ArticleInternational journal of applied & basic medical research
Prediction of Preterm Delivery among Low-risk Indian Pregnant Women: Discriminatory Power of Cervical Length, Serum Ferritin, and Serum Alpha-fetoprotein.
Article in International journal of applied & basic medical research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
- Machine learning prediction of preterm birth in women under 35 using routine biomarkers in a retrospective cohort study.Scientific reports · 2025Article
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Around 80% of preterm births (PTBs) occur spontaneously. Various biomarkers are being evaluated to assess the possible role of chorioamniotic inflammation in PTBs. Aim: The aim of this study was to establish the accuracy of serum bio-markers( cut off values of ferritin and alpha-fetoprotein [AFP] at midtrimester) along with cervical length [CL] assessment to predict preterm delivery among low-risk women. Methods: Three hundred low-risk pregnant women attending the antenatal clinic of a tertiary health care facility were included and underwent CL measurement during mid-trimester by transvaginal ultrasonography and their serum levels of ferritin and AFP were recorded. All were followed up till delivery. Results: Receptor-operated characteristic curves for ferritin, AFP, and CL were constructed. Area under curves and Youden Index calculated for each marker were very low (<0.5) which is statistically considered very poor for a screening test. Conclusion: Serum ferritin and AFP together with CL measurement in the second trimester of pregnancy had poor discriminatory value in predicting preterm delivery among low-risk asymptomatic pregnant women.
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