2.4. Meta-analysis
A minimum of 3 studies were used to perform a meta-analysis. If the
studies presented the same type of intervention (LPS) and control, with
the same outcome measure, we pooled the results using a meta-analysis of
random effects, with standardized mean differences for continuous
outcomes, calculating the 95% confidence intervals and two-sided P
values for each outcome. In studies where the effects of clustering have
not been taken into account, was to adjust the standard deviations for
the design effect. Statistical significance was defined as a p-value< 0.05 (Z test). Cochran’s Q was used to assess
heterogeneity, Q was used to calculate the excess variance. A p-value
can be calculated for Q, indicating whether all studies will share a
common effect size (p < 0.05) or not (p > 0.05),
We used univariate meta-regression, where sufficient data existed
(> 10 comparisons per variable). We also used the
I2 test to investigate heterogeneity (p >
0.1, heterogeneity, I2 > 50%). A
Stratified meta-analysis was used to explore heterogeneity in effect
estimates according to subgroups, and evidence of publication bias was
assessed using funnel plot analysis. For the stratified analyses,
subgroup analyses were carried out. The following characteristics of the
study were examined as a potential source of heterogeneity: time of
LPS-exposure (24 hours); interval of nitric oxide/nitrites concentration
on a positive control group (20-50 µM/ > 50 µM) (studies
showing mM/mL or another scale were converted to µM); and the method
used to determine cell density (cells per well or cells per mL). The
results of studies reported as zero were used 0.1 to perform a
meta-analysis. The sensitivity analysis was performed after removing
outliers, according to the assay range of the cytokines ELISA kit: TNF:
10 - 6.000 pg mL-1, IL-1: 3 - 3.000 pg
mL-1, and IL-6: 5 - 2.000 pg mL-1.