Just to follow up, I looked at the "Examples" section of the documentation for ggpredict() and I think the closest example to what you are trying to do in terms of plotting is this:
data(efc)
fit <- lm(barthtot ~ c12hour + neg_c_7 + c161sex + c172code, data = efc)
library(ggplot2)
library(ggeffects)
mydf <- ggpredict(fit, terms = "c12hour")
ggplot(mydf, aes(x, predicted)) +
geom_line() +
geom_ribbon(aes(ymin = conf.low, ymax = conf.high), alpha = .1)
That being said, I haven't installed ggeffects and so I don't know if you get CI from glmmPQL objects by default or not.