Salunkhe Avinash Hindurao, Pratinidhi Asha K, Salunkhe Jyoti A, Kakade Satish V, Mohite Vaishali R, Patange R P
Krishna Institute of Nursing Sciences, Karad, Maharashtra, India.
Department of Community Medicine, Krishna Institute of Medical Sciences, Deemed to be University, Karad, Maharashtra, India.
Indian J Community Med. 2019 Apr-Jun;44(2):97-101. doi: 10.4103/ijcm.IJCM_263_18.
Prediction of low birth weight (LBW) early during pregnancy may prevent LBW by appropriate interventions.
AIMS/OBJECTIVE: The aim of the study is to develop an antenatal risk scoring scale for prediction of LBW.
Routine and in-depth information on diet, occupation, and rest was collected from November 1, 2013, to November 13, 2015. A cohort of 1876 and subset of 380 pregnant women attending Krishna Hospital Karad, Maharashtra, India.
Multivariate analysis and relative risks (RRs) were found out by SPSS version 16 and tested on a separate set of 251 mothers.
The frequency of meals of <4, hard work <6 h of sleep and illiteracy, antenatal morbidity, <10 kg weight gain, <40 kg maternal weight, and anemia during the first trimester were the risk factors identified from subset and cohort, respectively. Based on their RRs, a new scoring system with a total score of 24 and cutoff "12" was identified by using receiver operating characteristics (ROC) curve analysis with 98.6% sensitivity and 41.1% specificity as tested on 251-independent individuals. The second cutoff of "15" score was identified based on the prevalence of LBW in babies of these 251 mothers.
The identification of low-, moderate-, and high-risk of LBW was possible at <12, between 12 and 15, and >15 scores, respectively, with good sensitivity and specificity.
孕期早期预测低出生体重（LBW）可通过适当干预措施预防低出生体重。
本研究旨在开发一种用于预测低出生体重的产前风险评分量表。
于2013年11月1日至2015年11月13日收集了关于饮食、职业和休息的常规及深入信息。研究队列包括1876名孕妇，其中380名孕妇的子集来自印度马哈拉施特拉邦卡拉德的克里希纳医院。
通过SPSS 16版进行多变量分析并计算相对风险（RRs），并在另外一组251名母亲中进行检验。
分别从子集和队列中确定了以下风险因素：进餐次数<4次、从事繁重工作、睡眠时间<6小时、文盲、产前发病、体重增加<10千克、孕早期母亲体重<40千克以及贫血。根据这些RRs，通过受试者工作特征（ROC）曲线分析确定了一个新的评分系统，总分为24分，临界值为“12”，在对251名独立个体进行测试时，灵敏度为98.6%，特异性为41.1%。根据这251名母亲所生孩子的低出生体重患病率确定了第二个临界值“15”分。
分别在得分<12分、12至十五分和>15分的情况下，可以识别低出生体重的低、中、高风险，且具有良好的灵敏度和特异性。
