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Ultrasound forecast model of ascites volume in patients with ovarian hyperstimulation syndrome:Establishment and validation / 中国医学影像技术
Chinese Journal of Medical Imaging Technology ; (12): 1680-1683, 2017.
Artículo en Chino | WPRIM | ID: wpr-668808
ABSTRACT
Objective To establish and validate the ascites volume forecast model of ascites puncture drainage operation with ultrasound measuring for 6 positions in patients with ovarian hyperstimulation syndrome (OHSS),including front of the uterus,Douglas pouch,right iliac fossa,left iliac fossa,hepatorenal recess and spleen kidney fossa.Methods Fifty patients received ultrasonographic measurement (measurement group) and then underwent ascites puncture drainage operation within 6 h.Three scatter diagrams of actual ascites volume (Y;ml) and key position ascites depth summation (X;mm),height correlation coefficient and surface area correlation coefficient were drawn.The simple and practical regression equation with better correlation was used to be the one verified.Then 100 subsequently HSS patients were enrolled in verrification group.Forecast ascites volume calculated with above-mentioned regression equation and actual ascites volume was analyzed with Bland-Altm an method and paired t test.Results Regression equation obtained with the scatter diagram was Y=-256.554 + 10.452X (R2 =0.577),which could be simplified as Y=10.5X-250.0.The limit of consistency between forecast ascites volume and actual ascites volume was (-1 314.02,1 560.48) ml,and the bias was 123.23 ml.The difference between forecast ascites volume and actual ascites volume was not statistically significant (t=-1.684,P=0.096).Conclusion The simplified equation is Y=10.5X-250.0 to forecast ascites volume caused by OHSS,therefore guiding clinical work.

Texto completo: Disponible Índice: WPRIM (Pacífico Occidental) Idioma: Chino Revista: Chinese Journal of Medical Imaging Technology Año: 2017 Tipo del documento: Artículo

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Texto completo: Disponible Índice: WPRIM (Pacífico Occidental) Idioma: Chino Revista: Chinese Journal of Medical Imaging Technology Año: 2017 Tipo del documento: Artículo