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toy <- data.frame(
age=c(55,72), sex_txt=c("male","female"),
eGFR=c(45,28), uACR=c(120,800),
dm=c(1,0), htn=c(1,1),
albumin=c(4.2,3.4), phosphorous=c(3.3,4.6),
bicarbonate=c(24,22), calcium=c(9.1,9.8)
)
rp <- kfre:::RiskPredictor$new(
df = toy,
columns = list(age="age", sex="sex_txt", eGFR="eGFR", uACR="uACR",
dm="dm", htn="htn", albumin="albumin", phosphorous="phosphorous",
bicarbonate="bicarbonate", calcium="calcium")
)
rp$predict_kfre(years=2, is_north_american=TRUE, num_vars=4)
#> [1] 0.01247073 0.09997874toy2 <- kfre::add_kfre_risk_col(toy, "age","sex_txt","eGFR","uACR",
dm_col="dm", htn_col="htn",
albumin_col="albumin", phosphorous_col="phosphorous",
bicarbonate_col="bicarbonate", calcium_col="calcium",
num_vars=c(4,6,8), years=c(2,5), is_north_american=TRUE)
head(toy2)
#> age sex_txt eGFR uACR dm htn albumin phosphorous bicarbonate calcium
#> 1 55 male 45 120 1 1 4.2 3.3 24 9.1
#> 2 72 female 28 800 0 1 3.4 4.6 22 9.8
#> kfre_4var_2year kfre_4var_5year kfre_6var_2year kfre_6var_5year
#> 1 0.01247073 0.03842137 0.0119651 0.03688339
#> 2 0.09997874 0.28026055 0.1094176 0.30356514
#> kfre_8var_2year kfre_8var_5year
#> 1 0.01126961 0.03624505
#> 2 0.11930161 0.33888148These 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.