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产前诊断列线图:一种预测高危患者胎儿染色体异常的新工具
Authors Zhou Y, Song Z, Sun L, Wang Y, Lin X, Zhang D
Received 16 July 2021
Accepted for publication 14 October 2021
Published 4 November 2021 Volume 2021:14 Pages 4523—4535
DOI https://doi.org/10.2147/RMHP.S327788
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Dr Jongwha Chang
Background: Amniocentesis is an invasive prenatal diagnostic technique that can provide genetic information of fetus for pregnant women and give them a choice. A straightforward predictive tool can show pregnant women the need for amniocentesis prior to the procedure.
Methods: The information of patients who underwent amniocentesis from 2014 to 2019 at the Obstetrics Clinic, Shengjing Hospital of China Medical University was extracted, and important independent prognostic factors were determined by univariate and multivariate logistic regression analysis to construct nomograms with total abnormalities (TA) and chromosome number abnormalities (CNA).
Results: A total of 19,683 patients undergoing amniocentesis were included in this study. Among 1761 patients with abnormal results, 917 had abnormal chromosome numbers, 439 had abnormal chromosome structures, and 405 had polymorphic results. Nomograms of TA and CNA were created using data such as age, nuchal translucency value, ultrasound results, Oscar’s testing and/or non-invasive prenatal testing abnormalities, parental chromosomes, and information whether they were twins. The nomogram has good predictive power and clinical practicality through the analysis of area under curve and decision curve analysis. Internal verification was performed for nomograms of TA and CNA, suggesting that the nomogram’s predicted probability and actual probability of the two are consistent.
Conclusion: The nomogram constructed is a good predictor of TA and CNA, which can be used in clinical practice to screen high-risk patients of chromosomal abnormalities.
Keywords: nomogram, amniocentesis, chromosome abnormal, prenatal diagnosis