### Install QRISK3 from CRAN

Source: https://github.com/yanliuk/qrisk3/blob/master/README.md

Install the QRISK3 package from CRAN.

```r
install.packages("QRISK3")
```

--------------------------------

### Install QRISK3 from GitHub

Source: https://github.com/yanliuk/qrisk3/blob/master/README.md

Install the QRISK3 package from GitHub using devtools.

```r
install.packages("devtools")

library(devtools)

install_github("YanLiUK/QRISK3")
```

--------------------------------

### QRISK3_2017

Source: https://github.com/yanliuk/qrisk3/blob/master/man/QRISK3_2017.Rd

Documentation for the QRISK3_2017 R function, including usage, arguments, return value, and an example.

```APIDOC
## QRISK3_2017

### Description
Calculates the 10-year individual cardiovascular disease (CVD) risk using the QRISK3-2017 algorithm.

### Usage
```r
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** - Specify your data.
- **patid** - Specify the patient identifier.
- **gender** - 1: women, 0: men.
- **age** - Age of the patient in years (e.g., 64).
- **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** - Diagnosis of or treatment for erectile dysfunction? (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 erythematosus (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** - Ethnic group coded 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 1 to 11, e.g., 4).
- **systolic_blood_pressure** - Systolic blood pressure (mmHg, e.g., 180).
- **std_systolic_blood_pressure** - Standard deviation of at least two most recent systolic blood pressure readings (mmHg).
- **smoke** - Smoke status coded as QRISK3: 1 non-smoker, 2 ex-smoker, 3 light smoker (<10), 4 moderate smoker (10-19), 5 heavy smoker (20 or over).
- **townsend** - Townsend deprivation scores.

### Value
Returns a dataset with three columns: patient identifier, calculated QRISK3 score, and calculated QRISK3 score with only 1 digit.

### Example
```r
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"))
```
```

--------------------------------

### Calculate QRISK3 risk and compare with reference scores

Source: https://github.com/yanliuk/qrisk3/blob/master/README.md

Example of calculating 10-year CVD risk using the QRISK3_2017 function on the included test dataset. It maps column names to the required variables, then compares the computed scores against the reference QRISK_C_algorithm_score column and prints the differences and identity check.

```r
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"))
```

--------------------------------

### Load and inspect QRISK3_2019_test dataset

Source: https://github.com/yanliuk/qrisk3/blob/master/man/QRISK3_2019_test.Rd

Loads the QRISK3_2019_test dataset and displays its structure. Use this to verify the dataset is available and to view its columns and types.

```r
data(QRISK3_2019_test)
str(QRISK3_2019_test)
```

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