The confidence interval (CI) gives a range of values which are likely to cover
the true but unknown value.  CIs provide more useful information than
the pvalue alone
 CI around a result obtained from a study sample indicates
the range of values within which there is a specific level of certainty (usually
95%) that the true population value for that result lies
 if a CI around
the difference in mean effects of two interventions contains the value zero, then
one cannot rule out the possibility that there is no difference in effect between
the interventions and therefore the differencebetween the interventions would
not be statistically significant. If however, if the CI excludes the value zero,
one can be reasonably (95%) certain that there is a difference between the interventions
and therefore the difference would be statistically significant
 if a CI
is around a statistic that is a ratio (e.g. relative risk, odds ratio, hazard
ratio)
 if the CI does not contain the value 1.0, this would indicate that
a statistically significant difference exists
 CIs can also
be constructed around the measure of effect of each separate intervention
 if
the CIs around each measure of effect do not overlap, this would indicate that
the effects of each separate intervention are significantly different. If the
CIs do overlap then it is less certain whether there is or is not a significant
difference between the effects of each intervention
 width of
the CI (i.e. the range of values of the CI) also provides useful information
 a
CI that is tight around the point estimate indicates that the study has sufficient
power to be relatively precise
 a CI that is very wide indicates that the
study could be underpowered and the point estimate imprecise
Reference:  MeReC
Briefing (2005);30:17.
 Best
Pract Res Clin Obstet Gynaecol. 2005;19(1):1526.
 Wiebe
S. The principles of evidencebased medicine.Cephalalgia. 2000;20 Suppl 2:103.
