Relationship between Nutritional Status, Food Consumption and Sarcopenia in Post-Stroke Rehabilitation: Preliminary Data

Mariacristina Siotto, Marco Germanotta, Alessandro Guerrini, Simona Pascali, Valeria Cipollini, Laura Cortellini, Elisabetta Ruco, Yeganeh Manon Khazrai, Laura De Gara, Irene Aprile, Mariacristina Siotto, Marco Germanotta, Alessandro Guerrini, Simona Pascali, Valeria Cipollini, Laura Cortellini, Elisabetta Ruco, Yeganeh Manon Khazrai, Laura De Gara, Irene Aprile

Abstract

After a stroke, patients can suffer from sarcopenia, which can affect recovery. This could be closely related to an impairment in nutritional status. In this preliminary analysis of a longitudinal prospective study, we screened 110 subjects admitted to our rehabilitation center after a stroke. We then enrolled 61 patients, who underwent a 6-week course of rehabilitation treatment. We identified a group of 18 sarcopenic patients (SG), according to the European Working Group on Sarcopenia in Older People 2 (EWGSOP2), by evaluating muscle strength with the handgrip test, and muscle mass with bioelectrical impedance analysis (BIA). With respect to the non-sarcopenic group (NSG), the SG at admission (T0) had worse muscle quality, according to the BIA-derived phase angle, and a lower score of MNA®-SF. In contrast to the NSG, the SG also exhibited lower values for both BMI and the Geriatric Nutritional Risk Index (GNRI) at T0 and T1. Moreover, 33% of the SG had a major risk of nutrition-related complications (GNRI at T0 < 92) and discarded on average more food during the six weeks of rehabilitation (about one-third of the average daily plate waste). Of note is the fact that the Barthel Index’s change from baseline indicated that the SG had a worse functional recovery than the NGS. These results suggest that an accurate diagnosis of sarcopenia, along with a proper evaluation of the nutritional status on admission to rehabilitation centers, appears strictly necessary to design individual, targeted physical and nutritional intervention for post-stroke patients, to improve their ability outcomes.

Keywords: Geriatric Nutritional Risk Index; bioelectrical impedance analysis; food consumption; functional recovery; malnutrition: nutrition; nutritional intake; plate waste; post-stroke; rehabilitation; sarcopenia.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
EWGSOP2 algorithm for case finding and diagnosis of sarcopenia at baseline in the sample group. Patients enrolled (n = 61) were assessed by handgrip test and the diagnosis in patients with probable sarcopenia (n = 32) was confirmed by muscle-quantity assessment using bioelectrical impedance analysis (BIA), identifying a Sarcopenic Group (SG) of 18 subjects and a Non-Sarcopenic Group (NSG) of 43 subjects.
Figure 2
Figure 2
Distribution of the change from baseline of the modified Barthel Index (ΔBI) after 6 weeks of rehabilitation in Non-Sarcopenic Group (NSG, n = 42) and Sarcopenic Group (SG, n = 16). Mean bars and 95% CI are reported. * Refers to the statistically significant difference (p value = 0.038).

References

    1. Kim J., Thayabaranathan T., Donnan G.A., Howard G., Howard V.J., Rothwell P.M., Feigin V., Norrving B., Owolabi M., Pandian J., et al. Global Stroke Statistics 2019. Int. J. Stroke. 2020;15:819–838. doi: 10.1177/1747493020909545.
    1. Go A.S., Mozaffarian D., Roger V.L., Benjamin E., Berry J.D., Blaha M.J., Dai S., Ford E.S., Fox C.S., Franco S., et al. Executive Summary: Heart Disease and Stroke Statistics—2014 Update. Circulation. 2014;129:399–410. doi: 10.1161/01.cir.0000442015.53336.12.
    1. Feigin V.L., Stark B.A., Johnson C.O., Roth G.A., Bisignano C., Abady G.G., Abbasifard M., Abbasi-Kangevari M., Abd-Allah F., Abedi V., et al. Global, regional, and national burden of stroke and its risk factors, 1990–2019: A systematic analysis for the Global Burden of Disease Study 2019. Lancet Neurol. 2021;20:795–820. doi: 10.1016/S1474-4422(21)00252-0.
    1. Cruz-Jentoft A.J., Sayer A.A. Sarcopenia. Lancet. 2019;393:2636–2646. doi: 10.1016/S0140-6736(19)31138-9.
    1. Li W., Yue T., Liu Y. New understanding of the pathogenesis and treatment of stroke-related sarcopenia. Biomed. Pharmacother. 2020;131:110721. doi: 10.1016/j.biopha.2020.110721.
    1. Scherbakov N., von Haehling S., Anker S.D., Dirnagl U., Doehner W. Stroke induced Sarcopenia: Muscle wasting and disability after stroke. Int. J. Cardiol. 2013;170:89–94. doi: 10.1016/j.ijcard.2013.10.031.
    1. Scherbakov N., Sandek A., Doehner W. Stroke-Related Sarcopenia: Specific Characteristics. J. Am. Med. Dir. Assoc. 2015;16:272–276. doi: 10.1016/j.jamda.2014.12.007.
    1. Matsushita T., Nishioka S., Taguchi S., Yamanouchi A. Sarcopenia as a predictor of activities of daily living capability in stroke patients undergoing rehabilitation. Geriatr. Gerontol. Int. 2019;19:1124–1128. doi: 10.1111/ggi.13780.
    1. Jang A., Bae C.H., Han S.J., Bae H. Association Between Length of Stay in the Intensive Care Unit and Sarcopenia Among Hemiplegic Stroke Patients. Ann. Rehabil. Med. 2021;45:49–56. doi: 10.5535/arm.20111.
    1. Park J.G., Lee K.W., Kim S.B., Lee J.H., Kim Y.H. Effect of Decreased Skeletal Muscle Index and Hand Grip Strength on Functional Recovery in Subacute Ambulatory Stroke Patients. Ann. Rehabil. Med. 2019;43:535–543. doi: 10.5535/arm.2019.43.5.535.
    1. Park S., Ham J.-O., Lee B.K. A positive association between stroke risk and sarcopenia in men aged ≥ 50 years, but not women: Results from the Korean National Health and Nutrition Examination Survey 2008–2010. J. Nutr. Health Aging. 2014;18:806–812. doi: 10.1007/s12603-014-0553-x.
    1. Ohyama K., Watanabe M., Nosaki Y., Hara T., Iwai K., Mokuno K. Correlation Between Skeletal Muscle Mass Deficit and Poor Functional Outcome in Patients with Acute Ischemic Stroke. J. Stroke Cerebrovasc. Dis. 2020;29:104623. doi: 10.1016/j.jstrokecerebrovasdis.2019.104623.
    1. Matsushita T., Nishioka S., Taguchi S., Yamanouchi A., Okazaki Y., Oishi K., Nakashima R., Fujii T., Tokunaga Y., Onizuka S. Effect of Improvement in Sarcopenia on Functional and Discharge Outcomes in Stroke Rehabilitation Patients. Nutrients. 2021;13:2192. doi: 10.3390/nu13072192.
    1. Lee Y.-C., Chiu E.-C. Nutritional status as a predictor of comprehensive activities of daily living function and quality of life in patients with stroke. NeuroRehabilitation. 2021;48:337–343. doi: 10.3233/NRE-201540.
    1. Nishioka S., Wakabayashi H., Nishioka E., Yoshida T., Mori N., Watanabe R. Nutritional Improvement Correlates with Recovery of Activities of Daily Living among Malnourished Elderly Stroke Patients in the Convalescent Stage: A Cross-Sectional Study. J. Acad. Nutr. Diet. 2016;116:837–843. doi: 10.1016/j.jand.2015.09.014.
    1. Shimazu S., Yoshimura Y., Kudo M., Nagano F., Bise T., Shiraishi A., Sunahara T. Frequent and personalized nutritional support leads to improved nutritional status, activities of daily living, and dysphagia after stroke. Nutrition. 2020;83:111091. doi: 10.1016/j.nut.2020.111091.
    1. Zielińska-Nowak E., Cichon N., Saluk-Bijak J., Bijak M., Miller E. Nutritional Supplements and Neuroprotective Diets and Their Potential Clinical Significance in Post-Stroke Rehabilitation. Nutrients. 2021;13:2704. doi: 10.3390/nu13082704.
    1. Lieber A.C., Hong E., Putrino D., Nistal D.A., Pan J.S., Kellner C.P. Nutrition, Energy Expenditure, Dysphagia, and Self-Efficacy in Stroke Rehabilitation: A Review of the Literature. Brain Sci. 2018;8:218. doi: 10.3390/brainsci8120218.
    1. Shiraishi A., Yoshimura Y., Wakabayashi H., Tsuji Y. Prevalence of stroke-related sarcopenia and its association with poor oral status in post-acute stroke patients: Implications for oral sarcopenia. Clin. Nutr. 2018;37:204–207. doi: 10.1016/j.clnu.2016.12.002.
    1. Yoshimura Y. Recent Advances in Clinical Nutrition in Stroke Rehabilitation. Nutrients. 2022;14:1130. doi: 10.3390/nu14061130.
    1. Irisawa H., Mizushima T. Correlation of Body Composition and Nutritional Status with Functional Recovery in Stroke Rehabilitation Patients. Nutrients. 2020;12:1923. doi: 10.3390/nu12071923.
    1. Irisawa H., Mizushima T. Assessment of changes in muscle mass, strength, and quality and activities of daily living in elderly stroke patients. Int. J. Rehabilitation Res. 2022;45:161–167. doi: 10.1097/MRR.0000000000000523.
    1. Lathuilière A., Mareschal J., Graf C.E. How to Prevent Loss of Muscle Mass and Strength among Older People in Neuro-Rehabilitation? Nutrients. 2019;11:881. doi: 10.3390/nu11040881.
    1. Honaga K., Mori N., Akimoto T., Tsujikawa M., Kawakami M., Okamoto T., Sakata Y., Hamano H., Takeda Y., Kondo K. Investigation of the Effect of Nutritional Supplementation with Whey Protein and Vitamin D on Muscle Mass and Muscle Quality in Subacute Post-Stroke Rehabilitation Patients: A Randomized, Single-Blinded, Placebo-Controlled Trial. Nutrients. 2022;14:685. doi: 10.3390/nu14030685.
    1. Park M.K., Lee S.J., Choi E., Lee S., Lee J. The Effect of Branched Chain Amino Acid Supplementation on Stroke-Related Sarcopenia. Front. Neurol. 2022;13:744945. doi: 10.3389/fneur.2022.744945.
    1. Aprile I., Cruciani A., Germanotta M., Gower V., Pecchioli C., Cattaneo D., Vannetti F., Padua L., Gramatica F. Upper Limb Robotics in Rehabilitation: An Approach to Select the Devices, Based on Rehabilitation Aims, and Their Evaluation in a Feasibility Study. Appl. Sci. 2019;9:3920. doi: 10.3390/app9183920.
    1. Aprile I., Germanotta M., Cruciani A., Loreti S., Pecchioli C., Cecchi F., Montesano A., Galeri S., Diverio M., Falsini C., et al. Upper Limb Robotic Rehabilitation After Stroke: A Multicenter, Randomized Clinical Trial. J. Neurol. Phys. Ther. 2020;44:3–14. doi: 10.1097/NPT.0000000000000295.
    1. Hudon C., Fortin M., Vanasse A. Cumulative Illness Rating Scale was a reliable and valid index in a family practice context. J. Clin. Epidemiol. 2005;58:603–608. doi: 10.1016/j.jclinepi.2004.10.017.
    1. Shah S., Vanclay F., Cooper B. Improving the sensitivity of the Barthel Index for stroke rehabilitation. J. Clin. Epidemiol. 1989;42:703–709. doi: 10.1016/0895-4356(89)90065-6.
    1. Cederholm T., Jensen G.L., Correia M.I.T.D., Gonzalez M.C., Fukushima R., Higashiguchi T., Baptista G., Barazzoni R., Blaauw R., Coats A.J., et al. GLIM criteria for the diagnosis of malnutrition—A consensus report from the global clinical nutrition community. J. Cachexia Sarcopenia Muscle. 2019;10:207–217. doi: 10.1002/jcsm.12383.
    1. Chumlea W.C., Roche A.F., Steinbaugh M.L. Estimating Stature from Knee Height for Persons 60 to 90 Years of Age. J. Am. Geriatr. Soc. 1985;33:116–120. doi: 10.1111/j.1532-5415.1985.tb02276.x.
    1. Cereda E., Pusani C., Limonta D., Vanotti A. The ability of the Geriatric Nutritional Risk Index to assess the nutritional status and predict the outcome of home-care resident elderly: A comparison with the Mini Nutritional Assessment. Br. J. Nutr. 2009;102:563–570. doi: 10.1017/S0007114509222677.
    1. Bouillanne O., Morineau G., Dupont C., Coulombel I., Vincent J.-P., Nicolis I., Benazeth S., Cynober L., Aussel C. Geriatric Nutritional Risk Index: A new index for evaluating at-risk elderly medical patients. Am. J. Clin. Nutr. 2005;82:777–783. doi: 10.1093/ajcn/82.4.777.
    1. Sherwin A.J., Nowson C.A., McPhee J., Alexander J.L., Wark J.D., Flicker L. Nutrient Intake at Meals in Residential Care Facilites for the Aged: Validated Visual Estimation of Plate Waste. Aust. J. Nutr. Diet. 1998;55:188–193.
    1. Dubois S. Accuracy of visual estimates of plate waste in the determination of food consumption. J. Am. Diet. Assoc. 1990;90:382–387. doi: 10.1016/S0002-8223(21)01531-5.
    1. Valero Díaz A., Caracuel García A. Evaluation of Factors Affecting Plate Waste of Inpatients in Different Healthcare Settings. Nutr. Hosp. 2013;28:419–427. doi: 10.3305/nh.2013.28.2.6262.
    1. SINU (Italian Society of Human Nutrition) Nutrients and Energy Reference Intake for Italian Population. SINU (Italian Society of Human Nutrition); Milano, Italy: 2014. 4th Revision.
    1. Cruz-Jentoft A.J., Bahat G., Bauer J., Boirie Y., Bruyère O., Cederholm T., Cooper C., Landi F., Rolland Y., Sayer A.A., et al. Sarcopenia: Revised European Consensus on Definition and Diagnosis. Age Ageing. 2019;48:16–31. doi: 10.1093/ageing/afy169.
    1. Reijnierse E.M., de Jong N., Trappenburg M.C., Blauw G.J., Butler-Browne G., Gapeyeva H., Hogrel J.-Y., McPhee J.S., Narici M.V., Sipilä S., et al. Assessment of maximal handgrip strength: How many attempts are needed? J. Cachex Sarcopenia Muscle. 2017;8:466–474. doi: 10.1002/jcsm.12181.
    1. Di Vincenzo O., Marra M., Di Gregorio A., Pasanisi F., Scalfi L. Bioelectrical impedance analysis (BIA) -derived phase angle in sarcopenia: A systematic review. Clin. Nutr. 2020;40:3052–3061. doi: 10.1016/j.clnu.2020.10.048.
    1. Su Y., Yuki M., Otsuki M. Prevalence of stroke-related sarcopenia: A systematic review and meta-analysis. J. Stroke Cerebrovasc. Dis. 2020;29:105092. doi: 10.1016/j.jstrokecerebrovasdis.2020.105092.
    1. Kyle U.G., Bosaeus I., De Lorenzo A.D., Deurenberg P., Elia M., Gomez J.M., Heitmann B.L., Kent-Smith L., Melchior J.-C., Pirlich M., et al. Bioelectrical impedance analysis? Part I: Review of principles and methods. Clin. Nutr. 2004;23:1226–1243. doi: 10.1016/j.clnu.2004.06.004.
    1. Fragala M.S., Kenny A.M., Kuchel G.A. Muscle Quality in Aging: A Multi-Dimensional Approach to Muscle Functioning with Applications for Treatment. Sports Med. 2015;45:641–658. doi: 10.1007/s40279-015-0305-z.
    1. Lim S.-K., Lim J.-Y. Phase angle as a predictor of functional outcomes in patients undergoing in-hospital rehabilitation after hip fracture surgery. Arch. Gerontol. Geriatr. 2020;89:104060. doi: 10.1016/j.archger.2020.104060.
    1. Bourgeois B., Fan B., Johannsen N., Gonzalez M.C., Ng B.K., Sommer M.J., Shepherd J., Heymsfield S.B. Improved strength prediction combining clinically available measures of skeletal muscle mass and quality. J. Cachex Sarcopenia Muscle. 2018;10:84–94. doi: 10.1002/jcsm.12353.
    1. Bise T., Yoshimura Y., Wakabayashi H., Nagano F., Kido Y., Shimazu S., Shiraishi A., Matsumoto A. Association between BIA-derived Phase Angle and Sarcopenia and Improvement in Activities of Daily Living and Dysphagia in Patients undergoing Post-Stroke Rehabilitation. J. Nutr. Health Aging. 2022;26:590–597. doi: 10.1007/s12603-022-1803-y.
    1. Abd-El-Gawad W.M., Abou-Hashem R.M., El Maraghy M.O., Amin G.E. The validity of Geriatric Nutrition Risk Index: Simple tool for prediction of nutritional-related complication of hospitalized elderly patients. Comparison with Mini Nutritional Assessment. Clin. Nutr. 2014;33:1108–1116. doi: 10.1016/j.clnu.2013.12.005.
    1. Kang M.K., Kim T.J., Kim Y., Nam K.-W., Jeong H.-Y., Kim S.K., Lee J.S., Ko S.-B., Yoon B.-W. Geriatric nutritional risk index predicts poor outcomes in patients with acute ischemic stroke—Automated undernutrition screen tool. PLoS ONE. 2020;15:e0228738. doi: 10.1371/journal.pone.0228738.
    1. Williams P., Walton K. Plate waste in hospitals and strategies for change. e-SPEN Eur. e-Journal Clin. Nutr. Metab. 2011;6:e235–e241. doi: 10.1016/j.eclnm.2011.09.006.
    1. Yoshimura Y., Wakabayashi H., Momosaki R., Nagano F., Bise T., Shimazu S., Shiraishi A. Stored Energy Increases Body Weight and Skeletal Muscle Mass in Older, Underweight Patients after Stroke. Nutrients. 2021;13:3274. doi: 10.3390/nu13093274.
    1. Aquilani R., Scocchi M., Iadarola P., Franciscone P., Verri M., Boschi F., Pasini E., Viglio S. Protein supplementation may enhance the spontaneous recovery of neurological alterations in patients with ischaemic stroke. Clin. Rehabil. 2008;22:1042–1050. doi: 10.1177/0269215508094244.
    1. Nguyen L., Do B., Vu D., Pham K., Vu M.-T., Nguyen H., Tran T., Le H., Nguyen T., Nguyen Q., et al. Physical Activity and Diet Quality Modify the Association between Comorbidity and Disability among Stroke Patients. Nutrients. 2021;13:1641. doi: 10.3390/nu13051641.

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