Results from 22 trials examining the effectiveness of intravenous magnesium in the prevention of death following acute myocardial infarction.

dat.li2007

Format

The data frame contains the following columns:

idnumerictrial id number
studycharacterfirst author or trial name
yearnumericpublication year
ainumericnumber of deaths in the magnesium group
n1inumericnumber of patients in the magnesium group
cinumericnumber of deaths in the control group
n2inumericnumber of patients in the control group

Details

The dataset includes the results from 22 randomized clinical trials that examined the effectiveness of intravenous magnesium in the prevention of death following acute myocardial infarction. It is similar to the dataset dat.egger2001, with some slight differences in the included trials and data used.

Source

Li, J., Zhang, Q., Zhang, M., & Egger, M. (2007). Intravenous magnesium for acute myocardial infarction. Cochrane Database of Systematic Reviews, 2, CD002755. https://doi.org/10.1002/14651858.CD002755.pub2

See also

Examples

### copy data into 'dat' and examine data
dat <- dat.li2007
dat
#>    id        study year   ai   n1i   ci   n2i
#> 1   1       Morton 1984    1    40    2    36
#> 2   2    Rasmussen 1986    4    56   14    74
#> 3   3        Smith 1986    2    92    7    93
#> 4   4      Abraham 1987    1    48    1    46
#> 5   5 Ceremuzynski 1989    1    25    3    23
#> 6   6     Shechter 1990    1    50    9    53
#> 7   7        Singh 1990    6    81   11    81
#> 8   8    Feldstedt 1991   10   150    8   148
#> 9   9     Shechter 1991    2    21    4    25
#> 10 10        Woods 1992   90  1150  118  1150
#> 11 11           Wu 1992    5   125   12   102
#> 12 12    Thogersen 1995    4   130    8   122
#> 13 13     Shechter 1995    4    96   17    98
#> 14 14       ISIS-4 1995 2216 29011 2103 29039
#> 15 15     Bhargava 1995    3    40    3    38
#> 16 16         Urek 1996    1    31    0    30
#> 17 17        Raghu 1999    6   169   18   181
#> 18 18        MAGIC 2000  475  3113  472  3100
#> 19 19     Gyamlani 2000    2    50   10    50
#> 20 20      Santoro 2000    0    75    1    75
#> 21 21          Zhu 2002  101  1691  134  1488
#> 22 22    Nakashima 2004    1    89    3    91

# \dontrun{

### load metafor package
library(metafor)

### meta-analysis of all trials except ISIS-4
res <- rma(measure="OR", ai=ai, n1i=n1i, ci=ci, n2i=n2i, data=dat, method="EE", subset=-14)
print(res, digits=2)
#> 
#> Equal-Effects Model (k = 21)
#> 
#> I^2 (total heterogeneity / total variability):   51.43%
#> H^2 (total variability / sampling variability):  2.06
#> 
#> Test for Heterogeneity:
#> Q(df = 20) = 41.18, p-val < .01
#> 
#> Model Results:
#> 
#> estimate    se   zval  pval  ci.lb  ci.ub     ​ 
#>    -0.20  0.05  -3.64  <.01  -0.31  -0.09  *** 
#> 
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> 
predict(res, transf=exp, digits=2)
#> 
#>  pred ci.lb ci.ub 
#>  0.82  0.74  0.91 
#> 

### meta-analysis of all trials including ISIS-4
res <- rma(measure="OR", ai=ai, n1i=n1i, ci=ci, n2i=n2i, data=dat, method="EE")
print(res, digits=2)
#> 
#> Equal-Effects Model (k = 22)
#> 
#> I^2 (total heterogeneity / total variability):   63.61%
#> H^2 (total variability / sampling variability):  2.75
#> 
#> Test for Heterogeneity:
#> Q(df = 21) = 57.72, p-val < .01
#> 
#> Model Results:
#> 
#> estimate    se   zval  pval  ci.lb  ci.ub   ​ 
#>    -0.01  0.03  -0.25  0.80  -0.06   0.05    
#> 
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> 
predict(res, transf=exp, digits=2)
#> 
#>  pred ci.lb ci.ub 
#>  0.99  0.94  1.05 
#> 

### contour-enhanced funnel plot centered at 0
funnel(res, refline=0, level=c(90, 95, 99), shade=c("white", "gray", "darkgray"))


# }