Seung Mi Lee1,2, Kyo Hoon Park1,3, Eun Young Jung1,3, Soo-Hyun Cho1,3, Aeli Ryu1,3. 1. Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea. 2. Department of Obstetrics and Gynecology, Seoul National University Hospital, Seoul, South Korea. 3. Department of Obstetrics and Gynecology, Seoul National University Bundang Hospital, Seongnam, South Korea.
Abstract
AIM: The purpose of this study is to determine whether proinflammatory cytokines and matrix metalloproteinases (MMPs) in amniotic fluid (AF), alone or in combination with clinical risk factors, can predict spontaneous preterm delivery (SPTD) at < 34 weeks in women with cervical insufficiency. METHODS: This retrospective cohort study included 57 consecutive singleton pregnant women (17-28 gestational weeks) with cervical insufficiency who underwent amniocentesis. AF was assayed for five cytokines (interleukin [IL]-6, IL-8, monocyte chemotactic protein-1, macrophage inflammatory protein [MIP]-1α, and MIP-1β) and five MMPs (MMP-1, MMP-2, MMP-3, MMP-8, and MMP-9) using multiplex immunoassay kits. The primary outcome measure was SPTD at < 34 weeks. RESULTS: The AF concentrations of MMP-1, MMP-3, MMP-8, MMP-9, IL-6, IL-8, MIP-1α and MIP-1β were significantly higher in women with SPTD at < 34 weeks. Women who had SPTD at < 34 weeks were younger, had significantly more advanced cervical dilatation at presentation and a higher rate of positive AF cultures. Using stepwise regression analysis, a combined prediction model was developed that included maternal age, cervical dilatation at presentation, AF MMP-1 and AF MMP-8 (area under the curve [AUC] 0.951). The AUC for this model was significantly greater than for any single protein alone in AF or for each of the clinical risk factors alone. CONCLUSION: A model combining proteins in AF and clinical factors can improve the accuracy of risk prediction for preterm birth and this combination is more accurate than each of the biomarkers alone in women with cervical insufficiency.
AIM: The purpose of this study is to determine whether proinflammatory cytokines and matrix metalloproteinases (MMPs) in amniotic fluid (AF), alone or in combination with clinical risk factors, can predict spontaneous preterm delivery (SPTD) at < 34 weeks in women with cervical insufficiency. METHODS: This retrospective cohort study included 57 consecutive singleton pregnant women (17-28 gestational weeks) with cervical insufficiency who underwent amniocentesis. AF was assayed for five cytokines (interleukin [IL]-6, IL-8, monocyte chemotactic protein-1, macrophage inflammatory protein [MIP]-1α, and MIP-1β) and five MMPs (MMP-1, MMP-2, MMP-3, MMP-8, and MMP-9) using multiplex immunoassay kits. The primary outcome measure was SPTD at < 34 weeks. RESULTS: The AF concentrations of MMP-1, MMP-3, MMP-8, MMP-9, IL-6, IL-8, MIP-1α and MIP-1β were significantly higher in women with SPTD at < 34 weeks. Women who had SPTD at < 34 weeks were younger, had significantly more advanced cervical dilatation at presentation and a higher rate of positive AF cultures. Using stepwise regression analysis, a combined prediction model was developed that included maternal age, cervical dilatation at presentation, AFMMP-1 and AFMMP-8 (area under the curve [AUC] 0.951). The AUC for this model was significantly greater than for any single protein alone in AF or for each of the clinical risk factors alone. CONCLUSION: A model combining proteins in AF and clinical factors can improve the accuracy of risk prediction for preterm birth and this combination is more accurate than each of the biomarkers alone in women with cervical insufficiency.
Authors: Alan Leviton; Robert M Joseph; Elizabeth N Allred; T Michael O'Shea; Karl K C Kuban Journal: Early Hum Dev Date: 2018-02-07 Impact factor: 2.079
Authors: Felicia Viklund; Maria Hallingström; Marian Kacerovsky; Teresa Cobo; Kristin Skogstrand; David M Hougaard; Karin Sävman; Ylva Carlsson; Panagiotis Tsiartas; Julius Juodakis; Staffan Nilsson; Bo Jacobsson Journal: Reprod Sci Date: 2020-10-07 Impact factor: 3.060