Relationship between nutritional assessment and nutritional risk screening in hospitalized children with cerebral palsy: a single-center prospective study

Abstract

Cerebral palsy (CP) strongly affects the growth and development of children and is accompanied by a high risk of malnutrition. This study aims to characterize the nutritional status of hospitalized children with CP, evaluate the efficacy of four nutritional risk screening tools, analyze influencing factors of malnutrition. In our study, 64.8% of all 91 patients were malnourished. Nutritional status was associated with the gross motor function classification system (GMFCS) grade, the manual ability classification system (MACS) grade, caregiver concern, and age (P < 0.05). Compared with Z score, the sensitivity and consistency of the four malnutrition risk screening tools were lower. Multivariate logistic regression analysis revealed that older age, lower albumin (ALB) concentration, and MACS grade II were independent influencing factors for malnutrition. The prediction model with 4 variables, including age, albumin, triglyceride and MACS grade, was included, the AUC (95% CI) was 0.88 (0.81-0.95), and the P value of the H-L goodness-of-fit test was 0.588, which has practical value. We indicate that the rate of malnutrition in hospitalized children with CP remains high and still requires extensive attention from society, especially in clinical nutrition.

Keywords: Cerebral palsy; Children; Effectiveness; Malnutrition; Nutritional assessment; Nutritional risk screening.

Fig. 1

Flowchart of the study patients.

Fig. 2

Distribution of malnutrition (risk) screened by the 5 tools.The WHZ, WAZ, HAZ and BAZ were calculated. For subjects with multiple Z scores, the lowest score was selected for the final outcome assessment. They were classified as normal, overweight or obese, moderately undernourished, and severely undernourished according to the Z-score results. While the other 4 tools classify the severity of the malnutrition risk as normal, moderate, or severe. Abbreviations SGNA, Subjective Global Nutrition Assessment; STRONGkids, Screening Tool Risk on Nutritional Status and Growth; STAMP, Screening Tool for the Assessment of Malnutrition in Pediatrics; PYMS, Paediatric Yorkhill Malnutrition Score.

Fig. 3

Performance evaluation of training set of malnutrition prediction model for children with CP. A: ROC curve of the training set of malnutrition prediction model for hospitalized children with CP. B: Nomogram of malnutrition prediction model for hospitalized children with CP. C: Calibration curve of training set of malnutrition prediction model for hospitalized children with CP - original; D: Calibration curve of training set of malnutrition prediction model for hospitalized children with CP - optimization. E: DCA curve of malnutrition prediction model for hospitalized children with CP - original; F: DCA curve of malnutrition prediction model for hospitalized children with CP - Optimization. Abbreviations AUC, area under the curve; CI, confidence interval; CP, cerebral palsy; DCA, decision curve analysis.