[Fetal malnutrition assessment program]

Zhongguo Dang Dai Er Ke Za Zhi. 2020 Dec;22(12):1273-1278. doi: 10.7499/j.issn.1008-8830.2007122.
[Article in Chinese]

Abstract

Objective: To study the application of ponderal index (PI), body mass index (BMI), mid-arm circumference/head circumference (MAC/HC), and Clinical Assessment of Nutritional Status (CANS) score in assessing the nutritional status of neonates at birth, and to find a simple and reliable scheme for the assessment of fetal nutritional status.

Methods: PI, BMI, MAC/HC, and CANS were used to assess the nutritional status of full-term infants and preterm infants shortly after birth. The assessment results of these methods were analyzed.

Results: Among the 678 full-term infants, 61, 102, 47, and 131 were diagnosed with malnutrition by PI, BMI, MAC/HC, and CANS respectively. Among the 140 preterm infants, 30, 87, 9, and 112 were diagnosed with malnutrition by PI, BMI, MAC/HC, and CANS respectively. The combination of BMI and CANS had a detection rate of 99.3% in full-term infants and 100% in preterm infants. Compared with the single method, the combination significantly improved the detection rate of malnutrition (P < 0.05), while there was no significant difference between the combination of BMI+CANS and the combination of PI+BMI+CANS (P > 0.05).

Conclusions: The combination of BMI+CANS can reduce the rate of missed diagnosis of fetal malnutrition. It is therefore a simple and reliable method for the assessment of fetal malnutrition.

目的: 比较重量指数(PI)、体重指数(BMI)、中段上臂围/头围(MAC/HC)及临床营养评估法(CANS)在新生儿出生时营养状况评估中的应用,以寻求一种简便而可靠的评估胎儿营养状况的方案。

结果: 在678名足月儿中,PI、BMI、MAC/HC及CANS法分别诊断61例、102例、47例、131例营养不良。在140名早产儿中,PI、BMI、MAC/HC及CANS法分别诊断30例、87例、9例、112例营养不良。BMI+CANS组合检出比例在足月儿和早产儿中分别为99.3%、100%,与1种方法相比,能够显著提高营养不良患者的检出率(P < 0.05),而与PI+BMI+CANS 3种方法组合相比,差异无统计学意义(P > 0.05)。

结论: BMI+CANS组合能减少胎儿营养不良的漏诊,是评估胎儿营养不良简便而可靠的方法。

MeSH terms

  • Body Mass Index
  • Fetal Nutrition Disorders / diagnosis*
  • Humans
  • Infant, Newborn
  • Infant, Premature
  • Nutrition Assessment*
  • Nutritional Status

Grants and funding

比尔盖茨·梅琳达基金子课题(2F022016015)