Trial reportAmerican journal of physiology. Lung cellular and molecular physiology2023
Development of a peripheral blood transcriptomic gene signature to predict bronchopulmonary dysplasia.
Trial report in American journal of physiology. Lung cellular and molecular physiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
What it found
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 21 citations in OpenAlex.
- Bronchopulmonary dysplasia in preterm neonates: Th2-Eosinophilic inflammation and asthma-like features.Pediatric research · 2026Pooled it
- Artificial intelligence in the care of children and adolescents with chronic diseases: a systematic review.European journal of pediatrics · 2024Pooled it
- KD-SqueezeNet: an efficient deep learning strategy for the multi-task diagnosis of neonatal lung diseases.Pediatric radiology · 2026Article
- Current Clinical Perspectives of Biomarkers in Respiratory Diseases: A Narrative Review.Journal of clinical medicine · 2026Review
- [Research progress in artificial intelligence for the diagnosis and management of diseases in preterm infants].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2026Review
- Urine Metabolomics to Predict Bronchopulmonary Dysplasia: A Single-Center Prospective Study.Pediatric pulmonology · 2026Article
- The evolving pathophysiology of bronchopulmonary dysplasia.Physiological reviews · 2026Review
- Comparison of nSOFA and RSS for predicting bronchopulmonary dysplasia in preterm infants: a retrospective cohort study.BMJ paediatrics open · 2025Article
- Defining endotypes of bronchopulmonary dysplasia in preterm infants to improve precision-based therapies.JCI insight · 2025Review
- AI models in clinical neonatology: a review of modeling approaches and a consensus proposal for standardized reporting of model performance.Pediatric research · 2025Review
- Enhancing bronchopulmonary dysplasia prediction in preterm infants using artificial intelligence and multimodal data integration.Frontiers in pediatrics · 2025Review
- Advancements in biomarkers and machine learning for predicting of bronchopulmonary dysplasia and neonatal respiratory distress syndrome in preterm infants.Frontiers in pediatrics · 2025Review
- Bronchopulmonary dysplasia: analysis and validation of ferroptosis-related diagnostic biomarkers and immune cell infiltration features.Pediatric research · 2024Article
- Bridging the Gap: Exploring Bronchopulmonary Dysplasia through the Lens of Biomedical Informatics.Journal of clinical medicine · 2024Review
- Predictive analytics in bronchopulmonary dysplasia: past, present, and future.Frontiers in pediatrics · 2024Review
- Transforming neonatal care with artificial intelligence: challenges, ethical consideration, and opportunities.Journal of perinatology : official journal of the California Perinatal Association · 2024Review
- A bioinformatics approach towards bronchopulmonary dysplasia.Translational pediatrics · 2023Review
- The eNAMPT/TLR4 inflammatory cascade drives the severity of intra-amniotic inflammation in pregnancy and predicts infant outcomes.Frontiers in physiology · 2023Article
Corrections and comments
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Authors and funding
15 authors at 6 institutions in 3 countries.
Funding
Abstract
Bronchopulmonary dysplasia (BPD) is the most common lung disease of extreme prematurity, yet mechanisms that associate with or identify neonates with increased susceptibility for BPD are largely unknown. Combining artificial intelligence with gene expression data is a novel approach that may assist in better understanding mechanisms underpinning chronic lung disease and in stratifying patients at greater risk for BPD. The objective of this study is to develop an early peripheral blood transcriptomic signature that can predict preterm neonates at risk for developing BPD. Secondary analysis of whole blood microarray data from 97 very low birth weight neonates on day of life 5 was performed. BPD was defined as positive pressure ventilation or oxygen requirement at 28 days of age. Participants were randomly assigned to a training (70%) and testing cohort (30%). Four gene-centric machine learning models were built, and their discriminatory abilities were compared with gestational age or birth weight. This study adheres to the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) statement. Neonates with BPD (
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What OpenQuestion holds
Registered trials
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.