Cardiovascular Disease

PH5 / 1509

Ellie Paige, Jessica Barret, David Stevens, Ruth H Keog, Michael J Sweeting, Irwin Nazareth, Irene Petersen, Angela M Wood

Oct 19, 2021

Clinical-Coded Phenotype

  1. Overview

    Phenotype Type
    Disease or syndrome
    Sex
    Both
    Valid Event Date Range
    01/01/1997 - 18/01/2016
    Coding System
    Read codes v2
    Data Sources
    CPRD GOLD
    Collections
    Phenotype Library
    Tags
    No data
    Ontology
    No data

  2. Definition

    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;

     or

    d) 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

  3. Implementation

    Implementation

    No data

  4. Clinical Codelist

  5. Publication

    Related publications

    • 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 27 January 2026]

  6. API

    To Export Phenotype Details:

    FormatAPI
    JSON site_root/api/v1/phenotypes/PH5/version/1509/detail/?format=json
    R Package

    # Download here

    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

    # Download here

    from pyconceptlibraryclient import Client


    # Connect to API

    client = Client(public=True)


    # Get details of Phenotype

    phenotype_detail = client.phenotypes.get_detail(
     'PH5',
     version_id=1509
    )

    To Export Phenotype Code List:

    FormatAPI
    JSON site_root/api/v1/phenotypes/PH5/version/1509/export/codes/?format=json
    R Package

    # Download here

    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

    # Download here

    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
    )

  7. Version History

    Version IDNameOwnerPublish date
    Cardiovascular Disease ieuan.scanlon2021-10-19 09:37