ArticleBMC pregnancy and childbirth2021
A hierarchical procedure to select intrauterine and extrauterine factors for methodological validation of preterm birth risk estimation.
Article in BMC pregnancy and childbirth, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07059286 (The Combination of Maternal Risk Factors and Functional/Structural Connectivity in Fetuses and Neonates to Predict Neurodevelopment From Birth Through Early Childhood), which is not on this map. Cited by 28 papers, 4 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
The Combination of Maternal Risk Factors and Functional/Structural Connectivity in Fetuses and Neonates to Predict Neurodevelopment From Birth Through Early Childhood: A Single-Center Observational Cohort Study
Who cites it
28 citing papers in PubMed, 4 syntheses or guidelines pooled it, 52 citations in OpenAlex.
- Antibiotic therapy in patients with amniotic fluid sludge and risk of preterm birth: a meta-analysis.Archives of gynecology and obstetrics · 2024Pooled it
- Prevalence of preterm birth in Scandinavian countries: a systematic review and meta-analysis.The Journal of international medical research · 2023Pooled it
- Association between interleukin-6 and preterm birth: a meta-analysis.Annals of medicine · 2023Pooled it
- Is there a maternal blood biomarker that can predict spontaneous preterm birth prior to labour onset? A systematic review.PloS one · 2022Pooled it
- Vaginal microbiome and its implications in preterm birth.Obstetrics & gynecology science · 2025Review
- Development and validation of a spontaneous preterm birth risk prediction algorithm based on maternal bioinformatics: A single-center retrospective study.BMC pregnancy and childbirth · 2024Article
- Cervical elastography: finding a novel predictor for improving the prediction of preterm birth in uncomplicated twin pregnancies.Archives of gynecology and obstetrics · 2024Article
- Development and external validation of a novel score for predicting postoperative 30‑day mortality in tumor craniotomy patients: A cross‑sectional diagnostic study.Oncology letters · 2024Article
- Article
- Placental Cannabinoid Receptor Expression in Preterm Birth.Journal of pregnancy · 2024Observational
- A pragmatic evaluation of the implementation and acceptance of a universal second trimester cervical length screening program in an un-selected population.Archives of gynecology and obstetrics · 2024Observational
- Article
- Development and validation of the 23-item preterm birth risk assessment scale-Korean version.BMC pregnancy and childbirth · 2023Article
- Article
- Neutrophil-to-Lymphocyte Ratio (NLR) and Platelet-to-Lymphocyte Ratio (PLR) Can Predict Spontaneous Preterm Birth?Journal of inflammation research · 2023Article
- Postoperative cervical length to predict success of repeat cerclage in singleton pregnancies with prolapsed membranes after prior cerclage.Frontiers in medicine · 2023Article
- Preterm birth and maternal heart disease: A machine learning analysis using the Korean national health insurance database.PloS one · 2023Article
- Maternal educational level and preterm birth: Exploring inequalities in a hospital-based cohort study.PloS one · 2023Article
- Advances in the clinical application of ultrasound elastography in uterine imaging.Insights into imaging · 2022Review
- Prevalence of preterm birth and risk factors associated with it at different gestational ages: A multicenter retrospective survey in China.Saudi medical journal · 2022Article
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundEtiopathogenesis of preterm birth (PTB) is multifactorial, with a universe of risk factors interplaying between the mother and the environment. It is of utmost importance to identify the most informative factors in order to estimate the degree of PTB risk and trace an individualized profile. The aims of the present study were: 1) to identify all acknowledged risk factors for PTB and to select the most informative ones for defining an accurate model of risk prediction; 2) to verify predictive accuracy of the model and 3) to identify group profiles according to the degree of PTB risk based on the most informative factors.
methodsThe Maternal Frailty Inventory (MaFra) was created based on a systematic review of the literature including 174 identified intrauterine (IU) and extrauterine (EU) factors. A sample of 111 pregnant women previously categorized in low or high risk for PTB below 37 weeks, according to ACOG guidelines, underwent the MaFra Inventory. First, univariate logistic regression enabled p-value ordering and the Akaike Information Criterion (AIC) selected the model including the most informative MaFra factors. Second, random forest classifier verified the overall predictive accuracy of the model. Third, fuzzy c-means clustering assigned group membership based on the most informative MaFra factors.
resultsThe most informative and parsimonious model selected through AIC included Placenta Previa, Pregnancy Induced Hypertension, Antibiotics, Cervix Length, Physical Exercise, Fetal Growth, Maternal Anxiety, Preeclampsia, Antihypertensives. The random forest classifier including only the most informative IU and EU factors achieved an overall accuracy of 81.08% and an AUC of 0.8122. The cluster analysis identified three groups of typical pregnant women, profiled on the basis of the most informative IU and EU risk factors from a lower to a higher degree of PTB risk, which paralleled time of birth delivery.
conclusionsThis study establishes a generalized methodology for building-up an evidence-based holistic risk assessment for PTB to be used in clinical practice. Relevant and essential factors were selected and were able to provide an accurate estimation of degree of PTB risk based on the most informative constellation of IU and EU factors.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.