Development and validation of predictive models for QUiPP App v.2: tool for predicting preterm birth in asymptomatic high-risk women.
Helena A WatsonP T SeedJenny CarterN L HezelgraveKaty KuhrtR M TribeA H ShennanPublished in: Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology (2021)
The QUiPP App v.2 is a highly accurate prediction tool for sPTB that is based on a unique combination of biomarkers, symptoms and statistical algorithms. It can be used reliably in the context of communicating to patients the risk of sPTB. Whilst further work is required to determine its role in identifying women requiring prophylactic interventions, it is a reliable and convenient screening tool for planning follow-up or hospitalization for high-risk women. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.
Keyphrases
- preterm birth
- polycystic ovary syndrome
- pregnancy outcomes
- end stage renal disease
- cervical cancer screening
- newly diagnosed
- machine learning
- ejection fraction
- chronic kidney disease
- low birth weight
- prognostic factors
- pregnant women
- systematic review
- type diabetes
- randomized controlled trial
- high resolution
- deep learning
- gestational age
- mass spectrometry
- depressive symptoms
- sleep quality