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Compute (weighted) comorbidity scores

Source: R/score.R
score.Rd

Compute (weighted) comorbidity scores

Usage

score(x, weights = NULL, assign0)

Arguments

x

An object of class comorbidty returned by a call to the comorbidity() function.

weights

A string denoting the weighting system to be used, which will depend on the mapping algorithm.

Possible values for the Charlson index are:

  • charlson, for the original weights by Charlson et al. (1987);

  • quan, for the revised weights by Quan et al. (2011).

Possible values for the Elixhauser score are:

  • vw, for the weights by van Walraven et al. (2009);

  • swiss, for the Swiss Elixhauser weights by Sharma et al. (2021).

Defaults to NULL, in which case an unweighted score will be used.

assign0

A logical value denoting whether to apply a hierarchy of comorbidities: should a comorbidity be present in a patient with different degrees of severity, then the milder form will be assigned a value of 0 when calculating the score. By doing this, a type of comorbidity is not counted more than once in each patient. If assign0 = TRUE, the comorbidities that are affected by this argument are:

  • "Mild liver disease" (mld) and "Moderate/severe liver disease" (msld) for the Charlson score;

  • "Diabetes" (diab) and "Diabetes with complications" (diabwc) for the Charlson score;

  • "Cancer" (canc) and "Metastatic solid tumour" (metacanc) for the Charlson score;

  • "Hypertension, uncomplicated" (hypunc) and "Hypertension, complicated" (hypc) for the Elixhauser score;

  • "Diabetes, uncomplicated" (diabunc) and "Diabetes, complicated" (diabc) for the Elixhauser score;

  • "Solid tumour" (solidtum) and "Metastatic cancer" (metacanc) for the Elixhauser score.

Value

A numeric vector with the (possibly weighted) comorbidity score for each subject from the input dataset.

References

Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. Journal of Chronic Diseases 1987; 40:373-383.

Quan H, Li B, Couris CM, et al. Updating and validating the Charlson Comorbidity Index and Score for risk adjustment in hospital discharge abstracts using data from 6 countries. American Journal of Epidemiology 2011; 173(6):676-682.

van Walraven C, Austin PC, Jennings A, Quan H and Forster AJ. A modification of the Elixhauser comorbidity measures into a point system for hospital death using administrative data. Medical Care 2009; 47(6):626-633.

Sharma N, Schwendimann R, Endrich O, et al. Comparing Charlson and Elixhauser comorbidity indices with different weightings to predict in-hospital mortality: an analysis of national inpatient data. BMC Health Services Research 2021; 21(13).

Examples

set.seed(1)
x <- data.frame(
  id = sample(1:15, size = 200, replace = TRUE),
  code = sample_diag(200),
  stringsAsFactors = FALSE
)

# Charlson score based on ICD-10 diagnostic codes:
x1 <- comorbidity(x = x, id = "id", code = "code", map = "charlson_icd10_quan", assign0 = FALSE)
score(x = x1, weights = "charlson", assign0 = FALSE)
#>  [1] 2 6 0 2 0 0 4 0 3 2 0 0 3 0 2
#> attr(,"map")
#> [1] "charlson_icd10_quan"
#> attr(,"weights")
#> [1] "charlson"

# Elixhauser score based on ICD-10 diagnostic codes:
x2 <- comorbidity(x = x, id = "id", code = "code", map = "elixhauser_icd10_quan", assign0 = FALSE)
score(x = x2, weights = "vw", assign0 = FALSE)
#>  [1]  4 -1  0  0  0  0 22  0  4  4  0  2  4  0  4
#> attr(,"map")
#> [1] "elixhauser_icd10_quan"
#> attr(,"weights")
#> [1] "vw"

# Checking the `assign0` argument.
# Please make sure to check the example in the documentation of the
# `comorbidity()` function first, with ?comorbidity().
# We use the same dataset for a single subject with two codes, for
# complicated and uncomplicated diabetes:
x3 <- data.frame(
  id = 1,
  code = c("E100", "E102"),
  stringsAsFactors = FALSE
)
# Then, we calculate the Quan-ICD10 Charlson score:
ccF <- comorbidity(x = x3, id = "id", code = "code", map = "charlson_icd10_quan", assign0 = FALSE)
ccF[, c("diab", "diabwc")]
#>   diab diabwc
#> 1    1      1
# If we calculate the unweighted score with `assign0 = FALSE`, both diabetes
# conditions are counted:
score(x = ccF, assign0 = FALSE)
#> [1] 2
#> attr(,"map")
#> [1] "charlson_icd10_quan"
# Conversely, with `assign0 = TRUE`, only the most severe is considered:
score(x = ccF, assign0 = TRUE)
#> [1] 1
#> attr(,"map")
#> [1] "charlson_icd10_quan"