Characterizing chronological accumulation of comorbidities in healthy veterans: a computational approach
| Autor: | Elizabeth R. Hauser, Terry Hyslop, David A. Lieberman, Ashton Madison, Brian Sullivan, Christina D. Williams, Meghan C. O'Leary, Julian C. Hong, Ziad F. Gellad, Thomas S. Redding, Xuejun Qin, A. Jasmine Bullard, Dawn Provenzale, David G. Weiss, Kellie J. Sims |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Male
Risk 0301 basic medicine medicine.medical_specialty Longitudinal study Databases Factual Science Myocardial Infarction MEDLINE Comorbidity Disease Article Comorbidities 03 medical and health sciences 0302 clinical medicine International Classification of Diseases Health care medicine Humans 030212 general & internal medicine Renal Insufficiency Chronic Data mining Veterans Affairs Aged Veterans Aged 80 and over Multidisciplinary business.industry Middle Aged medicine.disease 030104 developmental biology Relative risk Emergency medicine Cohort Medicine Female Neural Networks Computer Cardiomyopathies business |
| Zdroj: | Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021) Scientific Reports |
| ISSN: | 2045-2322 |
| Popis: | Understanding patient accumulation of comorbidities can facilitate healthcare strategy and personalized preventative care. We applied a directed network graph to electronic health record (EHR) data and characterized comorbidities in a cohort of healthy veterans undergoing screening colonoscopy. The Veterans Affairs Cooperative Studies Program #380 was a prospective longitudinal study of screening and surveillance colonoscopy. We identified initial instances of three-digit ICD-9 diagnoses for participants with at least 5 years of linked EHR history (October 1999 to December 2015). For diagnoses affecting at least 10% of patients, we calculated pairwise chronological relative risk (RR). iGraph was used to produce directed graphs of comorbidities with RR > 1, as well as summary statistics, key diseases, and communities. A directed graph based on 2210 patients visualized longitudinal development of comorbidities. Top hub (preceding) diseases included ischemic heart disease, inflammatory and toxic neuropathy, and diabetes. Top authority (subsequent) diagnoses were acute kidney failure and hypertensive chronic kidney failure. Four communities of correlated comorbidities were identified. Close analysis of top hub and authority diagnoses demonstrated known relationships, correlated sequelae, and novel hypotheses. Directed network graphs portray chronologic comorbidity relationships. We identified relationships between comorbid diagnoses in this aging veteran cohort. This may direct healthcare prioritization and personalized care. |
| Databáze: | OpenAIRE |
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