Keywords
Recovery phase
Delphi method
Malnutrition
Risk assessment
Scale
Submitted : 2026-05-11
Accepted : 2026-05-26
Published : 2026-06-10
Abstract
Objective: To develop a risk warning factor assessment scale for malnutrition in patients during the recovery phase of stroke, providing a basis for evaluating malnutrition risk in this population. Methods: Literature review and group discussions were initially used to screen potential risk factors for malnutrition in stroke recovery patients. The modified Delphi method was then employed to finalize the risk factor assessment scale. From 1st April 2022 to 1st June 2022, two rounds of expert consultations were conducted via WeChat, face-to-face interviews, and email. Data from the experts’ ratings and modification suggestions for each item were recorded using Excel 2013, and statistical analysis was performed using SPSS 26.0 to determine the final risk warning factor assessment scale. Results: Two rounds of expert consultations were completed, with response rates (active coefficients) of 96% and 100%, respectively. The judgment basis (Ca) for the two rounds was 0.926 and 0.933, familiarity (Cs) scores were 0.800 and 0.808, and authority coefficients (Cr) were 0.863 and 0.871. The Kendall’s W values for importance in the two rounds were 0.192 and 0.154 (both P < 0.001), while the Kendall’s W values for correlation were 0.071 and 0.061 (both P < 0.05), indicating consistency in the experts’ evaluations of the indicators. The item-level content validity index (I-CVI) ranged from 0.875 to 1.000, and the scale-level content validity index (S-CVI) was 0.977, demonstrating good content validity of the assessment scale. The final risk factor assessment scale consisted of 38 items across three dimensions. Conclusion: The developed malnutrition risk assessment scale for stroke recovery patients exhibits good scientific rigor and practicality, providing a reference for identifying malnutrition risks in this population.
References
Wang Y, Xiang L, Luo Y, et al., 2022, Evidence Summary on Nutrition Management for Post-stroke Dysphagia. American Journal of Translational Research, 14(11): 8252–8262.
Shestopalov AE, Yakovleva AV, Yadgarov MY, et al., 2024, Prevalence and Impact of Malnutrition Risk on Outcomes in Critically Ill Patients with Traumatic Brain Injury and Stroke: A Retrospective Cohort Study Using Electronic Health Records. Nutrients, 16(15): 2396.
Liu P, Tian H, Ji T, et al., 2023, Predictive Value of Malnutrition, Identified via Different Nutritional Screening or Assessment Tools, for Functional Outcomes in Patients with Stroke: A Systematic Review and Meta-Analysis. Nutrients, 15(14): 3280.
Hao R, Qi X, Xia X, et al., 2022, Malnutrition on Admission Increases the in-hospital Mortality and Length of Stay in Elder Adults with Acute Ischemic Stroke. Journal of Clinical Laboratory Analysis, 36(1): e24132.
Di Vincenzo O, Luisi MLE, Alicante P, et al., 2023, The Assessment of the Risk of Malnutrition (Undernutrition) in Stroke Patients. Nutrients, 15(3): 683.
Yuan CX, Zhang YN, Chen XY, et al., 2022, Association between Malnutrition Risk and Hemorrhagic Transformation in Patients with Acute Ischemic Stroke. Frontiers in Nutrition, 2022(9): 993407.
Nishioka S, Omagari K, Nishioka E, et al., 2020, Concurrent and Predictive Validity of the Mini Nutritional Assessment Short-Form and the Geriatric Nutritional Risk Index in Older Stroke Rehabilitation Patients. Journal of Human Nutrition and Dietetics: The Official Journal of the British Dietetic Association, 33(1): 12–22.
Liu W, Jiang N, Li Y, et al., 2025, Current Status and Factors Influencing Nutrition Literacy in Stroke Patients: A Cross-Sectional Study. Journal of Clinical Nursing, 34(11): 4769–4778.
Chen Y, Yang H, Lan M, et al., 2023, The Controlling Nutritional Status Score and Risk Factors Associated with Malnutrition in Patients with Acute Ischemic Stroke. Frontiers in Neurology, 2023(14): 1067706.
Xie Y, Liu Q, Xue H, et al., 2023, Validation of a Novel Nutrition Risk Screening Tool in Stroke Patients. Asia Pacific Journal of Clinical Nutrition, 32(1): 19–25.
Li Y, Luo G, Yi X, Wang X, et al., 2025, Postcompetency Index System for Assessing Pain Resource Nurses’ Competence: A Delphi Study. Pain Management Nursing: Official Journal of the American Society of Pain Management Nurses, 26(3): e278–e286.
Jiang N, Liu WB, Zon, Y, et al., 2024, Construction of an Index System of Core Competence Assessment for Sleep Medicine Nurse Specialists in China: A Delphi Study. BMC Nursing, 23(1): 689.
Cai W, Yao Y, Lei W, et al., 2025, Construction on Training Course and Training Quality Evaluation Index System of Chronic Disease Medication Therapy Management Service (MTMs) in China: A Delphi Study. Plos One, 20(1): e0318446.
Mancin S, Sguanci M, Andreoli D, et al., 2024, Nutritional Assessment in Acute Stroke Patients: A Systematic Review of Guidelines and Systematic Reviews. International Journal of Nursing Studies, 2024(158): 104859.
Wei Y, An Y, Cao Q, et al., 2025, Developing a Professional Competency Framework for General Practitioners in Tertiary Hospitals in China: A Modified Delphi Study. BMJ Open, 15(3): e082736.
Ho L, Kwong MH, Li ASC, et al., 2025, Contextualising Implementation Interventions for Promoting Outpatient Integrative Chinese-Western Oncology Service Delivery and Utilisation in Hong Kong: A Delphi Study. BMC Complementary Medicine and Therapies, 25(1): 118.
Zhou A, Li Z, Wang T, et al., 2024, Development of the Competency Evaluation Scale for Clinical Nutritionists in China: A Delphi Study. Nutrients, 16(16): 2593.
Xiao H, Lu Y, Huang F, et al., 2024, Construction of the Medical Virtual Teaching and Research Office Evaluation System in China Based on the Context, Input, Process, Product Model: A Delphi Study. BMC Medical Education, 24(1): 1322.
Labeit, B, Michou, E, Hamdy, S, et al., 2023, The Assessment of Dysphagia after Stroke: State of the Art and Future Directions. The Lancet. Neurology, 22(9): 858–870.
Huppertz VAL, Pilz W, Pilz Da Cunha G, et al., 2022, Malnutrition Risk and Oropharyngeal Dysphagia in the Chronic Post-stroke Phase. Frontiers in Neurology, 2022(13): 939735.
Wang Y, Zhang G, Shen Y, et al., 2024, Relationship between Prognostic Nutritional Index and Post-stroke Cognitive Impairment. Nutritional Neuroscience, 27(11): 1330–1340.
Solomon OM, Gu Y, Wei Y, 2025, Risk Factors for Enteral Nutrition Feeding Intolerance in Stroke Patients: A Scoping Review. Nursing in Critical Care, 30(3): e13183.
Yuan J, Cheng Y, Han X, et al., 2024, Association between C-reactive protein/albumin Ratio and All-cause Mortality in Patients with Stroke: Evidence from NHANES Cohort Study. Nutrition, Metabolism, and Cardiovascular Diseases: NMCD, 34(10): 2305–2314.
Shi M, Mao X, Wu X, et al., 2024, Serum Prealbumin Levels and Risks of Adverse Clinical Outcomes After Ischemic Stroke. Clinical epidemiology, 2024(16): 707–716.
Alvarado-Luis G, Mimiaga-Hernández C, 2025, Malnutrition Risk and Associated Factors in Hospitalized Older Adult Patients with Neurological Diseases: A Retrospective Cohort Study. Nutritional neuroscience, 28(2): 209–218.
Chen X, Li D, Liu Y, et al., 2022, Nutritional Risk Screening 2002 Scale and Subsequent Risk of Stroke-associated Infection in Ischemic Stroke: The REMISE Study. Frontiers in nutrition, 2022(9): 895803.