ArticleScientific reports2024
Comparing three cardiothoracic ratio measurement techniques and creating multivariable scoring system to predict Bart's hydrops fetalis at 17-22 weeks' gestation.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Article
- Evaluation of cardiac findings using speckle-tracking echocardiography in fetuses with hemoglobin Bart's disease.Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology · 2024Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
To assess the diagnostic performance of three cardiothoracic (CT) ratio techniques, including diameter, circumference, and area, for predicting hemoglobin (Hb) Bart's disease between 17 and 22 weeks' gestation, and to create a multivariable scoring system using multiple ultrasound markers. Before invasive testing, three CT ratio techniques and other ultrasound markers were obtained in 151 singleton pregnancies at risk of Hb Bart's disease. CT diameter ratio demonstrated the highest sensitivity among the other techniques. Significant predictors included CT diameter ratio > 0.5, middle cerebral artery-peak systolic velocity (MCA-PSV) > 1.5 multiples of the median, and placental thickness > 3 cm. MCA-PSV exhibited the highest sensitivity (97.8%) in predicting affected fetuses. A multivariable scoring achieved excellent sensitivity (100%) and specificity (84.9%) for disease prediction. CT diameter ratio exhibited slightly outperforming the other techniques. Increased MCA-PSV was the most valuable ultrasound marker. Multivariable scoring surpassed single-parameter analysis in predictive capabilities.
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