Cardiovascular Disease
Ellie Paige, Jessica Barret, David Stevens, Ruth H Keog, Michael J Sweeting, Irwin Nazareth, Irene Petersen, Angela M Wood
PH5 / 1509 Clinical-Coded Phenotype
Overview
Phenotype TypeDisease or syndromeSexBothValid Event Date Range01/01/1997 - 18/01/2016Coding SystemRead codes v2Data SourcesCollectionsPhenotype LibraryTagsNo dataDefinition
Individuals entered the study from the latest of the following dates:
1) the date of registration at a general practice plus 6 months 2) the date for acceptable computer usage (quality measurement defined as the year in which a general practice continuously used their computer system for recording of medical events and prescribing)
3) the date for acceptable mortality reporting (the date on which mortality recording reflected that of the United Kingdom general population)
4) the date on which the individual turned 30 years of age
or
5) January 1, 1997. Individuals exited the study at the earliest of the following dates:
a) their first (i.e., “incident”) newly recorded CVD event
b) transfer out of the general practice;
c) their date of death;
ord) January 18, 2016. The target population for which we wanted to estimate CVD risk included persons with general practice records and without a history of CVD or statin prescriptions
A 2-stage approach to construct a dynamic risk prediction model, first modeling historical repeated risk factor measurements using multivariate mixed-effects linear models and then estimating 10-year CVD risk using Cox proportional hazards models
Implementation
Implementation
Clinical Code List
PUBLISHED - 352 Codes
Publication
Ellie Paige, Jessica Barret, David Stevens, Ruth H Keog, Michael J Sweeting, Irwin Nazareth, Irene Petersen, Angela M Wood, "Landmark Models for Optimizing the Use of Repeated Measurements of Risk Factors in Electronic Health Records to Predict Future Disease Risk. American Journal of Epidemiology". 187(7), 1530-1538, 2018.
Citation Example
Ellie Paige, Jessica Barret, David Stevens, Ruth H Keog, Michael J Sweeting, Irwin Nazareth, Irene Petersen, Angela M Wood. PH5 / 1509 - Cardiovascular Disease. Phenotype Library [Online]. 19 October 2021. Available from: http://phenotypes.healthdatagateway.org/phenotypes/PH5/version/1509/detail/. [Accessed 30 October 2024]
API
To Export Phenotype Details:
Format API JSON site_root/api/v1/phenotypes/PH5/version/1509/detail/?format=json R Package library(ConceptLibraryClient)
# Connect to API
client = ConceptLibraryClient::Connection$new(public=TRUE)
# Get details of phenotype
phenotype_details = client$phenotypes$get_detail(
'PH5',
version_id=1509
)Py Package from pyconceptlibraryclient import Client
# Connect to API
client = Client(public=True)
# Get codelist of phenotype
phenotype_codelist = client.phenotypes.get_detail(
'PH5',
version_id=1509
)To Export Phenotype Code List:
Format API JSON site_root/api/v1/phenotypes/PH5/version/1509/export/codes/?format=json CSV site_root/phenotypes/PH5/version/1509/export/codes/ R Package library(ConceptLibraryClient)
# Connect to API
client = ConceptLibraryClient::Connection$new(public=TRUE)
# Get codelist of phenotype
phenotype_codelist = client$phenotypes$get_codelist(
'PH5',
version_id=1509
)Py Package from pyconceptlibraryclient import Client
# Connect to API
client = Client(public=True)
# Get codelist of phenotype
phenotype_codelist = client.phenotypes.get_codelist(
'PH5',
version_id=1509
)Version History