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dat.laopaiboon2015

Studies on the Effectiveness of Azithromycin for Treating Lower Respiratory Tract Infections


Description

Results from 15 studies on the effectiveness of azithromycin versus amoxycillin or amoxycillin/clavulanic acid (amoxyclav) in the treatment of acute lower respiratory tract infections.

Usage

dat.laopaiboon2015

Format

The data frame contains the following columns:

author character author(s)
year numeric publication year
ai numeric number of clinical failures in the group treated with azithromycin
n1i numeric number of patients in the group treated with azithromycin
ci numeric number of clinical failures in the group treated with amoxycillin or amoxyclav
n2i numeric number of patients in the group treated with amoxycillin or amoxyclav
age character whether the trial included adults or children
diag.ab numeric trial included patients with a diagnosis of acute bacterial bronchitis
diag.cb numeric trial included patients with a diagnosis of chronic bronchitis with acute exacerbation
diag.pn numeric trial included patients with a diagnosis of pneumonia
ctrl character antibiotic in control group (amoxycillin or amoxyclav)

Details

Azithromycin is an antibiotic useful for the treatment of a number of bacterial infections. Laopaiboon et al. (2015) conducted a meta-analysis of trials comparing the effectiveness of azithromycin versus amoxycillin or amoxycillin/clavulanic acid (amoxyclav) in the treatment of acute lower respiratory tract infections, including acute bacterial bronchitis, acute exacerbations of chronic bronchitis, and pneumonia. The results from 15 trials are included in this dataset.

Source

Laopaiboon, M., Panpanich, R., & Swa Mya, K. (2015). Azithromycin for acute lower respiratory tract infections. Cochrane Database of Systematic Reviews, 3, CD001954.

Examples

### copy data into 'dat' and examine data
dat <- dat.laopaiboon2015
dat

### analysis using the Mantel-Haenszel method
rma.mh(measure="RR", ai=ai, n1i=n1i, ci=ci, n2i=n2i, data=dat, digits=3)

### calculate log risk ratios and corresponding sampling variances
dat <- escalc(measure="RR", ai=ai, n1i=n1i, ci=ci, n2i=n2i, data=dat)

### random-effects model
res <- rma(yi, vi, data=dat)
res

### average risk ratio with 95% CI
predict(res, transf=exp)

metafor

Meta-Analysis Package for R

v2.4-0
GPL (>= 2)
Authors
Wolfgang Viechtbauer [aut, cre] (<https://orcid.org/0000-0003-3463-4063>)
Initial release
2020-03-19

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