Is there an efficient way to merge two sorted dataframes in pandas, maintaing sortedness?

If I have two dataframes (or series) that are already sorted on compatible keys, I'd like to be able to cheaply merge them together and maintain sortedness. I can't see a way to do that other than via concat() and explicit sort()

a = pd.DataFrame([0,1,2,3], index=[1,2,3,5], columns=['x'])
b = pd.DataFrame([4,5,6,7], index=[0,1,4,6], columns=['x'])
print pd.concat([a,b])
print pd.concat([a,b]).sort()

   x
1  0
2  1
3  2
5  3
0  4
1  5
4  6
6  7

   x
0  4
1  0
1  5
2  1
3  2
4  6
5  3
6  7

It looks like there has been a bit of related discussion with numpy arrays, suggesting an 'interleave' method, but I haven't found a good answer.