OBJECTIVE: To determine the effectiveness of a novel algorithm based on fetal fibronectin (FFN) for management of preterm labor (PTL). METHODS: A randomized trial was performed on patients who presented with symptoms of PTL at 24-34 weeks. Patients were randomized to algorithms with cervical exams only versus cervical exams plus FFN. In this algorithm, physicians had to discharge patients with a negative FFN result. The primary outcome was the evaluation time for triage. The secondary outcomes were admission to the hospital for PTL, preterm birth <34 weeks and preterm birth <37 weeks. RESULTS: A total of 76 patients were enrolled and randomized (control n = 32, FFN n = 44). There were no differences in triage time, hospital admissions or preterm deliveries (PTDs) between the two groups. CONCLUSION: An algorithm based on FFN for management of PTL does not reduce evaluation times for triage, hospital admissions or PTDs.
RCT Entities:
OBJECTIVE: To determine the effectiveness of a novel algorithm based on fetal fibronectin (FFN) for management of preterm labor (PTL). METHODS: A randomized trial was performed on patients who presented with symptoms of PTL at 24-34 weeks. Patients were randomized to algorithms with cervical exams only versus cervical exams plus FFN. In this algorithm, physicians had to discharge patients with a negative FFN result. The primary outcome was the evaluation time for triage. The secondary outcomes were admission to the hospital for PTL, preterm birth <34 weeks and preterm birth <37 weeks. RESULTS: A total of 76 patients were enrolled and randomized (control n = 32, FFN n = 44). There were no differences in triage time, hospital admissions or preterm deliveries (PTDs) between the two groups. CONCLUSION: An algorithm based on FFN for management of PTL does not reduce evaluation times for triage, hospital admissions or PTDs.
Authors: Rafał Rzepka; Barbara Dołęgowska; Aleksandra Rajewska; Daria Sałata; Marta Budkowska; Sebastian Kwiatkowski; Andrzej Torbé Journal: Biomed Res Int Date: 2016-07-31 Impact factor: 3.411