危重患儿营养评估及营养风险筛查工具的临床应用

目的调查住院危重患儿的营养状况，探讨营养风险筛查工具在危重患儿营养风险评估中的价值。方法收集2017年11月至2018年4月入住儿童重症监护病房的211例危重患儿的临床资料，对患儿入院、出院时的营养状况进行评估，运用STRONGkids和PYMS两种营养风险筛查工具进行营养风险筛查。结果 211例患儿中，入院时营养不良检出68例（32.2%），其中中、重度营养不良各检出34例。通过STRONGkids和PYMS分别筛查出154例（73.0%）、165例（78.2%）存在中度或高度营养风险。以年龄别体重Z评分法为金标准，对两种营养风险筛查工具的效能进行评价，显示STRONGkids的ROC曲线下面积为0.822，PYMS为0.759，两者用于筛查营养不良均有统计学意义（P < 0.05），但两者临床效能比较差异无统计学意义（P > 0.05）。STRONGkids和PYMS筛查营养不良的最佳界值点均为3分，其灵敏度分别为92.1%、76.2%。入院时中、高营养风险患儿临床预后较低营养风险患儿差（分别P=0.014、0.001）。入院时重度营养不良患儿的预后较营养正常患儿差（P=0.0009）。结论危重患儿营养不良及营养风险检出率较高；患儿营养状态和营养风险与预后相关。STRONGkids和PYMS对危重患儿营养风险筛查均有临床应用价值，临床效能类似，但STRONGkids灵敏度更高。

Nutritional assessment and clinical application of nutritional risk screening tools in critically ill children

Objective To investigate the nutritional status of critically ill hospitalized children and to explore the value of nutritional risk screening tools in the nutritional risk assessment. Methods The clinical data of 211 critically ill children who were admitted to the pediatric intensive care unit from November 2017 to April 2018 were collected to evaluate their nutritional status on admission and at discharge. Two nutritional risk screening tools, STRONGkids and PYMS, were used for nutritional risk screening in the 211 children. Results Among the 211 patients, 68 (32.2%) were found to have malnutrition on admission, with 34 cases each of moderate and severe malnutrition. Moderate or high nutritional risk was found in 154 cases (73.0%) with STRONGkids and 165 cases (78.2%) with PYMS. Using weight-for-age Z-score as the gold standard to evaluate the efficacy of the two nutritional risk screening tools, the areas under the receiver operating characteristic curves of STRONGkids and PYMS were 0.822 and 0.759 respectively. Both tools had a significant clinical value in screening for malnutrition (P < 0.05), but there was no significant difference in clinical efficacy between them (P > 0.05). With the optimal cut-off value of 3 points, the sensitivities of STRONGkids and PYMS for screening of malnutrition were 92.1% and 76.2% respectively. The children with moderate or high nutritional risk on admission had a significantly poorer prognosis than those with low nutritional risk (P=0.014 and 0.001 respectively). The children with severe malnutrition had a significantly poorer prognosis than those with normal nutrition (P=0.0009). Conclusions The detection rates of malnutrition and nutritional risk are high in critically ill children. Malnutrition/high nutritional risk is related to a poor prognosis. Both STRONGkids and PYMS have a clinical value for nutritional risk screening in critically ill children, and they have similar clinical efficacy; however, STRONGkids is more sensitive.