Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Child Healthcare Department, Foshan Women and Children Hospital, Foshan, China.
Ann Nutr Metab. 2022;78(4):187-196. doi: 10.1159/000522320. Epub 2022 May 6.
Premature infants are exceptionally vulnerable to nutrition-related diseases, and the utilization of standardized feeding guidelines may reduce nutritional practice variation, which can promote growth. Nutritional risk screening is the first step for standardized nutrition advice. However, risk screening tools specific for following up preterm infants are scarce. Hence, our study aimed to develop and evaluate a standardized Nutritional Risk Screening Tool for Preterm Infants (NRSP subscale 1) from birth to corrected age four months old .
This study was a two-phase (the development phase and evaluation phase) study. Initially, we used the Delphi expert consultation method to create NRSP subscale 1. Then, a professional panel interviewed the participated preterm infants using the screening tool, measured anthropometric parameters, and conducted an intellectual development test on the interview day and remeasured anthropometric parameters 2 weeks or 1 month after the first interview. In the development phase, we cross-tabulated the responses to the screening tool with the classifications of z-scores of the body weight, length, or head circumference to identify significant predictors of underweight, stunting, or microcephaly. We then combined significant predictors to produce models for predicting underweight, stunting, or microcephaly by multivariate logistic regression analysis. In the evaluation phase, the area under the curve (AUC), sensitivity, specificity, and correlation coefficient by Spearman's correlation analysis (rs) between the risk classifications by NRSP subscale 1 and the classifications of the z-scores of the body weight, length, or head circumference were calculated to assess the validity of the screening tool. Intellectual development levels between high and low nutritional risk infants were statistically compared.
A total of 219 and 244 preterm infants were included to two phases, respectively. AUC was 0.936 (95% CI: 0.860-1.000, p < 0.001), sensitivity was 0.667, specificity was 0.941, rs = 0.407 (p < 0.001); AUC was 0.794 (95% CI: 0.638-0.951, p = 0.002), sensitivity was 0.500, specificity was 0.953, rs = 0.339 (p < 0.001); AUC was 0.831 (95% CI: 0.737-0.925, p = 0.001), sensitivity was 0.889, specificity was 0.643, rs = 0.215 (p = 0.001) in predicting underweight, stunting, and microcephaly on the interview day, respectively. AUC was 0.905 (95% CI: 0.826-0.984, p = 0.006), sensitivity was 0.500, specificity was 0.905, rs = 0.504 (p < 0.001); AUC was 0.738 (95% CI: 0.515-0.960, p = 0.034), sensitivity was 0.429, specificity was 0.848, rs = 0.382 (p < 0.001); AUC was 0.664 (95% CI: 0.472-0.856, p = 0.071), sensitivity was 0.455, specificity was 0.809, rs = 0.169 (p = 0.037) in predicting underweight, stunting, and microcephaly 2 weeks or 1 month after the first interview, respectively. Gross motor development quotients (DQs) (95.85 [32.87] vs. 86.29 [17.19], p = 0.022), fine motor DQs (115.77 [46.03] vs. 102.12 [20.27], p = 0.010), and verbal DQs (110.73 [35.27] vs. 100.63 [21.28], p = 0.042) were higher in low nutritional risk infants than high-risk ones.
NRSP subscale 1 was acceptable and reliable in predicting underweight, but the validity in predicting stunting or microcephaly was slightly mild. Further investigations are required to authenticate NRSP subscale 1's effectiveness.
早产儿极易受到与营养相关的疾病的影响,采用标准化的喂养指南可以减少营养实践的差异,从而促进生长。营养风险筛查是进行标准化营养建议的第一步。然而,针对早产儿的风险筛查工具却十分稀缺。因此,我们的研究旨在制定和评估一种标准化的用于早产儿(NRSP 子量表 1)的营养风险筛查工具,从出生到校正年龄四个月大。
本研究分为两个阶段(发展阶段和评估阶段)。首先,我们使用德尔菲专家咨询法创建 NRSP 子量表 1。然后,一个专业小组使用该筛查工具对参与的早产儿进行访谈,并在访谈当天测量人体测量参数,以及进行智力发展测试,在第一次访谈后两周或一个月重新测量人体测量参数。在发展阶段,我们将筛查工具的应答情况与体重、身长或头围的 z 分数的分类进行交叉制表,以确定体重不足、发育迟缓或小头畸形的显著预测因素。然后,我们通过多元逻辑回归分析将显著预测因素结合起来,以生成预测体重不足、发育迟缓或小头畸形的模型。在评估阶段,我们计算了 NRSP 子量表 1 的风险分类与体重、身长或头围的 z 分数分类之间的曲线下面积(AUC)、敏感性、特异性和 Spearman 相关系数(rs),以评估该筛查工具的有效性。统计比较了高营养风险和低营养风险婴儿的智力发展水平。
共有 219 名和 244 名早产儿分别纳入两个阶段。AUC 为 0.936(95%CI:0.860-1.000,p<0.001),敏感性为 0.667,特异性为 0.941,rs=0.407(p<0.001);AUC 为 0.794(95%CI:0.638-0.951,p=0.002),敏感性为 0.500,特异性为 0.953,rs=0.339(p<0.001);AUC 为 0.831(95%CI:0.737-0.925,p=0.001),敏感性为 0.889,特异性为 0.643,rs=0.215(p=0.001),分别用于预测访谈当天的体重不足、发育迟缓和小头畸形。AUC 为 0.905(95%CI:0.826-0.984,p=0.006),敏感性为 0.500,特异性为 0.905,rs=0.504(p<0.001);AUC 为 0.738(95%CI:0.515-0.960,p=0.034),敏感性为 0.429,特异性为 0.848,rs=0.382(p<0.001);AUC 为 0.664(95%CI:0.472-0.856,p=0.071),敏感性为 0.455,特异性为 0.809,rs=0.169(p=0.037),分别用于预测第一次访谈后两周或一个月的体重不足、发育迟缓和小头畸形。大运动发育商(DQ)(95.85[32.87] vs. 86.29[17.19],p=0.022)、精细运动 DQ(115.77[46.03] vs. 102.12[20.27],p=0.010)和言语 DQ(110.73[35.27] vs. 100.63[21.28],p=0.042)在低营养风险婴儿中较高。
NRSP 子量表 1 在预测体重不足方面具有可接受性和可靠性,但在预测发育迟缓或小头畸形方面的有效性略显温和。需要进一步的研究来验证 NRSP 子量表 1 的有效性。