Creates a data frame with randomly generated patient data suitable for testing cardiovascular risk calculations. The function generates realistic ranges for all standard cardiovascular risk factors.
Value
A data frame with n rows and the following columns:
- id
Sequential patient identifier (1 to n)
- age
Patient age in years (30-79)
- sex
Sex at birth ("female" or "male")
- race
Patient race ("white", "aa", or "other")
- sbp
Systolic blood pressure in mm Hg (90-200)
- bp_med
Blood pressure medication status (TRUE/FALSE)
- totchol
Total cholesterol in mg/dL (130-320)
- hdl
HDL cholesterol in mg/dL (20-100)
- lipid_med
Lipid medication status (TRUE/FALSE)
- diabetes
Diabetes status (TRUE/FALSE)
- smoker
Smoking status (TRUE/FALSE)
- egfr
Estimated glomerular filtration rate in mL/min/1.73m2 (15-140)
- bmi
Body mass index in kg/m2 (18.5-39.9)
- hba1c
Hemoglobin A1c percentage (4.5-15.0 or NA)
- uacr
Urine albumin-to-creatinine ratio in mg/g (0.1-25000 or NA)
- zip
ZIP code (30 valid codes or NA)
Examples
library(CVrisk)
# Generate default 100 rows
sample_data <- make_sample_data()
# Generate 50 rows
sample_data_50 <- make_sample_data(n = 50)
# Use with compute_CVrisk
if (FALSE) { # \dontrun{
data <- make_sample_data(n = 10)
result <- compute_CVrisk(
data,
scores = "ascvd_10y_accaha",
age = "age",
gender = "sex",
race = "race",
sbp = "sbp",
totchol = "totchol",
hdl = "hdl",
bp_med = "bp_med",
smoker = "smoker",
diabetes = "diabetes"
)
} # }