Rallis D, Karagianni P, Papaharalambous E, Lithoxopoulou M, Chatziioannidis I, Soubasi-Griva V
Second Neonatal Intensive Care Unit and Neonatology Department of Aristotle University of Thessaloniki, School of Medicine, Thessaloniki, Greece.
Hippokratia. 2020 Jul-Sep;24(3):133-137.
Applying customized centiles may improve the accuracy of detecting small for gestational age (SGA) infants; however, the evidence is inconclusive whether adjusted centiles are more sensitive in identifying infants at increased risk of morbidity. We aimed to examine the validity of customized centiles in a Greek cohort and evaluate their performance compared to population-based centiles in predicting infants at risk of increased morbidity.
We prospectively recorded the neonatal and maternal characteristics of singleton, low-risk, term infants over a year. Infants were defined as SGA if their birth weight was under the tenth centile, classified both by population-based centiles and customized centiles, adjusted for maternal and innate factors. We performed a comparative analysis utilizing linear regression analysis and calculating the receiver operating characteristics (ROC) curves.
Overall 657 infants were identified. Population-based centiles detected 42 (6 %) SGA infants, while customized centiles 80 (12 %). Perinatal morbidity was associated with an odds ratio of 1.02 with customized centiles [95 % confidence interval (CI): 1.01-1.04] and with an odds ratio of 1.02 with population-based centiles (95 % CI: 1.02-1.02). In predicting perinatal morbidity, no significant difference was detected between customized centiles [area under the ROC curve 0.773 (95 % CI: 0.699-0.847)] and population-based centiles [area under the ROC curve 0.737 (95 % CI: 0.662-0.813)] (p =0.272).
Customized centiles provided increased accuracy in comparison to the population-based centiles in detecting SGA term infants. However, customized centiles had no better impact on predicting a poor perinatal outcome. HIPPOKRATIA 2020, 24(3): 133-137.
应用定制百分位数可能会提高检测小于胎龄儿（SGA）的准确性；然而，关于调整后的百分位数在识别发病风险增加的婴儿方面是否更敏感，证据尚无定论。我们旨在检验希腊队列中定制百分位数的有效性，并评估其与基于人群的百分位数相比在预测发病风险增加的婴儿方面的表现。
我们前瞻性地记录了一年中单胎、低风险、足月婴儿的新生儿和母亲特征。如果婴儿的出生体重低于第十百分位数，则将其定义为SGA，分别根据基于人群的百分位数和针对母亲和先天因素进行调整的定制百分位数进行分类。我们利用线性回归分析并计算受试者工作特征（ROC）曲线进行了比较分析。
共识别出657名婴儿。基于人群的百分位数检测出42名（6%）SGA婴儿，而定制百分位数检测出80名（12%）。围产期发病率与定制百分位数的比值比为1.02 [95%置信区间（CI）：1.01 - 1.04]，与基于人群的百分位数的比值比为1.02（95% CI：1.02 - 1.02）。在预测围产期发病率方面，定制百分位数[ROC曲线下面积0.773（95% CI：0.699 - 0.847）]与基于人群的百分位数[ROC曲线下面积0.737（95% CI：0.662 - 0.813）]之间未检测到显著差异（p = 0.272）。
与基于人群的百分位数相比，定制百分位数在检测足月SGA婴儿方面提供了更高的准确性。然而，定制百分位数在预测不良围产期结局方面没有更好的影响。《希波克拉底》2020年，24(3): 133 - 137。
