Biomarkers and Cervical Length to Predict Spontaneous Preterm Birth in Asymptomatic High-Risk Women

Bastek, Jamie A.; Hirshberg, Adi; Chandrasekaran, Suchitra; Owen, C.M.; Heiser, Laura M.; Araujo, Brittany A.; McShea, Meghan A.; Ryan, Meghan; Elovitz, Michal A.

doi:10.1097/aog.0b013e31829ab714

Cited by 25 publications

(28 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The “PREDICT” study was performed at a single, urban tertiary care institution between August 2011 and November 2012. 24,25 This study was approved by the Institutional Review Board at the University of Pennsylvania. Women with a singleton pregnancy who were at high risk for preterm birth based on a prior history of preterm birth or second trimester loss, previous cervical surgery without a subsequent full term birth, and/or uterine anomaly were approached for recruitment into the study.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Women with preterm birth have a distinct cervicovaginal metabolome

Ghartey

Bastek

Brown

et al. 2015

American Journal of Obstetrics and Gynecology

Self Cite

View full text Add to dashboard Cite

Objective Metabolomics has the potential to reveal novel pathways involved in the pathogenesis of preterm birth (PTB). The objective of this study was to investigate if the cervico-vaginal (CV) metabolome was different in asymptomatic women destined to have a PTB compared to term birth. Study Design A nested case-control study was performed using CV fluid collected from a larger prospective cohort. CV fluid was collected between 20-24 weeks (V1) and 24-28 weeks (V2). The metabolome was compared between women with a spontaneous PTB (n=10) to women who delivered at term (n=10). Samples were extracted and prepared for analysis using a standard extraction solvent method (Metabolon®, Durham, NC). Global biochemical profiles were determined using GC/MS and UPLC MS/MS. ANOVA was used to detect differences in biochemical compounds between the groups. A false discovery rate was estimated to account for multiple comparisons. Result A total of 313 biochemicals were identified in CV fluid. 82 biochemicals were different in the CV fluid at V1 in those destined to have a PTB compared to term birth while 48 were different at V2 (Table 1). Amino acid, carbohydrate, and peptide metabolites were distinct between women with and without PTB. Conclusion These data suggest that the CV space is metabolically active during pregnancy. Changes in the CV metabolome may be observed weeks, if not months, prior to any clinical symptoms. Understanding the CV metabolome may hold promise for unraveling the pathogenesis of PTB and may provide novel biomarkers to identify women most at risk.

show abstract

Section: Methodsmentioning

confidence: 99%

“…Pertinent demographic, clinical, and obstetric data were abstracted from the medical record as previously described. 24 Women with spontaneous preterm birth at less than 37 weeks of gestation were identified (n=10). Controls were selected at random from women having deliveries at > 38 weeks of gestation without evidence of chorioamnionitis.…”

Section: Methodsmentioning

confidence: 99%

Women with preterm birth have a distinct cervicovaginal metabolome

Ghartey

Bastek

Brown

et al. 2015

American Journal of Obstetrics and Gynecology

Self Cite

View full text Add to dashboard Cite

show abstract

“…13,14,17,18 More recent efforts have focused on biomarkers such as pregnancy-associated plasma protein A, fetal fibronectin, and placental growth factor to augment the predictive capacity of demographic and clinical risk factors; however, this body of research has not yet yielded a clear approach for implementation in clinical practice. [19][20][21][22] As with prior studies, important risk factors in our model included race and obstetric history. Our inclusion of childhood abuse in the model is also consistent with recent literature demonstrating the importance of childhood history as a significant risk factor.…”

Section: Figmentioning

confidence: 99%

“…[13][14][15] More recently, risk models including cervical length as well as various biomarkers have shown promise in increasing prognostic performance. [16][17][18][19][20][21][22] However, this research has not yet yielded a risk assessment tool for use in clinical practice; moreover, the majority of these prediction models have been derived using a general population, which may overinflate their ability to discriminate risk within an a priori at-risk population of Medicaid recipients.…”

Section: Introductionmentioning

confidence: 99%

Risk Prediction for Adverse Pregnancy Outcomes in a Medicaid Population

Goyal

Hall

Greenberg

et al. 2015

Journal of Women's Health

View full text Add to dashboard Cite

Background: Despite prior efforts to develop pregnancy risk prediction models, there remains a lack of evidence to guide implementation in clinical practice. The current aim was to develop and validate a risk tool grounded in social determinants theory for use among at-risk Medicaid patients. Methods: This was a retrospective cohort study of 409 women across 17 Cincinnati health centers between September 2013 and April 2014. The primary outcomes included preterm birth, low birth weight, intrauterine fetal demise, and neonatal death. After random allocation into derivation and validation samples, a multivariable model was developed, and a risk scoring system was assessed and validated using area under the receiver operating characteristic curve (AUROC) values. Results: The derived multivariable model (n = 263) included: prior preterm birth, interpregnancy interval, late prenatal care, comorbid conditions, history of childhood abuse, substance use, tobacco use, body mass index, race, twin gestation, and short cervical length. Using a weighted risk score, each additional point was associated with an odds ratio of 1.57 for adverse outcomes, p < 0.001, AUROC = 0.79. In the validation sample (n = 146), each additional point conferred an odds ratio of 1.20, p = 0.03, AUROC = 0.63. Using a cutoff of 20% probability for the outcome, sensitivity was 29%, with specificity 82%. Positive and negative predictive values were 22% and 85%, respectively. Conclusions: Risk scoring based on social determinants can discriminate pregnancy risk within a Medicaid population; however, performance is modest and consistent with prior prediction models. Future research is needed to evaluate whether implementation of risk scoring in Medicaid prenatal care programs improves clinical outcomes.

show abstract

“…The association between shortening of the CL over time and the risk of PTB is controversial 3 4. This systematic review and meta-analysis investigates the predictive accuracy of changes in CL with gestation in quantifying the risk of PTB.…”

Section: Contextmentioning

confidence: 99%