bp_distribution: Pediatric Blood Pressure Distribution

Description

Distribution and quantile functions for pediatric blood pressure.

Usage

p_bp(
  q_sbp,
  q_dbp,
  age,
  male,
  height = NA,
  height_percentile = NA,
  default_height_percentile = 50,
  source = getOption("pedbp_bp_source", "martin2022"),
  ...
)
q_bp(
  p_sbp,
  p_dbp,
  age,
  male,
  height = NA,
  height_percentile = NA,
  default_height_percentile = 50,
  source = getOption("pedbp_bp_source", "martin2022"),
  ...
)
z_bp(
  q_sbp,
  q_dbp,
  age,
  male,
  height = NA,
  height_percentile = NA,
  default_height_percentile = 50,
  source = getOption("pedbp_bp_source", "martin2022"),
  ...
)

Value

A pedbp_bp object. This is a list of two numeric vectors for the systolic and diastolic pressure respectively. The names for the vectors depends on the call. p_bp returns a list of vectors with the names: sbp_p and dbp_p. q_bp returns a list of vectors with names: sbp and dbp. z_bp returns a list of vectors with names: sbp_z and dbp_z.

Additionally, a pedbp_bp object has a bp_params attribute which provides details on the data source and parameters used in the estimates.

Arguments

q_sbp: a vector of systolic blood pressures
q_dbp: a vector of diastolic blood pressures
age: numeric age, in months
male: integer value, 1 = male, 0 = female
height: numeric, in centimeters, can be missing. See Details.
height_percentile: height percentile to use; range from [0, 100]. See Details.
default_height_percentile: default height percentile to use if height is missing; range (0, 100).
source: the method, or data set, to use as the reference. See Details.
...: not currently used
p_sbp: a vector of systolic blood probabilities; range from [0, 1].
p_dbp: a vector of diastolic blood probabilities; range from [0, 1].

Details

source is used to specify the method or source data sets by which the distributions are estimated. This can be controlled by the option pedbp_bp_source. End users are encouraged to set the option if not using the default so all calls to these functions will use the same source.

Options:

martin2022 (default) uses a combination of references to generate distribution values for ages 1 months through 18 years, without or without known stature. This was the only method implemented in version 1 of the pedbp package.
gemelli1990 uses only the reference values from Gemelli et al. (1990). These values are applicable to patients from 1 month to 12 months of age. Stature is not used in the look up for the parameters.
lo2013 uses only the reference values from Lo et al. (2013). This is applicable to patients of at least three years of age. Height is not considered when looking up the parameters.
nhlbi uses only reference values from the National Heart, Lung, and Blood Institute [NHLBI] and the Centers for Disease Control and Prevention [CDC] published in 2011. These are for patients of at least one year of age and with a known stature. These values were publish
flynn2017 uses only reference values from Flynn et al. (2017). These values are similar to the nhlbi values _but_ "do not include children and adolescents with overweight and obesity (ie, those with a BMI >= 85th percentile).

There is a hierarchy for the use of the height, height_percentile, and default_height_percentile. If height is provided, it takes precedence over the other two arguments. height_percentile is used if height is missing and takes precedence over default_height_percentile. The height is only needed if using the nhlbi or flynn2017 data sources (including as part of the martin2022 workflow).

References

Gemelli, Marina, Rosa Manganaro, Carmelo Mamì, and F. De Luca. "Longitudinal study of blood pressure during the 1st year of life." European journal of pediatrics 149 (1990): 318-320.

Lo, Joan C., Alan Sinaiko, Malini Chandra, Matthew F. Daley, Louise C. Greenspan, Emily D. Parker, Elyse O. Kharbanda et al. "Prehypertension and hypertension in community-based pediatric practice." Pediatrics 131, no. 2 (2013): e415-e424.

"Expert panel on integrated guidelines for cardiovascular health and risk reduction in children and adolescents: summary report." Pediatrics 128, no. Suppl 5 (2011): S213. <doi:10.1542/peds.2009-2107C>

The Fourth Report on the Diagnosis, Evaluation, and Treatment of High Blood Pressure in Children and Adolescents National High Blood Pressure Education Program Working Group on High Blood Pressure in Children and Adolescents Pediatrics 2004;114;555-576 <doi:10.1542/peds.114.2.S2.555>

Flynn, Joseph T., David C. Kaelber, Carissa M. Baker-Smith, Douglas Blowey, Aaron E. Carroll, Stephen R. Daniels, Sarah D. De Ferranti et al. "Clinical practice guideline for screening and management of high blood pressure in children and adolescents." Pediatrics 140, no. 3 (2017).

Examples

Run this code


x <- p_bp(q_sbp = 100, q_dbp = 60, age = 8, male = 0)
x
str(x)

x <- p_bp(q_sbp = c(NA, 82), q_dbp = c(60, 72), age = 9.2, male = 0)
x
str(x)

x <- p_bp(q_sbp = c(NA, 82), q_dbp = c(60, 72), age = 29.2, male = 0, height = 82.8)
x
str(x)

x <- q_bp(p_sbp = 0.78, p_dbp = 0.65, age = 8, male = 0)
x
str(x)

#############################################################################
# compare results when height is known or unknown
p_bp(q_sbp = rep(100, 2),
     q_dbp = rep( 60, 2),
     age   = rep(35.75, 2),
     male  = c(0, 0),
     height = c(NA, 100))

#############################################################################
# Working with multiple patients records
d <- read.csv(system.file("example_data", "for_batch.csv", package = "pedbp"))
d

bp_percentiles <-
  p_bp(
      q_sbp = d$sbp..mmHg.
    , q_dbp = d$dbp..mmHg.
    , age   = d$age_months
    , male  = d$male
    )
bp_percentiles

# Standard (z) scores:
z_bp(
    q_sbp = d$sbp..mmHg.
  , q_dbp = d$dbp..mmHg.
  , age   = d$age_months
  , male  = d$male
  )

q_bp(
    p_sbp = bp_percentiles$sbp_p
  , p_dbp = bp_percentiles$dbp_p
  , age   = d$age_months
  , male  = d$male
  )


#############################################################################
# Selecting different source values

# default
p_bp(q_sbp = 92, q_dbp = 60, age = 29.2, male = 0, default_height_percentile = 0.95,
     source = "martin2022")
p_bp(q_sbp = 92, q_dbp = 60, age = 29.2, male = 0, default_height_percentile = 0.95,
     source = "gemelli1990")
p_bp(q_sbp = 92, q_dbp = 60, age = 29.2, male = 0, default_height_percentile = 0.95,
     source = "lo2013")
p_bp(q_sbp = 92, q_dbp = 60, age = 29.2, male = 0, default_height_percentile = 0.95,
     source = "nhlbi")
p_bp(q_sbp = 92, q_dbp = 60, age = 29.2, male = 0, default_height_percentile = 0.95,
     source = "flynn2017")

q_bp(p_sbp = 0.85, p_dbp = 0.85, age = 29.2, male = 0, default_height_percentile = 0.95,
     source = "martin2022") # default
q_bp(p_sbp = 0.85, p_dbp = 0.85, age = 29.2, male = 0, default_height_percentile = 0.95,
     source = "gemelli1990")
q_bp(p_sbp = 0.85, p_dbp = 0.85, age = 29.2, male = 0, default_height_percentile = 0.95,
     source = "lo2013")
q_bp(p_sbp = 0.85, p_dbp = 0.85, age = 29.2, male = 0, default_height_percentile = 0.95,
     source = "nhlbi")
q_bp(p_sbp = 0.85, p_dbp = 0.85, age = 29.2, male = 0, default_height_percentile = 0.95,
     source = "flynn2017")

Run the code above in your browser using DataLab