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Specialty: Radiology
Condition: Pregnancy
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Total 1321 results found since Jan 2013.
Prediction of large-for-gestational age at 36 weeks' gestation: two-dimensional vs three-Dimensional vs magnetic resonance imaging
CONCLUSION: At 36 WG, MRI performs better than 2D-US and 3D-US in predicting birthweight > 95th percentile at birth, especially in patients at high-risk for macrosomia, while 2D-US and 3D-US are comparable. For low-risk patients, the three modalities perform similarly. This article is protected by copyright. All rights reserved.PMID:37725758 | DOI:10.1002/uog.27485
Source: The Ultrasound Review of Obstetrics and Gynecology - September 19, 2023 Category: Radiology Authors: E Mazzone C Kadji M M Cannie D A Badr J C Jani Source Type: research
Externally validated prediction models for pre-eclampsia: systematic review and meta-analysis
CONCLUSION: Existing externally validated prediction models for any-, early-, and late-onset pre-eclampsia have limited discrimination and calibration performance with inconsistent input variables. The triple test FMF model had excellent discrimination performance in predicting preterm pre-eclampsia in numerous settings, but the inclusion of specialised biomarkers may limit feasibility and implementation outside of high-resource settings. This article is protected by copyright. All rights reserved.PMID:37724649 | DOI:10.1002/uog.27490
Source: The Ultrasound Review of Obstetrics and Gynecology - September 19, 2023 Category: Radiology Authors: S A Tiruneh T T Thanh Vu L J Moran E J Callander J Allotey S Thangaratinam D L Rolnik H J Teede R Wang J Enticott Source Type: research
Validating a machine-learning model for first-trimester prediction of pre-eclampsia using the cohort from the PREVAL study
CONCLUSION: A machine learning model for first-trimester prediction of PE based on a neural network provides effective screening for PE that can be applied in different populations but before doing so it is essential to make adjustments for the analyzers used for biochemical testing. This article is protected by copyright. All rights reserved.PMID:37698356 | DOI:10.1002/uog.27478
Source: The Ultrasound Review of Obstetrics and Gynecology - September 12, 2023 Category: Radiology Authors: M M Gil D Cuenca-G ómez V Rolle M Pertegal C D íaz R Revello B Adiego M Mendoza F S Molina B Santacruz Z Ansbacher-Feldman H Meiri R Martin-Alonso Y Louzoun C de Paco Matallana Source Type: research
Screening for pre-eclampsia with competing risks model using placental growth factor measurements in blood samples collected before 11 weeks' gestation
CONCLUSIONS: Gestational age for PlGF samples might be expanded from 11-14 weeks to 10-14 weeks in risk assessment for preeclampsia using the FMF first trimester screening model. There is little evidence to support the use of PlGF collected before 10 weeks' gestation. This article is protected by copyright. All rights reserved.PMID:37698230 | DOI:10.1002/uog.27462
Source: The Ultrasound Review of Obstetrics and Gynecology - September 12, 2023 Category: Radiology Authors: I Riishede C K Ekelund L Sperling M Overgaard C S Knudsen T D Clausen K Pihl H J Zingenberg A Wright D Wright A Tabor L Rode Collaborators Source Type: research
Validating a machine-learning model for first-trimester prediction of pre-eclampsia using the cohort from the PREVAL study
CONCLUSION: A machine learning model for first-trimester prediction of PE based on a neural network provides effective screening for PE that can be applied in different populations but before doing so it is essential to make adjustments for the analyzers used for biochemical testing. This article is protected by copyright. All rights reserved.PMID:37698356 | DOI:10.1002/uog.27478
Source: The Ultrasound Review of Obstetrics and Gynecology - September 12, 2023 Category: Radiology Authors: M M Gil D Cuenca-G ómez V Rolle M Pertegal C D íaz R Revello B Adiego M Mendoza F S Molina B Santacruz Z Ansbacher-Feldman H Meiri R Martin-Alonso Y Louzoun C de Paco Matallana Source Type: research
Screening for pre-eclampsia with competing risks model using placental growth factor measurements in blood samples collected before 11 weeks' gestation
CONCLUSIONS: Gestational age for PlGF samples might be expanded from 11-14 weeks to 10-14 weeks in risk assessment for preeclampsia using the FMF first trimester screening model. There is little evidence to support the use of PlGF collected before 10 weeks' gestation. This article is protected by copyright. All rights reserved.PMID:37698230 | DOI:10.1002/uog.27462
Source: The Ultrasound Review of Obstetrics and Gynecology - September 12, 2023 Category: Radiology Authors: I Riishede C K Ekelund L Sperling M Overgaard C S Knudsen T D Clausen K Pihl H J Zingenberg A Wright D Wright A Tabor L Rode Collaborators Source Type: research
Validating a machine-learning model for first-trimester prediction of pre-eclampsia using the cohort from the PREVAL study
CONCLUSION: A machine learning model for first-trimester prediction of PE based on a neural network provides effective screening for PE that can be applied in different populations but before doing so it is essential to make adjustments for the analyzers used for biochemical testing. This article is protected by copyright. All rights reserved.PMID:37698356 | DOI:10.1002/uog.27478
Source: The Ultrasound Review of Obstetrics and Gynecology - September 12, 2023 Category: Radiology Authors: M M Gil D Cuenca-G ómez V Rolle M Pertegal C D íaz R Revello B Adiego M Mendoza F S Molina B Santacruz Z Ansbacher-Feldman H Meiri R Martin-Alonso Y Louzoun C de Paco Matallana Source Type: research
Screening for pre-eclampsia with competing risks model using placental growth factor measurements in blood samples collected before 11 weeks' gestation
CONCLUSIONS: Gestational age for PlGF samples might be expanded from 11-14 weeks to 10-14 weeks in risk assessment for preeclampsia using the FMF first trimester screening model. There is little evidence to support the use of PlGF collected before 10 weeks' gestation. This article is protected by copyright. All rights reserved.PMID:37698230 | DOI:10.1002/uog.27462
Source: The Ultrasound Review of Obstetrics and Gynecology - September 12, 2023 Category: Radiology Authors: I Riishede C K Ekelund L Sperling M Overgaard C S Knudsen T D Clausen K Pihl H J Zingenberg A Wright D Wright A Tabor L Rode Collaborators Source Type: research
Validating a machine-learning model for first-trimester prediction of pre-eclampsia using the cohort from the PREVAL study
CONCLUSION: A machine learning model for first-trimester prediction of PE based on a neural network provides effective screening for PE that can be applied in different populations but before doing so it is essential to make adjustments for the analyzers used for biochemical testing. This article is protected by copyright. All rights reserved.PMID:37698356 | DOI:10.1002/uog.27478
Source: The Ultrasound Review of Obstetrics and Gynecology - September 12, 2023 Category: Radiology Authors: M M Gil D Cuenca-G ómez V Rolle M Pertegal C D íaz R Revello B Adiego M Mendoza F S Molina B Santacruz Z Ansbacher-Feldman H Meiri R Martin-Alonso Y Louzoun C de Paco Matallana Source Type: research
Screening for pre-eclampsia with competing risks model using placental growth factor measurements in blood samples collected before 11 weeks' gestation
CONCLUSIONS: Gestational age for PlGF samples might be expanded from 11-14 weeks to 10-14 weeks in risk assessment for preeclampsia using the FMF first trimester screening model. There is little evidence to support the use of PlGF collected before 10 weeks' gestation. This article is protected by copyright. All rights reserved.PMID:37698230 | DOI:10.1002/uog.27462
Source: The Ultrasound Review of Obstetrics and Gynecology - September 12, 2023 Category: Radiology Authors: I Riishede C K Ekelund L Sperling M Overgaard C S Knudsen T D Clausen K Pihl H J Zingenberg A Wright D Wright A Tabor L Rode Collaborators Source Type: research
Validating a machine-learning model for first-trimester prediction of pre-eclampsia using the cohort from the PREVAL study
CONCLUSION: A machine learning model for first-trimester prediction of PE based on a neural network provides effective screening for PE that can be applied in different populations but before doing so it is essential to make adjustments for the analyzers used for biochemical testing. This article is protected by copyright. All rights reserved.PMID:37698356 | DOI:10.1002/uog.27478
Source: The Ultrasound Review of Obstetrics and Gynecology - September 12, 2023 Category: Radiology Authors: M M Gil D Cuenca-G ómez V Rolle M Pertegal C D íaz R Revello B Adiego M Mendoza F S Molina B Santacruz Z Ansbacher-Feldman H Meiri R Martin-Alonso Y Louzoun C de Paco Matallana Source Type: research
Screening for pre-eclampsia with competing risks model using placental growth factor measurements in blood samples collected before 11 weeks' gestation
CONCLUSIONS: Gestational age for PlGF samples might be expanded from 11-14 weeks to 10-14 weeks in risk assessment for preeclampsia using the FMF first trimester screening model. There is little evidence to support the use of PlGF collected before 10 weeks' gestation. This article is protected by copyright. All rights reserved.PMID:37698230 | DOI:10.1002/uog.27462
Source: The Ultrasound Review of Obstetrics and Gynecology - September 12, 2023 Category: Radiology Authors: I Riishede C K Ekelund L Sperling M Overgaard C S Knudsen T D Clausen K Pihl H J Zingenberg A Wright D Wright A Tabor L Rode Collaborators Source Type: research
Enhanced myometrial vascularity secondary to retained pregnancy tissue: time has come to stop misusing the term arterio-venous malformation!
Ultrasound Obstet Gynecol. 2023 Sep 7. doi: 10.1002/uog.27476. Online ahead of print.NO ABSTRACTPMID:37676250 | DOI:10.1002/uog.27476
Source: The Ultrasound Review of Obstetrics and Gynecology - September 7, 2023 Category: Radiology Authors: K Dewilde Y Groszmann D Van Schoubroeck K Grewal J Huirne R de Leeuw T Bourne D Timmerman T Van den Bosch Source Type: research
