 patients were assessed (50 men) with a mean age of 51.4 (± 17.4) years and median time since injury was 37.5 (10–450) days. The mean body mass index was 24.7 (± 4.2) kg/m², and 1-month involuntary weight loss was 5.7 (± 4.4)%. FFMI for men was 17.3 (± 1.9) and for women 15.3 (± 1.6) kg/m². Forty-one patients (62%) were malnourished according to the GLIM criteria: 27 moderately and 14 severely malnourished. MUST was not able to detect malnutrition risk of nine patients, giving a moderate agreement (kappa 0.66), with a sensitivity of 0.78 and a specificity of 0.92 compared to the GLIM diagnosis.

Conclusions: In this cross-sectional study, 62% of subacute SCI patients were malnourished according to the GLIM criteria. The screening tool MUST showed moderate agreement with the GLIM criteria and did not detect risk of all patients with a malnutrition diagnosis. The clinical implications of these findings need further investigation.

Downloads

Download data is not yet available.

Author Biographies

Maria Bastakis, Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Norway

Master student (MSc)

Fin Biering-Sørensen , Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark; Department for Brain- and Spinal Cord Injuries, Bodil Eskesen Center, Glostrup, Denmark

Professor, SCI medical doctor

Vegard Strøm, Sunnaas Rehabilitation Hospital, Bjørnemyr, Norway

PhD, project manager, Sunnaas Rehabilitation Hospital

Christine Henriksen , Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Norway

Associate professor, University of Oslo

References

1.
Felleiter P, Krebs J, Haeberli Y, Schmid W, Tesini S, Perret C. Post-traumatic changes in energy expenditure and body composition in patients with acute spinal cord injury. J Rehabil Med 2017; 49(7): 579–84. doi: 10.2340/16501977-2244

2.
Rodriguez DJ, Clevenger FW, Osler TM, Demarest GB, Fry DE. Obligatory negative nitrogen balance following spinal cord injury. JPEN J Parenter Enteral Nutr 1991; 15(3): 319–22. doi: 10.1177/0148607191015003319

3.
Laven GT, Huang CT, DeVivo MJ, Stover SL, Kuhlemeier KV, Fine PR. Nutritional status during the acute stage of spinal cord injury. Arch Phys Med Rehabil 1989; 70(4): 277–82.

4.
Castro MJ, Apple DF Jr., Hillegass EA, Dudley GA. Influence of complete spinal cord injury on skeletal muscle cross-sectional area within the first 6 months of injury. Eur J Appl Physiol Occup Physiol 1999; 80(4): 373–8. doi: 10.1007/s004210050606

5.
Saunders J, Smith T. Malnutrition: causes and consequences. Clin Med (Lond) 2010; 10(6): 624–7. doi: 10.7861/clinmedicine.10-6-624

6.
Jensen GL, Mirtallo J, Compher C, Dhaliwal R, Forbes A, Grijalba RF, et al. Adult starvation and disease-related malnutrition: a proposal for etiology-based diagnosis in the clinical practice setting from the International Consensus Guideline Committee. JPEN J Parenter Enteral Nutr 2010; 34(2): 156–9. doi: 10.1177/0148607110361910

7.
Henriksen C, Gjelstad IM, Nilssen H, Blomhoff R. A low proportion of malnourished patients receive nutrition treatment – results from nutritionDay. Food Nutr Res 2017; 61(1): 1391667. doi: 10.1080/16546628.2017.1391667

8.
Shin JC, Chang SH, Hwang SW, Lee JJ. The nutritional status and the clinical outcomes of patients with a spinal cord injury using nutritional screening tools. Ann Rehabil Med 2018; 42(4): 591–600. doi: 10.5535/arm.2018.42.4.591

9.
Wong S, Derry F, Jamous A, Hirani SP, Grimble G, Forbes A. The prevalence of malnutrition in spinal cord injuries patients: a UK multicentre study. Br J Nutr 2012; 108(5): 918–23. doi: 10.1017/S0007114511006234

10.
Steensgaard R, Bonne S, Wojke P, Kasch H. SCI-SCREEN: a more targeted nutrition screening model to detect spinal cord-injured patients at risk of malnutrition. Rehabil Nurs 2019; 44(1): 11–9. doi: 10.1097/rnj.0000000000000108

11.
Wong S, Derry F, Jamous A, Hirani SP, Forbes A. Is undernutrition risk associated with an adverse clinical outcome in spinal cord-injured patients admitted to a spinal centre? Eur J Clin Nutr 2014; 68(1): 125–30. doi: 10.1038/ejcn.2013.238

12.
Wong S, Derry F, Jamous A, Hirani SP, Grimble G, Forbes A. Validation of the spinal nutrition screening tool (SNST) in patients with spinal cord injuries (SCI): result from a multicentre study. Eur J Clin Nutr 2012; 66(3): 382–7. doi: 10.1038/ejcn.2011.209

13.
Wong S, Kenssous N, Hillier C, Pollmer S, Jackson P, Lewis S, et al. Detecting malnutrition risk and obesity after spinal cord injury: a quality improvement project and systematic review. Eur J Clin Nutr 2018; 72(11): 1555–60. doi: 10.1038/s41430-018-0194-y

14.
Cederholm T, Jensen GL, Correia M, Gonzalez MC, Fukushima R, Higashiguchi T, et al. GLIM criteria for the diagnosis of malnutrition – a consensus report from the global clinical nutrition community. J Cachexia Sarcopenia Muscle 2019; 10(1): 207–17. doi: 10.1002/jcsm.12383

15.
Stratton RJ, Hackston A, Longmore D, Dixon R, Price S, Stroud M, et al. Malnutrition in hospital outpatients and inpatients: prevalence, concurrent validity and ease of use of the ‘malnutrition universal screening tool’ (‘MUST’) for adults. Br J Nutr 2004; 92(5): 799–808. doi: 10.1079/BJN20041258

16.
Landi F, Camprubi-Robles M, Bear DE, Cederholm T, Malafarina V, Welch AA, et al. Muscle loss: the new malnutrition challenge in clinical practice. Clin Nutr 2019; 38(5): 2113–20. doi: 10.1016/j.clnu.2018.11.021

17.
Bosy-Westphal A, Schautz B, Later W, Kehayias JJ, Gallagher D, Muller MJ. What makes a BIA equation unique? Validity of eight-electrode multifrequency BIA to estimate body composition in a healthy adult population. Eur J Clin Nutr 2013; 67(Suppl 1): S14–21. doi: 10.1038/ejcn.2012.160

18.
Buchholz AC, McGillivray CF, Pencharz PB. The use of bioelectric impedance analysis to measure fluid compartments in subjects with chronic paraplegia. Arch Phys Med Rehabil 2003; 84(6): 854–61. doi: 10.1016/S0003-9993(02)04950-X

19.
Panisset MG, Desneves K, Ward LC, Rafferty J, Rodi H, Roff G, et al. Bedside quantification of fat-free mass in acute spinal cord injury using bioelectrical impedance analysis: a psychometric study. Spinal Cord 2018; 56(4): 355–65. doi: 10.1038/s41393-017-0035-1

20.
Kocina PS, Heyward VH. Validation of a bioimpedance equation for estimating fat-free mass of spinal cord injured adults Med Sci Sports Exerc 1997; 29: 55. doi: 10.1097/00005768-199705001-00319

21.
Rupp R, Biering-Sorensen F, Burns SP, Graves DE, Guest J, Jones L, et al. International standards for neurological classification of spinal cord injury: Revised 2019. Top Spinal Cord Inj Rehabil 2021; 27(2): 1–22. doi: 10.46292/sci2702-1

22.
Qin W, Zhao W, Li X, Peng Y, Harlow LM, Li J, et al. Mice with sclerostin gene deletion are resistant to the severe sublesional bone loss induced by spinal cord injury. Osteoporos Int 2016; 27(12): 3627–36. doi: 10.1007/s00198-016-3700-x

23.
Siri WE. Body composition from fluid spaces and density: analysis of methods. 1961. Nutrition 1993; 9(5): 480–91; discussion, 92.

24.
Kocina P. Body composition of spinal cord injured adults. Sports Med 1997; 23(1): 48–60. doi: 10.2165/00007256-199723010-00005

25.
Cederholm T, Bosaeus I, Barazzoni R, Bauer J, Van Gossum A, Klek S, et al. Diagnostic criteria for malnutrition – an ESPEN consensus statement. Clin Nutr 2015; 34(3): 335–40. doi: 10.1016/j.clnu.2015.03.001

26.
McHugh ML. Interrater reliability: the kappa statistic. Biochem Med (Zagreb) 2012; 22(3): 276–82. doi: 10.11613/BM.2012.031

27.
Bland JM, Altman DG. Comparing methods of measurement: why plotting difference against standard method is misleading. Lancet 1995; 346(8982): 1085–7. doi: 10.1016/S0140-6736(95)91748-9

28.
Nash MS, Groah SL, Gater DR, Jr., Dyson-Hudson TA, Lieberman JA, Myers J, et al. Identification and management of cardiometabolic risk after spinal cord injury: clinical practice guideline for health care providers. Top Spinal Cord Inj Rehabil 2018; 24(4): 379–423. doi: 10.1310/sci2404-379

29.
Boehl G, Raguindin PF, Valido E, Bertolo A, Itodo OA, Minder B, et al. Endocrinological and inflammatory markers in individuals with spinal cord injury: a systematic review and meta-analysis. Rev Endocr Metab Disord 2022; 23(5): 1035–50. doi: 10.1007/s11154-022-09742-9

30.
Stumpf F, Keller B, Gressies C, Schuetz P. Inflammation and nutrition: friend or foe? Nutrients 2023; 15(5): 1159. doi: 10.3390/nu15051159

31.
Flury I, Mueller G, Perret C. The risk of malnutrition in patients with spinal cord injury during inpatient rehabilitation – a longitudinal cohort study. Front Nutr 2023; 10: 1085638. doi: 10.3389/fnut.2023.1085638

32.
Shah PK, Stevens JE, Gregory CM, Pathare NC, Jayaraman A, Bickel SC, et al. Lower-extremity muscle cross-sectional area after incomplete spinal cord injury. Arch Phys Med Rehabil 2006; 87(6): 772–8. doi: 10.1016/j.apmr.2006.02.028

33.
Goldstein RL, Walia P, Teylan M, Lazzari AA, Tun CG, Hart JE, et al. Clinical factors associated with C-reactive protein in chronic spinal cord injury. Spinal Cord 2017; 55(12): 1088–95. doi: 10.1038/sc.2017.81

34.
Bloom O, Herman PE, Spungen AM. Systemic inflammation in traumatic spinal cord injury. Exp Neurol 2020; 325: 113143. doi: 10.1016/j.expneurol.2019.113143

35.
Laughton GE, Buchholz AC, Martin Ginis KA, Goy RE, Group SSR. Lowering body mass index cutoffs better identifies obese persons with spinal cord injury. Spinal Cord 2009; 47(10): 757–62. doi: 10.1038/sc.2009.33

36.
Mojtahedi MC, Valentine RJ, Evans EM. Body composition assessment in athletes with spinal cord injury: comparison of field methods with dual-energy X-ray absorptiometry. Spinal Cord 2009; 47(9): 698–704. doi: 10.1038/sc.2009.20

37.
Kaegi-Braun N, Boesiger F, Tribolet P, Gomes F, Kutz A, Hoess C, et al. Validation of modified GLIM criteria to predict adverse clinical outcome and response to nutritional treatment: a secondary analysis of a randomized clinical trial. Clin Nutr 2022; 41(4): 795–804. doi: 10.1016/j.clnu.2022.02.009

38.
Holm NJ, Steensgaard R, Schou LH, Moller T, Kasch H, Biering-Sorensen F. An observational study on body mass index during rehabilitation and follow-up in people with spinal cord injury in Denmark. Spinal Cord 2022; 60(2): 157–62. doi: 10.1038/s41393-021-00730-5

39.
de Groot S, Post MW, Postma K, Sluis TA, van der Woude LH. Prospective analysis of body mass index during and up to 5 years after discharge from inpatient spinal cord injury rehabilitation. J Rehabil Med 2010; 42(10): 922–8. doi: 10.2340/16501977-0605