impact {metamisc}

IMPACT data

Description

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.

Usage

data("impact")

Format

A data frame with 11022 observations on the following 11 variables.

name

Name of the study

type

Type of study, RCT: randomized controlled trial,OBS: observational cohort

age

Age of the patient

motor_score

Glasgow Coma Scale motor score

pupil

Pupillary reactivity

ct

Marshall Computerized Tomography classification

hypox

Hypoxia (0=no, 1=yes)

hypots

Hypotension (0=no, 1=yes)

tsah

Traumatic subarachnoid hemorrhage (0=no, 1=yes)

edh

Epidural hematoma (0=no, 1=yes)

mort

6-month mortality (0=alive, 1=dead)

Details

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).

Source

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.

References

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.

Examples

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")