ArticleGenes2021
Clinical Phenotypic Spectrum of 4095 Individuals with Down Syndrome from Text Mining of Electronic Health Records.
Article in Genes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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Who cites it
7 citing papers in PubMed, 13 citations in OpenAlex.
- Craniofacial Surgery in Children With Down Syndrome: A 6-decade Scoping Review.Plastic and reconstructive surgery. Global open · 2025Article
- Characterizing trends in clinical genetic testing: A single-center analysis of EHR data from 1.8 million patients over two decades.American journal of human genetics · 2025Article
- Implications of mappings between International Classification of Diseases clinical diagnosis codes and Human Phenotype Ontology terms.JAMIA open · 2024Article
- Visual Impairment in Women with Turner Syndrome-A 49-Year Literature Review.Journal of clinical medicine · 2024Review
- Natural language processing and expert follow-up establishes tachycardia association with CDKL5 deficiency disorder.Genetics in medicine open · 2024Article
- Phenotype-Driven Molecular Genetic Test Recommendation for Diagnosing Pediatric Rare Disorders.Research square · 2023Article
- Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases.Briefings in bioinformatics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
Human genetic disorders, such as Down syndrome, have a wide variety of clinical phenotypic presentations, and characterizing each nuanced phenotype and subtype can be difficult. In this study, we examined the electronic health records of 4095 individuals with Down syndrome at the Children's Hospital of Philadelphia to create a method to characterize the phenotypic spectrum digitally. We extracted Human Phenotype Ontology (HPO) terms from quality-filtered patient notes using a natural language processing (NLP) approach MetaMap. We catalogued the most common HPO terms related to Down syndrome patients and compared the terms with those from a baseline population. We characterized the top 100 HPO terms by their frequencies at different ages of clinical visits and highlighted selected terms that have time-dependent distributions. We also discovered phenotypic terms that have not been significantly associated with Down syndrome, such as "Proptosis", "Downslanted palpebral fissures", and "Microtia". In summary, our study demonstrated that the clinical phenotypic spectrum of individual with Mendelian diseases can be characterized through NLP-based digital phenotyping on population-scale electronic health records (EHRs).
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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.