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Nutritional risk, body mass index and rehabilitation outcome in cognitively impaired vs. cognitively normal patients
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EURGER-729; No. of Pages 5 European Geriatric Medicine xxx (2016) xxx–xxx
Available online at
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Research paper
Nutritional risk, body mass index and rehabilitation outcome in cognitively impaired vs. cognitively normal patients M. Vassallo a,b,*, L. Poynter b,*, J.C. Sharma c, J.S.K. Kwan d a
University of Bournemouth, Fern Barrow, Poole BH12 5BB, UK Royal Bournemouth Hospital, Castle Lane East, Bournemouth BH7 7DW, UK c University of Nottingham, University Park, Nottingham NG7 2RD, UK d University of Hong Kong, Queen Mary Hospital, 102 Pok Fu Lam Road, Hong Kong b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 11 December 2015 Accepted 28 January 2016 Available online xxx
Introduction: The role of low body weight and body mass index in the rehabilitation of cognitively impaired (CI) patients is unclear. Materials and methods: In a prospective cohort study in a rehabilitation unit for elderly patients recovering from acute illness, we explored functional outcomes in patients with a BMI < 20 kg/m2 and Malnutrition Universal Screening Tool (MUST) 2 as a marker of high risk of malnutrition, in cognitively intact and impaired patients. One hundred and fifteen patients (mean age 84.7 years, range 69–98, 70 females) were followed up. All received an individually tailored rehabilitation programme as standard. The Barthel Activity of Daily Living (BADL) score was performed on admission and discharge and the primary outcome was improvement in BADL. Results: Patients with an improved BADL had a higher mean MMSE (20.7v17.7; P = 0.02) and BMI (24.1v 20.9; P = 0.006) and lower mean MUST (0.45v1.11; P = 0.002). A 2-way ANOVA showed significant variance and cognitively normal patients with a BMI 20 showed the greatest improvement in BADL (P = 0.03). CI patients who improved had a higher BMI (23.8v21.2; P = 0.02) and lower MUST (0.43v1.09; P = 0.004). Patients with a BMI 20 (19.3v12.8; P = 0.31) and MUST < 2 (18.4 v15.9; P = 0.64) showed a greater mean improvement in BADL after rehabilitation. The total number of CI patients showing improvement in BADL was significantly higher in those with a BMI of 20 kg/m2 [55/75 (73.3%) v10/22 (45.5%); P = 0.02]. Conclusion: Patients with cognitive impairment and a BMI < 20 kg/m2 or MUST 2 on admission to rehabilitation are less likely to show improvement in BADL with rehabilitation when compared to cognitively impaired patients with a MUST < 2 or BMI 20 kg/m2. ß 2016 Elsevier Masson SAS and European Union Geriatric Medicine Society. All rights reserved.
Keywords: BMI Dementia Elderly MUST Rehabilitation
1. Introduction Cognitive impairment, weight loss, low physical activity and slow gait speed are key indicators of frailty and associated with poor outcomes such as nursing home placements, chronic disability and death [1]. Weight loss is associated with sarcopenia, which is the unintentional loss of lean body mass with loss of strength and muscle contributing to functional impairment [2]. It is recognised that the loss of lean mass is accelerated in patients with Alzheimer’s dementia (AD) and is associated with brain
* Corresponding authors at: Royal Bournemouth Hospital, Castle Lane East, Bournemouth BH7 7DW, UK. Tel.: +44 1202 704 539; fax: +44 1202 704 542. E-mail addresses: [email protected] (M. Vassallo), [email protected] (L. Poynter).
atrophy and loss of cognitive performance [3]. Malnutrition and cognition are therefore closely related in patients with dementia and nutritional care and support should be an integral part of the management of patients with dementia [4]. In community-based studies, poor nutrition was significantly related to advanced age, worse cognitive, functional and behavioural profiles [5]. A BMI of less than 25 kg/m2 was identified as a cut-off point for worse cognitive status and a likelihood of progression of dementia [6]. Malnutrition is also related to poor physical function. Community-dwelling AD patients at risk of malnutrition were more impaired in basic and complex daily functioning than wellnourished AD patients [7]. In a long-term care setting there was a strong correlation between poor nutritional status, the MiniMental State Examination (MMSE), poor performance in activities of daily living and the Barthel Activity of Daily Living score (BADL)
http://dx.doi.org/10.1016/j.eurger.2016.01.010 1878-7649/ß 2016 Elsevier Masson SAS and European Union Geriatric Medicine Society. All rights reserved.
Please cite this article in press as: Vassallo M, et al. Nutritional risk, body mass index and rehabilitation outcome in cognitively impaired vs. cognitively normal patients. Eur Geriatr Med (2016), http://dx.doi.org/10.1016/j.eurger.2016.01.010
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[8]. It therefore seems plausible that pathophysiology controlling sarcopenia, gait, physical function and cognition is shared and controlled in the brain via mechanisms that are vulnerable to multiple age related pathologies that may be caused or accentuated by malnutrition or deficiencies. The identification of common modifiable risk factors such as malnutrition may serve an important preventive strategy to reduce cognitive and mobility impairments [9]. Nutritional Supplementation with oral protein and energy supplementation in older people can produce a small but consistent weight gain and may reduce mortality and complications of malnutrition in older people who are undernourished. However, there remains no evidence of functional benefit or reduction in length of hospital stay with supplements [10]. The effect of nutrition supplementation in patients with dementia remains unknown and there is also insufficient evidence to suggest that enteral tube feeding is beneficial in patients with advanced dementia [11]. While the nutritional status in dementia can be improved [12] the ‘‘NutriAlz’’ programme showed that there was no effect on functional decline in AD patients living at home over one year [13]. In a rehabilitation environment, malnutrition has been shown to be an independent predictor of mortality, adverse clinical events and poor clinical outcomes [14] particularly in stroke and fracture neck of femur patients [15,16]. However, the relationship between malnutrition and short term rehabilitation outcomes in cognitively impaired patients has to our knowledge not been explored. We evaluated rehabilitation outcomes in cognitively impaired and cognitively intact patients with a low BMI and MUST as a marker of risk of malnutrition to test the hypothesis that low BMI and/or risk of malnutrition are associated with less favourable rehabilitation outcomes in patients with cognitive impairment.
2. Methods In a prospective observational study, we evaluated a cohort of consecutive patients admitted for rehabilitation. Data were collected over a 1-year period from 2 general rehabilitation wards in a UK rehabilitation unit for older people by a trained researcher. Participants were recruited within the first week of admission and followed until discharge. All patients were transferred from an acute setting after an admission with an acute medical or surgical condition. Ninety percent of admissions were from medical wards. Individuals with hip fracture and stroke were not admitted to these wards and were naturally excluded however patients with other neurological conditions such as Parkinson’s disease were included. Patients were also excluded if they had delirium or other acute illness that precluded participation in rehabilitation at the point of admission. Patients would have been assessed prior to transfer by a multidisciplinary team consisting of a doctor, nurse, physiotherapist and occupational therapist and were deemed to have sufficiently recovered from their acute illness to be able to participate in rehabilitation. As this was an observational study, there was no defined time period for rehabilitation but an analysis was made at a cut-off point of 80 days. The ‘Malnutrition Universal Screening Tool’ (‘MUST’) is a fivestep screening tool to identify adults, who are malnourished or at risk of malnutrition. A scoring system is based on calculation of BMI in step one followed by an estimate of recent weight loss and the impact of acute illness on food intake. It is the most widely used nutritional screening tool for patients at risk of malnutrition in the UK and is recommended by the National Institute for Clinical Excellence [17]. It is also commonly used worldwide. It has been evaluated in hospital wards, outpatient clinics, general practice, community and in care homes [18]. All patients had a BMI and MUST
score calculated on admission. A score of 2 indicated a high risk of malnutrition. Although the BMI is part of the MUST this latter score requires further assessments and patients with a normal BMI may still have a high risk MUST or medium risk MUST with a low BMI. We therefore reported outcomes for both measures. Cognition was assessed on admission using the MMSE [19] and participants were grouped using MMSE scores as described by National Institute for Health and Clinical Excellence guidelines [20]. Patients were cognitively normal if they had a MMSE score of 27–30 and cognitively impaired if they had a score less than 27. Cognition was also evaluated using the CLOX test [21] and the correlation to MMSE evaluated. Functional ability was also assessed on admission using the BADL score [22]. This validated tool assesses the ability to care for oneself based on 10 activities including: feeding, bathing, grooming, dressing, bowel control, bladder control, toileting, chair transfer, ambulation and stair climbing. This score was calculated within 2 days of admission. Function was then reassessed at discharge. As the BADL score is made up of discrete items and is not scored in a continuous fashion, our primary outcome was improvement in the score. This was defined as improvement in at least one item that will have resulted in an improvement of at least 5 points in the score. Information pertaining to comorbidities was collected and scored using the Charlson Comorbidity Index (CCI) [23]. Comorbidity was defined as the number of disorders/diseases that the patient suffered from. This could include behavioural or mental disorders. To complete the CCI diseases noted included myocardial infarct, congestive heart failure, peripheral vascular disease, dementia, cerebrovascular disease, chronic lung disease, connective tissue disease, peptic ulcer, chronic liver disease, diabetes, hemiplegia, kidney disease, diabetes with end organ damage, tumour, leukemia, lymphoma, malignant tumours, metastasis, acquired immunodeficiency syndrome. The number of medications taken regularly was recorded. Medications taken occasionally were not included. We evaluated patient mood using the Hospital Anxiety and Depression scale [24]. Each participant had formal input from physiotherapists and occupational therapists and informal therapy by nursing staff. Each had a personalized plan depending on individual abilities with the intention of addressing rehabilitation needs on a daily basis. Physiotherapy was aimed to increasing mobility with therapies to increase muscle strength and balance. This included individual and supervised group training to maintain or improve mobility and performance of daily activities. Exercises were of gradually increasing intensity and comprised walking, exercise to-set routines, skills training, stretching, and relaxation activities. Physical therapist led group training combining aerobic, resistance, flexibility and balance exercises depending on individual need [25] Occupational therapist input aimed to improve activities of daily living. All patients had informal therapy by nursing staff when mobilising and through support for activities of daily living. Patients identified to be nutritionally at risk were reviewed by a dietician or doctor with a view of formulating an individual care plan aimed at improving nutrition. When appropriate on discharge patients had advice about home exercises and/or outpatient physiotherapy. Ethical approval was obtained from the Dorset Research and Ethics Committee, and informed consent was obtained from all participants. Participants with severe cognitive impairment who could not give informed consent were included after next of kin gave assent on their behalf. 2.1. Statistics Categorical data were analysed using Fishers Exact Probability Test and medians for non-parametric data using the MannWhitney U Test as appropriate. The interaction between cognition
Please cite this article in press as: Vassallo M, et al. Nutritional risk, body mass index and rehabilitation outcome in cognitively impaired vs. cognitively normal patients. Eur Geriatr Med (2016), http://dx.doi.org/10.1016/j.eurger.2016.01.010
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and nutritional status on change in BADL scores was evaluated using a 2-way ANOVA. Univariate and multiple logistic regression analyses were used to investigate the association between the various patient characteristics and improvement in BADL. These variables were studied in a forward selection to build a multiple logistic regression analysis model to identify significant independent variables predisposing to BADL improvement. Cox regression analysis was used to study improvement in BADL over time. Analysis was carried out using SPSS. 3. Results We studied 115 patients [mean age 84.7 (SD 6.26), female 70 (61%)]. We compared characteristics for those who showed no improvement in BADL to those showing improvement (Table 1). Patients improving BADL had a higher MMSE [mean 20.7 (SD 5.39) median 21 v 17.7 (7.33)18; P = 0.02], CLOX [mean 6.3 (SD 4.0) median 6.0 v 3.9 (3.85)3.0; 0.004], BMI [mean 24.1 (SD 5.89) median 22 v 20.9 (4.70)20; P = 0.006] and lower MUST score [mean 0.45 (SD 0.84) median 0 v 1.11 (1.25)1; P = 0.002] compared to those not improving. There was strong correlation between the CLOX and MMSE r = .522 P = 0.000. We identified a BMI cut-off point of < 20 kg/m2 where the BADL score improved for 14/28 (50%) compared to 66/87 (75.8%) patients with a BMI of 20 kg/m2 (P = 0.017). Significantly different parametres were entered in a logistic regression, forward conditional regression analysis model with improvement in BADL as the dependent variable. We identified MMSE (P = 0.02: 95% CI 1.01–1.16) and MUST (P = 0.002: 95% CI 0.35–0.80) as the only independent variables that influenced outcome of rehabilitation in this cohort. The same significant finding was identified if BMI replaced MUST in this model (P = 0.027, 95% CI 0.04–0.15). We explored the interaction between cognition and nutrition on BADL improvement using a 2-way ANOVA (Fig. 1). Patients with normal cognition and a BMI 20 kg/m2 showed greater improvements in BADL than those with abnormal cognition and BMI < 20 kg/m2 (P = 0.03). We compared patient characteristics for those showing improvement to those showing no improvement in BADL score in the cognitively impaired group (MMSE 26) only. BMI [mean 23.8 (SD 4.99) median 23 v 21.2 (4.67)17; P = 0.02] was higher and MUST [mean 0.43 (SD 0.85) median 0 v 1.09 (1.28)1; P = 0.004] was significantly lower in the patients showing improvement. These characteristics were entered in a logistic regression, forward conditional regression analysis model. We identified BMI (P = 0.02; 95% CI: 1.02–1.25) and in a separate analysis MUST (P = 0.006; 95% CI: 0.36–0.84) as the independent variables that influenced outcome of rehabilitation in this cohort. In these cognitively impaired patients, there was a non-significant trend for a greater improvement in mean
Fig. 1. Two-way Anova exploring change in Barthel Score with body mass index (BMI 20/BMI < 20) and cognition (Normal Mini-Mental State Exam 27). Levenes Test for Homogeneity of Variance: P = 0.031
BADL score in patients with a MUST < 2 compared to MUST 2 [mean 18.4 (SD 18.5) median 18 v 15.9 (SD 20.9) 16; P = 0.64]. Similarly there also was a non-significant trend to a greater improvement in BADL score with a BMI 20 [mean 19.3 (SD 17.0) median 19 v12.8 (SD 25.4) 13; P = 0.31]. We analysed the total number of patients who showed an improvement in BADL score by BMI 20 kg/m2 vs < 20 kg/m2. 66/ 87 (77.1%) vs 14/28 (50.0%) showed an improvement (P = 0.017). A further subgroup analysis by cognitive status was carried out. Cognitively normal subjects showed no difference in number of patients improving by BMI stratification. Cognitively impaired patients with BMI of 20 kg/m2 were significantly more likely to show improvement than cognitively impaired patients with a BMI < 20 kg/m2 [55/75 (73.3%) v 10/22 (45.5%); P = 0.02]. Similar results were noted by MUST risk status. A Cox regression analysis (Fig. 2) correcting for age and CCI index looking at 4 groups of patients, showed a similar trajectory of improvement in cognitively intact patients regardless of nutrition state. However, in cognitively impaired patients a MUST score 2 was associated with worse outcome and much slower improvement in BADL than patients with a MUST < 2. 4. Discussion Our study has shown that a BMI < 20 kg/m2 and a MUST 2 are associated with poor rehabilitation outcomes in patients with cognitive impairment. Patients with cognitive impairment and a BMI < 20 kg/m2 show less improvement as measured by their
Table 1 Factors associated with an improvement in Barthel Score with rehabilitation. Parameter
Barthel Improvement Total 80
No Barthel Improvement Total 35
Mean
(SD)
Median
Mean
(SD)
Median
Age Barthel Admission Barthel Discharge BMI Charlson Comorbidity Score MUST score MMSE CLOX Hospital Anxiety Score Hospital Depression Score Length of stay
84.7 45.4 70.9 24.2 5.95 0.45 20.7 6.3 3.9 4.1 32.7
(6.85) (19.9) (18.6) (5.89) (1.46) (0.84) (5.39) (4.0) (3.3) (3.4) (19.9)
85.0 45.0 75 22.0 6.0 0.0 20.0 6.0 3.0 3.0 28.0
84.9 40.4 34.3 20.9 6.17 1.11 17.7 3.9 3.8 4.1 44.3
(4.70) (20.9) (24.5) (4.70) (1.71) (1.25) (7.33) (3.85) (3.8) (4.5) (41.4)
85.0 40.0 22.5 20.0 6.0 1.0 18.0 3.0 2.0 3.0 45.0
P
0.9 0.24 0.000 0.003 0.49 0.001 0.018 0.004 0.65 0.42 0.006
BMI: body mass index; MUST; Malnutrition Universal Screening Tool; MMSE: Mini-Mental State Examination.
Please cite this article in press as: Vassallo M, et al. Nutritional risk, body mass index and rehabilitation outcome in cognitively impaired vs. cognitively normal patients. Eur Geriatr Med (2016), http://dx.doi.org/10.1016/j.eurger.2016.01.010
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aerobic capacity, muscle strength and endurance, by improving aerobic conditioning and/or strength [27]. In addition, an improved meal environment in nursing homes has been shown to markedly improve the psychosocial and nutrition status of residents thus demonstrating that benefits can be obtained from a more proactive approach to nutrition in dementia [28]. This study therefore raises the question whether a more active approach to nutrition improvement and exercise in this group of patients will help improve outcomes [29,30]. This is an area that needs further exploring. Ethical statement Ethical approval was obtained from the Dorset Research and Ethics Committee, and informed consent was obtained from all participants. Participants with severe cognitive impairment who could not give informed consent were included after next of kin gave assent on behalf of the patient. Fig. 2. Improvement in Barthel Score by Cognitive State and Malnutrition Universal Screening Tool (MUST) risk status. P = 0.04. Group 1: cognition normal-MUST < 2 (13 patients). Group 2: cognition normal-MUST (5 patients). Group 3: cognition impaired-MUST < 2 (75 patients). Group 4: cognition impaired-MUST 2 (22 patients).
Disclosure of interest The authors declare that they have no competing interest. Acknowledgments
change in BADL score compared to cognitively intact patients with a BMI 20 kg/m2. In the cognitively impaired group of patients, BMI and MUST were the most important determinants of improvement and less patients with a low BMI or a MUST 2, improved with rehabilitation. To our knowledge, this is a new finding and offers a potentially reversible risk factor that may impact rehabilitation in patients with cognitive impairment. There are limitations to this study. The number of patients recruited was small and this may have influenced the results such as the lack of effect of anxiety or depression on rehabilitation. This effect of malnutrition was also not apparent in the cognitively intact group. It is possible that this was due to the small size of this group. In addition, we only measured nutritional status on admission, so another possible reason for the similar improvement in the cognitively intact group was that it was easier to address issues of malnutrition in this group than it was in the cognitively impaired. These findings are not surprising in view of the increasingly recognised link between cognition, nutrition, sarcopenia and physical performance. It is likely that malnutrition and cognitive decline work together in leading to the physical deterioration of patients reflected in poor rehabilitation outcomes we observed [26]. A BMI below 25 kg/m2 has been identified as a prognostic indicator for poor rehabilitation outcomes in other studies. Our study confirms that a low BMI has an adverse prognosis, however, the cut-off in our study was 20 kg/m2. This may be explained by our smaller sample size or a different patient population, particularly the fact that this patient cohort consisted of predominantly cognitively impaired patients. The Cox regression analysis showed that cognitively intact patients had a rapid trajectory of improvement in BADL score with the improvement having occurred by 30 days regardless of nutritional status. Conversely, cognitively impaired patients had a slower rate of improvement. Within this group, patients with a MUST 2 showed an even slower rate of improvement. Although improvement was slower, it was improvement nonetheless and here is no suggestion that this group of patients are not given the opportunity for rehabilitation but rather provision made to allow more time for rehabilitation. Regular exercise is the only strategy found to consistently prevent frailty and improve sarcopenia and physical function in older adults. Physical exercises increase
No funding to this research but the research was supported by the Royal Bournemouth and Christchurch Hospitals NHS Foundation Trust UK. All authors fulfil authorship criteria and have access to data supporting the publication. References [1] Bales CW, Ritchie CS. Sarcopenia, weight loss, and nutritional frailty in the elderly. Annu Rev Nutr 2002;22:309–23 [Epub 2002 Jan 4]. [2] Rothman MD, Leo-Summers L, Gill TM. Prognostic significance of potential frailty criteria. J Am Geriatr Soc 2008;56(12):2211–6. [3] Burns JM, Johnson DK, Watts A, Swerdlow RH, Brooks WM. Lean mass is reduced in early Alzheimer’s disease and associated with brain atrophy. Arch Neurol 2010;67(4):428–33. [4] Volkert D, Chourdakis M, Faxen-Irving G, Fruhwald T, Landi F, Suominen MH, Vandewoude M, Wirth R, Schneider SM. ESPEN guidelines on nutrition in dementia. Clin Nutr 2015;34(6):1052–73. [5] Roque´ M, Salva` A, Vellas B. Malnutrition in community-dwelling adults with dementia (NutriAlz Trial). J Nutr Health Aging 2013;17(4):295–9. [6] Coin A, Bolzetta F, De Rui M, et al. Nutritional and global indexes of progression in dementia: a 12-month prospective study. Am J Alzheimers Dis Other Demen 2012;27(7):504–8. [7] Droogsma E, Van Asselt DZ, Scho¨lzel-Dorenbos CJ, et al. Nutritional status of community-dwelling elderly with newly diagnosed Alzheimer’s disease: prevalence of malnutrition and the relation of various factors to nutritional status. J Nutr Health Aging 2013;17(7):606–10. [8] Malara A, Sgro` G, Caruso C, et al. Relationship between cognitive impairment and nutritional assessment on functional status in Calabrian long-term care. Clin Interv Aging 2014;9:105–10. [9] Ayers E, Verghese J. Locomotion, cognition and influences of nutrition in ageing. Proc Nutr Soc 2014;73(2):302–8. [10] Milne AC, Potter J, Vivanti A, Avenell A. Protein and energy supplementation in elderly people at risk from malnutrition. Cochrane Database Syst Rev 2009;2:CD003288. http://dx.doi.org/10.1002/14651858.CD003288.pub3. [11] Sampson EL, Candy B, Jones L. Enteral tube feeding for older people with advanced dementia. Cochrane Database Syst Rev 2009;2:CD007209. http:// dx.doi.org/10.1002/14651858.CD007209.pub2. [12] Jesus P, Desport JC, Massoulard A, et al. Nutritional assessment and follow-up of residents with and without dementia in nursing homes in the Limousin region of France: a health network initiative. J Nutr Health Aging 2012;16(5):504–8. [13] Salva` A, Andrieu S, Fernandez E, et al. Health and nutrition promotion program for patients with dementia (NutriAlz): cluster randomized trial. J Nutr Health Aging 2011;15(10):822–30. [14] Neuman SA, Miller MD, Daniels L, et al. Nutritional status and clinical outcomes of older patients in rehabilitation. J Hum Nutr Diet 2005;2:129–36. [15] Landi F, Bernabei R, Russo A, et al. Predictors of rehabilitation outcomes in frail patients treated in a geriatric hospital. J Am Geriatr Soc 2002;50(4):679–84. [16] Wyers CE, Reijven PLM, Evers SMA, et al. Cost-effectiveness of nutritional intervention in elderly subjects after hip fracture. A randomized controlled trial. Osteoporois Int 2013;24(1):151–62.
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[25] Gine´-Garriga M, Roque´-Fı´guls M, Coll-Planas L, Sitja`-Rabert M, Salva` A. Physical exercise interventions for improving performance-based measures of physical function in community-dwelling, frail older adults: a systematic review and meta-analysis. Arch Phys Med Rehabil 2014;95(4):753–69. http://dx.doi.org/10.1016/j.apmr.2013.11.007 [e3. Epub 2013 Nov 27]. [26] Cruz-Jentoft AJ, Baeyens JP, Bauer JM, et al. Sarcopenia: European consensus on definition and diagnosis Report of the European Working Group on Sarcopenia in Older People. Age Ageing 2010;39(4):412–23. [27] Landi F, Marzetti E, Martone AM, Bernabei R, Onder G. Exercise as a remedy for sarcopenia. Curr Opin Clin Nutr Metab Care 2014;17(1):25–31. [28] Kamo T, Nishida Y. Direct and indirect effects of nutritional status, physical function and cognitive function on activities of daily living in Japanese older adults requiring long-term care. Geriatr Gerontol Int 2014;4:799–805. [29] Steen B. Maximizing outcome of dementia treatment: the role of nutrition. Arch Gerontol Geriatr Suppl 2004;(9):413–7. [30] Stow R, Ives N, Smith C, Rick C, Rushton A. A cluster randomised feasibility trial evaluating nutritional interventions in the treatment of malnutrition in care home adult residents. Trials 2015;16:433. http://dx.doi.org/10.1186/s13063015-0952 [Published online 2015 September 28].
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EURGER-729; No. of Pages 5 European Geriatric Medicine xxx (2016) xxx–xxx
Available online at
ScienceDirect www.sciencedirect.com
Research paper
Nutritional risk, body mass index and rehabilitation outcome in cognitively impaired vs. cognitively normal patients M. Vassallo a,b,*, L. Poynter b,*, J.C. Sharma c, J.S.K. Kwan d a
University of Bournemouth, Fern Barrow, Poole BH12 5BB, UK Royal Bournemouth Hospital, Castle Lane East, Bournemouth BH7 7DW, UK c University of Nottingham, University Park, Nottingham NG7 2RD, UK d University of Hong Kong, Queen Mary Hospital, 102 Pok Fu Lam Road, Hong Kong b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 11 December 2015 Accepted 28 January 2016 Available online xxx
Introduction: The role of low body weight and body mass index in the rehabilitation of cognitively impaired (CI) patients is unclear. Materials and methods: In a prospective cohort study in a rehabilitation unit for elderly patients recovering from acute illness, we explored functional outcomes in patients with a BMI < 20 kg/m2 and Malnutrition Universal Screening Tool (MUST) 2 as a marker of high risk of malnutrition, in cognitively intact and impaired patients. One hundred and fifteen patients (mean age 84.7 years, range 69–98, 70 females) were followed up. All received an individually tailored rehabilitation programme as standard. The Barthel Activity of Daily Living (BADL) score was performed on admission and discharge and the primary outcome was improvement in BADL. Results: Patients with an improved BADL had a higher mean MMSE (20.7v17.7; P = 0.02) and BMI (24.1v 20.9; P = 0.006) and lower mean MUST (0.45v1.11; P = 0.002). A 2-way ANOVA showed significant variance and cognitively normal patients with a BMI 20 showed the greatest improvement in BADL (P = 0.03). CI patients who improved had a higher BMI (23.8v21.2; P = 0.02) and lower MUST (0.43v1.09; P = 0.004). Patients with a BMI 20 (19.3v12.8; P = 0.31) and MUST < 2 (18.4 v15.9; P = 0.64) showed a greater mean improvement in BADL after rehabilitation. The total number of CI patients showing improvement in BADL was significantly higher in those with a BMI of 20 kg/m2 [55/75 (73.3%) v10/22 (45.5%); P = 0.02]. Conclusion: Patients with cognitive impairment and a BMI < 20 kg/m2 or MUST 2 on admission to rehabilitation are less likely to show improvement in BADL with rehabilitation when compared to cognitively impaired patients with a MUST < 2 or BMI 20 kg/m2. ß 2016 Elsevier Masson SAS and European Union Geriatric Medicine Society. All rights reserved.
Keywords: BMI Dementia Elderly MUST Rehabilitation
1. Introduction Cognitive impairment, weight loss, low physical activity and slow gait speed are key indicators of frailty and associated with poor outcomes such as nursing home placements, chronic disability and death [1]. Weight loss is associated with sarcopenia, which is the unintentional loss of lean body mass with loss of strength and muscle contributing to functional impairment [2]. It is recognised that the loss of lean mass is accelerated in patients with Alzheimer’s dementia (AD) and is associated with brain
* Corresponding authors at: Royal Bournemouth Hospital, Castle Lane East, Bournemouth BH7 7DW, UK. Tel.: +44 1202 704 539; fax: +44 1202 704 542. E-mail addresses: [email protected] (M. Vassallo), [email protected] (L. Poynter).
atrophy and loss of cognitive performance [3]. Malnutrition and cognition are therefore closely related in patients with dementia and nutritional care and support should be an integral part of the management of patients with dementia [4]. In community-based studies, poor nutrition was significantly related to advanced age, worse cognitive, functional and behavioural profiles [5]. A BMI of less than 25 kg/m2 was identified as a cut-off point for worse cognitive status and a likelihood of progression of dementia [6]. Malnutrition is also related to poor physical function. Community-dwelling AD patients at risk of malnutrition were more impaired in basic and complex daily functioning than wellnourished AD patients [7]. In a long-term care setting there was a strong correlation between poor nutritional status, the MiniMental State Examination (MMSE), poor performance in activities of daily living and the Barthel Activity of Daily Living score (BADL)
http://dx.doi.org/10.1016/j.eurger.2016.01.010 1878-7649/ß 2016 Elsevier Masson SAS and European Union Geriatric Medicine Society. All rights reserved.
Please cite this article in press as: Vassallo M, et al. Nutritional risk, body mass index and rehabilitation outcome in cognitively impaired vs. cognitively normal patients. Eur Geriatr Med (2016), http://dx.doi.org/10.1016/j.eurger.2016.01.010
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[8]. It therefore seems plausible that pathophysiology controlling sarcopenia, gait, physical function and cognition is shared and controlled in the brain via mechanisms that are vulnerable to multiple age related pathologies that may be caused or accentuated by malnutrition or deficiencies. The identification of common modifiable risk factors such as malnutrition may serve an important preventive strategy to reduce cognitive and mobility impairments [9]. Nutritional Supplementation with oral protein and energy supplementation in older people can produce a small but consistent weight gain and may reduce mortality and complications of malnutrition in older people who are undernourished. However, there remains no evidence of functional benefit or reduction in length of hospital stay with supplements [10]. The effect of nutrition supplementation in patients with dementia remains unknown and there is also insufficient evidence to suggest that enteral tube feeding is beneficial in patients with advanced dementia [11]. While the nutritional status in dementia can be improved [12] the ‘‘NutriAlz’’ programme showed that there was no effect on functional decline in AD patients living at home over one year [13]. In a rehabilitation environment, malnutrition has been shown to be an independent predictor of mortality, adverse clinical events and poor clinical outcomes [14] particularly in stroke and fracture neck of femur patients [15,16]. However, the relationship between malnutrition and short term rehabilitation outcomes in cognitively impaired patients has to our knowledge not been explored. We evaluated rehabilitation outcomes in cognitively impaired and cognitively intact patients with a low BMI and MUST as a marker of risk of malnutrition to test the hypothesis that low BMI and/or risk of malnutrition are associated with less favourable rehabilitation outcomes in patients with cognitive impairment.
2. Methods In a prospective observational study, we evaluated a cohort of consecutive patients admitted for rehabilitation. Data were collected over a 1-year period from 2 general rehabilitation wards in a UK rehabilitation unit for older people by a trained researcher. Participants were recruited within the first week of admission and followed until discharge. All patients were transferred from an acute setting after an admission with an acute medical or surgical condition. Ninety percent of admissions were from medical wards. Individuals with hip fracture and stroke were not admitted to these wards and were naturally excluded however patients with other neurological conditions such as Parkinson’s disease were included. Patients were also excluded if they had delirium or other acute illness that precluded participation in rehabilitation at the point of admission. Patients would have been assessed prior to transfer by a multidisciplinary team consisting of a doctor, nurse, physiotherapist and occupational therapist and were deemed to have sufficiently recovered from their acute illness to be able to participate in rehabilitation. As this was an observational study, there was no defined time period for rehabilitation but an analysis was made at a cut-off point of 80 days. The ‘Malnutrition Universal Screening Tool’ (‘MUST’) is a fivestep screening tool to identify adults, who are malnourished or at risk of malnutrition. A scoring system is based on calculation of BMI in step one followed by an estimate of recent weight loss and the impact of acute illness on food intake. It is the most widely used nutritional screening tool for patients at risk of malnutrition in the UK and is recommended by the National Institute for Clinical Excellence [17]. It is also commonly used worldwide. It has been evaluated in hospital wards, outpatient clinics, general practice, community and in care homes [18]. All patients had a BMI and MUST
score calculated on admission. A score of 2 indicated a high risk of malnutrition. Although the BMI is part of the MUST this latter score requires further assessments and patients with a normal BMI may still have a high risk MUST or medium risk MUST with a low BMI. We therefore reported outcomes for both measures. Cognition was assessed on admission using the MMSE [19] and participants were grouped using MMSE scores as described by National Institute for Health and Clinical Excellence guidelines [20]. Patients were cognitively normal if they had a MMSE score of 27–30 and cognitively impaired if they had a score less than 27. Cognition was also evaluated using the CLOX test [21] and the correlation to MMSE evaluated. Functional ability was also assessed on admission using the BADL score [22]. This validated tool assesses the ability to care for oneself based on 10 activities including: feeding, bathing, grooming, dressing, bowel control, bladder control, toileting, chair transfer, ambulation and stair climbing. This score was calculated within 2 days of admission. Function was then reassessed at discharge. As the BADL score is made up of discrete items and is not scored in a continuous fashion, our primary outcome was improvement in the score. This was defined as improvement in at least one item that will have resulted in an improvement of at least 5 points in the score. Information pertaining to comorbidities was collected and scored using the Charlson Comorbidity Index (CCI) [23]. Comorbidity was defined as the number of disorders/diseases that the patient suffered from. This could include behavioural or mental disorders. To complete the CCI diseases noted included myocardial infarct, congestive heart failure, peripheral vascular disease, dementia, cerebrovascular disease, chronic lung disease, connective tissue disease, peptic ulcer, chronic liver disease, diabetes, hemiplegia, kidney disease, diabetes with end organ damage, tumour, leukemia, lymphoma, malignant tumours, metastasis, acquired immunodeficiency syndrome. The number of medications taken regularly was recorded. Medications taken occasionally were not included. We evaluated patient mood using the Hospital Anxiety and Depression scale [24]. Each participant had formal input from physiotherapists and occupational therapists and informal therapy by nursing staff. Each had a personalized plan depending on individual abilities with the intention of addressing rehabilitation needs on a daily basis. Physiotherapy was aimed to increasing mobility with therapies to increase muscle strength and balance. This included individual and supervised group training to maintain or improve mobility and performance of daily activities. Exercises were of gradually increasing intensity and comprised walking, exercise to-set routines, skills training, stretching, and relaxation activities. Physical therapist led group training combining aerobic, resistance, flexibility and balance exercises depending on individual need [25] Occupational therapist input aimed to improve activities of daily living. All patients had informal therapy by nursing staff when mobilising and through support for activities of daily living. Patients identified to be nutritionally at risk were reviewed by a dietician or doctor with a view of formulating an individual care plan aimed at improving nutrition. When appropriate on discharge patients had advice about home exercises and/or outpatient physiotherapy. Ethical approval was obtained from the Dorset Research and Ethics Committee, and informed consent was obtained from all participants. Participants with severe cognitive impairment who could not give informed consent were included after next of kin gave assent on their behalf. 2.1. Statistics Categorical data were analysed using Fishers Exact Probability Test and medians for non-parametric data using the MannWhitney U Test as appropriate. The interaction between cognition
Please cite this article in press as: Vassallo M, et al. Nutritional risk, body mass index and rehabilitation outcome in cognitively impaired vs. cognitively normal patients. Eur Geriatr Med (2016), http://dx.doi.org/10.1016/j.eurger.2016.01.010
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and nutritional status on change in BADL scores was evaluated using a 2-way ANOVA. Univariate and multiple logistic regression analyses were used to investigate the association between the various patient characteristics and improvement in BADL. These variables were studied in a forward selection to build a multiple logistic regression analysis model to identify significant independent variables predisposing to BADL improvement. Cox regression analysis was used to study improvement in BADL over time. Analysis was carried out using SPSS. 3. Results We studied 115 patients [mean age 84.7 (SD 6.26), female 70 (61%)]. We compared characteristics for those who showed no improvement in BADL to those showing improvement (Table 1). Patients improving BADL had a higher MMSE [mean 20.7 (SD 5.39) median 21 v 17.7 (7.33)18; P = 0.02], CLOX [mean 6.3 (SD 4.0) median 6.0 v 3.9 (3.85)3.0; 0.004], BMI [mean 24.1 (SD 5.89) median 22 v 20.9 (4.70)20; P = 0.006] and lower MUST score [mean 0.45 (SD 0.84) median 0 v 1.11 (1.25)1; P = 0.002] compared to those not improving. There was strong correlation between the CLOX and MMSE r = .522 P = 0.000. We identified a BMI cut-off point of < 20 kg/m2 where the BADL score improved for 14/28 (50%) compared to 66/87 (75.8%) patients with a BMI of 20 kg/m2 (P = 0.017). Significantly different parametres were entered in a logistic regression, forward conditional regression analysis model with improvement in BADL as the dependent variable. We identified MMSE (P = 0.02: 95% CI 1.01–1.16) and MUST (P = 0.002: 95% CI 0.35–0.80) as the only independent variables that influenced outcome of rehabilitation in this cohort. The same significant finding was identified if BMI replaced MUST in this model (P = 0.027, 95% CI 0.04–0.15). We explored the interaction between cognition and nutrition on BADL improvement using a 2-way ANOVA (Fig. 1). Patients with normal cognition and a BMI 20 kg/m2 showed greater improvements in BADL than those with abnormal cognition and BMI < 20 kg/m2 (P = 0.03). We compared patient characteristics for those showing improvement to those showing no improvement in BADL score in the cognitively impaired group (MMSE 26) only. BMI [mean 23.8 (SD 4.99) median 23 v 21.2 (4.67)17; P = 0.02] was higher and MUST [mean 0.43 (SD 0.85) median 0 v 1.09 (1.28)1; P = 0.004] was significantly lower in the patients showing improvement. These characteristics were entered in a logistic regression, forward conditional regression analysis model. We identified BMI (P = 0.02; 95% CI: 1.02–1.25) and in a separate analysis MUST (P = 0.006; 95% CI: 0.36–0.84) as the independent variables that influenced outcome of rehabilitation in this cohort. In these cognitively impaired patients, there was a non-significant trend for a greater improvement in mean
Fig. 1. Two-way Anova exploring change in Barthel Score with body mass index (BMI 20/BMI < 20) and cognition (Normal Mini-Mental State Exam 27). Levenes Test for Homogeneity of Variance: P = 0.031
BADL score in patients with a MUST < 2 compared to MUST 2 [mean 18.4 (SD 18.5) median 18 v 15.9 (SD 20.9) 16; P = 0.64]. Similarly there also was a non-significant trend to a greater improvement in BADL score with a BMI 20 [mean 19.3 (SD 17.0) median 19 v12.8 (SD 25.4) 13; P = 0.31]. We analysed the total number of patients who showed an improvement in BADL score by BMI 20 kg/m2 vs < 20 kg/m2. 66/ 87 (77.1%) vs 14/28 (50.0%) showed an improvement (P = 0.017). A further subgroup analysis by cognitive status was carried out. Cognitively normal subjects showed no difference in number of patients improving by BMI stratification. Cognitively impaired patients with BMI of 20 kg/m2 were significantly more likely to show improvement than cognitively impaired patients with a BMI < 20 kg/m2 [55/75 (73.3%) v 10/22 (45.5%); P = 0.02]. Similar results were noted by MUST risk status. A Cox regression analysis (Fig. 2) correcting for age and CCI index looking at 4 groups of patients, showed a similar trajectory of improvement in cognitively intact patients regardless of nutrition state. However, in cognitively impaired patients a MUST score 2 was associated with worse outcome and much slower improvement in BADL than patients with a MUST < 2. 4. Discussion Our study has shown that a BMI < 20 kg/m2 and a MUST 2 are associated with poor rehabilitation outcomes in patients with cognitive impairment. Patients with cognitive impairment and a BMI < 20 kg/m2 show less improvement as measured by their
Table 1 Factors associated with an improvement in Barthel Score with rehabilitation. Parameter
Barthel Improvement Total 80
No Barthel Improvement Total 35
Mean
(SD)
Median
Mean
(SD)
Median
Age Barthel Admission Barthel Discharge BMI Charlson Comorbidity Score MUST score MMSE CLOX Hospital Anxiety Score Hospital Depression Score Length of stay
84.7 45.4 70.9 24.2 5.95 0.45 20.7 6.3 3.9 4.1 32.7
(6.85) (19.9) (18.6) (5.89) (1.46) (0.84) (5.39) (4.0) (3.3) (3.4) (19.9)
85.0 45.0 75 22.0 6.0 0.0 20.0 6.0 3.0 3.0 28.0
84.9 40.4 34.3 20.9 6.17 1.11 17.7 3.9 3.8 4.1 44.3
(4.70) (20.9) (24.5) (4.70) (1.71) (1.25) (7.33) (3.85) (3.8) (4.5) (41.4)
85.0 40.0 22.5 20.0 6.0 1.0 18.0 3.0 2.0 3.0 45.0
P
0.9 0.24 0.000 0.003 0.49 0.001 0.018 0.004 0.65 0.42 0.006
BMI: body mass index; MUST; Malnutrition Universal Screening Tool; MMSE: Mini-Mental State Examination.
Please cite this article in press as: Vassallo M, et al. Nutritional risk, body mass index and rehabilitation outcome in cognitively impaired vs. cognitively normal patients. Eur Geriatr Med (2016), http://dx.doi.org/10.1016/j.eurger.2016.01.010
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aerobic capacity, muscle strength and endurance, by improving aerobic conditioning and/or strength [27]. In addition, an improved meal environment in nursing homes has been shown to markedly improve the psychosocial and nutrition status of residents thus demonstrating that benefits can be obtained from a more proactive approach to nutrition in dementia [28]. This study therefore raises the question whether a more active approach to nutrition improvement and exercise in this group of patients will help improve outcomes [29,30]. This is an area that needs further exploring. Ethical statement Ethical approval was obtained from the Dorset Research and Ethics Committee, and informed consent was obtained from all participants. Participants with severe cognitive impairment who could not give informed consent were included after next of kin gave assent on behalf of the patient. Fig. 2. Improvement in Barthel Score by Cognitive State and Malnutrition Universal Screening Tool (MUST) risk status. P = 0.04. Group 1: cognition normal-MUST < 2 (13 patients). Group 2: cognition normal-MUST (5 patients). Group 3: cognition impaired-MUST < 2 (75 patients). Group 4: cognition impaired-MUST 2 (22 patients).
Disclosure of interest The authors declare that they have no competing interest. Acknowledgments
change in BADL score compared to cognitively intact patients with a BMI 20 kg/m2. In the cognitively impaired group of patients, BMI and MUST were the most important determinants of improvement and less patients with a low BMI or a MUST 2, improved with rehabilitation. To our knowledge, this is a new finding and offers a potentially reversible risk factor that may impact rehabilitation in patients with cognitive impairment. There are limitations to this study. The number of patients recruited was small and this may have influenced the results such as the lack of effect of anxiety or depression on rehabilitation. This effect of malnutrition was also not apparent in the cognitively intact group. It is possible that this was due to the small size of this group. In addition, we only measured nutritional status on admission, so another possible reason for the similar improvement in the cognitively intact group was that it was easier to address issues of malnutrition in this group than it was in the cognitively impaired. These findings are not surprising in view of the increasingly recognised link between cognition, nutrition, sarcopenia and physical performance. It is likely that malnutrition and cognitive decline work together in leading to the physical deterioration of patients reflected in poor rehabilitation outcomes we observed [26]. A BMI below 25 kg/m2 has been identified as a prognostic indicator for poor rehabilitation outcomes in other studies. Our study confirms that a low BMI has an adverse prognosis, however, the cut-off in our study was 20 kg/m2. This may be explained by our smaller sample size or a different patient population, particularly the fact that this patient cohort consisted of predominantly cognitively impaired patients. The Cox regression analysis showed that cognitively intact patients had a rapid trajectory of improvement in BADL score with the improvement having occurred by 30 days regardless of nutritional status. Conversely, cognitively impaired patients had a slower rate of improvement. Within this group, patients with a MUST 2 showed an even slower rate of improvement. Although improvement was slower, it was improvement nonetheless and here is no suggestion that this group of patients are not given the opportunity for rehabilitation but rather provision made to allow more time for rehabilitation. Regular exercise is the only strategy found to consistently prevent frailty and improve sarcopenia and physical function in older adults. Physical exercises increase
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Please cite this article in press as: Vassallo M, et al. Nutritional risk, body mass index and rehabilitation outcome in cognitively impaired vs. cognitively normal patients. Eur Geriatr Med (2016), http://dx.doi.org/10.1016/j.eurger.2016.01.010