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Title: 10-Year Cardiovascular Disease Risk Calculator (QRISK3 2017)
Version: 0.6.0
Author: Yan Li <bluefatterplaydota@gmail.com> [aut, cre, trl], Matthew Sperrin [aut, ctb], ClinRisk Ltd. [cph], Tjeerd Pieter van Staa [aut, ths]
Maintainer: Yan Li <bluefatterplaydota@gmail.com>
Description: This function aims to calculate risk of developing cardiovascular disease of individual patients in next 10 years. This unofficial package was based on published open-sourced free risk prediction algorithm QRISK3-2017 https://qrisk.org/src.php.
Copyright: file inst/COPYRIGHTS
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.3
NeedsCompilation: no
Packaged: 2023-07-20 04:41:05 UTC; legendmiao
Repository: CRAN
Date/Publication: 2023-07-20 05:10:02 UTC

Cardiovascular Disease 10-year Risk Calculation (QRISK3 2017)

Description

This function allows you to calculate 10-year individual CVD risk using QRISK3-2017.

Usage

QRISK3_2017(
  data,
  patid,
  gender,
  age,
  atrial_fibrillation,
  atypical_antipsy,
  regular_steroid_tablets,
  erectile_disfunction,
  migraine,
  rheumatoid_arthritis,
  chronic_kidney_disease,
  severe_mental_illness,
  systemic_lupus_erythematosis,
  blood_pressure_treatment,
  diabetes1,
  diabetes2,
  weight,
  height,
  ethiniciy,
  heart_attack_relative,
  cholesterol_HDL_ratio,
  systolic_blood_pressure,
  std_systolic_blood_pressure,
  smoke,
  townsend
)

Arguments

data

Specifiy your data.

patid

Specifiy the patient identifier.

gender

1: women 0: men.

age

Specify the age of the patient in year (e.g. 64 years-old)

atrial_fibrillation

Atrial fibrillation? (0: No, 1:Yes)

atypical_antipsy

On atypical antipsychotic medication? (0: No, 1:Yes)

regular_steroid_tablets

On regular steroid tablets? (0: No, 1:Yes)

erectile_disfunction

A diagnosis of or treatment for erectile disfunction? (0: No, 1:Yes)

migraine

Do patients have migraines? (0: No, 1:Yes)

rheumatoid_arthritis

Rheumatoid arthritis? (0: No, 1:Yes)

chronic_kidney_disease

Chronic kidney disease (stage 3, 4 or 5)? (0: No, 1:Yes)

severe_mental_illness

Severe mental illness? (0: No, 1:Yes)

systemic_lupus_erythematosis

Systemic lupus erythematosis (SLE)? (0: No, 1:Yes)

blood_pressure_treatment

On blood pressure treatment? (0: No, 1:Yes)

diabetes1

Diabetes status: type 1? (0: No, 1:Yes)

diabetes2

Diabetes status: type 2? (0: No, 1:Yes)

weight

Weight of patients (kg)

height

Height of patients (cm)

ethiniciy

Ethic group must be coded as the same as QRISK3

1 White or not stated
2 Indian
3 Pakistani
4 Bangladeshi
5 Other Asian
6 Black Caribbean
7 Black African
8 Chinese
9 Other ethnic group

heart_attack_relative

Angina or heart attack in a 1st degree relative < 60? (0: No, 1:Yes)

cholesterol_HDL_ratio

Cholesterol/HDL ratio? (range from 1 to 11, e.g. 4)

systolic_blood_pressure

Systolic blood pressure (mmHg, e.g. 180 mmHg)

std_systolic_blood_pressure

Standard deviation of at least two most recent systolic blood pressure readings (mmHg)

smoke

Smoke status must be coded as the same as QRISK3

1 non-smoker
2 ex-smoker
3 light smoker (less than 10)
4 moderate smoker (10 to 19)
5 heavy smoker (20 or over)

townsend

Townsend deprivation scores

Value

Return a dataset with three columns: patient identifier, caculated QRISK3 score, caculated QRISK3 score with only 1 digit

Examples

data(QRISK3_2019_test)
test_all <- QRISK3_2019_test

test_all_rst <- QRISK3_2017(data=test_all, patid="ID", gender="gender", age="age",
atrial_fibrillation="b_AF", atypical_antipsy="b_atypicalantipsy",
regular_steroid_tablets="b_corticosteroids", erectile_disfunction="b_impotence2",
migraine="b_migraine", rheumatoid_arthritis="b_ra", 
chronic_kidney_disease="b_renal", severe_mental_illness="b_semi",
systemic_lupus_erythematosis="b_sle",
blood_pressure_treatment="b_treatedhyp", diabetes1="b_type1",
diabetes2="b_type2", weight="weight", height="height",
ethiniciy="ethrisk", heart_attack_relative="fh_cvd", 
cholesterol_HDL_ratio="rati", systolic_blood_pressure="sbp",
std_systolic_blood_pressure="sbps5", smoke="smoke_cat", townsend="town")

test_all_rst$"QRISK_C_algorithm_score" <- test_all$"QRISK_C_algorithm_score"
test_all_rst$"diff" <- test_all_rst$"QRISK3_2017_1digit" - test_all_rst$"QRISK_C_algorithm_score"
print(test_all_rst$"diff")
print(identical(test_all_rst$"QRISK3_2017_1digit", test_all_rst$"QRISK_C_algorithm_score"))


Test data for QRISK3 2017 algorithm - 2017 data

Description

Data from QRISK3 original algorithm (C code) in 2017. The aim is to compare whether this package calculates the same score as the original algorithm. "QRISK_C_algorithm_score" in dataset is the score calculated using original algorithm in 2017. It should give the same score as this package.

Usage

data(QRISK3_2017_test)

Format

An object of class data.frame with 48 rows and 27 columns.

Examples

data(QRISK3_2017_test)
str(QRISK3_2017_test)

Test data for QRISK3 2017 algorithm - 2019 data

Description

Data from QRISK3 original algorithm (C code) in 2019. The aim is to compare whether this package calculates the same score as the original algorithm. "QRISK_C_algorithm_score" in dataset is the score calculated using original algorithm in 2019. It should give the same score as this package. This data was similar to QRISK3_2017_test except that several test values have been changed.

Usage

data(QRISK3_2019_test)

Format

An object of class data.frame with 49 rows and 27 columns.

Examples

data(QRISK3_2019_test)
str(QRISK3_2019_test)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.