Prediction of adverse perinatal outcomes following induction of labour

PhD Thesis

Fiolna, M. 2021. Prediction of adverse perinatal outcomes following induction of labour. PhD Thesis Canterbury Christ Church University Institute of Medical Sciences
AuthorsFiolna, M.
TypePhD Thesis
Qualification nameDoctor of Philosophy

Induction of labour (IOL) is one of the most common obstetric procedures which is carried out in 20-30% of pregnancies. More than a third of women having IOL will need either an instrumental delivery or a caesarean section. Induction will fail for approximately 10% of women who undergo the process. The number of indications for IOL have increased in the last few years with guidelines from professional bodies recommending induction for a range of obstetric and medical complications. This has a significant impact on the capacity and flow on antenatal wards and delivery suites across the country. There are currently no effective methods that can accurately predict the success of IOL.

The current method for assessment prior to IOL includes a vaginal examination to assess the Bishop Score, which is an objective way of defining the extent of cervical ripening. There are other methods described in the current literature such as the measurement of cervical length, posterior cervical angle and more recently the angle of progression (AOP), head to perineum distance (HPD) and cervical compression index (CCI). There is also some evidence that biochemical markers such as placental alpha macroglobulin-1 and fetal fibronectin may predict the onset of labour. This has been used in management of patients with threatened preterm birth. However, there is no composite model for the accurate prediction of adverse maternal or neonatal outcomes following IOL.

The main objective of this thesis is to examine which factors amongst maternal demographics and components of obstetric history, biophysical and biochemical markers, are altered in women who have adverse outcomes following IOL. I propose to develop a model that will accurately predict the risk of caesarean section for failure to progress or for suspected fetal distress using a combination of maternal and fetal factors measured at a pre-induction clinic (PIC). This model would be of significant benefit in counselling women prior to IOL.

KeywordsLabour; Induction; Adverse perinatal outcomes; Prediction
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Deposited14 Dec 2022
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