Calculate 2023 Miller PTP for obstructive CAD (stenosis \(\geq\) 50% in left main vessel or \(\geq\) 70% in non-left main vessel)

This function returns a patient's pre-test Probability (PTP) of obstructive coronary artery disease (CAD) based on 2023 Miller et. al. likelihood table likelihood table for CAD (stenosis \(\geq\) 50% in left main vessel or \(\geq\) 70% in non-left main vessel).

Usage

calculate_miller_2023_lm_50_non_lm_70_cad_ptp(
  age,
  sex,
  have_chest_pain,
  coronary_calcium_score,
  output = c("grouping", "numeric", "percentage"),
  label_sex_male = c("male"),
  label_sex_female = c("female"),
  label_sex_unknown = c(NA, NaN),
  label_have_chest_pain_no = c("no"),
  label_have_chest_pain_yes = c("yes"),
  label_have_chest_pain_unknown = c(NA, NaN),
  error_call = rlang::caller_env()
)

Arguments

age

Input integer value to indicate the age of the patient in years.

sex

The value of variable in the parameters label_sex_male,
label_sex_female and label_sex_unknown.

have_chest_pain

The value of variable in the parameters
label_have_chest_pain_no, label_have_chest_pain_yes,
and label_have_chest_pain_unknown.

coronary_calcium_score

Input non-negative numeric to indicate the total coronary calcium score of the patient.

output

Input text to indicate the how pre-test probability results be expressed Default: c("grouping", "numeric", "percentage")

• grouping means the PTP will be expressed as Low, Intermediate and High.

  • low if PTP is less than 15%.

  • intermediate if PTP is in between 15% to 50%.

  • high if PTP is more than 50%.

• numeric means the PTP will be expressed as an integer probability (0-100).

• percentage means the PTP will be expressed as percentage text (0-100%).

label_sex_male

Label(s) for definition(s) of male sex. Default: c("male")

label_sex_female

Label(s) for definition(s) of female sex. Default: c("female")

label_sex_unknown

Label(s) for definition(s) of missing sex. Default: c(NA, NaN)

label_have_chest_pain_no

Label(s) for patient not having chest pain symptoms. Default: c("no")

label_have_chest_pain_yes

Label(s) for patient having chest pain symptoms. Default: c("yes")

label_have_chest_pain_unknown

Label(s) for patient with unknown chest pain symptoms. Default: c(NA, NaN)

error_call

The execution environment of a currently running function, e.g. caller_env(). The function will be mentioned in error messages as the source of the error. See the call argument of abort() for more information.

Value

An integer, percentage or category representing the patient's PTP for obstructive CAD based on 2023 Miller et. al. likelihood table for CAD defined as stenosis \(\geq\) 50% in left main vessel or \(\geq\) 70% in non-left main vessel. See parameter option output for more information.

Details

The predictive model is based on 2055 patients from 3 multinational sites. They are Henry Ford Hospital (n=853), Ottawa Heart Institute (n=808), and University Hospital Zurich (n=394).

Examples

# 40 female with cardiac chest pain and coronary calcium score of 0
calculate_miller_2023_lm_50_non_lm_70_cad_ptp(
  age = 40,
  sex = "female",
  have_chest_pain = "yes",
  coronary_calcium_score = 0,
  output = "percentage"
)
#> [1] "1.6%"