pretestcad (version 1.1.0)

calculate_aha_2021_ptp: Calculate AHA/ACC 2021 PTP for obstructive CAD

Description

This function returns a patient's pre-test Probability (PTP) of obstructive coronary artery disease (CAD) based on the American Heart Association/American College of Cardiology (AHA/ACC) 2021 guidelines.

Usage

calculate_aha_2021_ptp(
  age,
  sex,
  have_dyspnoea,
  have_chest_pain,
  output = c("grouping", "numeric", "percentage"),
  label_sex_male = c("male"),
  label_sex_female = c("female"),
  label_sex_unknown = c(NA, NaN),
  label_have_dyspnoea_no = c("no"),
  label_have_dyspnoea_yes = c("yes"),
  label_have_dyspnoea_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)
)

Value

An integer, percentage or category representing the patient's PTP for obstructive CAD based on the AHA/ACC 2021 guidelines. See parameter option output for more information.

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_dyspnoea

The value of variable in the parameters label_have_dyspnoea_no, label_have_dyspnoea_yes and label_have_dyspnoea_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.

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.

  • very low if PTP is less than 5%.

  • low if PTP is in between 5% to 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_dyspnoea_no

Label(s) for patient having no dyspnoea symptoms. Default: c("no")

label_have_dyspnoea_yes

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

label_have_dyspnoea_unknown

Label(s) for patient having unknown dyspnoea symptoms. 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)

Details

The predictive model used to create the guidelines are based on patients from European countries with low cardiovascular disease (CVD) risk.

If the patient has both dyspnoea and a particular chest pain type (typical, atypical, nonanginal), The chest pain type will take precedence over dyspnoea

Examples

# 35 year old female with chest pain
calculate_aha_2021_ptp(
    age = 35,
    sex = "female",
    have_dyspnoea = "no",
    have_chest_pain = "yes",
    output = "percentage"
)

# 75 year old male with only dyspnoea
calculate_aha_2021_ptp(
    age = 75,
    sex = "male",
    have_dyspnoea = "yes",
    have_chest_pain = "no",
    output = "percentage"
)