Phenotyping Down syndrome: discovery and predictive modelling with electronic medical records.
Background: Individuals with Down syndrome (DS) have a heightened risk for various co‐occurring health conditions, including congenital heart disease (CHD). In this two‐part study, electronic medical records (EMRs) were leveraged to examine co‐occurring health conditions among individuals with DS (S...
| Publicado en: | Journal of Intellectual Disability Research Vol. 68; no. 5; pp. 491 - 512 |
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| Autores principales: | , , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
May2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=176650630&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 176650630 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09642633 EUL jtl: Journal of Intellectual Disability Research issn: 09642633 maglogo: Y pubinfo: dt: May2024 vid: 68 iid: 5 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 176650630 175157813 176650630 176650630 10.1111/jir.13124 176650630 ppf: 491 ppct: 21 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P tig: atl: Phenotyping Down syndrome: discovery and predictive modelling with electronic medical records. aug: au: Nguyen, T. Q. Kerley, C. I. Key, A. P. Maxwell‐Horn, A. C. Wells, Q. S. Neul, J. L. Cutting, L. E. Landman, B. A. affil: Vanderbilt Brain Institute, Vanderbilt University, Nashville TN,, USA sug: subj: Phenotype Down Syndrome Therapy Down Syndrome Complications Heart Defects, Congenital Risk Factors Comorbidity Evaluation Risk Assessment Electronic Health Records Human Funding Source Male Female Infant, Newborn Infant Child Adolescence Academic Medical Centers Heart Failure Intellectual Disability Prospective Studies Descriptive Statistics Prediction Models Record Review Infant, Newborn: birth-1 month Infant: 1-23 months Child: 6-12 years Adolescent: 13-18 years Male Female ab: Background: Individuals with Down syndrome (DS) have a heightened risk for various co‐occurring health conditions, including congenital heart disease (CHD). In this two‐part study, electronic medical records (EMRs) were leveraged to examine co‐occurring health conditions among individuals with DS (Study 1) and to investigate health conditions linked to surgical intervention among DS cases with CHD (Study 2). Methods: De‐identified EMRs were acquired from Vanderbilt University Medical Center and facilitated creating a cohort of N = 2282 DS cases (55% females), along with comparison groups for each study. In Study 1, DS cases were one‐by‐two sex and age matched with samples of case–controls and of individuals with other intellectual and developmental difficulties (IDDs). The phenome‐disease association study (PheDAS) strategy was employed to reveal co‐occurring health conditions in DS versus comparison groups, which were then ranked for how often they are discussed in relation to DS using the PubMed database and Novelty Finding Index. In Study 2, a subset of DS individuals with CHD [N = 1098 (48%)] were identified to create longitudinal data for N = 204 cases with surgical intervention (19%) versus 204 case–controls. Data were included in predictive models and assessed which model‐based health conditions, when more prevalent, would increase the likelihood of surgical intervention. Results: In Study 1, relative to case–controls and those with other IDDs, co‐occurring health conditions among individuals with DS were confirmed to include heart failure, pulmonary heart disease, atrioventricular block, heart transplant/surgery and primary pulmonary hypertension (circulatory); hypothyroidism (endocrine/metabolic); and speech and language disorder and Alzheimer's disease (neurological/mental). Findings also revealed more versus less prevalent co‐occurring health conditions in individuals with DS when comparing with those with other IDDs. Findings with high Novelty Finding Index were abnormal electrocardiogram, non‐rheumatic aortic valve disorders and heart failure (circulatory); acid–base balance disorder (endocrine/metabolism); and abnormal blood chemistry (symptoms). In Study 2, the predictive models revealed that among individuals with DS and CHD, presence of health conditions such as congestive heart failure (circulatory), valvular heart disease and cardiac shunt (congenital), and pleural effusion and pulmonary collapse (respiratory) were associated with increased likelihood of surgical intervention. Conclusions: Research efforts using EMRs and rigorous statistical methods could shed light on the complexity in health profile among individuals with DS and other IDDs and motivate precision‐care development. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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