A prospective, double-blinded cohort study using quantitative fetal fibronectin testing in symptomatic women for the prediction of spontaneous preterm delivery

一项前瞻性、双盲队列研究,采用定量胎儿纤维连接蛋白检测方法,对有症状的孕妇进行研究,以预测自发性早产。

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Abstract

BACKGROUND: Spontaneous preterm birth (PTB) affects 6.5% of deliveries in Hong Kong. Quantitative fetal fibronectin (fFN) is under-utilised as a test for PTB prediction in Hong Kong. Our objective was to evaluate the effectiveness of quantitative fFN in predicting spontaneous PTB in women with symptoms of threatened preterm labour (TPTL) in our population. METHODS: A prospective, double-blinded cohort study of women with a singleton gestation and TPTL symptoms presenting to a tertiary hospital in Hong Kong between 24 + 0 to 33 + 6 weeks was performed from 1st October 2020 and 31st October 2021. Women with vaginal bleeding, ruptured membranes, and cervical dilation > 3 cm were excluded. The primary outcome was to test the characteristics of quantitative fFN in predicting spontaneous PTB < 37 weeks. Secondary outcome was to investigate the relationship between fFN value and time to PTB. Test characteristics of quantitative fFN at different thresholds were evaluated. RESULTS: 48 women with TPTL were recruited. All had fFN testing at admission with the results being concealed from the obstetrician managing the patient. 10 mothers had PTB (< 37 weeks' gestation). 7/48 (15%) had a subsequent PTB within 14 days from testing and 5 (10%) delivered within 48 h. The negative predictive value (NPV) of predicting delivery within 14 days was 97.3% and 100% when using a cut-off of < 50ng/ml and < 10ng/ml respectively. Using > 200 ng/ml as cut-off can also reliably predict delivery within 48 h - 7 days with positive predictive value PPV of 100%; as well as PTB before 37 weeks. CONCLUSIONS: Quantitative fFN has predictive value for spontaneous PTB prediction in symptomatic women in a Hong Kong population. fFN concentration could help clinicians rule out PTB and avoid unnecessary interventions and hospitalisation.

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