| Autor: |
Nicholas I. Cole, Harshana Liyanage, Rebecca J. Suckling, Pauline A. Swift, Hugh Gallagher, Rachel Byford, John Williams, Shankar Kumar, Simon de Lusignan |
| Jazyk: |
angličtina |
| Rok vydání: |
2018 |
| Předmět: |
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| Zdroj: |
BMC Nephrology, Vol 19, Iss 1, Pp 1-6 (2018) |
| Druh dokumentu: |
article |
| ISSN: |
1471-2369 |
| DOI: |
10.1186/s12882-018-0882-9 |
| Popis: |
Abstract Background Accurately identifying cases of chronic kidney disease (CKD) from primary care data facilitates the management of patients, and is vital for surveillance and research purposes. Ontologies provide a systematic and transparent basis for clinical case definition and can be used to identify clinical codes relevant to all aspects of CKD care and its diagnosis. Methods We used routinely collected primary care data from the Royal College of General Practitioners Research and Surveillance Centre. A domain ontology was created and presented in Ontology Web Language (OWL). The identification and staging of CKD was then carried out using two parallel approaches: (1) clinical coding consistent with a diagnosis of CKD; (2) laboratory-confirmed CKD, based on estimated glomerular filtration rate (eGFR) or the presence of proteinuria. Results The study cohort comprised of 1.2 million individuals aged 18 years and over. 78,153 (6.4%) of the population had CKD on the basis of an eGFR of |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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