ASCVD risk (ACC/AHA Pooled Cohort Equations) — cvd_risk

Wrapper around the PooledCohort ASCVD calculators with added input validation, optional data-quality warnings, and quiet failure to NA if the backend errors.

Usage

cvd_risk_ascvd(data, year = 10, na_warn_prop = 0.2, verbose = FALSE, ...)

Arguments

data: A data frame with columns: age, sex (1 = male, 0 = female), race ("white","black","other"), smoker (logical), total_chol, HDL_c, sbp, bp_treated (logical), diabetes (logical), bmi.
year: Risk horizon: 10 or 30.
na_warn_prop: Proportion (0-1) to flag high missingness warnings (default 0.2). Only used when verbose = TRUE; underlying backend handles NA as per its API.
verbose: Logical; if TRUE, prints progress and a short summary.
...: Passed to the underlying PooledCohort function.

Value

A tibble with columns model, year, risk (percentage).

References

Goff DC, Lloyd-Jones DM, Bennett G, Coady S, D'Agostino RB, et al. (2014). “2013/2014 ACC/AHA Guideline on the Assessment of Cardiovascular Risk.” Circulation, 129(25 Suppl 2), S49–S73. doi:10.1161/01.cir.0000437741.48606.98 , Pooled Cohort Equations; ACC/AHA Task Force on Practice Guidelines.

Examples

df <- tibble::tibble(
  age = 55, sex = 1, race = "white", smoker = FALSE,
  total_chol = 200, HDL_c = 50, sbp = 140, bp_treated = FALSE,
  diabetes = FALSE, bmi = 27
)
if (requireNamespace("PooledCohort", quietly = TRUE)) {
  cvd_risk_ascvd(df, year = 10, verbose = TRUE)
}
#> cvd_risk_ascvd(): preparing inputs; non-finite=1 var(s), high-NA=1, all-NA=1
#> cvd_risk_ascvd(): results: 10yr risk, 1 row(s)
#> # A tibble: 1 × 3
#>   model  year   risk
#>   <chr> <int>  <dbl>
#> 1 ASCVD    10 0.0652