Saw Shier Nee, Lim Mei Cee, Liew Chuan Nyen, Ahmad Kamar Azanna, Sulaiman Sofiah, Saaid Rahmah, Loo Chu Kiong
Department of Artificial Intelligence, Faculty of Computer Science and Information Technology, Universiti Malaya, Kuala Lumpur, Malaysia.
Department of Paediatrics, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia.
Front Surg. 2023 Apr 11;10:1123948. doi: 10.3389/fsurg.2023.1123948. eCollection 2023.
To construct a national fetal growth chart using retrospective data and compared its diagnostic accuracy in predicting SGA at birth with existing international growth charts.
This is a retrospective study where datasets from May 2011 to Apr 2020 were extracted to construct the fetal growth chart using the Lambda-Mu-Sigma method. SGA is defined as birth weight <10th centile. The local growth chart's diagnostic accuracy in detecting SGA at birth was evaluated using datasets from May 2020 to Apr 2021 and was compared with the WHO, Hadlock, and INTERGROWTH-21st charts. Balanced accuracy, sensitivity, and specificity were reported.
A total of 68,897 scans were collected and five biometric growth charts were constructed. Our national growth chart achieved an accuracy of 69% and a sensitivity of 42% in identifying SGA at birth. The WHO chart showed similar diagnostic performance as our national growth chart, followed by the Hadlock (67% accuracy and 38% sensitivity) and INTERGROWTH-21st (57% accuracy and 19% sensitivity). The specificities for all charts were 95-96%. All growth charts showed higher accuracy in the third trimester, with an improvement of 8-16%, as compared to that in the second trimester.
Using the Hadlock and INTERGROWTH-21st chart in the Malaysian population may results in misdiagnose of SGA. Our population local chart has slightly higher accuracy in predicting preterm SGA in the second trimester which can enable earlier intervention for babies who are detected as SGA. All growth charts' diagnostic accuracies were poor in the second trimester, suggesting the need of improvising alternative techniques for early detection of SGA to improve fetus outcomes.
利用回顾性数据构建全国胎儿生长曲线，并将其预测出生时小于胎龄儿（SGA）的诊断准确性与现有的国际生长曲线进行比较。
这是一项回顾性研究，提取2011年5月至2020年4月的数据集，采用Lambda-Mu-Sigma方法构建胎儿生长曲线。SGA定义为出生体重低于第10百分位数。利用2020年5月至2021年4月的数据集评估本地生长曲线在检测出生时SGA的诊断准确性，并与世界卫生组织（WHO）、哈德洛克（Hadlock）和INTERGROWTH-21st生长曲线进行比较。报告了平衡准确性、敏感性和特异性。
共收集了68897次扫描，并构建了五条生物测量生长曲线。我们的全国生长曲线在识别出生时的SGA方面，准确率达到69%，敏感性为42%。WHO生长曲线显示出与我们的全国生长曲线相似的诊断性能，其次是哈德洛克生长曲线（准确率67%，敏感性38%）和INTERGROWTH-21st生长曲线（准确率57%，敏感性19%）。所有生长曲线的特异性均为95%-96%。与孕中期相比，所有生长曲线在孕晚期的准确性更高，提高了8%-16%。
在马来西亚人群中使用哈德洛克和INTERGROWTH-21st生长曲线可能会导致SGA的误诊。我们的人群本地生长曲线在孕中期预测早产SGA方面的准确性略高，这可以使被检测为SGA的婴儿得到更早的干预。所有生长曲线在孕中期的诊断准确性都很差，这表明需要改进替代技术以早期检测SGA，从而改善胎儿结局。
