Stroke 10-year risk — cvd_risk_stroke • HealthMarkers

Wrapper around PooledCohort::predict_10yr_stroke_risk() with quiet fallback to NA if the backend errors.

Usage

cvd_risk_stroke(data, col_map = NULL, na_warn_prop = 0.2, verbose = TRUE, ...)

Arguments

data: A data frame with the required cardiovascular risk columns.
col_map: Optional named list mapping internal keys (age, sex, race, smoker, total_chol, HDL_c, sbp, bp_treated, diabetes, bmi) to actual column names in data. If NULL (default), column names are auto-inferred then fall back to the key names themselves. sex accepts 1/0, "m"/"f", or "male"/"female" (case-insensitive).
na_warn_prop: Proportion (0-1) to flag high missingness warnings (default 0.2). Only used when verbose = TRUE.
verbose: Logical; if TRUE, prints progress and a short summary.
...: Passed to PooledCohort::predict_10yr_stroke_risk().

Value

A tibble with model, year, risk.

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

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