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Objectives <p>Ultrasound soft markers (USMs) are associated with increased risk of fetal chromosomal abnormalities but lack standardized risk assessment methods, often leading to unnecessary amniocentesis procedures. We aimed to develop a practical nomogram tool to quantify this risk and help clinicians make more objective decisions about invasive testing, particularly in resource-limited settings.</p> Results <p>We retrospectively analyzed 565 pregnancies with USMs who underwent amniocentesis between 2016 and 2024. Our nomogram integrated six readily available clinical factors: maternal age, thickened nuchal translucency, adverse pregnancy history, structural malformations, fetal growth restriction, and short long bones. The tool demonstrated moderate discriminatory ability with an AUC of 0.738 (95% CI 0.652–0.823) in the training set and 0.647 (95% CI 0.511–0.784) in the validation set. Calibration curves confirmed good agreement between predicted and observed outcomes. Rather than discovering new associations between USMs and chromosomal abnormalities, this tool simply converts established clinical knowledge into a user-friendly format that allows clinicians to objectively assess the need for amniocentesis in clinical practice.</p>

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A simple nomogram tool for predicting fetal chromosomal abnormalities based on ultrasound soft markers: a research note

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月27日

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  • Chen Jin,
  • Xuefei Yu,
  • Ming Lei,
  • Ping Deng,
  • Xiumei Li,
  • Wei Jiang

摘要

Objectives

Ultrasound soft markers (USMs) are associated with increased risk of fetal chromosomal abnormalities but lack standardized risk assessment methods, often leading to unnecessary amniocentesis procedures. We aimed to develop a practical nomogram tool to quantify this risk and help clinicians make more objective decisions about invasive testing, particularly in resource-limited settings.

Results

We retrospectively analyzed 565 pregnancies with USMs who underwent amniocentesis between 2016 and 2024. Our nomogram integrated six readily available clinical factors: maternal age, thickened nuchal translucency, adverse pregnancy history, structural malformations, fetal growth restriction, and short long bones. The tool demonstrated moderate discriminatory ability with an AUC of 0.738 (95% CI 0.652–0.823) in the training set and 0.647 (95% CI 0.511–0.784) in the validation set. Calibration curves confirmed good agreement between predicted and observed outcomes. Rather than discovering new associations between USMs and chromosomal abnormalities, this tool simply converts established clinical knowledge into a user-friendly format that allows clinicians to objectively assess the need for amniocentesis in clinical practice.