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SARC-F Sarcopenia Screening Score

Source: R/sarc_f_score.R
sarc_f_score.Rd

Computes the SARC-F questionnaire score, a quick screening tool for sarcopenia risk.

Usage

sarc_f_score(
  data,
  col_map = NULL,
  na_action = c("keep", "omit", "error", "ignore", "warn"),
  verbose = TRUE
)

Arguments

data

A data.frame or tibble with SARC-F questionnaire responses.

col_map

Named list mapping the five SARC-F components to columns: strength, walking, chair, stairs, falls.

na_action

One of c("keep","omit","error","ignore","warn").

verbose

Logical; if TRUE (default), emits progress messages.

Value

A tibble with:

  • sarc_f_score (numeric 0-10; NA if any component is NA)

  • sarc_f_high_risk (logical; TRUE if score >= 4, NA if score is NA)

Details

SARC-F has 5 items: Strength, Assistance in walking, Rise from a chair, Climb stairs, and Falls. Each item is scored 0 (no difficulty) to 2 (high difficulty). Total SARC-F score ranges 0-10. A score >= 4 indicates high risk of sarcopenia and suggests further assessment.

References

Malmstrom TK, Morley JE (2013). “SARC-F: a simple questionnaire to rapidly diagnose sarcopenia.” Journal of the American Medical Directors Association, 14(8), 531–532. doi:10.1016/j.jamda.2013.05.018 . Malmstrom TK, Miller DK, Simonsick EM, Ferrucci L, Morley JE (2016). “SARC-F: a symptom score to predict persons with sarcopenia at risk for poor functional outcomes.” Journal of Cachexia, Sarcopenia and Muscle, 7(1), 28–36. doi:10.1002/jcsm.12048 . (SARC-F validation and functional outcome prediction; background)

Examples

df <- data.frame(Strength = c(1, 2, 0), Walking = c(0, 1, 2),
                 Chair = c(1, 1, 2), Stairs = c(0, 2, 2), Falls = c(0, 1, 1))
sarc_f_score(df)
#> sarc_f_score(): reading input 'df' — 3 rows × 5 variables
#> sarc_f_score(): col_map (5 columns — 5 inferred from data)
#>   strength          ->  'Strength'    (inferred)
#>   walking           ->  'Walking'    (inferred)
#>   chair             ->  'Chair'    (inferred)
#>   stairs            ->  'Stairs'    (inferred)
#>   falls             ->  'Falls'    (inferred)
#> sarc_f_score(): computing markers:
#>   sarc_f_score      [0-10 sum]
#>   sarc_f_high_risk  [score >= 4]
#> sarc_f_score(): results: sarc_f_score 3/3, sarc_f_high_risk 3/3
#> # A tibble: 3 × 2
#>   sarc_f_score sarc_f_high_risk
#>          <dbl> <lgl>           
#> 1            2 FALSE           
#> 2            7 TRUE            
#> 3            7 TRUE