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Classify head size in data.frame-like objects with GIGS-recommended growth standards

Source: R/growth_classify.R
classify_headsize.Rd

Classify head size in data.frame-like objects with GIGS-recommended growth standards

Usage

classify_headsize(
  .data,
  headcirc_cm,
  age_days,
  gest_days,
  sex,
  id = NULL,
  .new = c("hcaz", "headsize")
)

Arguments

.data

A data.frame-like tabular object with one or more rows. Must be permissible by checkmate::assert_data_frame(), so you can also supply a tibble, data.table, or similar.

headcirc_cm

<data-masking> The name of a column in .data which is a numeric vector of head circumference values in cm.

age_days

<data-masking> The name of a column in .data which is a numeric vector of age values in days.

gest_days

<data-masking> The name of a column in .data which is a numeric vector of gestational age(s) at birth in days. This column, in conjunction with the column referred to by age_days, is used to select which growth standard to use for each observation.

sex

<data-masking> The name of a column in .data which is a case-sensitive character vector of sexes, either "M" (male) or "F" (female). By default, gigs will warn you if any elements of sex are not "M" or "F", or are missing (NA). You can customise this behaviour using the GIGS package-level options.

id

<data-masking> The name of a column in .data which is a factor variable with IDs for each observation. When not NULL, this variable is used to ensure that only the first measurement taken from each infant is used as a birth measure. If all your data is from one individual, leave this parameter as NULL. Default = NULL.

.new

A three-length character vector with names for the output columns. These inputs will be repaired if necessary using vctrs::vec_as_names(), which will print any changes to the console. If any elements in .new are the same as elements in colnames(.data), the function will throw an error. Default = c("hcaz", "headsize").

Value

A tabular object of the same class that was provided as .data, with three new columns named according to .new. These columns will be (from left to right):

  • hcaz - Numeric vector of weight-for-length/height zscores

  • headsize - Factor of head size categories

Details

Cut-offs for head size categories are:

CategoryFactor levelZ-score bounds
Severe microcephaly"microcephaly_severe"hcaz =< -3
Microcephaly"microcephaly"-3 < hcaz =< -2
Normal head circumference"normal_headcirc"abs(hcaz) < 2
Macrocephaly"macrocephaly"hcaz >= 2
Severe macrocephaly"macrocephaly_severe"hcaz >= 3

Note

Categorical (factor) columns produced here may contain unused factor levels. By default, gigs will inform you if these columns have unused factor levels. You can change this behaviour using the GIGS package-level option .gigs_options$handle_unused_levels.

References

Victora CG, Schuler-Faccini L, Matijasevich A, Ribeiro E, Pessoa A, Barros FC. Microcephaly in Brazil: how to interpret reported numbers? The Lancet 2016, 387(10019):621-624 doi:10.1016/S0140-6736(16)00273-7

Accogli A, Geraldo AF, Piccolo G, Riva A, Scala M, Balagura G, et al. Diagnostic Approach to Macrocephaly in Children. Frontiers in Paediatrics 2022, 9:794069 doi:10.3389/fped.2021.794069

See also

See classify_growth() to run this analysis and others at the same time.

Examples

# This dummy dataset contains data from two people, from birth (<3 days) to
# 500 days of age.
data <- data.frame(
  child = factor(rep.int(c("A", "B"), c(3, 3))),
  agedays = c(0, 100, 500, 2, 100, 500),
  gestage  = c(rep(35 * 7, 3), rep(35 * 7, 3)),
  sex = rep.int(c("M", "F"), c(3, 3)),
  headcirc_cm = rep.int(c(40, 50, 60), 2)
)

# Use the `id` argument to ensure that `classify_headsize()` uses the correct
# standard for each observation
data |>
  classify_headsize(headcirc_cm = headcirc_cm,
                    age_days = agedays,
                    gest_days = gestage,
                    sex = sex,
                    id = child)
#> Warning: There was 1 'at birth' observation where `age_days` > 0.5.
#> ℹ This occurred for ID B.
#> ! Unused factor levels kept after head size categorisation:
#> "microcephaly_severe", "microcephaly", "normal_headcirc", and "macrocephaly".
#>   child agedays gestage sex headcirc_cm      hcaz            headsize
#> 1     A       0     245   M          40  4.759628 macrocephaly_severe
#> 2     A     100     245   M          50 10.907943 macrocephaly_severe
#> 3     A     500     245   M          60  9.804805 macrocephaly_severe
#> 4     B       2     245   F          40  4.807734 macrocephaly_severe
#> 5     B     100     245   F          50 11.700306 macrocephaly_severe
#> 6     B     500     245   F          60 10.202535 macrocephaly_severe

# If you don't specify `id`, `classify_headsize()` will assume data is from
# one child only
data |>
  classify_headsize(headcirc_cm = headcirc_cm,
                    age_days = agedays,
                    gest_days = gestage,
                    sex = sex)
#> ! Unused factor levels kept after head size categorisation:
#> "microcephaly_severe", "microcephaly", "normal_headcirc", and "macrocephaly".
#>   child agedays gestage sex headcirc_cm      hcaz            headsize
#> 1     A       0     245   M          40  4.759628 macrocephaly_severe
#> 2     A     100     245   M          50 10.907943 macrocephaly_severe
#> 3     A     500     245   M          60  9.804805 macrocephaly_severe
#> 4     B       2     245   F          40  7.961152 macrocephaly_severe
#> 5     B     100     245   F          50 11.700306 macrocephaly_severe
#> 6     B     500     245   F          60 10.202535 macrocephaly_severe