| الوصف: |
Reducing the rate of preterm birth (PTB) is a cornerstone of global efforts to address child mortality. However, without accurate techniques to identify those at risk, success will be limited. Existing tests offer imperfect prediction, particularly for universal screening. Cervical electrical impedance spectroscopy (EIS) is a novel technique to quantify the ripening changes which precede labour. For the first time, this thesis provides a comprehensive assessment of its use in PTB screening by: (1) confirming measurement reliability; (2) evaluating predictive accuracy in pregnant women with no symptoms of preterm labour; (3) evaluating predictive accuracy in women presenting with symptoms of preterm labour and (4) assessing test acceptability. Cervical length (CL) and fetal fibronectin (FFN) measurements were employed alongside EIS to allow assessment of its performance in isolation and in conjunction with these conventional tests. Significantly lower mid-trimester cervical impedance was observed in untreated asymptomatic women destined to deliver preterm. EIS-based prediction compared favourably with CL and FFN in unselected, high risk and low risk groups. Incorporating obstetric history further improved predictive accuracy. Moreover, a trend towards superior prediction via multimodal testing was observed. Lower impedance was also observed in symptomatic women delivering shortly after assessment. In this cohort, EIS had good ability to discriminate those at risk of imminent delivery, with comparable and superior performance to FFN and CL respectively. Again, a trend towards optimal prediction via multimodal testing was noted. Mixed-methods analysis of test acceptability suggests EIS is well tolerated and acceptable to high and low risk women, with reduced anxiety noted following screening. Overall, cervical EIS may offer a useful, acceptable test to predict PTB. Further large studies are required to determine the value of EIS in specific groups, the effect of prophylactic treatment on measurements and the potential for incorporation into existing risk algorithms and treatment pathways. |
