| impact | R Documentation |
The IMPACT dataset comprises 15 studies of patients suffering from traumatic brain injury, including individual patient data from 11 randomized controlled trials and four observational studies.
data("impact")
A data frame with 11022 observations on the following 11 variables.
nameName of the study
typeType of study, RCT: randomized controlled trial,OBS: observational cohort
ageAge of the patient
motor_scoreGlasgow Coma Scale motor score
pupilPupillary reactivity
ctMarshall Computerized Tomography classification
hypoxHypoxia (0=no, 1=yes)
hypotsHypotension (0=no, 1=yes)
tsahTraumatic subarachnoid hemorrhage (0=no, 1=yes)
edhEpidural hematoma (0=no, 1=yes)
mort6-month mortality (0=alive, 1=dead)
The included studies were part of the IMPACT project, where a total of 25 prognostic factors were considered for prediction of 6-month mortality. Missing values were imputed using the study as a fixed effect in the imputation model (Steyerberg et al, 2008).
Steyerberg EW, Nieboer D, Debray TPA, Van Houwelingen JC. Assessment of heterogeneity in an individual participant data meta-analysis of prediction models: An overview and illustration. Stat Med. 2019;38(22):4290–309.
Murray GD, Butcher I, McHugh GS, et al. Multivariable prognostic analysis in traumatic brain injury: results from the IMPACT study. J Neurotrauma. 2007;24(2):329–337.
Steyerberg EW, Mushkudiani N, Perel P, et al. Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics. PLOS Med. 2008;5(8):e165.
data(impact)
by(impact, impact$name, summary)
# Plot the distribution of age by study
library(ggplot2)
e <- ggplot(impact, aes(x = name, y = age))
e + geom_violin(aes(fill = type), trim = FALSE) +
theme(axis.text.x = element_text(angle = 45)) +
xlab("Study")
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